acta energetica electrical power engineering quarterly no. 04/2011

Power Engineering Quarterlynergeticaact

www. actaenergetica.org

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1. ARTICLE

2. ABSTRACT

ENERGA SA

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featuringA METHOD OF MEDIUM VOLTAGE DISTRIBUTION SYSTEMS RELIABILITY ANALYSISJoachim Bargiel, Paweł Sowa, Katarzyna ZającTomasz Sierociński

A DECENTRALISED MODEL OF THE REGULATING ANCILLARY SERVICES MARKETPaweł Bućko

APPLICATION CAPABILITIES OF THE MAXIMUM DISTRIBUTED GENERATION ESTIMATE METHODOLOGYKrzysztof Dobrzyński, Jacek Klucznik, Zbigniew Lubośny

A CONCEPT OF RECIPIENT ALLOWANCE SYSTEM FOR SUPPLIER’S FAILURE TO MAINTAIN THE REQUIRED VOLTAGE QUALITYZbigniew Hanzelka, Grzegorz Błajszczak

SMALL AND MEDIUM NUCLEAR REACTORSMarcin Jaskólski

SHORT-CIRCUIT ANALYSIS OF POWER GRID WITH CONSIDERATION OF WIND FARMS AS CONTROLLED CIRCUIT SOURCESPiotr Kacejko, Piotr Miller

CURRENT DISTRIBUTED GENERATION DEVELOPMENT OPPORTUNITIES IN THE NATIONAL POWER SYSTEMSylwester Robak, Désiré Dauphin RasolomampiononaGrzegorz Tomasik, Paweł Chmurski

THE DYNAMIC ASPECTS OF WIND FARM OPERATION – MEASUREMENTS AND ANALYSISTomasz Sikorski, Edward Ziaja, Bogusław Terlecki

FERRORESONANCE AS A SOURCE OF DISTURBANCES AND FAILURES IN MEDIUM VOLTAGE DISTRIBUTION GRIDSRafał Tarko, Wiesław Nowak, Waldemar Szpyra, Mariusz Benesz, Andrzej Makuch

1. ARTICLE

2. ABSTRACT

ENERGA SA


ENERGA SA

Increase in power systems’ saturation with small electricity sources making up so-called distributed generation, has become a reality. This is by no means a revelation. Just as the observation that the development of distributed generation is quite far from expectations isn’t revealing. This development’s extremely limited pace is mainly a result of legal regulations in the power sector, and not only, as it may seem, the grid’s technical limitations. It results not only from the law directly relating to renewable energy sources, but also from other provisions, such as the so-called right of way. We mean here not only the laws in force at present, but in large part those applicable at the beginning of the wind power generation development, i.e. over a dozen years ago. Fortunately, the law in this area is changing, increasing opportunities for faster development of power grids and thus stimulating the pace of connection of further sources of so-called renewable energy.

The status and development of the national legislation on renewable power generation and power grids is a typical example of law lagging behind reality. In a general sense, lagging law leads (or may lead) to some deformation of reality (compared to expectations) and possibly to pathology, which in turn forces the need for correction. Not all corrective actions are effective, unfortunately. And even if they are effective, the correction of irregularities may take very long.

An example of this is the practical inability to connect new sources to power grids in many areas due to technical limitations, whereas the powers installed in these sources are relatively small (just over 1,000 MW in wind farms). This theoretical inability to connect new sources results from the fact of granting in the past to virtual investors a large number of permits to connect wind turbines, which in fact have never been built. It should be emphasized here that not power grid operators, but the legislators are responsible for this condition. The projects that virtual investors have failed to implement now suppress the possibility of action to real investors, i.e. those who have money and want to build power plants.

The conclusion from the foregoing, which in fact is also not a revelation either, is that the law should keep pace with reality. This is a necessary condition. Ideally, the law should be ahead of reality. Then it would be the right tool for the creation of reality (a stimulus for its development), and not just a cataplasm.

This issue of Acta Energetica is dedicated to selected problems of wind turbines’ operation in the power system. And since individual wind turbines are connected to MV grids (including turbines in wind farms), the issue also presents articles relating to issues of MV network operation. Enjoy reading!

I am pleased to announce the launch of Acta Energetica’s new website, where you can find articles whichhave been published in the magazine so far, and various other important and interesting information from the world of the energy and power industries. Please visit us at www.actaenergetica.org.

Prof. Zbigniew Lubośny Editor in Chief Acta Energetica

4Joachim Bargiel, Paweł Sowa, Katarzyna Zając / Silesian University of TechnologyTomasz Sierociński / TAURON Dystrybucja GZE S.A.

Authors / Biographies

Paweł SowaGliwice / Poland

Director of the Institute of Electrical Power and Systems Control of the Silesian University of Technology, Associate Dean for Science and Organization of the Department of Electrical Engineering. Specialist in power engineering, power system modelling, and transient electromagnetic phenomena. Author of numerous papers, articles, and books.

Joachim BargielGliwice / Poland

Assistant Professor at the Institute of Electrical Power and Systems Control of Silesian University of Technology, Vogt of the Gierałtowice Municipality. Author of numerous papers and articles on the reliability of power systems, a promoter of e-municipality and distributed energy generation.

Katarzyna ZającGliwice / Poland

Graduated from the Department of Electrical Engineering, Silesian University of Technology (2010). Since October 2010 a doctoral student in electrical engineering at the Department.

Tomasz SierocińskiWarsaw / Poland

Graduated from the Department of Electrical Engineering, Silesian University of Technology (1999). Since 2000 professionally involved in industrial power engineering. His main interests include distribution system operation and customer supply continuity.

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A METHOD OF MEDIUM VOLTAGE DISTRIBUTIION SYSTEMS RELIABILITY ANALYSIS

Joachim Bargiel / Silesian University of TechnologyPaweł Sowa / Silesian University of Technology

Katarzyna Zając / Silesian University of TechnologyTomasz Sierociński / TAURON Dystrybucja GZE S.A.

1. PRESENT CONDITION OF MEDIUM VOLTAGE GRIDS

A MV distribution network is an overhead or cable grid, less often an overhead/cable grid; it supplies diverse areas, including cities, suburbs and villages, as well as industrial sites. This is a very large number of recipients, usually low-power, receiving electricity directly from a medium voltage network, but also customers operating a low-voltage, supplied in groups of MV / LV power transformers, which form MV / 0. 4 kV transformer reception – generally called a group recipient. This grid operates as radial grid. Each separate “radius” is an extended branch. A branch is usually powered in a single point (grid node) from a superior 110 kV network. In a post-failure condition the dispatcher (operator) has the option to switch part of the recipients to reserve power supply from neighbouring branches (“radii”) of the MV grid, in a few (2 to 5) – prepared in advance – points within it.

A MV power grid’s supply sources include 110 kV grid nodes supplied from transmission grids and large power plants, as well as local electricity sources, so called local generation. Such local sources, located deep within medium and low voltage distribution grids, create new situations of cooperation with the commercial power grid in normal and post-failure conditions and in island operation. In many cases these are minor facility sources, (offices, hospitals, schools, swimming pools, municipality power centres).

The present condition of such local medium voltage power grids is unsatisfactory, despite increasing demand for electricity, especially among recipients supplied from these grids. Household-municipal recipients, agriculture, small industry, and services have significantly contributed to this increase. Increased power andenergy intake forces development of the grid by way of procurement of new lines and MV / LV substations. Therefore, relatively more investment in grid development is required. However, given the current structure of local grids, scattered reception points in rural areas, length of linear strings with no option of supply from the other end in emergencies, the reconstruction of the most worn out and least efficient grids can be neitherfast nor modelled on urban grids. It should be preceded by research work to establish viable and economically reasonable directions of changes in the status quo.

2. RELIABILITY MODEL FOR MEDIUM VOLTAGE DISTRIBUTION GRIDS

From the reliability viewpoint a network is required to continuously supply electricity of sufficientquality to each receiving node in defined periods of time. Recipient sensitivity electricity supply disruptions are determined by the following parameters:

• duration of a single power outage, which includes the very important “allowable outage time limit”, beyond which the outage effects become significant to the recipient (economic damage)

• overall duration of outages in an analysed time period (usually one year)• overall number of outages in an analysed time period• overall number of outages in excess of an allowable outage time limit. From these parameters various

reliability indicators result.

Abstract

This article presents one of the most current methods and a computer program for evaluation of the reliability of power supply of recipients in middle voltage grids in the country. It is an extension of the NIEZ method and program, developed at the Power Engineering

Institute of the Silesian University of Technology for the HV and 110 kV transmission grid. The main assumptions of the method and computational model, as well as exemplary calculation results for a medium voltage grid model section, are presented.

A Method of Medium Voltage Distributiion Systems Reliability Analysis

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Distortions in power grids may deprive some receiving stations of power supply due to the interruption of their connections to supplying stations. Such events are reported as random unexpected power outages. Outage occurrences depend on the grid topology layout, and the manner and speed of their fixing are related to the system configuration, available switching equipment and grid automation, and the operator’s working methods. Ina radial, single-sided supplied grid – except a few grid systems with local sources – virtually any disruption leads to the outage of recipients’ power supply. All disruptions are eliminated by an appropriate repair, namely:

• spontaneous, whereby the action of automatic controls recovers the system’s initial condition, e.g. auto reclosing, or creates a substitute system with ATSE

• man-made and involving:a) manual switching to another reserve supply (power supply path) with simultaneous replacement of

an item or a post-failure repair in order to reduce the outage of the node’s power – if it is possibleb) post-failure repair of an item where it is installedc) replacement of a damaged item.

Planned preventative works (maintenance, inspection and planned repairs) are carried out in grids to prevent system components’ inoperability. Works relating to the need to switch off components are important, which leads to weakening of the system or to switching off receiving nodes, so called. “announced outages of recipient power supply”, and must be reproduced in the model.

Local generation sources located within a medium voltage grid can contribute to shortening the duration of power outage and to reducing the power outaged when planned works are performed, as well as during emergency interruptions. From the standpoint of reliability of power supply of recipients (as well as of receiving MV / LV stations), in the event of loss of the primary power supply path the demand may be covered by local generation. This is possible when the damaged section of the grid is separated, and other stations are supplied in the “insular” mode from local generation.

The following factors are considered in a medium voltage grid reliability model:• system configurations, including grid operation system• disposable power of the local generation sources and their distribution in the grid nodes• planned repairs of the grid’s components• available automatic and remote controls of the grid and the impact of grid automatic controls• impact of the dispatcher’s operation in normal and emergency conditions, and service activities.

In order to solve the assumed task an existing MV grid has been divided into radii supplied in a single point from a main supply point, thus forming branches. Inside the branches there are automatic switches, remotely controlled switches, and local sources. Depending on the location of automatic switches and remotely controlled switches, the grid branch gets divided into segments, which are automatically switched off or switched over in disturbance (emergency or post-emergency) conditions. These segments are named system elements, so-called integrated elements. Many recipients are switched off or switched over along with these elements. This model enables calculation of the following indicators for recipients or receiving stations:

D – expected number of power supply outagesQ – failure rate, which is usually interpreted as the relative duration of the system’s inoperabilityA nd – unsupplied electricity, MWh/a.They may be supplemented with easily calculable indicators, for example: tśr – average outage duration, h/outage, and other.

3. RELIABILITY MODEL ASSUMPTIONS

A MV distribution grid consists of numerous devices which are grouped in the model into the following elements: lines, transformers, busbar systems (in receiving and supplying stations) and generation units. As a result of disturbances in the grid it may be may again divided into sections disconnected with each other, and the following conditions may occur in each such section:

• if in a separate section there are only receiving stations, they will be cut off from the supply

Joachim Bargiel, Paweł Sowa, Katarzyna Zając / Silesian University of TechnologyTomasz Sierociński / TAURON Dystrybucja GZE S.A.

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• if in a separate section there are receiving as well as supplying stations, the following may occur: – complete supply of the receiving stations, if the supplying station’s power suffices,– limited supply or supply outage for recipients (in receiving stations) due to power deficit in the

separated section.

The following two complementary issues should be distinguished here:• the issue of continuity of receiving stations’ supply as a result of the disruptions that have occurred,

including switchings (ability to search for a “new” power supply path after closing of an open switch)• the issue of power balance in the sections created by the new divisions resulting from the new disruptions

that have occurred and, consequently:• balance of power and the recipients suffer no effects of• imbalance of power and resulting limitations.

A solution of both issues requires an algorithm that will scan the grid operating conditions conducive to the situations discussed above. Due to the complexity of the issues and available practical options the following simplifications have been implemented:

• disposable source power represented by average disposable power• receiving stations’ peak load considered in a deterministic manner• generation source operates autonomously; the condition is met that the disposable power is greater

than or equal to the separated area’s power demand and stepless adjustment of the generated power is ensured and correlated with the resultant frequency characteristics of the recipients demand

• grid equipment repairs are considered in a deterministic way• phenomena associated with instability conditions are neglected.

4. CHARACTERISTICS OF INDIVIDUAL STAGES OF THE RECIPIENTS POWER SUPPLY RELIABILITY ANALYSIS

The reliability analysis of recipient power supply from a specific medium voltage grid consists of thefollowing four stages:

Stage 1: Analysis of the system of the distribution grid components’ connection – identificationof the analyzed system’s grid structure

The basic component algorithm is power supply path identification. Its task is to determine the gridgraph elements that connect the (analysed) receiving node to the supplying node. The following is required for identification of the analysed system’s grid structure:

a) development of a table of the analysed receiving node supply paths (XO)b) development of a matrix of the analysed receiving node supply paths (Z).

Stage 2: Determination of discontinuity indicators of the analysed receiving node’s supply. The determination of the discontinuity indicators of the analysed receiving node’s supply involves:1. Determination of failure statistics for the analyzed grid system’s elements:di

’ – disturbance incidence rate of the integrated element i, composed of its component devices, i.e. the expected number of outages per 100 elements and one year

ti – average disturbance duration for the system’s element i, in hours per disturbance (h/disturb.),

2. Designation of individual elements and pairs of triples of elements, the outage of which causes interruption of the analysed receiving node’s supply.

Resultant node supply reliability indicators are derived from:• node’s own indicators• indicators related to outages of the grid’s individual integrated elements• indicators related to outages of pairs of the grid’s integrated elements


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No triple outages are considered in the calculations, because the probability of concurrent failure of more than two elements is marginal and irrelevant to practical calculations.

The following is calculated for each node:a) expected annual number of the node’s supply interruptions, designated with letter Db) inoperability rate Q, i.e. relative interruption durationc) expected electricity not supplied yearly due to disturbances, calculated as the product of the electricity

received from the node and the inoperability rate Q:

And = Q × A (1)

From the above indicators the average duration may be derived of single supply interruption in the period of time T, designated with the letter ta from the following formula:

(2)

DTQta

Stage 3: Determination of a synthetic measure of supply discontinuity – unsupplied electricityAfter analyzing all supply conditions for the station, the unsupplied electricity And is calculated. For the

receiving node i it is calculated after the formula:

Andi = Qi × Ari (3)

Ari = Psi × Tsi (4)

where:Qi – reliability rate calculated for the node iAri – electricity received yearly by the node i Ps, i – average power received by the node i Ts, i – average load duration.

Stage 4: Analysis of results and selection of variantSample supply reliability calculations have been performed for the medium voltage model grid shown in

Fig. 1. The calculations have been performed for the system operation’s three options (variants). In the first variantall stations are supplied from the main supply point (MSP), a circuit breaker is installed in the line, and disconnectors are installed in the branches and at the MV / LV transformer.


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Fig. 1. Model local MV grid system – basic variant

Fig. 2. Model local MV grid system – variant with reclosers

In the second variant, shown in Fig. 2, the sectioning of the main line using the circuit breaker (recloser R1) and installation of reclosers R2 and R3 in the branches of the receiving section III and IV were introduced. The use of circuit breakers (reclosers) can reduce the frequency of faults, and the total duration of fault by 37% (compared to the system model shown in Fig. 1). The number of disconnected customers is limited, and the time location of fault greatly reduced. The value of undelivered energy is reduced by 34% compared to the baseline (variant 1).


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Fig. 3. Model local MV grid system – variant with reclosers and local generation

In the third variant apart from sectioning off the main line using reclosers R1 and R2 and R3 in the branches of the receiving section III and IV, the local generation of the receiving section IV were introduced. The present system allows the automatic location of fault with the help of running reclosers, as well as the sectioning of the main path line and cutting off the damaged section III and IV in the branches with reclosers R2 and R3. The presence of a local source allows supplies power to undamaged sections. For such system, a decrease of total time (68%) and the number of interruptions, resulting in a significant reduction of energy notsupplied to customers. The value of undelivered energy compared to baseline (variant 1) is 68.5% lower. The calculation results are shown in Tab. 1.

Tab. 1. Reliability rates calculated for each variant

variant 1 D Q Ta t.śr f P Type El

Section No. Node No. fault/year *10 h/year h/faultyears/1

faultkW of recipient MWh/a

node 1 Xz1 0.5 0.37 0.3 0.7 2.04

1

node 2 Xo1 13.7 36.1 31.6 2.3 0.07 120 KB 3.8

node 3 Xo2 13.7 36.1 31.6 2.3 0.07 180 KB 5.7

node 4 Xo3 13.7 36.1 31.6 2.3 0.07 250 P 7.9

node 5 Xo4 13.7 36.1 31.6 2.3 0.07 180 KB 5.7

2node 6 Xo5 13.7 36.1 31.6 2.3 0.07 200 KB 6.3

node 7 Xo6 13.7 36.1 31.6 2.3 0.07 130 KB 4.1

3node 8 Xo7 13.7 36.1 31.6 2.3 0.07 340 P 10.8

node 9 Xo8 13.7 36.1 31.6 2.3 0.07 220 KB 7.0

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node 10 Xo9 13.7 36.1 31.6 2.3 0.07 450 P 14.2

node 11 Xo10 13.7 36.1 31.6 2.3 0.07 190 KB 6.0

node 12 Xo11 13.7 36.1 31.6 2.3 0.07 190 KB 6.0

total 77.5


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variant 2 D Q Ta t.śr f P Type El

Section No. Node No. fault/year *10-4 h/a h/fault.years/1

faultkW of recipient MWh/a

node 1 Xz1 0.5 0.4 0.3 0.7 2.0

1

node 2 Xo1 5.7 14.6 12.8 2.2 0.17 120 KB 1.5

node 3 Xo2 5.7 14.6 12.8 2.2 0.17 180 KB 2.3

node 4 Xo3 5.7 14.6 12.8 2.2 0.17 250 P 3.2

node 5 Xo4 5.7 14.6 12.8 2.2 0.17 180 KB 2.3

2node 6 Xo5 8.9 23.2 204 2.3 0.11 200 KB 4.1

node 7 Xo6 8.9 23.2 204 2.3 0.11 130 KB 2.6

3node 8 Xo7 10.1 25.4 22.2 2.2 0.1 340 P 7.6

node 9 Xo8 10.1 25.4 22.2 2.2 0.1 220 KB 4.9

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node 10 Xo9 12.5 31.2 27.3 2.2 0.08 450 P 12.3

node 11 Xo10 12.5 31.2 27.3 2.2 0.08 190 KB 5.2

node 12 Xo11 12.5 31.2 27.3 2.2 0.08 190 KB 5.2

total 51.1

variant 3 D Q Tat.śr

f P Type El

Section No. Node No. dist/year *10-4 h/a h/dist.years/1

dist.kW of recipient MWh/a

node 1 Xz1 0.5 04 0.3 0.7 2.0

1

node 2 Xo1 5.3 14.2 12. 4 2. 4 0.19 120 KB 1.5

node 3 Xo2 5.3 14.2 12.4 2. 4 0.19 180 KB 2.2

node 4 Xo3 5.3 14.2 12. 4 2. 4 0.19 250 P 3.1

node 5 Xo4 5.3 14.2 12.4 2. 4 0.19 180 KB 2.2

2node 6 Xo5 3.5 8.7 7.6 2.2 0.28 200 KB 1.5

node 7 Xo6 3.5 8.7 7.6 2.2 0.28 130 KB 1.0

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node 8 Xo7 4.7 11.9 10.5 2.2 0.21 340 P 3.6

node 9 Xo8 4.7 11.9 10.5 2.2 0.21 220 KB 2.3

node 10 Xo9 4.0 9.6 8.4 2.1 0.25 450 P 3.8

4node 11 Xo10 4.0 9.6 8.4 2.1 0.25 190 KB 1.6

node 12 Xo11 4.0 9.6 8.4 2.1 0.25 190 KB 1.6

total 24. 4

It follows from the presented calculations that the installation of automatic circuit breakers – reclosers, used for remote grid reconfiguration, and the local generation sources’ capability of autonomous operation, mayto a large extent contribute to a reduction of interruptions in recipients’ power supply, and to a reduction of the power outaged during the performance of scheduled works and during emergency breaks.

5. SUMMARY

Development of the model is necessary and a programme for the calculation of basic indicators to assess the reliability of recipients’ supply from a medium voltage grid. This is mainly due to the increasing number of local generation sources having a definite impact on the reliability of supply from medium voltage grids. Thispublication presents the final stage of work on the issue of adapting the NIEZ method and program so far appliedto high voltage transmission and distribution grids.


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REFERENCES1. Bargiel J., Goc W., Teichman B., Średniookresowy deficyt energii elektrycznej – horyzont sezonowy, ORDERED

REASEARCH PROJECT No. PBZ-MEIN-1/2/2006 „Bezpieczeństwo elektroenergetyczne kraju”, Gliwice, 2008.2. Bargiel J., Goc W., Sowa P., Teichman B., Średniookresowy deficyt mocy i energii elektrycznej, Scientific Conference

„Rynek Energii ’09”, Kazimierz Dolny, June 2009.3. Bargiel J., Goc W., Sowa P., Teichman B., Sierociński T., Ryzyko awarii w lokalnych systemach rozdzielczych, Scientific

Conference „Blackout”, Poznań 2010.4. Bargiel J., Goc W., Sowa P., Teichman B., Średniookresowy deficyt mocy i energii elektrycznej, Scientific Conference

„Rynek Energii ’10”, Kazimierz Dolny, June 2010.


14Paweł Bućko / Gdańsk University of Technology


Paweł BućkoGdańsk / Poland

The author works at the Power Engineering Department of Gdańsk University of Technology. His scientific activity is associated with the powersector’s economics with special consideration to issues of power system development planning in market conditions. His professional activity is focused on capital expenditure analysis for renewable generation sources and on analysis of market mechanisms and settlement of accounts principles in electricity supply. He is also an energy auditor and deals with issues of rational energy usage.

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Abstract

The article presents a model of regulating ancillary services provision in a decentralised manner. A concept of the operation of local markets for ancillary services is presented. Exploitation of the service provision capabilities of recipients, distributed sources,

and local system operators is proposed. The role of Distribution System Operators is discussed, as well as of energy traders, as intermediaries in the procurement of regulating services from distributed providers.

A DECENTRALISED MODEL OF THE REGULATING ANCILLARY SERVICES MARKET

Paweł Bućko / Gdańsk University of Technology

This study has been financed with funds allocated to science in 2008-2010 as research project N511 376235

1. INTRODUCTION

Currently, ancillary services are procured and managed in a centralized model by the Transmission System Operator (TSO). The services procurement mechanism, although included in the mechanisms of Balancing Market (BM), in practice operates as a separate mechanism, especially in terms of trade. Integration covers mainly the technical aspect of BM operations [3, 4]. Power required in various types of reserves is treated as a technical limitation in the development of daily coordination plans. System power plants mainly participate in the provision of the services; the biggest recipients may be involved to a very limited extent. Price for the services is not determined in an auction cycle, but their pricing is based on either simplified estimation of theservice provision costs (with regard to primary and secondary regulation), or at the rate negotiated in bilateral agreements (with regard to emergency reserve, prices are determined on the basis of the rates negotiated in annual contracts). Primary and secondary reserve is valued based on the prices for generation forced in sources, which result from cost-based pricing and in practice are regulated prices. Emergency reserve is priced based on the rates negotiated in annual contracts. The rate cannot be currently modified in relation to the actual systemcondition. Therefore, in practice there is no active competition of reserve suppliers.

The mechanism needs to be modernized if the services are to be provided under competitive conditions. It is proposed to decentralize the regulation services management. In order to exploit the opportunity to provide services by distributed sources and receivers, it is appropriate to introduce intermediaries to the regulating services market. The task of these traders is to aggregate the capabilities of distributed entities and to manage the service provision. In a natural way such traders may assume the role of Distribution System Operators (DSOs). It is proposed to establish local balancing markets managed by the DSOs, and operating as a complement to the system BM. Establishing local balancing markets must be associated with a modification of the system market’soperating principles.

The power reserves necessary for the system’s safe operation is strictly conditioned by the achievable accuracy of demand forecasts. Currently, in the centralized structure of regulating services management, the reserve requirements are adjusted to the system demand forecast. This leads to their overestimation. The current central demand forecast not only increases the required power reserves, but also does not create conditions for use of any regulating mechanism other than that on the generation side. Lack of stimulating mechanisms renders recipients’ regulating capacity practically unused. The market decentralisation may provide such stimulation.

Supply of various services is not evenly distributed in the system. Distributed generation’s current small share in the total generation in the system means that the available range of primary and secondary regulation is concentrated in large system power plants. Market decentralization (in the current generation structure) with regard to primary and secondary regulation will not at present bring about big benefits. The situation will changequalitatively only as the generation capability decentralisation progresses. Distributed sources’ increased share will increase the supply of such services in the area under DSOs’ management.

A Decentralised Model of the Regulating Ancillary Services Market

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The emergency reserve services supply distribution and energy balancing capabilities between the transmission system area and the distribution system areas are more balanced. It is hereby proposed that the decentralization of balancing and services procurement in the first phase will relate to these regulating activities.Most of the effects of implementing these markets’ can be achieved through the launch of organizational activities, and their expected effect will consist in the generation of incentives to exploit the regulating capabilities of recipients and DSOs’ active role in the system balancing management.

Decentralization of the regulating services procurement for secondary reserve will effectively be possible if accompanied by decentralisation of the secondary regulation structure in the system. Due to the significantcosts of implementing such structures, its rationale may be analyzed when the supply of these services in the DSO areas of OSD has considerably increased. The decentralisation’s second phase will be conditioned by the appropriate development of distributed sources.

2. MODIFICATION OF THE SYSTEM BALANCING MARKET OPERATION

2.1. Changes in the Balancing MarketThe following medications are proposed for the Balancing Market’s mechanisms:• primary and secondary regulation services should be priced based on an offering mechanism, subject

to rules similar to the energy balancing service procurement rules• procurement of balancing energy and regulating power reserves should be optimised together,• buyers (recipients, traders, and DSOs) should be capable of assuming active positions in the BM

mechanisms,• DSOs (and traders) should be capable of the emergency reserve service provision (agency in service

procurement in the distribution grid areas).The evolution of secondary regulation related market mechanisms may aim at further decentralization,

associated with the introduction of a hierarchical and pluralistic structure of the secondary regulation in the system. This phase may be contemplated in the event of distributed generation’s significant development in thedistribution grid areas.

2.2. Primary and secondary regulation bidding mechanismCurrently the Schedule Units offering primary and secondary regulation do not quote prices for these

services. The service provision is priced for each customer individually based on the forced generation cost. Therefore the service providers cannot compete on price. In order to enable such competition, it is proposed that entities obliged to maintain the efficiency of control systems shall submit price bids for the service provisionin daily cycles, synchronized with price bids for balancing energy submitted to BM.

The demand for reserves in primary and secondary regulation for each hour of the day shall be determined, like presently, on the basis of technical criteria.

In such a case the service providers are selected based on the price quotes’ auction. It is proposed that the services for each supplier shall be billed based on the equilibrium price for the hour of trade. This settlement of accounts method increases the market participants’ tendency to submit bids resulting from actual costs incurred by the bidder. To avoid the abuse of market power by dominant players, it is proposed to set an upper limit for an acceptable market bid contingent upon the costs incurred by the service provider. Due to the complicated service provision costing rules, it is proposed that the upper price bid limit for a Schedule Unit shall be dependent on the forced generation cost determined for the purpose of BM.

At present the basic elementary interval of time for electricity billing in domestic trade is one hour. In such settlements the effects of second and minute regulations are often averaged and do not consider the power plant units’ actual participation in the regulation. In settlement of accounts for the balancing energy resulting from implementation of second and minute regulations

the system condition should be identified more frequently than once every hour (e.g. every few minutes).It seems that the most reasonable would be to introduce billing by the ex post principle, on the basis of the system condition’s temporary identification. To simplify the billing process, the temporary prices may beintegrated over longer periods of time, e.g. hours.


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2.3. Joint optimisation of balancing energy and regulating power reserves procurementAll regulation reserves and balancing energy should be procured on the joint optimisation principle. The

criterion should be the total of all costs incurred by the BM operator. The currently used criterion leads to minimization of the balancing energy procurement cost (including costs of forced generation and of starting the units). After supplementing with the regulating services procurement cost items, the criteria function has the following formula:

where:OPChi – price bid of the schedule unit for the provision of primary reserve service in the hour hPjh – scheduled usage of primary reserve of the schedule unit i in the hour h OWChi – price bid of the schedule unit for the provision of secondary reserve service in the hour hPjh – scheduled usage of secondary reserve of the schedule unit i in the hour h OIChi – price bid of the unit i for the provision of emergency reserve service in the hour h RIhi – scheduled usage of emergency reserve of the schedule unit i in the hour h OFChik – price bid for electricity generation in the range k of the bid of the schedule unit i in the hour hEhik – scheduled electricity output in the range k of the bid of the generation unit i in the hour h CWi – price for forced generation by the unit iERhi – electricity input to the system during start of the generation unit i in the hour h, in the amount resulting from the initial start up conditions and the relevant start up characteristicsRZhi – decision variable (0 or 1) representing start up of the generation unit i from the cold state ending in the hour hCUZi – price for start of the generation unit i from the cold stateRChi – decision variable (0 or 1) representing start up of the generation unit i from the warm state in the hour hCUCi – price for start of the generation unit i from the warm stateRGhi – decision variable (0 or 1) representing start up of the generation unit i from the hot state ending in the hour hCUGi – price for start of the generation unit from the hot stateNO – number of the generation units submitting balancing bidsHk – number of hours covered by the optimisation.

Benefits of the joint optimisation of purchase costs of various regulating services are accounted for inanalyzes of various power systems [1, 5, 6, 7].

2. 4. Active participation of buyers in Balancing MarketAt present electricity buyers are represented on BM by passive schedule units. Allowing active participation

in the balancing of schedule units assigned to the BM participants that take electricity buyer positions is meant to allow these units’ submittal of offers for reducing energy demand, at certain price levels determined in the offers. Inclusion in the electricity balancing of offers submitted by buyers will have an impact on the level of global settlement prices designated for BM.

(CRO prices and derivatives). The buyer’s offers will be competitive to the now accepted offers of generation units. In addition to influencing the MB price level, the receiving schedule units’ active position is supposedto enable trading and distribution companies’ brokerage in the submission of the aggregated regulating bids obtained from entities dispersed in the distribution grid or participating in balancing groups.

2.5. Provision of emergency reserve service by Distribution System Operators and trading companies

Currently, the emergency reserve service may be provided by pumped storage and gas power plants (via active TSO Schedule Units) and end-recipients (who have entered into a contract for the provision of the

RPp

RWp


18

service with the TSO). Due to the scale of the system Balancing Market, the TSO is willing to enter into contracts for the emergency reserve service provision directly with recipients, who are ready to offer sufficiently largepowers – the pool of potential service providers narrows to the largest recipients with the technical capabilities of dispositional control of their own consumption. Also medium-sized industrial recipients have these technical capabilities, but due to the smaller powers they offer they may not conclude agreements directly with the TSO.

It is proposed to allow the emergency reserve service provision by trading companies Distribution System Operators. They could offer the service in quantities suited to the scale of BM, and they would make adequate power available as a result of aggregation the capabilities of entities dispersed in their own grids.

2.6. Decentralisation of secondary reserve procurementThe current structure of the system and the existing regulating solutions are adjusted to centralised

procurement of the secondary reserve services and its use by the ARCM system controller. The small share of distributed generation makes these sources remain largely outside the central dispatch or TSO’s coordination. As a consequence, they are not used for the secondary reserve service provision, and this function in the system is fully implemented by large system power plants.

If the share of distributed generation will grow, then utilisation of these sources’ capacity for the secondary reserve service provision should be considered. Effective utilisation of the distributed reserves for secondary regulation will be possible if the configuration is modified with secondary regulation automatic controls in thesystem. The current system with one central regulator may be replaced with a system with several areal regulators and one central regulator that collaborate in a pluralistic or hierarchical system. A pluralistic structure is the most adequate to the current ties relative to organisation of the electricity commodity market at the KSE National Power System with the wholesale and retail markets. As shown in [2], in the case of decentralized regulation, organized in a pluralistic structure, there are fewer consequences in terms of regulation energy flows betweenregulation areas, and if the structure of separate areas is properly planned it is easier to organize the energy market, and the interareal settlements for energy flow in particular. To achieve this, there must be sufficientsecondary regulation reserves available in each regulation area. Implementation of a decentralized structure should be correlated with the rate of decentralization of power generation in the system. Decentralization will allow for efficient use of local regulation reserves and will be an additional incentive promoting furtherdevelopment of distributed generation.

It should be noted, however, that modification of the secondary regulation structure will require extensionof the data and regulation signals transmission system.

3. LOCAL BALANCING MARKETS

3.1. Local balancing market tasksIt is proposed to establish local balancing markets in the grid areas managed by DSOs. The purpose of

such markets should be to use local energy balancing capabilities of the recipients and generators connected to the distribution network, who are not subject to the central coordination provided by TSO.

The result of establishing such markets by DSOs should be the possibility to actively control non-balancing of an area for the purpose of settlement on the system Balancing Market, by utilisation of the balancing bids submitted to a DSO on the local market. A consequence of the establishment of local balancing markets should be providing the local market operators with the option to make active bids for schedule units of such participants of the system BM. A local market operator can then act as an intermediary and aggregator in the energy balancing service provision between distribution grid areas and the system BM.

Following the local balancing market establishment DSOs will obtain the opportunity to reduce the cost of participation in the system BM and to submit balancing bids (resulting from balancing offers locally acquired) to the system market. The system BM will use balancing bids submitted by local market operators, according to the rules of competition of bids accepted at the system BM.

It is proposed that within local balancing markets the energy balancing service shall be acquired, as well as the emergency reserve service. At present there are sufficient technical resources to provide such services in


19

distribution grid areas. In the future, when the supply of other services to local markets increases (mainly due to distributed generation development), expansion of the scope of such markets’ business with other types of services should be considered. The introduction of a secondary reserve as a service to local markets will require the secondary regulation structure decentralization discussed earlier.

3.2. Local energy balancingThe local energy balancing service will be procured in a local balancing market on the basis of offers

submitted by recipients (for energy consumption reduction) and generators (for output increase/reduction compared to the contractual position), and traders (for change in the energy consumption by a balancing group). It is proposed that the formulation of offers on a local market and optimisation of their selection by a local market operator shall be similar to the rules of the system BM.

Simplification of the rules of offering on a local market with respect to offering time periods is proposed.Submittal of offers with validity periods over one day should be permitted. In designing the offering process the organizational costs of potential market participants should be limited. The daily offering requirement may impede participation in the market, particularly as regards recipients.

The possibility of current use of energy balancing offers requires modification of the dispatch proceduresof the power of distributed sources and recipients by DSOs. Effective exploitation of recipients’ balancing capabilities requires the offered power’s availability to DSO dispatch. The service should be activated in a manner agreed with the dispatch (automatic response to signals transmitted from DSO, or access to power by way of remote command). As regards recipients who announce their willingness to participate in the energy balancing, remote (from DSO) control is possible of the power of specific receivers (in accordance with the general principlesagreed between the DSO and the recipient) or by sending remote commands to the recipient. As regards exploitation of a recipient’s balancing offer it is appropriate to establish rules of recipients’ prior notification ofthe need to use the offer by the DSO in advance, stipulated in the respective bilateral agreement.

A portion of the power used by a DSO on the recipient side may be procured by way of DSM procedures. The accounts for an energy balancing service so provided may be settled between DSO and the recipient, whose offer is used, subject to rules different from the general billing principles on the respective local balancing market. The settlement shall be tailored to the principles adopted in the demand side control strategies in use in the respective area.

3.3. Procurement and usage of emergency Making emergency reserve available to a local market should be (as in the system market) preceded by

conclusion of a future contract for the service provision by and between the DSO and the supplier. Accounts for the service provision (because of its probably rare use) should in all cases be settled on the basis of two rates negotiated with the service provider (stipulated the future contract):

• for the readiness to provide it (billed at a time when the regulating power is available for the DSO’s dispatch),

• for the usage (billed with regard to the regulating energy obtained from the supplier as a result of the service’s deliberate use by the DSO).

The readiness to provide the service should be procured on the basis of periodic auctions, organized by DSOs in the areas of the respective local balancing markets. The following entities may provide the emergency reserve service to a local market:

• generators with technical capabilities of emergency power’s fast delivery to the system (gas-fired,hydro),

• recipients offering the option of quick reduction of their energy consumption,• traders that intermediate in submitting offers of the market participants included in a trader’s schedule units.Contracts for the emergency service provision should include agreed rules of quick access to the power

and, possibly, principles of prior notification of the need to use the power.DSO may use DSM strategies for exploitation of the emergency power located at distributed recipients.Exploiting the emergency reserve offers obtained from a local balancing market the local market operator

may submit aggregate offers to the system BM. The DOS role shall be limited to the intermediary in the service provision. The emergency reserve service shall be used to restore secondary regulation reserves.

After possible decentralization of the secondary regulation structure, the emergency reserves shall be in the first instance used to restore local power reserves in secondary regulation.


20

REFERENCES

4. LOCAL MARKET IMPACT ON THE SYSTEM MARKET OF REGULATING SERVICES

Local markets should create a competitive offer for the service providers on the system BM. Exploiting the regulating offers obtained from their local markets and aggregating them to the volumes that may be offered on the system market, local market operators will create a competitive offer for the existing service providers. With the proposed organisation of the markets, the competitive offer of the service will mainly focus on balancing energy and emergency reserve.

Local use of reserves for areal balancing will allow for a reduction of the operating costs of system BM participants operators RB (demand for balancing energy in this market will decrease). In the context of local balancing market operations not only the exploitation of dispersed balancing capabilities is important, but also the opportunity to forecast the demand more accurately than on the system market. The effect of these two factors should reduce the global balancing costs.

It is expected that in the proposed structure the main effect will be achieved through the exploitation of local balancing capabilities, while the balancing energy transfer to the system market will be an additional effect of a smaller scale.

In this author’s opinion, in order to propose a secondary regulation market structure it is necessary to obtain the ability to cover the local demand for the service. An undesirable situation is when the structure of markets and allocation of regulating power would require large flows of regulating energy: intertribal andbetween areas and the system market. The purpose of the local markets’ establishment should be to exploit local regulating reserves and to create incentives for their development.

1. Arroyo J.M., Galiana F. D., Energy and reserve pricing in security and network-constrained electricity markets, IEEE Trans. on Power Systems, vol. 20, no. 2, 2005.

2. Bućko P., Usługi systemowe w zdecentralizowanych układach regulacji wtórnej, Rynek Energii, No. 4 (89), 2010.3. Bućko P., Konkurencja w dostawie regulacyjnych usług systemowych, Rynek Energii, No. 2, 2008.4. Bućko P., Usługi regulacyjne w uwarunkowaniach wynikających z funkcjonowania Rynku Bilansującego, Archiwum

Energetyki, 2007 , vol. XXXVII, specjal issue: XII International Scientific Conference “Current Problems in Power Engineering– APE07” , 2007.

5. Chen J., Thorp J.S., Thomas J.R., Mount T.D., Locational pricing and scheduling for an integrated energy-reserve market. Proceedings of the 36th Hawaii International Conference on System Sciences, IEEE, January 2003.

6. Chicco G., Gross G., Competitive acquisition of prioritizable capacity-based ancillary services, IEEE Transactions on Power Systems, vol. 19, issue 1, Feb. 2004.

7. Korab R., Łączna optymalizacja energii bilansującej i operacyjnych rezerw mocy na konkurencyjnym rynku energii elektrycznej, Przegląd Elektrotechniczny, No. 9, 2006.


22Krzysztof Dobrzyński, Jacek Klucznik, Zbigniew Lubośny / Gdańsk University of Technology


Jacek KlucznikGdańsk / Poland

Graduated as master of science from the Faculty of

Electrical and Control Engineering at Gdańsk University

of Technology in 1999. Five years later he obtained his

Ph.D. An assistant professor at the Power Engineering

Department of Gdańsk University of Technology. His

areas of interest include control systems for generators

and turbines, wind power generation, and power system

automatic protections.

Krzysztof DobrzyńskiGdańsk / Polska

Graduated from the Faculty of Electrical Engineering of Warsaw University of Technology in 1999. Since 2005, an assistant lecturer at the Department of Electrical and Control Engineering of Gdansk University of Technology. His areas of interest include cooperation of distributed generation sources with the power system, mathematical modelling, power system control, and intelligent systems in buildings.

Zbigniew LubośnyGdańsk / Poland

Mr. Lubośny graduated from the Department of Electrical

and Control Engineering Gdansk University of Technology

in 1985. In 1991 he defended his doctoral thesis, and

eight years later obtained a post-doctoral degree at the

same university. A professor of engineering since 2004.

Currently an associate professor at Gdańsk University of

Technology. His areas of interest include mathematical

modelling, power system stability, power system control,

use of artificial intelligence application in power system

control, and modelling and control of wind turbines.

23

APPLICATION CAPABILITIES OF THE MAXIMUM DISTRIBUTED GENERATION ESTIMATE METHODOLOGY

Krzysztof Dobrzyński / Gdańsk University of TechnologyJacek Klucznik / Gdańsk University of Technology

Zbigniew Lubośny / Gdańsk University of Technology

1. INTRODUCTION

For several years a relatively high investor interest in wind farm development has been observed in Poland. This is directly related to the Polish state’s effort to meet the obligations which Poland faced with its accession as a full member to the European Union structure. These commitments obligate, among other things, to a certain percentage share of electricity generated from renewable sources in the country’s total electricity output. Because of the conditions presently existing in Poland, wind power generation faces the biggest growth prospects. This is evidenced by the number of applications submitted to the Polish transmission operator for the range of connectivity study, or by the number of grid connection requirements issued. Such a prospect of wind power generation rapid development confronts the transmission operator and distribution operators with many problems to solve. One of the major problems is the possibility of connecting these sources to the power system, the parameters of which are the allowable powers which can be connected to the SEE power system’s nodes.

Because of its generality, the methodology presented in this article can be applied not only for distributed generation (including wind generation), but also for consideration of connectivity of other electricity sources (e.g. classic thermal power plants).

2. ESTIMATION ALGORITHM FOR THE MAXIMUM POWER IN DISTRIBUTED GENERATION SOURCES

Connection of an electricity source to a power system is related to the fulfilment of certain requirementsof the power system’s safe operation. These requirements are grounded in dedicated standards and legal documents. Based on them, key criteria may be specified that should be considered upon connection of a newsource to the system. It should be noted that these criteria (their number and type) strongly depend on the type of source and its installed power. Other criteria will be relevant to connection of a photovoltaic source to a low voltage (LV) grid, and others to consideration of connection of a wind farm with power of several MW to a high voltage (HV) the grid. The criteria applied to a calculation algorithm determine its universality. In the presented algorithm the following criteria are used for assessing the impact of energy source on a power system:

• harmonic content of voltage and current,• active power fluctuations, and thus system frequency fluctuations and exchange power fluctuations• short-circuit parameters• local stability• global stability• electricity quality in terms of voltage fluctuations and short-term and long-term flicker• load of power system branches

Application Capabilities of the Maximum Distributed Generation Estimate Methodology

Abstract

The paper presents application capabilities of the maximum distributed generation estimate methodology. This subject is an example of solutions to the problem that today face the transmission system operator and

distribution system operators, which is related to the high saturation with wind power generation predicted for the near future.

24

Application of the algorithm leads to determining what power can be connected to selected nodes in the system using electricity sources of specific types. To determine this power the objective function is used, theformulation of which depends on whether the power is estimated in a single node, or in multiple nodes.

The objective function for single node power estimate is as follows:

(1) ,minw j wK k

, , ,1

n

j w i w i wi

k

where:Kw – objective function value in the node wj – configuration j dependent on input parameters, e.g. source typei – criterion iw – node w, if the maximum power is estimated in the selected node, w = 1k – objective function value for the configuration j in the node wαi, – weight of the optimisation criterion i in the node wξi, – criterion function, the formulation of which depends on the criterion i in the node wUltimately looked after is the maximum power Pmax, which can be connected to the selected node w.

(2) , max ,j w wk f P j

On the other hand, when estimating the power in n-nodes the objective function’s formula is as follows:

(3) minl lH h

1

m

l ww

h K

where:l – calculation variant, depending on the number of nodes adopted in the analysis, the locations of these

nodes and the criteriahl – sum, which consists of the values of the objective function Kw (1) determined in the analysed nodesm – number of the nodes considered in the analysis.Using the objective function (3) looked for in the summary power PMAX equal to the sum of maximum

powers P determined in the given variant l, in the analysed nodes w:

(4) ,l MAXh f P l

The objective function (1) used in the presented algorithm equals the sum of the products of criterion functions ξ and the weight function α, defined as follows:

(5)

, ,

2, , , ,

, , , ,, ,

0 dla

dla

i w i w

i w i w i w i wi w i w i w i w

i w i w

a

ab a c

c

where:ai,w, bi,w, ci,w – the weight function parameters for the criterion i.The power estimate algorithm’s overall structure is presented in Fig. 1. This structure provides for the

determination of many input parameters, the purpose of which is to define a variant, which we want to analyze.

Krzysztof Dobrzyński, Jacek Klucznik, Zbigniew Lubośny / Gdańsk University of Technology

25

Fig. 1. Overall structure of the maximum power estimate algorithm (Territorial division of distribution system operators, DSO)

3. APPLICATION CAPABILITIES OF THE MAXIMUM DISTRIBUTED GENERATION POWER ESTIMATE METHODOLOGY

Algorithms, such as the algorithm presented in this paper, are currently implemented using specialist computational programs for modelling and simulation of power systems. This may be accomplished in either of the following two ways:

a) Algorithm implementation in computational programmeMost of the computational environments provide the opportunity to control the computing process through an internal programming language1. Using a defined syntax and built-in functions a user canto a certain extent affect the calculation process, as well as implement own operating algorithms. The feasible range of calculations will vary depending on the computing environment’s characteristics. The disadvantage of this approach is cumbersome operation if a large number of parameters need to be set before running the programme. Then, at least, the user’s basic knowledge of the internal programming language is advisable. And yet working with such a programme is still quite uncomfortable.

Criteria• Harmonic content• Power and frequency control• Short-circuit parameters• Local stability• Global stability• Voltage stability• Voltage fluctuations• Allowable power system load

Input parameters• System structure• System operation point• Existing DG in system• System technical limitations• Electricity source type• Single-node variant• Node relevance level• Node ranking

ALGORITHM

OBJECTIVE FUNCTION

Pmax

1 E.g. in Pslf environment Epcl programming language is available, in Plans environment macros are available, and in DIgSilent environment DPL programming language.


26

b) Using computational programme as an environment for calculationsAnother way to implement one’s own algorithm is to use the program as a computational environment to perform calculations. In this case, data may be prepared, input and control parameters set, and results presented in an external program, implemented in any programming language, e.g.: C, C++, Visual Basic, Java. A prerequisite here is the ability to activate a subroutine written in the computing environment’s programming language from the command lines of Windows operating system2. Owing to such implementation, the end user does need to know the computing environment, and works in the external program only.

Fig. 2 presents the structure of a dedicated external programme’s cooperation with the computing environment.

2 Only Windows operating system is there considered.

Fig. 2. Structure of external programme’s cooperation with computing environment

c) Algorithm and calculation process implementation in an external programme. This solution allows full tailoring of the software tasks to the end user’s needs, but such a programme’s development requires a lot of work.

4. AN EXAMPLE APPLICATION OF THE MAXIMUM DISTRIBUTED GENERATION ESTIMATE METHODOLOGY

This example application implementation of the maximum power estimate methodology involves an external programme as controlling software. It was developed in Visual Basic Express programming language. Plans platform was used as the computing environment. The data exchange diagram is presented in Fig. 3.

Input parameters

Application including:Maximum

PowerEstimateAlgorithm

Calculationengine

Results

Model

+ ΔPGRI

Calculationresults


27

Fig. 3. Data exchange structure in the maximum distributed generation power estimate example application

In the presented application the Plans programme was used as the computing software, and therefore the objective function could not take into account the criteria that are determined by way of dynamic calculations (Plans can only do static calculations).

The work with the application begins with entering the power system model in *.KDM format3. Then a working directory is selected and access path to the Plans program’s boot file. In the next step the existingdistributed generation sources may be considered that have not been previously modelled in the loaded system model. For this a user pre-prepared text file is used, whereby connection nodes, source powers, sourcetypes, and the source power factors are specified. With this approach, by creating multiple files with differentconfigurations, the user can in a simple way obtain the possibility to use multiple deployment variants of theexisting distributed generation. Such an approach with existing energy sources is used, for example, for expert assessment of wind farm connectivity, where individual calculation variants differ in terms of saturation with wind farms.

The next step is selection of the criterion conditions that should be included in the objective function. At the same time by changing parameters of the weight function (5) the impact of individual criteria on the objective function value is differentiated. Then the node(s) is/are selected for potential connection of new sources. The nodes selected may be divided into two groups with relevance levels I and II. Relevance level I nodes are analysed first, and their powers are estimated until the allowed or preset power is reached. Then thepowers of relevance level II nodes are estimated. Besides such nodes classification according to their relevance,a power increase sequence (node ranking option) may be determined.

In the next step the user decides how to stop the simulation. The following three options are available:• Upon excess of any criterion condition

In the single-node analysis this means the end of calculations. In the multiple-node analysis upon excess of any criterion the respective node is excluded from the analysis, and if the criterion is of a

Criteria (constraints)• allowable branch loads• allowable voltage levels• flicker• etc.

Additional assumptions• Nodes• DG source parameters• n-1 analysis• gradation• ranking• Pmax in system• Pmax in node

Plans+

macros

+ ΔPGRI

Calculationresults

Results

Flow data

*.KDM

3 File format used by Plans program.


28

general nature (such as, for instance, load of the system’s branches) the node of the highest impact on the exceeded criterion is excluded.

• Upon reaching allowable powers preset for individual nodesThe algorithm enables presetting the maximum allowable power for each node individually. This is particularly useful where a user knows the rated powers of individual sources and is determining their connection points. This allows analyzing various connection points, and determining the most appropriate ones based on the received series of values associated with each criterion, and based on the values of the objective function.

• Upon reaching a summary allowable power preset for all nodesIn this case a single power is predetermined as the sum of all node powers. The analysis is stopped when the sum of the analysed sources’ powers has reached such a predefined value.

The next input parameter is selection of the system area for the analysis. It is appropriate in cases where connection of sources in a particular area, such as a branch of Distribution Company (DC), is considered. It is then advisable to narrow the analyzed area to the branch and, possibly, to the directly adjacent branches.

Then the types of the electricity source in the analysed nodes are determined. With the source types, data of the harmonic current input from the source is associated, and parameters associated with the quality of electricity (allowing one to designate electricity quality indicators, such as flicker, for example). The data isstored in text files; therefore, a user can easily enter a new source type to the programme. In addition, powerfactors are specified for the sources, and neutral point operating regimes for the transformers that connect thesources with the HV grid. In addition, in each analysed node the short-term and long-term flicker that occursbefore the analysed source’s connection may be determined.

The next step allows consideration in the estimation process of the “n-1” states, whereby a user may select the branches to be switched off.

Once the above described input parameters have been set, the stimulation process is started, which involves cyclical activation of the Plans environment. In each such cycle power in the subsequent analysed node is increased by ∆P, calculations are made, and data transferred to the controlling programme.

The end outcome of the analysis is presentation of results, which include a lot of information, such as, for example:

• changes in values related to the criterion conditions considered, in the function of power changes individually for each analyzed node

• powers obtained in each node• objective function values for each node and for all nodes• reason to stop node’s analysis (excess of a criterion condition or reaching a preset power)• list of the most loaded nodes in each step of the analysis• nodes with minimum and maximum voltage.


Fig. 4. Example estimate of the maximum power that may be connected to the power system’s individual node

29

REFERENCES

4 Using the Plans program proposed static calculation may be performed. If calculations are needed that cover the entire standard scope of connectivity study, then calculations should be performed on the dynamic model as well. For this, instead of Plans, another calculation environment should be used that enables dynamic calculations, such as the Pslf platform, for instance.

Besides the text format, the results are also presented in a graphical format. Fig. 4 presents an example radar graph showing changes in the considered criteria, numbered in the diagram for reference.

The criteria are expressed here in relative values, and the various markers denote the following:• – initial value of the criterion• × – final value at the end of the estimation process• – above this value the criterion affects the objective function• ◊ – limit value of the criterionThe graph shows that the power estimate process for the analysed node is stopped because of criterion

No. 11 (branch load in the system). Also easily readable from the graph is how individual criterion values were changing and how far they are from their respective limits.

5. SUMMARY

Potential rapid development of wind power generation forces the transmission operator and distribution operators to undertake intensive efforts aimed at determining the possibility of connecting new generation capacities in specific areas of the system. Recent amendments to the legislation have imposed the burden ofconnectivity study development on operators, and there are basically two ways to obtain such studies. The firstway is to outsource it, the other to do it in-house. The presented methodology of the maximum power estimate, and the application based on it, constitute a tool that can be helpful in the process of connecting yet another electricity source to the power system. On the one hand, the application can be used to perform automatic calculations for the purpose of connectivity study4, on the other hand, it enables verification of results obtainedby an external provider of such a study.

1. Dobrzyński K., Metodyka szacowania maksymalnej generacji rozproszonej ulokowanej w elektrowniach wiatrowych, doctoral thesis in progress.

2. Dobrzyński K., Lubośny Z., Metodyka szacowania maksymalnej generacji rozproszonej ulokowanej w elektrowniach wiatrowych, XII XII International Scientific Conference “Current Problems in Power Engineering – APE’05”, 8–10 June2005, Gdańsk–Jurata.

3. Lubośny Z., Elektrownie wiatrowe w systemie elektroenergetycznym, WNT, Warsaw 2006.4. Lubośny Z., Farmy wiatrowe w systemie elektroenergetycznym, WNT, Warsaw 2009.5. Kundur P., Power System Stability and Control, McGraw Hill, Inc. 1993.6. Instrukcja Ruchu i Eksploatacji Sieci Przesyłowej.7. Instrukcja Ruchu i Eksploatacji Sieci Dystrybucyjnej.


30Zbigniew Hanzelka / AGH University of Science and Technology Grzegorz Błajszczak / PSE Operator SA


Zbigniew HanzelkaKraków / Poland

A professor at the Institute of Electrical Drives and Industrial Equipment Automation of AGH University of Science and Technology Author and co-author of more than two hundred articles and chapters in books. Editor of Electrical Power Quality & Utilization magazine. The areas of the co-author’s interest include electricity quality, and in particular reduction of the adverse impact of static converters on supplying grid. A member of scientific committees of numerous internationaland national conferences, international and national engineering organizations, i.e. IEC, UIE, CIGRE, PKN, The Electrical Engineering Committee of PAN (The Polish Academy of Sciences), Chairman of the Scientific and EngineeringCommittee of SEP (The Association of Polish Electrical Engineers) for Electricity Quality.

Grzegorz BłajszczakWarsaw / Poland

In 1984-1994 a research fellow at Warsaw University of Technology, and then at Budapest University of Technology and Rand Afrikaans University in Johannesburg. Specialist in International Relations at Energoprojekt Warsaw SA (1994-1995), Drives and Backup Power Manager at French company Schneider Electric (1995-1996), Training and Implementation Deputy Director at the European Process Control Division of Westinghouse Electric (1996-1999). Since 1999 employed at PSE Operator SA firstin system services, then in international energy exchange settlement, and now in new technologies implementation, and energy quality and reactive power management. A member of SEP, IEEE, CIGRE, Eurelectric, KT w PKN, The Energy Economics Committee of NOT Central Technical Organisation, The Polish Committee for Electricity Quality and Effective Utilisation. An expert in electricity quality, and author of over 100 scientificand technical publications.

31

A CONCEPT OF RECIPIENT ALLOWANCE SYSTEM FOR SUPPLIER’S FAILURE TO MAINTAIN THE REQUIRED VOLTAGE QUALITY

Zbigniew Hanzelka / AGH University of Science and Technology Grzegorz Błajszczak / PSE Operator SA

1. VOLTAGE QUALITY ASSESSMENT

The level of voltage quality, which is to be ensured by the electricity supplier, is defined in the legislation(e.g. [4]) by means of a set of featured indicators. These regulations do not specify, however, the consequences of failure to comply with these parameters. Nor are there tools available to facilitate the launch of an effective benchmarking mechanism for voltage quality. The existing indicators make this process difficult, and the resultsare ambiguous, as shown by the first Polish benchmarking report [2].

1.1. The overall voltage quality indicatorIt is here proposed to establish an aggregate and overall voltage quality indicator CWJU, which is based

on a set of the traditional (in accordance with the current wording of “the system regulation” [4]) numerical measures of individual disturbances. It would be determined on the basis of excesses over the permitted levels collected during one week of measurements by numerical measures describing various disturbances of a continuous nature: slow changes, higher harmonics, unbalance, and fluctuations of voltage. This indicator maybe extended so as to include in the future also assessment of voltage events. The CWJU indicator is determined by the relative values of the numerical measures of individual disturbances related to their acceptable levels. If all the disturbance rates are less than 1, the indicator CWJU is equal to the maximum value in the set of individual disturbance rates.

4321 ,,,max WWWWCWJU (1)

If one or more rates exceed 1, CWJU equals 1 plus the total of acceptable level excesses. If N disturbances exceed their respective acceptable levels, then CWJU equals:

N

iiiU WkCWJ

11 (2)

The fact that the detrimental effect depends on the types of disturbances and the receivers under their influence may be taken into account by weighting factors ki, related to each individual excess. Each weighting factor can assume a value between 0 and 1 and can be negotiated between the parties: the electricity supplier and recipient. The value of CWJU indicators is the basis for determining the voltage quality grade in a measurement point under consideration: grade Z (satisfactory, CWJU < 1), G (acceptance limit, CWJU = 1) or grade NZ (unsatisfactory, CWJU > 1).

Abstract

The article presents a proposal to establish an overall (aggregate) indicator determined on the basis of a set of the traditional numerical measures of individual disturbances, as a point and system level numerical measures of voltage quality. The following three quality grades are distinguished on this basis: Z, G and NZ. In the authors’ opinion their establishment would facilitate comparative analysis between featured elements of the

national power system, i.e. between regions belonging to a single operator, between various operators, and between divisions within the transmission operator’s grid. The following two levels are proposed for the voltage quality regulation and the allowances system: (a) - local, i.e. taking into account the interaction of electricity suppliers and recipients at the point of common connection and (b) - system.

A Concept of Recipient Allowance System for Supplier’s Failure to Maintain the Required Voltage Quality

32

1.2. Calculation of overall voltage quality indicator component ratesSlow voltage change rate W1 = WUIf ΔT[%] > 95, where ΔT[%] is the percentage share of the time in the week, during which the voltage is

contained in the change range allowed by provisions of the system regulation or by the connection agreement, i.e. (U min - U max ), then:

increasereductionU UUW ,max (3)

U

downward deviationUreductionU

,

max,

U

UincreaseU

,

max,

downward deviation

upward deviation

upward deviation (4)

τΔUmax, downward deviation

(τΔUmax, upward deviation) the maximum recorded voltage deviation downwards (upwards) from the nominal value or the declared value out of the three phase or phase-to-phase values, measured at the grid point under consideration in the assumed time of the assessment (10 minute average, PN EN 61000-4-30)

τΔU, upward deviation

(τΔU, downward deviation) he maximum allowable downward voltage reduction, which according to [4] in HV grids amounts to: -10%; and the allowable voltage increase in 110 and 220 kV grids: +10%, and in 400 kV grids: +5%.

The deviations are determined based on the following formula:

C

CU U

UU (5)

- 10 minute average of measured voltage RMS Uc – declared or rated voltage RMS (as stipulated in the connection agreement or provided for in the

system regulation [4].Relative value of WU rate equal to 1 means that the disturbance’s statistical measure is on the brink of

acceptance, any value greater than one – means an excess of the allowable level, any value less than one - means that the quality requirements are met. This applies to all numerical voltage quality measures referred to hereafter. On this basis the excess level:

(6) 11 UU WWW

If ΔT[%] < 95 then: ΔW =Δ W1 = 0. If CP99 percentile is adopted in the regulations (e.g. as per EN 50160:2010), 99 shall replace 95.

Voltage distortion rate W2 = WH

,...,,,max 432 FFFWW THDUH (7)

(8)

allowable levelTHDU THD

THDW

40...,3,2,

95,

hh

CPhh U

UF

allowable level


33

THDCP95– the maximum CP95 percentile of the THD rate out of the three phase or phase-to-phase values, measured at the grid point under consideration in the assumed time of the assessment (10 minute average)

THDallovable level – the THD rate limit as per the system regulation or contract (in transmission grids THD allowable level = 3% [4])

Uh,CP95 – the maximum CP95 percentile of the harmonic h. out of the three phase (phase-to-phase) values measured at the grid point under consideration in the assumed time of the assessment (10 minute average)

Uh, allovable level – the allowable level of harmonic has per the system regulation or the connection agreement.

On this basis:

11 HH WWW (9)

Voltage unbalance rate W3 = WASY:

)2(

)2(95

allowavle level

CPASY K

KW (10)

K C95 – CP95 percentile of the unbalance rate for the negative sequence component measured at the grid point

under consideration in the assumed time of the assessment (10 minute average)Kallowable level – the allowable unbalance rate for the negative sequence component (in transmission grids = 1% [4]).

On this basis:

13 ASYASY IWW (11)

Voltage fluctuation rate W4 = WWN

allowable levelLT

CPLTPLT P

PW

,

95, (12)

PLT, CP95 – the maximum CP95 percentile of the PLT rate out of the three phase or phase-to-phase values, measured at the grid point under consideration in the assumed time of the assessment (10 minute average)PLT, allowable level – the allowable level of the PLT rate (in transmission grids PLT, allowable rate = 0.8 1.[4]).

On this basis:

14 PLTPLT WWW (13)

2. ALLOWANCE SYSTEM

The following two regulation levels are hereby proposed:1. local regulation level taking into account the interaction of electricity suppliers and recipients at the

point of common connection2. system regulation level.

(2)

(2)


34

2.1. Local regulation levelLocal regulations should take into account the requirements of both sensitive receivers that need special

voltage quality, and should focus on disrupting recipients, with regard to which mechanisms are required to control their emission levels. The interaction is described by numerical measures in the contract for electricity supply. For a NZ grade measurement point an analysis should be carried out of the disturbance source location and the perpetrator of the excess over the allowable quality level should by clearly identified.

The procedure’s next step involves agreeing on a so-called improvement path for the offender, according to which within a specified time limit (e.g. a year or two years, depending on the technical difficulties) the Z grade quality should be achieved in the respective grid point (fig. 1). Therefore, the paces of accomplishing thereference levels differ depending on the condition identified in the initial year.

The control is based on measurement in the common connection point. The electricity supplier performs measurements at selected fixed points of the supplying grid with pre-installed measuring devices. The meterrecords 10 minute averages of voltage RMS, fluctuations level, harmonics, voltage unbalance, and deliveredenergy. Any excess of the levels allowable according to the “improvement path” is penalised with a penalty, which the supplier pays to the recipient. This penalty depends on the degree of the excess over the allowable level and the value of the bad quality energy supplied. In subsequent years, in line with the “improvement path,” the regulator / operator shall compare the existing quality levels with targets and, if the quality has improved to a greater extent than required, shall enhances the incentive, e.g. by way of reducing to X% the bonus payable to the recipient. The present regulating mechanism based on penalty and reward, motivates operators to rapid interventions in improving the voltage quality, and recipients to not exceeding the emission levels agreed with the electricity supplier.

Voltage fluctuationsIn the event of exceeding the allowable level of voltage fluctuations, the penalty charge is assessed based

on the following formula:

21

2

kk

kkkW ECEWCP (14)

where: Ek is the energy delivered in the time interval with the order number k, and Wk is the punishable voltage fluctuation level

st

allowable levelstkstk P

PPW

,

,,,0maxallowable level

(15)

Ω1 is a set of the time intervals where Wk ≤ 1, and Ω2 is the set of time intervals in which Vk > 1. Pst, s is the short time light flicker rate measured in the interval k, is its allowable level. Wk is determined for each 10-minute time interval in the week-long measurement period (k = 1, 2…, 1008) and assumes a nonzero value only if the

Qualityindictor

* *

Initial value

Allowablelevel

1 2 3 4 5 6

Penalty

Award

Minimum, e.g yearly

poziom poprawy

Time [year] Fig. 1. The Italian voltage quality indicator „improvement path” [1]


35

allowable level has been exceeded. As follows from the formula (14), in each interval k during which excessive voltage fluctuation has occurred, the penalty charge shall be charged in the amount of:

C × Wk [PLN/kWh] where 0 < Wk < 1 i C [PLN/kWh] where Wk ≥ 1.

In practice the value C may be assumed at the supply outage cost level. This means that the intervals in which Wk ≥ 1, are treated as unacceptable supply conditions. When a voltage fluctuation in excess of theallowable level voltage is consistent with the “improvement path,” then the penalty charge is reduced according to the formula: PW = R · PW , where R is the allowance reduction rate of a fixed value (e.g. 0.5) or a valuedependent on the voltage quality improvement duration, e.g. R= (1 – m / M), where M is the time (in months) adopted as needed to achieve voltage quality grade Z in the specific grid point, and m = 0,1,2… are successive months / years from the start of the “improvement path” implementation The same principle can be applied to all other voltage quality rates.

Voltage distortionWith regard to higher harmonics that have exceeded the allowable level, the penalty function takes the

form:

43

2

kk

kkkH CEEHCP (16)

where: Hk is the punishable voltage distortion level

40

2*

,,,0max1,0maxh h

hkhallowable levelkk U

UUnTHD

THDTHDH

allowable level

allowable level (17)

Ω3 is the set of intervals in which Hk ≤ 1, and Ω4 is the set of intervals in which Hk > 1. Value n that reduces the penalty amount charged for exceeded allowable levels of individual harmonics may in the initial period amount, for example, to 3. It may change in the period of implementation of the regulation without financialconsequences. Value THDk is the maximum distortion rate, and U is the maximum voltage harmonic h out of the three phases recorded in each interval k. Hk is determined for each time interval in the week-long measurement period (k = 1, 2…, 1008) and assumes a nonzero value only if the allowable level has been exceeded. As follows from formula (16), in each interval k, during which excessive voltage distortion has occurred, the penalty fee shall be charged in the amount of:

C × Hk [PLN/kWh] gdy 0 < Hk < 1 i C [PLN/kWh] gdy Hk ≥ 1.

Voltage unbalanceFor this disturbance the penalty function assumes the form:

65

2

kk

kkkA ECEACP (18)

where: Ak is the punishable voltage unbalance level:

)2(

)2()2(

,0max allowable levelkk K

KKA

allowable level (19)

Ω 5 is the set of intervals, in which Ak ≤ 1, and Ω6 is the set of intervals, in which Ak > 1. Kk(2) is the

unbalance rate recorded in each interval k. Ak is determined for each interval in the week-long measurement period (k = 1, 2…, 1008) and assumes a nonzero value only if the allowable level has been exceeded.

(2)

(2)


*

36

As follows from formula (18), in each interval k, during which excessive voltage unbalance has occurred, the penalty fee shall be charged in the amount of:

C × Ak [PLN/kWh] where 0 < Ak < 1 i C [PLN/kWh] where Ak ≥ 1.

Slow voltage changesIn accordance with applicable provisions of the tariff regulation, the amount of penalty paid to recipient

is very small and practically does not activate any mechanism to incentivize the supplier to improve the power supply quality [2]. Thus, the proposed amendment, pursuant to which, if voltage exceeds the allowable levels, the supplier shall pay the penalty in accordance with the formula:

87

2

kk

kkkU ECEVCP (20)

where: Vk is the punishable low voltage change level

C

CkU U

UU ,

Where )()( , kUsign

upward deviationU

upward deviationUkUkV

max,

max, ,,0max

)()( , kUsign

downward deviationU

downward deviationUkUkV

max,

max,,,0max

(21)

Where

Ω7 is the set of intervals, in which Vk ≤ 1, and Ω8 jest is the set of intervals, in which Vk > 1. Vk is determined for each time interval in the week-long measurement period (k = 1,2…,1008) and assumes a nonzero value only if the allowable level has been exceeded.

As follows from formula (20), in each interval k, during which excessive voltage change has occurred, the penalty fee shall be charged in the amount of:

C × Ak [PLN/kWh] gdy 0 < Wk < 1 i C [PLN/kWh] gdy Wk ≥ 1

Penalties defined by formulas (14), (16), (18) and (20) (resulting from a one-week measurement) are paidon a continuous basis in each subsequent week until measurements show that the allowable levels arising from the adopted “improvement path” have not been exceeded. As regards measurements taken by stationary meters the penalty is assessed on a continuous basis, in accordance with the actual excesses over the allowable voltage quality rates. This may be an additional incentive for building distributed energy supply quality monitoring systems.

2.2. System voltage quality indicatorSystem-level quality indicators are not guaranteed for each recipient, whereas guaranteed is an appropriate

average quality level for all recipients. The Polish power system is divided into areas administered by TSO and DSO network operators, each of which is internally subdivided into smaller organizational units. The transmission system operator’s grid is divided into five divisions. Therefore, benchmarking analysis can be carried out both ona national scale, between independent operators, and at the single operator level.

For the purpose of global system assessment (for a selected area or part of the system) the system indicator (CWJU)S may be defined:

M

jj

M

jjUjSU wCWJwCWJ

11, / (22)

(2)

(2)


37

REFERENCES

where: wj and CWJU,j are the weighting factor and quality indicator, respectively, for the measurement point j, and M is the total number of the supplying grid’s monitoring points. The point weighting factor may depend on, for instance, the number/ordered power of recipients connected at a given point.

Implementing the voltage quality improvement process the regulator/operator compares the system indicator with its adopted level, in each year depending on the “improvement path.” If, for example, the level of (CWJU)S,n indicator is adopted for the year n in line with the “improvement path”, and the tolerance level is adopted at ± 5%, then the following assessment condition may be formulated:

if (CWJU)S > 1,05 (CWJU)S,n a penalty for the operator shall be assessedif (CWJU)S < 0.95 (CWJU)S,n an award for the operator shall be assessed.For the penalty/award assessment mechanism the same algorithm may be adopted as proposed for the

point regulation. Penalties are assessed in proportion to the bad quality energy supplied, while the penalty increases with the increase of deviation from the allowable disturbance level until an adopted threshold. Beyond the threshold the supplier is punished as for undelivered electricity/supply outage. The regulator should determine the penalty’s analytical form. A similar concept may be applied to the award.

A rate defined with the following formula carries additional information:

%100/* NNSWJ ASU (23)

where: NA is the number of Z grade measurement points, and N is the total number of measurement points, where meters are installed. The indicator equal to 1 means that quality requirements have been met in all measuring points in the part of the system under consideration. A value less than 1 means that the requirements have not been met in at least one point. N may also be the total number of points, which have been classifiedas points of quality rate measurement. These are both points in which the rates are measured and the points in which measuring devices’ installation is planned. In a similar way as in the case of a single measurement point, a voltage quality grade can be assigned with regard to the system indicator.

3. SUMMARY

It is proposed to introduce to the system regulation:a) overall voltage quality indicator (SWJU)b) voltage quality gradesc) system voltage quality indicator (SWJU)s as a benchmarking reference.Amending the tariff regulation in a way that establishes the system of allowances paid by the supplier to

recipient in respect of non-compliance with allowable voltage quality levels shall require time and measurement data. Launch of each regulation mechanism requires initial testing of the respective procedure without imposing financial consequences, only to analyze the consequences of its operation.

1. Caramia P. , Carpinelli G., Verde P., Power quality indices in liberalized markets, Wiley, 2009.2. Krajowy Raport Benchmarkingowy nt. jakości dostaw energii elektrycznej, URE, 2009.3. Regulation of voltage quality for the Italian network…, Workshop organized in the 14th IEEE International Conference

on Harmonics and Quality of Power (ICHQP), 29 September 2010, Bergamo, Italy.4. Regulation of the Minister of Economy of 4 May 2007, Journal of Laws No. 93 dated 29 May 2007


38Marcin Jaskólski / Gdańsk University of Technology


Marcin JaskólskiGdańsk / Polska

After graduating from the Faculty of Electrical and

Control Engineering at Gdańsk University of Technology

(2002) Mr. Jaskólski started a doctoral dissertation in the

field of regional energy system development modelling

in the MARKAL framework and the use of biomass for

electricity and heat cogeneration. He completed training

at the University of Lund in Sweden (2002-2003) and

research internships at the International Institute

for Applied Systems Analysis (IIASA) in Laxenburg,

Austria (2003) and the Institute of Energy Economics

and Rational Use of Energy (IER) at the University of

Stuttgart (2004). He obtained his PhD in engineering

at the Faculty of Electrical and Control Engineering at

Gdańsk University of Technology (2006). Currently, an

assistant professor at the Power Engineering Department

of Gdańsk University of Technology. His scientific

interests, besides integrated modelling of energy system

development, include the use of renewable energy

resources and nuclear power generation. In 2010 the

author participated in a three-month training programme

in nuclear power generation at the Atomic Energy and

Alternative Energies Commission (CEA) in Saclay, France.

In 2011 he took up an internship in nuclear reactor

safety analysis at EDF SEPTEN research centre in Lyon.

39

SMALL AND MEDIUM NUCLEAR REACTORS

Marcin Jaskólski / Gdańsk University of Technology

1. INTRODUCTION

In recent years throughout the world, and in member states of IAEA International Atomic Energy Agency, renewed interest has been observed in the development and application of small and medium power nuclear reactors [1]. This is a direction opposite to that so far preferred by suppliers of commercialised power reactors, the installed capacities of which have greatly exceeded the barrier of 1,000 MWe. For example, the output of EPR Evolutionary Power Reactor, European Pressurized Reactor offered by French company Areva is 1,650 MWe.

IAEA defines small power reactors (small reactors) as those with an installed electric capacity up to 300 MWe, and medium power reactors (medium reactors) as those with an installed electric capacity from 300 MWe to 700 MWe [2]. This author points out that the English word “reactor” means a power unit with a nuclear reactor as well as a nuclear reactor itself. The term “small and medium power reactors” is commonly shortened to small and medium reactors (SMR), which is not accidental, since as a rule, besides smaller installed capacity, they also have smaller sizes.

2. SMALL REACTOR FEATURES

According to the IAEA definition, 139 of 442 power reactors (as of 2008) are regarded as small andmedium reactors (SMR) [2]. This follows from the fact that at the beginning of the nuclear power technology era reactors featured smaller power outputs. For example, Shippingport, the first reactor in the U.S., had a poweroutput of 60 MWe. They accounted for a stage of the development towards large power reactors, the power of which now exceeds 1,000 MWe. In recent years the world’s interest has grown in nuclear reactors, for which the small power is designed intentionally. They are often referred to as deliberately small reactors (DSR).

Typically, this category includes the following types of reactors:a) researchb) testc) prototype & demonstrationd) propulsion [2].They are not of interest to electrical power engineering, which focuses on those that output heat to

a coolant to produce electricity and / or district / process heating.

Small and Medium Nuclear Reactors

Abstract

Recent years have brought about increased interest in small and medium reactors with 700 MW or less output power, as an alternative to large commercialized nuclear units. Currently developed small and medium reactors can compete with large reactors due to the following advantages:

1) smaller sizes allowing manufacture of reactor components in supervised factories

2) less heat output from the secondary circuit, which facilitates location selection

3) less investment and financial risk

4) improved power system stability. The most advanced small nuclear reactor designs appear to be the light water reactors with integrated primary systems, such as Westinghouse IRIS and NuScale, and Toshiba 4S fast-neutron sodium-cooled reactor. The latter is expected to be installed in Galena, Alaska. The main barriers to small reactor technology development are: too many competing projects, fear of new reactor technologies, and perception of small units through the prism of the economy of scale.

40

In many countries DSR technology is currently being researched and developed. They include: Russia, Japan, the United States, India, China, Argentina, and South Korea.

There are many aspects to which attention should be drawn when comparing small nuclear reactors with large reactors LR. These aspects have been discussed in [1, 2–6], and the discussion is synthesised below:

• Manufacturing of reactor structural components There are more opportunities to manufacture components for physically smaller reactors, because only a few manufacturers in the world are able to make large steel components for modern large reactors. This may change and the number of suppliers will increase, but it is a highly capital and time intensive process. Besides, forged elements of small reactors may be supplied domestically.

• Transportation of reactor structural componentsThe use of large tanks in LWR light water reactors restricts the choice of location primarily to sites on a coast or along major rivers. Small reactors may be transported by rail, road, or river (on barges), because they are much lighter.

• Reactor construction processA significant portion of the work associated with construction of a power unit with a nuclear reactoris executed on the site of its later operation. The option of manufacturing many components of small reactors in factories, which are strictly controlled, and of on-site assembling (not manufacturing) them not only reduces the uncertainty associated with the construction cost and schedule, but also increases the reactor reliability and safety.

• Amount of radionuclides produced by fission in reactorThe amount of radionuclides is proportional to the reactor capacity, hence small reactors produce fewer of them than large reactors. This is manifested in the option to reduce the sizes of reactor shields, plant sites, and EPZ emergency planning zones (in the US: EPZ – a zone within 10 miles radius around the plant).

• Susceptibility to accidentsElimination of the systems of water injection to a reactor in emergencies (e.g. broken pipeline connecting a reactor vessel with a steam generator) reduces the cost, but requires an integrated reactor vessel design that includes a steam generator and pressuriser. This approach is applied to deliberately small nuclear reactors. It has the advantage of eliminating large diameter pipes through which primary circuit cooling water flows.

• Decay heat removal Compared to large reactors, small reactors are capable of more efficient removal of the decay heat inthe event of reactor outage. This is so for the following reasons:

a) reactors with less output power feature less decay powerb) smaller reactor core volume allows for more efficient heat conductionc) heat removal from the outer surface of the vessel is more efficient (although the heat

dissipation surface area is smaller) – the reactor core volume has a greater impact on the amount of heat given off.

• Reactor location selectionThe reduced amount of radionuclides in small and medium reactors is manifested in the size reduction of plant sites and emergency planning zones. This creates the possibility to apply the small reactor technology to electricity and heat cogeneration, reducing the losses of heat transmission over long distances, while the EPZ reduction allows locating a reactor closer to populated areas. Lighter and smaller nuclear islands of small reactors can be founded on seismic isolators, resulting in greater reactor design standardization and reduced susceptibility to the effects of earthquakes.

• Heat demand characteristicsSmaller reactors are more flexible to consumer requirements, especially with regard to the use ofprocess heat from a reactor. For economic viability of a plant, the excess thermal power produced by its reactor has to find a consumer.

• Use of water for secondary system coolingDue to the need to give off large amounts of heat to the environment from power plants, including dispersal in an open circuit to water reservoirs, the problem of plant location arises. As regards nuclear power plants, this problem mounts, because, due to the lower thermal cycle efficiency, such a plant gives


41

off more heat to the environment (water, air) than a conventional coal-fired power plant, assuming thesame energy production. Where available location options are scarce in terms of water cooling (too little water body surface or too little water flow), an alternative may be a small reactor which needsmuch less cooling per power unit.

• Growing power demand in local power gridsSmaller nuclear plants allow for easier adjustment to gradual increases in power demand characterized by low dynamics, which is in a way reflected in the reactor economics and flexible operating characteristics.

• Plant construction overall capital expendituresUsually the main economic indicator is specific investment cost, relative to the plant’s installed electriccapacity. However, no less important, if not more important, criterion is the sum of overall capital expenditures. This is particularly important for clients with reduced capacity to finance nuclear powerunits that today cost even as much as ca. 5 billion EUR. Small units are easier to finance by smallercustomers, such as less wealthy states or smaller power utilities.

• Economies of scaleThe prevailing belief is that larger nuclear reactors are cheaper per unit of installed capacity due to the economies of scale. The relevance of economies of scale, however, may be reduced by: modular construction, standardized components manufacturing in factories, learning by doing process, simplifiedreactor structure, compact design, etc. In addition, economies of scale could be applied to compare reactors of the same structure, and all indications are that large reactors and small and medium reactors will be significantly different in terms of design.

• Investment riskAs regards capital expenditure projects, besides economic indicators, cash flows are also veryimportant. From this perspective, it may be advantageous to build four smaller nuclear power units than a single large unit (with the same installed power as the four small blocks have), while maintaining such a development sequence that the following block is built after the completion of the previous one. Then such another unit’s construction is partially funded by the revenues from the previous unit’s commissioning. This approach can significantly mitigate the capex project’s financial risk. In addition,a smaller unit’s construction is less susceptible to delays in implementation that add to the project’s risk. It is anticipated that the construction of a unit with a small reactor will take three years, and with a large reactor – five years [5]. Another important feature of this approach is small reactors’ betteradaptability to changing market conditions.

• Power system constraintsSmall and medium reactors may be used in a power grid with limited capacity of installed generation sources, in which a deviation of the active power balance in excess of 10% of the sources’ installed capacity may jeopardize the power system’s operation and stability. They may also be located far away from civilization in order to avoid construction of a long power transmission lines. Many power systems are not suited to the connection of power units in excess of 1,000 MW. Smaller reactors can be advantageous in systems with large renewable sources based generation, wind farms in particular, where load follow in the power system is necessary. Small reactors offer better flexibility in this respect,also in the perspective of the electric power sector’s development towards smart grids.

These characteristics show that under certain conditions, the construction of small nuclear reactors would be more advantageous than the construction of large reactors. There remain, however, many barriers to overcome of a technological, social, and economic nature. Overcoming technical barriers is the subject of research conducted within numerous demonstration and development projects.

3. SELECTED SMALL AND MEDIUM REACTOR PROJECTS

According to an IAEA report, there are more than 60 projects of small and medium reactors, listed in [1]. This creates certain obstacles and threats to the technology development because of dispersion of the involved resources and lack of standardization. This chapter presents selected small and medium reactor projects, especially those for which the commercialization moment seems to be the closest. The projects are listed in Tab. 1. Below some selected reactor projects are discussed in more detail.


42

Tab. 1. Selected small and medium reactor projects. Based on [2, 3]

# Specification IRIS NuScale 4S

1 Designer Westinghouse NuScale Toshiba

2 Primary circuit coolant light water light water sodium

3 Coolant circulation forced natural forced

4 Primary circuit configuration integrated integrated pool

5 Electric power [MW] 335 45 10 (to 50)

6 Reactor output temperature [°C] 330 300 485

7 Secondary circuit configuration intermediate intermediate intermediate

8 Heat cycle Rankine Rankine Rankine

9 Reactor vessel diameter [m] 6.2 2.7 3.5

10 Reactor vessel height [m] 22.2 14.0 24.0

11 Fuel UO2 UO2 U-Zr

12 Fuel enrichment rate [%] <5 <5 18

13 Fuel cycle duration [a] 3.5 2.5 10-30

14 Scheduled launch 2015 2015 2013

International Reactor Innovative and Secure (IRIS) as well NuScale are deliberately small Integral Primary System Reactors – IPSR. The IRIS project is developed by Westinghouse and based on the known light water reactor technology, which will soon allow for the launch of the FOAK – first-of-a-kind unit. The solution’s mainfeatures [2] include:

• Availability of installed capacity in the range of 100 to 350 MWe. Typical unit installed capacity is 335 MWe (reactor thermal power output – 1000 Wt). The reactor’s structure is modular

• All primary system components (core, control rods, drive mechanisms, steam generators, primary coolant pumps, pressuriser) are integrated in a single reactor vessel

• The reactor core consists of 89 fuel assemblies (289 rods each) known from pressurized water reactors (PWR) containing uranium oxide UO2 fuel enriched at the rate of ca. 5%. The expected in-core fuel cycle duration is 3.5 years, and fuel burn-up is 50,000 MWd / t

• The reactivity is controlled by solid burnable absorbers and control rods, as well as using soluble boron.

NuScale, on the other hand, is situated at the opposite pole in terms of IPSR reactors’ power range. Its design installed capacity is 45 MWe. The technology provider’s idea is to develop an installation with a large number of units, e.g. 10, of a total power of 450 MWe. Its features are similar to those of IRIS. Instead of 89 cassettes (IRIS) there are 24 fuel assemblies designed for NuScale, although an in-core fuel cycle extension is considered from 30 to 60 months, using a fuel with an enrichment rate of 8%. An important difference is the use of natural circulation of coolant in the reactor vessel [2].

A relatively interesting project, also due to the anticipated short time of its completion, seems to be the 4S reactor (Super Safe Small and Simple) developed by Toshiba Corp. and Central Research Institute of Electric Power Industry (CRIEPI) in Japan. The 4S reactor is a small power, fast neutron, sodium cooled reactor. It employs passive safety systems, which allow improving their economics [3]. The first planned location is Galena,Alaska. The reactor planned for installation in Alaska will have an installed electrical power of 10 MW (thermal power 30 MJ / s). However, an option to increase the reactor’s power in subsequent installations up to 50 MW is considered. The fuel will be an alloy of zirconium and uranium (U-Zr). The intermediate system that uses sodium as coolant takes heat from the reactor and delivers to the steam generator in the secondary circuit – a Rankine steam heat cycle [2].

The 4S reactor’s basic design assumptions include [3]:• No need to refuel for over ten years (ultimately throughout the useful life of thirty years, if possible).• Simple control of fuel burn-up with no control rod drive mechanism – CRDM)• Minimization of reactor system controls • Load follow operation with no need to activate the reactor control system


43

• Minimization of reactor components’ repairs and inspections.• Negative temperature coefficient of reactivity• Security system independent of the emergency power supply systems and the decay heat removal

system (this system is passive and does not require power supply from the plant’s auxiliary system).A very interesting feature, and also the 4S reactor’s key technological innovation, is its core, in which

fuel is made of metal, and its burning is controlled by a neutron reflector, allowing the economical balance ofneutrons in the fuel.

4. SUMMARY

Once appropriately technologically matured, small and medium reactors (SMR) will compete with large reactors. The modern fleet of large reactors features high standards of safety, and in this way it will definethe technology offerings market. At first glance, it seems that economies of scale may be an issue. Due totheir integrated modular design, small reactors will have to prove their competitiveness. Also the associated equipment will have to be developed, as well as the control and measurement instruments and automation (for example inside the tank containing the reactor’s integrated primary circuit) for small and medium reactors [2].

Non-technical challenges will include [2]:• Too many competing SMR projects• Widespread perception of large, centralized nuclear power plants as a better solution, since they are

considered high risk objects and their centralization in locations remote from major cities is desirable• High capital expenditures and anxieties related to disasters at nuclear power plants as well as concerns

from the early era of nuclear technology have created a kind of fear of projects referred to as the firstof a kind – FOAK)

• Longer in-core fuel cycle will require ongoing monitoring, diagnostics, and forecasting of the reactor’s technical condition

• The use of reactors for cogeneration or polygeneration will require development of automation systems designed to balance demand for two or more products offered by a unit with a reactor.

Yet another issue is management of the waste generated during current production or remaining at the end of a reactor life cycle, like for the 4S reactor, in which fuel is not supplemented throughout its technological life cycle. Currently available large commercial reactors are designed for a sixty year useful life cycle, though certainly reactor operators will seek to extend it.

Small and medium reactors at the moment are designed for thirty years of use. After its technical lifetime completion a nuclear power plant must be decommissioned and dismantled, which requires substantial outlays.

In light of the high demand for new powergeneration sources, and even the need to build distributed generation sources based on renewable energy resources or natural gas, it seems unlikely that this technology, despite its advantages, will be adapted to the Polish national powers system over the next two decades. Certainly, it can be used in places such as Galena, Alaska, which are far away from civilization. Time will tell whether it will be possible to significantly simplify the reactor design in such a way as not to endanger the safety of thepopulation and whether the public will accept dispersed nuclear reactors in view of an alternative in the form of a smaller number of such sources, but with higher installed capacity. Overcoming the barriers of economies of scale would encourage an alternative approach to the construction of power plants with large units – the construction of plants of the same capacity, but with a respectively larger number of units.


44

REFERENCES

1. Kuznetsov V., IAEA activities for innovative Small and Medium sized Reactors (SMRs), Progress in Nuclear Energy 4 7, no. 1–4, 2005, pp. 61–73.

2. Ingersoll D. T., Deliberately small reactors and the second nuclear era, Progress in Nuclear Energy 51, 2009, pp. 589–603.

3. Ueda N., Kinoshita I., Minato A., Shigeo K., Yokoyama T., Maruyama S., Sodium Cooled Small Fast Long-Life Reactor “4S”, Progress in Nuclear Energy 4 7, no. 1–4, 2005, pp. 222–230.

4. Carelli M., Garrone P., Locatelli G., Mancini M., Mycoff C., Trucco P. , Ricotta M. E., Economic features of integral, modular, small-to-medium size reactors, Progress in Nuclear Energy 52, 2010, pp. 403–414.

5. Shropshire D., Economic viability of small to medium-sized reactors deployed in future European energy markets, Progress in Nuclear Energy 53, 2011, pp. 299–307.

6. Locatelli G., Mancini M., The role of the reactor size for an investment in the nuclear sector: An evaluation of non- -financial parameters, Progress in Nuclear Energy 53, 2011, pp. 212–222.


46Piotr Kacejko, Piotr Miller / Lublin University of Technology


Piotr KacejkoLublin / Poland

Head of the Department of Electrical Grids and Protections of Lublin University of Technology. The author was awarded his post-doctoral degree at the Faculty of Electrical Engineering of Warsaw University of Technology in 1999, and the title of professor in 2006. He specializes in power system analysis, especially in emergency conditions, and numerical methods of analysis.

Piotr MillerLublin / Poland

Graduated from the Electrical Engineering Faculty of Lublin University of Technology. Currently an assistant professor at the Department of Electrical Grids and Protections. He specializes in numerical methods and software used in the analysis of power system emergencies. The chief developer of SCC computer program SCC commonly used by operators in the commercial power sector and by designers.

47Short-Circuit Analysis of Power Grid with Consideration of Wind Farms

as Controlled Circuit Sources

SHORT-CIRCUIT ANALYSIS OF POWER GRID WITH CONSIDERATION OF WIND FARMS AS CONTROLLED CIRCUIT SOURCES

Piotr Kacejko / Lublin University of Technology Piotr Miller / Lublin University of Technology

1. SHORT-CIRCUIT MODELS OF WIND TURBINES

Currently, generators of the following two types are used for wind power generation. Induction machines are abbreviated as DFIG Double Feed Induction Generators, and synchronous machines as FC Full Converters, because such generators operate through converters. Extensive reports on these generators’ performance in the short circuit condition were presented by Nordex [2] and Enercon [3]. Availability of documentation describing the performance of other manufacturers’ generators is not satisfactory, yet it may be assumed that it is similar to that of the basic DFIG and FC turbine types.

Short-circuit analysis for the purpose engineering practice is regulated for induction machines and synchronous machines with converters by short-circuit standard PN-EN 60 909 [4]. Even if the standard refers to motors, its approach should not differ substantially as regards simplified methods of generator short-circuitmodelling. However, it seems that this simplistic approach does not reflect the essence of the phenomenaassociated with generator short-circuits at power plants. Hence the search for other solutions.

Simplified models are introduced, among other reasons, to facilitate a user’s quick estimate of certainvalues – in this case those associated with short-circuit conditions, taking into account a large number of wind farms. It is necessary to determine where and how to connect a farm to a grid (directly to a PCC point, a tap or a cut into an existing line), and then to adopting simplifying assumptions for the farm structure. These are the following:

• farm of the declared power Pnf consists of a specific number of wind turbines of the same power Pnw• wind turbines are connected to the grid through the reference (marked with symbols) number of set

transformers HV / MV, whereby the same number of fans (a group) is connected to each transformer• set transformer power is estimated on the basis of the power assigned to a single group of turbines

from a series of types applicable in Poland.Fig. 1 presents a description of the input variables required and estimated to develop the wind farm’s

simplified model.

Abstract

This paper presents a method for the short-circuit parameter estimate in a network including wind power plants. The originality of the method consists in the treatment of wind generators (as well as whole farms) as current sources that “inject” to grid network in the connection node an inductive current being a multiple

of the rated current of a single generator (or a group of generators, respectively). This behaviour occurs when the voltage in the generator connection point has dropped below a certain level. Thus, the traditional generator short-circuit model in the form of electromotive force is replaced with a voltage-controlled current source.

48

Fig. 1. Diagram of a large wind farm with division into s groups

Required input variables• name of the node to which farm is connected• name of the line connecting PCC (this also may be the branch point) with farm MSP• name of farm MSP• Pf – farm power [MW]• Pn – turbine rated power (in the simplified variant a single value is assumed for the whole farm) [MW]• s – number of turbine groups (equals the number of HV/MV transformers in farm MSP)• l – length of the line connecting PCC with farm MSP [km] (zero value is allowable)• type – turbine generator type (either DFIG – doubly fed induction generator, or FC – full converter

synchronous generator).

Estimated input variables• Sntf – farm transformer rated power

tfnfntf 1,1 PS

s

Function<<x>>tf causes selection of value x > x w and equals a number from set <6; 10; 16; 25; 32; 40; 50; 63; 80; 100; 125; 160>

• u – farm transformer short-circuit voltage (default 12%)• S – wind turbine transformer rated power ntw

twntw nw1,1S P

Function<<x>>tw causes selection of value xw > x and equals a number from set <1.65; 2.2; 2.5; 2.75;3.0; 3.5; 4.0>

• uktw – wind turbine transformer short-circuit voltage (default 6%)• xj – unit line reactance (default 0.4 Ω/km)

Piotr Kacejko, Piotr Miller / Lublin University of Technology

LINEF_CODE_NAME

(allowable value zero)

PCC_CODE_NAME

FARM_CODE_NAME

Group 1

Group 2

Group S

49

• farm transformer grounding on the HV side (default YES)• U – farm rated power (default 30 kV – it is a formal selection that doesn’t affect the farm model)• U – wind turbine rated power (default 690 V – it is a formal selection that doesn’t affect the farm

model).The simplified default farm model for short-circuit calculations is the traditional model in the form of

uncontrollable voltage source and constant impedance. Thus, in qualitative terms, it is the same model as that of the conventional set of a hydro or thermal power plant. Of course, the electromagnetic phenomena occurring in wind turbine generators in short-circuit conditions differ from those in conventional synchronous generators. An important role in these phenomena is played by the control system of the converters coupled with wind turbine generator.

In light of the foregoing, to determine the wind turbine generator positive impedance used in the simplifiedshort circuit model the formula was used included in the standard [4].

(1)

nW

nW

LRW S

UK

Z21

Coefficient KLR, although called the start-up rate (in the standard it is used to describe induction motor characteristics) is the wind turbine impedance measure adopted in the reference literature. Its value may vary, which allows taking into account the generator-converter system properties changing during a short-circuit. Generally, as regards wind turbines, the first subtransient state phase (duration 20-40 ms) and the second periodincluding in the classic sense the second subtransient state phase and the transient state (duration up to a few hundred milliseconds) may be considered.

Coefficient KLR is determined based on the assumptions presented below:1. DFIG type, subtransient state KLR = 52. DFIG type, short circuit steady state KLR = 2 3. FC type, subtransient state KLR = 34. FC type, short-circuit steady state KLR = 1.4In the modelling identified as “accurate” (proposed in the presented method) wind power generators are

treated as current sources with a specified multiple (greater than 1) of the rated current. The word “accurate”written in quotation marks should be understood as meaning that such a model is also approximate and simplified.Accurate modelling of farm-related short-circuit phenomena requires the use of software such as EMTP, with appropriate models of converter devices. It is a difficult undertaking that requires abandoning the use of short-circuit software, which is traditionally used to analyze quasi-steady short-circuit conditions.

To the extent relevant to short-circuit calculation the “exact” models involve a change in the short-circuit calculation philosophy, and the treatment of a “generator – converter” system differently in the above indicated first phase than in the second phase. In the second phase the system is treated as a current source with aspecified multiple of the rated current. It is also a positive current source, regardless of the short-circuit type.

2. SHORT-CIRCUIT ANALYSIS OF POWER GRID WITH CONSIDERATION OF CURRENT SOURCES

Fig. 2 presents a diagram of the grid model representing the pre-fault condition. The following designations are used:

G – set of the nodes, to which subtransient electromotive forces of classical generators are connected; the number of these nodes is represented by variable G, the lower the index of a grid describing variable means that the variable relates to this set of nodes

W – set of the nodes to which such wind farms are connected, where the user decides to use the accurate models (current sources), they may be, by definition, all farms in the grid, or only one – it depends onthe calculator’s intention, the number of these nodes is represented by variable W, the lower the index of a grid describing variable means that the variable relates to this set of nodes.

L – set the other network nodes (loads, power plants, connection points of the non-exactly-modelled wind farms), the number of these nodes is represented by variable W, the lower the index of a grid describing variable means that the variable relates to this set of nodes, the set includes the short-circuited node labelled k.

Short-Circuit Analysis of Power Grid with Consideration of Wind Farms as Controlled Circuit Sources

50

Fig. 2. Grid model diagram representing the pre-fault condition

The pre-fault short-circuit model may be described by the following equation (2). It is worth noting that both the load and the generation in a wind farm are treated as in the case of nodes of (P, Q) type, whereas their nodal currents are zero due to the fact that they are treated as internal elements of the model.

(2)

o oG GG GW GL G

oWG WW WL W

oLG LW LL L

00

I Y Y Y EY Y Y UY Y Y U

i.e.:

(3) o

WG WW WLo WG o

LG LW LL L

00

Y Y Y UE

Y Y Y U

and finally:

(4) 1o

WW WL WG oWGo

LW LL LGL

Y Y YUE

Y Y YU

The short-circuit model after a three-phase fault in node k is described by the following equation (5). Upper index “z” of currents and voltages identify the short-circuit condition.

(5)

z zG GG GW GL G

zW WG WW WL W

zL LG LW LL L

I Y Y Y EI Y Y Y UI Y Y Y U

Subtransient and transient electromotive forces meet the requirement z oG GE E , while in the set of

nodes W the current vector [Iw] is “activated” (it corresponds to a farm with LVRT controlled turbines).After transformations:

(6) z

WG WW WLW z WG z

LG LW LLL L

Y Y YI UE

Y Y YI U


51

and then:

(7) z

WW WL WGW zWGz

LW LL LGLL

Y Y YIUE

Y Y YIU

the following formula is finally obtained:

(8) 1 1z

WW WL WG WW WL WzWGz

LW LL LG LW LL LL

Y Y Y Y Y IUE

Y Y Y Y Y IU

To this description corresponds Fig. 3.

Fig. 3. Grid model diagram representing the pre-fault condition

It should be noted, on the basis of equation (4), that the first element on the right side of the equation (8)determines the voltage vector in the grid in its normal operation. Thus:

(9) 1z o

WW WL WW Wz o

LW LL LL L

Y Y IU UY Y IU U

Equation (9) can be formulated in more detail, by distinguishing in the group of nodes L the short-circuited node and the other nodes, i.e. L R k . The node current k is labelled as Ik (outgoing direction), the nodal currents for nodes in the setR remain zero, so therefore:

(10)

z oW W WW WR W Wz oR R RW RR RWz o

W R

0-

k

k k k k kk kU U Z I

U U Z Z Z IU U Z Z Z

Z Z

From the last equation the following formula is obtained:

(11)

Wz oW R 0k k k k kk kU U Z I

IZ Z

(12) z oW Wk k k kk kU U Z I Z I


52

Since to a three-phase fault the formula Ukz =0, applies, the basic sought after variable, i.e. short-circuit

current Ik, may be determined. According to the voltage condition in short-circuit point, the following formula is obtained:

(13) oW Wkk k k kZ I U Z I

Ultimately, therefore, the formula for the short-circuit current with the participation of wind farms injecting current to the connection nodes is:

(14) o

W Wk kk

kk

UI

Z

Z I

or

(14a) o

W Wkkk

kk kk

UIZ Z

Z I

The first component in this formula denotes the current in the grid without wind farms, the second takesinto account their impact in the form of current sources:

` (14b) W W

bWk

k kkk

I IZ

Z I

Equation (14b) can be reformulated by considering actions on individual impedance elements:

(14c)

1bW

w

k i ii

k kkk

Z II I

Z

It should, however, be noted that the farm model farm in fault condition corresponding to current source is appropriate for the state whereby the voltage at the point of connection drops below 80% of the rated voltage (or below another specified value). Calculations should verify whether for all nodes in the setW this condition is fulfilled, and if not (the voltage is higher), the node should be excluded from the set, because in this casethe farm is not a fault current source, but it only operates in the normal regime of active power generation (compatible with the current wind speed and controller settings).

Thus, an important element of the calculation is the determination of the voltages at the connection nodes of the farms in the set W. For this purpose equation (10) is used to produce the following matrix formula:

(15a) z oW W WW W Wk kI U U Z I Z

or for each node in the set W

(15b) z o

W W W1

w

i i ij i ik kj

U U Z I Z I

Formula(15b) of the voltage on farm busbars (or on turbine terminals, depending on the model) for short circuit at node k therefore takes into account the voltage in the normal condition, which is adjusted by the


53

impact of the current at the short-circuit point (voltage reduction) and the impact of current from the other farms (voltage increase).

The wind farm current impact consists of the positive current component only. There is no current impact for negative and zero components. Of course, the farm transformer’s grounded neutral points play an important role, but they are subject to classical modelling. Therefore, modification of the short-circuit current formulasconsists in introduction to the current formula’s numerator of a component that represents the wind farm impact, i.e.:

(16)

W W[ ] [ ]k kZ I

As a result, for example, the formula for short-circuit current in the case of L1 phase’s single phase ground fault takes the form:

(17)Z I o

1 2 0 W W1 2 0

[ ] [ ]k k kk k k

kk kk kk

UI I IZ Z Z

Other variables (phase currents) are determined in the same way as for faults without the farm participation.

Voltages at wind farm connection points are determined based on the voltages determined in accordance with the symmetrical components theory from equations in which only the consistent component of wind farm impact is considered, i.e.:

(18)

z(1) o 1W W WW W Wz(2) 2 2W Wz(0) 0 0W W

[ ] [ ] [ ][ ] [ ]

[ ] [ ]

[ ] [ ]

k k

k k

k k

III

U U Z I ZU ZU Z

The presented formulas can be quite easily taken into account in the short circuit calculation algorithms.

3. EXAMPLE CALCULATION

A very simple grid example was analysed (Fig. 4) that included two conventional sources and two wind farms. A short-circuit was modelled in node 3.

Fig. 4. Simple grid diagram (short-circuit in node 3, wind farms connected to nodes 1 and 2, all reactances equal 1.0 r.u..)

To emphasize the example’s simplicity all reactances were adopted equal (resistances were neglected) and the normal condition with no load. The example was related to 110 kV grid.


54

1.0 j.w.X typical 20X

2 2p

p p

110 20 U

XS S

ie p 600 MVAS

Fig. 5. Model of the grid in Fig. 4

If

p p110 kV 600 MVAU S

then

pp

p

600 3kA3 3110S

IU

Wind farm 50MW 50MVA (in simplification)

nF

50 0,262kA3110

I

nF

0, 262 0,087 j.w.3

I

We assume therefore that the farm rated current is 0.1 r.w. and the current it “injects” at fault IwF =0.2 r.u.

Calculations:Short-circuit model impedance matrix (determined by inversion of the nodal admittance matrix)

0,75 0,25 0,50,25 0,75 0,50,5 0,5 1,0

Z

Short-circuit current 31 w1 32 w2k

33

1,1 0,5 0,2 0,5 0,21,1 1,1 0,1 0,1 1,3 j.w.1,0 1

Z I Z IIZ

With no consideration of the farms the current was 1.1 r.u. (increase by 0.2 r.u.). Voltages in nodes 1 and 2

z ow1 w1 11 w1 12 w2 13 3 1,05 0,75 0,2 0,25 0,2 0,5 1,25

1,05 0,15 0,05 0,65 0,6 j.w.U U Z I Z I Z I

Thus, the condition that the voltage at the farm connection of farms was lower than 0.8 was fulfilled.


55

4. ALGORITHM DESCRIPTION

The following points describe the short-circuit current calculation algorithm with wind farm exact modelling consideration. Such an approach is an alternative to a block diagram, and at the same time it enables including some tips and comments for programmers. Because of the need to consider the impact of the current injected by farms on the voltage at the point of their installation, and the need to take into account the interaction of wind farms, it is necessary to develop the algorithm in the form of multiple nested loops greatly complicating the calculations.

1. Start, reading the complete data set and building the fault model, farms are modelled by the simplifiedmethod as conventional sources with impedances derived from the declared coefficients KLR .

2. User selects the option of accurate calculation for wind farms, all farms included in the set W will be considered in the short-circuit calculations as current sources.

3. For the set W so composed and the farms identified on its basis the short-circuit impedances resultingfrom simplified modelling are eliminated.

4. The programme factorizes the modified full grid model.5. Out of all nodes user selects a node (only one) for short-circuit calculation, which is labelled k.6. The programme performs FFS (simple substitution) operation for the factorization path P(k), in position

k there is 1 [6].7. The programme performs BFS (reverse substitution) operation for path P(W) – [6], it is the path

set for all nodes in set W, as a result vector [Z k] is obtained that includes impedance elements in appropriate positions.

8. Current in the short-circuit point is determined after formula

(19)

W1

( )1,05( ) ( )

i

i W

ki

kk k

i II

k k

Z

Z Z

where: )(ikZ – the element i of the impedance vector

WiI – current injected to the node i of connection of a farm from the set W determined as multiple of

the sum of rated current of the turbines that make up the farm (default for the farm i is k =1,8).9. The next node i from the set of nodes W is analysed and voltage is determined after formula:

(20) W 1,0 ( )i k kU Z i I

10. If U > 0.8, the node is eliminated from the set W, i.e. W:=W-i; return to 8.11. Have all nodes been analysed from the set W? If not, return to 9.12. Commentary: here these farm connection nodes are eliminated from the set W, which are far away

from the short circuit point, and the voltage of which has not dropped resulting from the short-circuit impact below 0.8 U, so, therefore, they must be ignored in the analysis, because this farm operates normally; however, this voltage verification must be carried on because of farm’s interaction.

13. The next node i is analysed from the connection node set W.14. The programme performs FFS operation for the path P(i) – [6], in position i there is 1.15. The programme performs BFS operation for the path P(W) - [6], the path is set for all nodes in the

set W, as a result vector iZ is obtained.16. Voltage is adjusted for the node i by consideration of the impact of the other nodes in the set W

(21) W

W W W1

( )i i i jj

U U Z j I

17. If the list of nodes has been exhausted, jump to 18, if not, return to 13.


56

REFERENCES

18. Voltages are reviewed for the set of nodes that belong to W (the set arranged in descending order with regard to voltage).

19. The node i is now selected.20. If UW i < 0.8, return to 19, if all nodes have been reviewed, jump to 22.21. If U > 0.8, the node i is removed from the set W:=W-i; and the programme returns to point 6

(the entire calculation operation starts anew).22. Print out of the current Ik and the voltages in nodes from the set W (after adjustments) - these are

input variables in this calculation option of the short-circuit programme.23. The End.

5. SUMMARY

In the framework of the tests of the “accurate” (or rather “more accurate”) wind farm modelling described above calculations were performed for the actual farm planned for inclusion in the 110 kV National Power System. The short-circuit currents obtained this way differed significantly from those obtained by traditionalmethods. This may indicate the advisability of implementing this type of wind farm modelling in computational programs used in the power industry.

1. Lubośny Z., Farmy wiatrowe w systemie elektroenergetycznym, WNT, Warsaw 2009.2. Nordex F008_224_EN, Revision 2, 2008_07, Technical Description, Simulation of short circuit, K08, Grid short circuit

with double fed asynchronous generator.3. Enercon Representation of Enercon Wind Turbines for Steady State Short-Circuit Calculations, proprietary document

dated 19.11.2007.4. PN-EN 60909 Short circuit calculations in three phase a.c. systems (IEC 60909 standard adopted for the use in

Poland without translation).5. Wind Power in Power Systems (editor Thomas Akerman) John Willey and Sons 2005.6. Kacejko P ., Machowski J., Zwarcia w systemach elektroenergetycznych, II Edition, WNT, Warsaw 2009.


58Sylwester Robak, Désiré Dauphin Rasolomampionona / Warsaw University of TechnologyGrzegorz Tomasik, Paweł Chmurski / CATA Centre for Advanced Technology Applications Ltd.


Désiré Dauphin RasolomampiononaWarsaw / Poland

A graduate of Warsaw University of Technology. He has been working at the Department of Electrical Engineering at the Warsaw Institute of Electric Power. He is currently the head of the Department of Electrical Power Automation. His research interests are focused mainly on the issues of electrical power automation, power system operation, and applications of telecommunications and modern information technologies in electrical power engineering

Sylwester RobakWarsaw / Poland

Graduated from the Faculty of Electrical Engineering at Warsaw University of Technology (1996). In 1999 he defended his doctoral thesis, and nine years later received the habilitation degree at his alma mater. Since 1999 an assistant professor, and since 2010 an associate professor at Warsaw University of Technology. Since 2008 Deputy Director for Science at the Electric Power Engineering Institute of the University. His interests include power system stability, power system control, mathematical modelling, design and selection of control systems, and distributed generation.

Grzegorz TomasikWarsaw / Poland

Graduated in power grid engineering from the Faculty of Electrical Engineering of Silesian University of Technology in Gliwice. He started his career in 1995 as technical director in the company JUPITER. From July 2004 to July 2005 Vice Chairman of the Board, and then Energy Market Director, at EPC SA. Then he worked as Task Director at CATA Centre for Advanced Technology Applications Ltd. managed strategic projects related to development of the electricity market, and to power system security. Since September 2009 Chairman of the Board at CATA, and since January 2011 Member of the Board at PSE Operator SA.

Paweł ChmurskiWarsaw / Poland

Graduated in electric power engineering from the Faculty of Electrical Engineering of Warsaw University of Technology. He started his career in 1990 at the Department of Protection Automation of Institute of Power Engineering in Warsaw. In 1996-1997 he worked at PSE SA, and then, until 2008, at Energoprojekt-Consulting SA (now EPC SA), where he dealt mainly with issues of electricity markets operations. Since 2008 at CATA Centre for Advanced Technology Applications Ltd., first a Task Director, now a Member of the Board.

59

CURRENT DISTRIBUTED GENERATION DEVELOPMENT OPPORTUNITIES IN THE NATIONAL POWER SYSTEM

Sylwester Robak /Warsaw University of TechnologyDésiré Dauphin Rasolomampionona /Warsaw University of Technology

Grzegorz Tomasik / CATA Centre for Advanced Technology Applications Ltd.Paweł Chmurski / CATA Centre for Advanced Technology Applications Ltd.

A research study financed with funds for research in the years 2010-2012 as research project

1. INTRODUCTION

Development of a single distributed generation definition which would be acceptable to the academics andthe industrial sector in various countries around the world faces great difficulties. Thus, numerous definitionsof the concept may be found in the reference literature. Also domestic references offer different definitions ofdistributed generation sources. The following factors are regarded as typical differentiators of the distributed generation, thus allowing setting this generation type in the context of other sources [1], [2]:

1. Intended application (purpose)2. Location in system (power grid)3. Rated power:4. Power supply (distribution) area5. Generation technology6. Environmental impact7. Operating mode8. Source ownership type9. Share in total energy output.It follows from analysis of the reference literature on distributed generation that its essential feature is

the source location close to the load. Hence, it is defined as the installation and operation of the power generatedby a generation facility, which is connected directly to a distribution grid, or connected on the demand side.

Another important feature of distributed generation is the capacity of distributed generation units, and the generation technology - distributed generation typically consists of sources that generate electricity from renewable or unconventional sources as well as in cogeneration with heat, and energy storage, whereas:

• Renewable energy sources are those that exploit in the conversion process the energy of wind, solar radiation, geothermal, waves, sea currents and tidal flows, river drop, and the energy procured frombiomass, landfill biogas, as well as biogas produced in the process of sewage disposal and treatmentor decomposition of plant and animal debris deposits;

• Cogeneration (combined energy generation) is a process whereby electricity and heat are generated in combination. Cogeneration is based on conversion of the chemical energy of a fuel (e.g. natural gas) for electricity and heat. Cogeneration is used wherever demands for heat (cold) and electricity are combined. Electricity and heat/ cold cogeneration is also called trigeneration or double cogeneration.

Current Distributed Generation Development Opportunities in the National Power System

Abstract

The article presents a brief discussion on the definition of wind generation. It outlines the distributedgeneration present state and development prospects

in Poland. It describes the availability of distributed generation units for the purpose of power system control by way of ancillary services provision.

60

Given these factors, with regard to conditions in force in the National Power System, the following definition of distributed generation may be adopted:

Distributed generation (distributed sources) are generators units, the generation capacity of which usually not exceeding 50 MW, that are not subject to the central power dispatch, that work with the distribution network (110 kV, MV and LV) or directly supply recipients, and the development of which is not centrally planned. Distributed generation typically consists of units generating electricity from renewable or unconventional sources, as well as in combination with heat, and energy storages.

2. DISTRIBUTED GENERATION SOURCES INSTALLED IN THE KSE NATIONAL POWER SYSTEM

The SNEWS Association of Independent Combined Power & Heat Generators database lists nearly 250 currently generated distribution sources installed in Poland fired with natural gas, biogas (landfill, sewagetreatment and agricultural, from biogas plants) and with bio-methane from mine drainage. They are very diverse sources: turbine or engine driven, mostly cogeneration, but also to electricity only, with electric power from 5 kW to about 7.5 MW (the database ignores larger sources).

The turbine sources (14 sources) account for the total electric power of ca. 60 MW. Natural-gas firedengine sources (36 sources with unit electric power below 0.5 MW, 15 sources with unit electric power over 0.5 MW) account for the total electric power of ca. 20 MW. Landfill and sewage treatment biogas fired enginesources (ca. 150 sources) account for a total electric power of ca. 60 MW. Agricultural biogas fired enginesources (12) account for a total electric power of ca. 15 MW. Biomethane fired sources (13) account for a totalelectric power of ca. 30 MW.

Total electrical power of the sources listed in the database is 185 MW.It follows from the statistics of the Energy Regulatory Office as of 31 December 2010 that the total

capacity of renewable sources of electricity generation in Poland is 2,556 MW. The structure of renewable electricity generation in Poland is presented in Fig. 1. and in Tab. 1.

Sylwester Robak, Désiré Dauphin Rasolomampionona / Warsaw University of TechnologyGrzegorz Tomasik, Paweł Chmurski / CATA Centre for Advanced Technology Applications Ltd.

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Fig. 1. Structure of renewable electricity generation in Poland (as of 31.12.2010) [3]

* Because of different ranges of the percentage biomass share (in the total fuel flow), no total installed capacity is specified for co-fired plants

Type Qua Pow 2 0.938 8 2.394 22 420.208 59 4.263 4 2.54 3 5.95 2 0.000

zachodniopomorskie

Type Qua Pow Type Qua Pow 3 1.363 4 4.415 4 2.654 1 84.6 21 140.995 87 6.466 14 8.392 4 11.353 1 6.675 2 0.000

pomorskie

Type Qua Pow Type Qua Pow 5 1.589 2 1.142 1 0.220 1 0.5 11 50.375 75 5.619 7 3.889 3 5.8

warmińsko-mazurskie

2 1.782 1 2.126 7 2.818 2 7.4 1 42 155 166.309 43 2.26 5 3.375 3 11.2 1 8 2 186.2 2 0.000

kujawsko-pomorskie

Type Qua Pow Type Qua Pow 3 2.072 1 0.7 8 78.25 11 0.643 1 93.5

podlaskie

Type Qua Pow Type Qua Pow 1 0.37 2 1.25 1 0.5 1 1.8 2 0.6 31 0.971 13 10.585 9 15.356 1 91.33

lubuskie


wielkopolskieType Qua Pow Type Qua Pow 4 1.06 17 9.21 2 100.5 1 2.08 1 0.011 22 10.57 18 1.254 2 0.825 1 20 4 0.000

mazowieckie

Type Qua Pow Type Qua Pow 2 2.989 4 3.336 66 63.745 1 3.564 36 2.154 3 0.000

łódzkie


dolnośląskie

Type Qua Pow Type Qua Pow 2 0.96 2 0.66 1 2.6 2 0.75 21 1.174 1 0.37 2 0.000

lubelskie

Type Qua Pow Type Qua Pow 2 0.98 1 0.36 1 1.9 1 10.8 12 4.406 33 1.62 1 0.000

świętokrzyskie

Type Qua Pow Type Qua Pow 2 0.862 2 0.9 17 1.513 3 2.68 11 20.81 1 0.000

opolskie

Type Qua Pow Type Qua Pow 11 4.249 14 8.583 1 0.21 2 0.022 11 3.8 27 2.397 1 0.36 2 33.6 9 0.000 1 0.000

śląskie

Type Qua Pow Type Qua Pow 4 1.124 5 2.938 7 1.464 30 2.661 5 2.27 7 17.4 1 8 1 50 1 92.75 5 0.000

małopolskie

Type Qua Pow Type Qua Pow 5 2.083 3 1.764 1 0.58 1 6 14 26.78 9 0.649 1 0.825 1 8.3 1 198.6 2 0.000

podkarpackie

Type Qua Pow

Type Qua Pow Type Qua Pow


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Tab. 1. Structure of renewable electricity generation

# Plant type No. of plants Power [MW]

1

biogas plants 144 82.884

a) sewage treatment biogas fired 56 28. 474

b) landfill biogas fired 80 45.994

c) agricultural biogas fired 8 8. 416

2wind farms 413 1 180.272

a) onshore wind farms 413 1 180.272

3

hydroelectric power stations 727 937.044

a) flow plant up to 0.3 MW 578 41.873

b) flow plant up to 1 MW 78 48.248

c) flow plant up to 5 MW 56 126.163

d) flow plant up to 10 MW 6 48.280

e) flow hydro plant over 10 MW 6 289.800

f) pumped - storage or flow with pump element hydro plant 3 382.680

4

co-fired plants 41 0.000*

a) co-fired (fossil fuels and biomass) plants 40 0.000*

b) co-fired (fossil fuels and biogas) plants 1 0.000*

5

biomass plants 18 356.190

a) forest, agriculture, and garden waste biomass fired 7 12.110

b) wood-derivative and cellulose and paper waste biomass fired 6 230.200

c) mixed biomass fired 5 113.880

6solar plants 3 0.033

a) solar plants 3 0.033

TOTAL: 1 346 2 556. 423

* Because of different ranges of the percentage biomass share (in the total fuel flow), no total installed capacity is specified for co-fired plants

3. DISTRIBUTED GENERATION DEVELOPMENT IN POLAND

The Ministry of Economy’s document “Polish Energy Policy until 2030” [4], adopted by the Council of Ministers in 2010, provides in the matter of distributed generation that: “An important element of the energy security improvement is development of distributed power generation, using local energy sources, like methane or RES. Development of such power generation also allows reducing grid investment, particularly in the transmission system. The system of incentives for distributed power generation in the form of support schemes for RES and CHP will result in substantial investment in distributed energy resources”.

The distributed power generation related objectives of the Polish Energy Policy include:a) as regards energy efficiency improvement

Reduction of transmission and distribution grid losses by upgrading the existing and building new grids, replacement of low efficiency transformers, and development of distributed generation

b) as regards electricity and heat generation and transmissionExpansion of distribution networks to enable development of distributed generation using local energy sources

c) as regards mitigation of the power sector’s environmental impact.Changes in the energy distribution structure towards low carbon technologies and increased relevance

of cogeneration and distributed generation. According to “Polish Energy Policy until 2030” vital in the Polish conditions and in the context of accomplishing the adopted objective of a 15% share of energy from renewable sources in the gross final energy consumption structure by 2020, will be the progress made in wind generation,biogas and solid biomass production,and in transportation biofuels. In 2020 these four areas will altogether


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represent ca. 94% of energy consumption from all renewable sources. Table 2 shows a forecast developed in the ‘’Energy Policy” framework of the gross installed electricity generation capacity broken down by 17 types of fuel and applied generation technologies. By 2020 renewable technologies will altogether account for 25.4% of the total generation capacity (22.6% in 2030). A decrease in this percentage in 2020-2030 will be mainly due to inclusion in the specification of nuclear energy, which is to appear in Poland after 2020.

Tab. 2. Forecast of gross electricity generation capacity until 2030 [4]

Fuel/ technologyGross electricity generation capacity, MW

2010 2015 2020 2025 2030

Lignite - PC / fluidized bed 9 177 9 024 8 184 10 344 10 884

Coal - PC / fluidized bed 15 796 15 673 15 012 11 360 10 703

Coal - CHP 4 950 5 394 5 658 5 835 5 807

Natural gas CHP 710 810 873 964 1 090

Natural gas GTCC 0 400 600 1 010 2 240

Large hydro 853 853 853 853 853

Pump-storage hydro 1 406 1 406 1 406 1 406 1 406

Nuclear 0 0 1 600 3 200 4 800

Industrial, coal - CHP 1 411 1 416 1 447 1 514 1 555

Industrial, gas - CHP 50 63 79 85 92

Industrial, other - CHP 730 834 882 896 910

Local gas 0 22 72 167 278

Small hydro 107 192 282 298 298

Wind 976 3 396 6 089 7 564 7 867

Solid biomass - CHP 40 196 623 958 1 218

Biogas CHP 74 328 802 1 293 1 379

Photovoltaic systems 0 0 2 16 32

Total 36 280 40 007 44 464 47 763 51 412

“Polish Energy Policy until 2030” does not include the high-rate growth of DG, and development of plus-energy buildings, assumed in EU directives. Hence, there are other, different concepts of the energy sector development in Poland, which assume:

1. Option to entirely abandon nuclear power2. Significant reduction of the traditional coal technology based power generation3. Rapid development of CHP in industry4. Rapid development of biogas fired CHP systems5. Generation capacity reduction by about 6,000 MW (compared to the government assumptions) because

of the planned power generation decentralisation (smaller transmission and conversion losses, higher efficiency of receiving devices)

6. High-rate development of the prosumer market (plus-energy buildings), whereby over 20% of the domestic energy will be generated locally in plus-energy buildings.

There are the following reasons for the forecast high-rate long-term development of distributed power generation [5]:

1. Depletion of the potential resulting from implementation of TPA principle as a mechanism, commonly applied throughout the world,

intensified competition in electricity and gas markets2. Rise of new technologies increasing competitiveness in the electricity and gas market beyond TPA

principle3. Launch of CO2 emission trade


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4. Unbalanced tax system, in particular the excise tax system (e.g. high excise duty on petrol and diesel, no excise duty on natural gas)

5. The European Commission strategy (development of a unified EU energy, rather than electricity, securityspace)

6. Growing relevance of the trend in which distributed generation development is a „by-product” of environmental protection measures.

7. Distributed generation impact on settlement system development and transformations (regional development policy).

8. Distributed generation impact on settlement system development and transformations (regional development policy).

4. DISTRIBUTED GENERATION AS A SOURCE OF REGULATING ANCILLARY SERVICES

The current rules of distributed generation sources management and the technical to be met by these sources depend largely on the source specific capacity (power of a single generation unit), the rated voltage of thegrid to which the sources are connected, and on the point of connection (closed grid, open grid). Depending on the above listed factors, these rules and technical requirements are defined in the transmission and distributiongrid codes IRiESP and IRiESD, respectively.

It is currently believed that the existing distributed generation management capabilities may be extended by obtaining such sources for provision of regulating ancillary services. Regulating ancillary services are the services provided to the transmission system operator that are necessary for the national power system’s proper operation, and ensure maintaining certain values of reliability and quality parameters [6]. Obtaining distributed generation for the purpose of the power system control from the transmission system operator level should be associated with relatively large (30 MW +50 MW) rated powers of individual distributed generation units, or with the possibility of grouping small distributed generation units. The first case will occur relatively rarely, and now it may be regarded as belonging tothe group of coordinated generation units. In practice, solutions should be sought concerning a large number of small generation units.

The results of preliminary studies on the application of distributed generation sources in the provision of ancillary services indicate that in the short-term perspective, from the viewpoint of the transmission system operator (TSO), distribution generation’s participation may be considered in the provision of the following services [7], [8]:

1. Primary control reserve 2. Operating reserve (spinning and emergency) for secondary and tertiary regulation, including distributed

generation participation in DSR programmes [9] offered by TSO (fault control programmes).In the longer time perspective, the distribution generation participation in the following services may be

considered:1. Reactive power and node voltage regulation2. Autmatic generator start3. Supply of separated island systems.The autostart and island operation systems may now be considered as prospective solutions. From the

technical point of view the application potential of power reserve services is the greatest.The primary regulation service will be especially attractive for large distributed generation units based on

non-renewable energy sources. In order to exploit the potential of distributed generation application in primary control, appropriate technical measures must be implemented in the control (management) system. This means that communication must be established with each distributed generation unit to control and monitor which generators and to what extent are involved at the moment in the primary regulation. In turn, each generation unit should be provided with a proportional turbine control system (adjustable according to the turbine droop).

Furthermore, because of its participation in primary regulation, a source’s generation capacity cannot be fully utilised (operation at a load below the maximum power). Therefore the service price must compensate the cost of this performance loss. This cost may be particularly high in renewable energy sources that use various financial support mechanisms (certificates).

It can be assumed that all distributed generation technologies feature short response time, and as such are well suited for primary regulation. Especially the systems equipped with power electronic converters, such as wind turbines, fuel cells and microturbines are able to provide this service.


65

REFERENCES

In systems using wind power plants for frequency regulation it is necessary to apply the delta mode active power control mode, whereby a constant power margin is maintained with the option to use it for regulation purposes.

Particularly capable of primary regulation of frequency are CCGT gas-steam plants and CHP systems with gas fired engines (technology-wise biogas-fired generation and cogeneration plants do not differ much fromsimilar natural gas-fired systems, they also have similar operating properties). Effective use of such systemsas ancillary service providers requires, first and foremost, enabling electricity generation in the absence ofdemand for heat. Asynchronicity of the demands for heat and electricity is therefore a significant obstacle. Units’operating flexibility may be obtained through the use of heat accumulators or through system expansion by acooler to disperse the excess heat. In this type of system the revenues from the provision of ancillary services should be significant enough to offset the additional costs and the lost revenues.

In order to enable distributed generation participation in the KSE national power system control process, solutions are still needed for a several key issues, which include:

1. Rules for distributed generation unit groups’ creation and operation2. Service procurement mode3. Service billing 4. Scope and manner of information exchange between grid operator and generators5. Rules of the KSE national power system operation planning with consideration of the distributed

generation management system.

5. SUMMARY

The currently observed broad development of distributed generation in Poland results from, among other factors, the European Union’s promotion of electricity from distributed energy sources, particularly from renewable sources. The large-scale advent of distributed generation in the power system is still a new phenomenon and causes many problems of a technical and economic nature. To obtain distributed generation for the purpose of power system control the appropriate and consistent management mechanisms need to be implemented. Development of the distributed generation management mechanism is a very difficult task and sofar has not been practically and comprehensively resolved. Numerous R&D centres, often in cooperation with distribution grid and transmission grid operators, are currently implementing numerous projects aimed at the development of consistent mechanisms for distributed generation management that would enable acquisition of this type of generation for the provision of ancillary services.

1. Ackermann T., Andersson G., Söder L., Distributed generation: a definition, Electric Power Systems Research 57(2001), pp. 195–204.

2. Paska J., Wytwarzanie rozproszone energii elektrycznej i ciepła, Warsaw University of Technology Publishers, Warsaw 2010.

3. The Energy Regulatory Office, http://www.ure.gov.pl/uremapoze/mapa.html.4. Polityka energetyczna Polski do 2030 roku, The Ministry of Economy, adopted by The Council of Ministers on

10.11.2009.5. Stabilizacja bezpieczeństwa energetycznego Polski w okresie 2008–2020 (z uwzględnieniem perspektywy 2050) za

pomocą mechanizmów rynkowych, własnych zasobów i innowacyjnych technologii, collective work edited by. J. Popczyk, Gliwice, 2008.

6. Glossary of terms, http://slownik.cire.pl/?id=235.7. Nyeng P ., Pedersen K.O.H. and Østergaard J., Ancillary services from distributed energy resources – perspectives for

the Danish power system, IYCE 2007 Conference.8. Porter D., Strbac G., Mutale J., Ancillary service provision from distributed generation, CIRED2005 18th Interna

tional Conference on Electricity Distribution.9. Rasolomampionona D.D., Robak S., Chmurski P ., Tomasik G., Przegląd istniejących mechanizmów DSR stosowanych

na rynkach energii elektrycznej, Rynek Energii, No. 2 (87), 2010, pp. 138–143.


66Tomasz Sikorski / Electrical Engineering Faculty, Wrocław University of TechnologyEdward Ziaja / Institute of Power Systems Automation Ltd., WrocławBogusław Terlecki / Kamieńsk Wind Power Plant Capital Group PGE Energia Odnawialna Warsaw


Edward ZiajaWrocław/ Poland

A graduate of the Electrical Engineering Department of Wroclaw University of Technology. Since 1980 associated with the Institute of Power System Automation in Wroclaw. Author and co-author of numerous patents, utility models, and implementations in the Polish, as well as Turkish and Algerian power sectors. Now, as chairman of the board, he manages the Institute of Power Systems Automation Ltd.

Tomasz SikorskiWrocław / Poland

A graduate of the Electrical Engineering Faculty of Wrocław University of Technology, where he is now an assistant professor. His PhD thesis concerned analysis of power disturbance signals using time-frequency analysis. His interests currently focus on issues of power quality and integration of distributed generation with power systems. Since the implementation of a grant from the Ministry of Science and Higher Education, also an associate researcher at the Institute of Power Systems Automation in Wroclaw.

Bogusław TerleckiKamieńsk / Poland

A graduate of the Chemical Engineering Department

of Gdansk University of Technology, and of the

Department of Economics and Social Sciences of Łódź

University. He works at the Operations Department of

Polska Grupa Energetyczna Energia Odnawialna SA as

the Department’s Deputy Director. He deals with the

operation of wind farms, including the wind farm in

Kamieńsk, which has been incorporated into Capital

Group PGE Energia Odnawialna Warsaw. His research

interests include issues related to regulating capabilities

of wind farms in a power system.

67

THE DYNAMIC ASPECTS OF WIND FARM OPERATION – MEASUREMENTS AND ANALYSIS

Tomasz Sikorski / Electrical Engineering Faculty, Wrocław University of Technology Edward Ziaja / Institute of Power Systems Automation Ltd., Wrocław

Bogusław Terlecki / Kamieńsk Wind Power Plant Capital Group PGE Energia Odnawialna Warsaw

1. INTRODUCTION

The specific nature of wind turbine operation depends on wind conditions. On the other hand, theflexibility of active and reactive power output adjustment offered by contemporary power electronic systemsmake integration of wind farms with the national power system a current and constantly developed subject. The Distribution Grid Code IRiESD [1] Transmission Grid Code IRiESP [2] distinguish several groups of issues related to the working of wind farms with the NPS. They include: active power control, operation at various voltages and frequencies, switching on and off to the grid, voltage and reactive power control, requirements for operation at faults in the grid, maintaining power quality standards, coordination of power system electronic protections, monitoring and telecommunications system, and checking tests.

This paper deals with the issues of wind farm operation dynamics in the context of fault events in the grid. For this purpose actual measurements were taken at a 110 kV common connection point of a 30 MW wind farm. Theoretical analysis of the technical capabilities to maintain farm operation in undervoltage conditions was introduced, and confronted with results of farm performance measurements in the constant power factor regime.

At the same time, it is worth noting that the aspect addressed in this paper of wind farm active participation in the process of working with the NPS, as a source of active and reactive power alike, follows the latest trends now discussed in the development of smart power grids. One of the products widely discussed in the scope of generation is a so-called virtual power plant gathering many distributed generation sources into a single common information and control system associated with the instantaneous demand for electricity and the share in the energy market. This would allow for development of so-called clusters that could flexibly respond to dynamic changes in powerdemand, or participate in the regulation of the system operation and its reserve capacity [10, 11].

2. CHARACTERISTCS OF ANALYSED WIND FARM AND MEASUREMENT SYSTEM

The test wind farm consists of 15 Enercon GmbH E70 - E4 type 2 MW turbines. The turbines are interconnected with 30 kV cable lines. Together with the necessary technical equipment they comprise a complete technical assembly used to generate the farm’s total output of 30 MW electric power [3, 4].

A ring-type synchronous E70 - E4 generator is directly driven by a turbine rotor, reaching rated power at the rotor speed of ca. 21.5 rpm and wind speed 12.7 m/sec. The power is output at 0.4 kV by a WEC Wind Energy Converter with an AC-DC-AC frequency converter in the stator circuit, and is an example of the flexible

FIC (Full Converter Interface) solution. The farm is coupled with the grid at the connection point to the internal cable grid by a 30/0.4 kV set transformer. The conversion parameters are controlled by a superior Grid Management System. This system also controls to a large extent the plant’s co-operation with the system in terms of implementing the operator requirements, including coordination of the plant’s behaviour in fault

Abstract

This paper presents selected results of actual measurements of a 30 MW wind farm connected to the 110 kV distribution grid. Presented analyses pertain to the dynamic aspects of the cooperation with the system

in grid fault conditions. Discussed are the possibilities to maintain the 30 MW plant operation in the undervoltage conditions in relation to the operator requirements.

The Dynamic Aspects of Wind Farm Operation – Measurements and Analysis

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conditions, the maintenance of electricity quality parameters, and the capability to control active power and frequency, and reactive power and voltage [5]. The E70 plant’s basic functional blocks are presented in Fig. 1.

The internal 30 kV grid structure is divided into radiuses of seven and eight E70 turbines, while in each radius there is one turbine additionally equipped with a STATCOM static reactive power compensation system (Static Compensator). A MW shunt reactor is installed in the 30 kV substation.

The farm is connected to the 110 kV distribution grid with a cable line to the Distribution System Operator (DSO) MSP substation. The farm is not subject to superior control by substation automation, i.e. automatic voltage and reactive power control at the generation node (ARNE - Automatic Power Plant Voltage Regulation) and automatic grid voltage regulation by way of transformer voltage control (ARST - Automatic Transformer Station Voltage Regulation). In addition, because of the farm location in the vicinity of a large conventional power plant, the grid condition should be considered as rigid and largely enforced by the system power plant system operation.

Measurements were made in the secondary circuits of the voltage and current transformers at the upper side of the 110 kV grid transformer (power output to the system), and additionally at the 30 kV grid transformer’s lower side. Results were recorded by a Class A device configured for continuous data recording with averagingat 1 min, 10 mins, 15 mins, and for recording of 200 ms RMS values using the half-cycle algorithm. In addition, registration was triggered of 0.8 s oscilloscope voltage and current signals, depending on the adopted exceedance levels, to capture and save the faults. The recording time division was 0.2 s / 0.6 s, where 0.2 s included the time before the transient state. Sampling frequency was 10240 Hz. The location of measurement points in the diagram of power output from the farm is shown in Fig. 2.

Fig. 1. Visual rendering of E70 turbine basic blocks

Tomasz Sikorski / Electrical Engineering Faculty, Wrocław University of TechnologyEdward Ziaja / Institute of Power Systems Automation Ltd., WrocławBogusław Terlecki / Kamieńsk Wind Power Plant Capital Group PGE Energia Odnawialna Warsaw

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Fig. 2. Wind farm connection to the system and measuring system locations

3. THEORETICAL ANALYSIS OF TECHNICAL CAPABILITIES TO MAINTAIN WIND FARM OPERATION IN THE GRID

To discuss the farm operation in fault conditions, attention should be paid to the interaction of a group of basic power electronic protections that safeguard individual turbines and ultimately the farm and the protections from the effects of system faults. The basic protection group includes delayed and instantaneous overcurrent protections, ground fault protections, overvoltage protections, and temperature protections. The protections against system faults include undervoltage, overvoltage, underfrequency, and overfrequency protections. The role of protection against system fault effects includes the farm protection, such as overvoltage protection, but also preventing the farm’s unnecessary outages from operation in the system. This objective gains particular importance in weaker grids, whereby a farm can provide reinforcement, or in systems with high saturation of local farms. Most commonly quoted examples refer to the farm operation maintenance in spite of a frequency drop due to a power loss in the system, or to the turbine behaviour in the face of short-circuits in the system. The farm’s quick switch off by underfrequency protections could lead to a further imbalance of active power and a deeper drop in frequency. Short circuits in the system are recognized by undervoltage protections as voltage dips. At the same time, automatic short-circuit system (substation) protections respond to short-circuits in a relatively short time (from a few to over a hundred milliseconds). Just as a rapid plant switch off by the plant’s undervoltage protections in a time shorter than the short-circuit elimination by the system automatics may introduce additional deregulation in the system [6, 7].

Ultimately, the plant operating point profiles with regard to frequency and voltage conditions in theconnection point have been formulated and published in the IRiESP and IRiESD grid codes for wind farms as well as in the ENTSO-E grid codes. Fig. 3 illustrates the voltage conditions in the form of characteristics U = f (t) of the required range of the wind turbine operation maintenance in the event of grid fault occurrence resulting with undervoltage (typically because of short-circuits). For faults with voltages and durations in the area over the curve, the farm operation should be maintained [1, 2].


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According to references provided by the manufacturer and available from literature [5, 8, 9], the solutions incorporated in the Enercon turbine enable extension of the AC-DC-AC (WEC+FACTS) main conversion system capabilities by features of turbines’ characteristics of transition through undervoltage fault conditions in the form of the UVRT (Under Voltage Ride Through) option. The manufacturer reports the solution’s capabilities up to 5 s fault, as it is defined in the system operator characteristics. Due to the separation of the generation side from thepoint of connection to the internal LV grid by the DC connection, the rotor and inverter may operate regardless of the voltage conditions. In order to maintain control of the AC-DC-AC conversion process and of the technical equipment operation, an internal UPS power supply system is connected to the DC part. The WEC+FACTS system solution provides flexible options of active or reactive power generation during a grid fault.

The plant operation may be maintained during a short-circuit in the system according to the following four scenarios:

• active and reactive power output maintenance at fixed P/Q ratio• maintenance of active power output only• mainly reactive power “injection”• ZPM Zero Power Mode.

Fig. 3. Characteristics U = f (t) of the required range of wind turbine operation maintenance in the event of grid fault occurrence referring to IRiESP, IRiESD in comparison with ENTSO-E

Fig. 4. Theoretical analysis of E70 turbine operation maintenance capabilities at short-circuit using UVRT regulation


71

The available modes of turbine operation in undervoltage conditions described by the manufacturer are limited by the allowable characteristics U = f (t) and the tripping of other protections, from the basic group as well as dedicated to working with the grid.

In the first mode, due to the reduction of voltage conditions the active and reactive power is reduced witha constant power factor. In the second mode only the active power is reduced, but at zero reactive power. In the boundary conditions the energy conversion system passes over from the grid supply with active power to the “injection” of reactive current to the grid up to the rated power ranges. In this way one of the newest concepts of wind turbine application as a reactive power source and of support of the system operation during a short circuit can be implemented. It should be underlined, however, that such an application depends on the plant location in the system in terms of power flows. The UVRT solution’s other operating mode is the so-called ZPM Zero Power Mode. This modeof UVRT system operation stops reactive current injection into the system and active power generation. In many cases this depends on the connection point characteristics, and on the technical requirements of connection.

Also a combination of the UVRT system operating modes is possible, for instance upon the short-circuit start the system operates in the active mode, and at a very low voltage level it passes over to ZPM operation, ready for re-activation if during the 5 seconds of the short-circuit’s transience, the required U = f (t) characteristics are complied with.

4. ACTUAL MEASUREMENTS

In the course of measurements events in the grid were recorded, mostly those seen from the farm side, as short voltage dips. For the farm operation dynamics’ analysis and presentation the event was selected with the longest duration and deepest voltage dip, i.e. the dip caused by transient earth fault in phase L1 of the 110 kV grid. Details of the event and parameters of the WPP recording in the 110 kV grid are presented in Tab. 1.

Tab. 1. Characteristics of the selected event and WPP recording in 110 kV grid

Characteristics of the recorded event

Fault type Date, hour Parameter 1 Parameter 2 Conditions

3-phase voltage dip at significant dipin phase L1

22.05.2010 20:07:50.85 Dip duration 159,90 ms Voltage at L1 dip 40.26 kV

P = 3.7 MWQ = -0.2 Mvar

Recording parameters

Recording triggered with oscilloscopic voltage and current signals

recording duration 0.8 s divided into 0.2 s prior to event and 0.6 s after event; sampling frequency 10,240 kHz (time definition 0.0976 ms, 2048 samples per 10 basic component cycles)

Continuous recording of RMS values half-cycle algorithm, averaging interval 200 ms, time resolution 1 value per 10 basic component cycles

In the effect of the discussed grid event a current surge was recorded of ca. 20 A per phase prior to the event up to ca. 140 A after the event, and a voltage dip in L1 phase down to 40.26 kV, i.e. 63.4% of the rated RMS voltage on the 110 kV side, of 160 ms duration. Then the farm was disconnected from the system, and reconnected after ca. 4 minutes.

Fig. 5. Fragment of voltage and current waveforms recorded in WPP 110 kV at transient ground fault in phase L1 in the grid


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The discussed event of short-circuit in the grid is seen from the farm side as a transient voltage dip. The phenomenon’s parameters, i.e. the dip depth and duration, situate it on the U = f (t) characteristics required by IRiESP and IRiESD grid codes in the farm operability maintenance area. However, the cooperation of basic protections, including overcurrent protections and protections against system event effects, doesn’t allow for the farm operation maintenance during the phenomenon.

The theoretical analysis presented here of the AC-DC-AC system control available options and modes as an addition to the UVRT regulation indicates a broad range of opportunities for the farm’s cooperation with the system in the farm operability maintenance scenario. Currently, however, the farm operates in the constant power factor control mode, and the operability maintenance is not implemented.

Fig. 6. Assessment of power generation in 110 kV WPP at single-phase short-circuit with regard to the farm operation “with constant power factor”

Fig. 7. Assessment of voltage conditions in 110 kV WPP at single-phase short-circuit with regard to U=f(t) characteristics according to IRiESD and IRiESP grid codes


73

REFERENCES

5. SUMMARY

Requirements for wind farm interoperability with the power system cover a wide range of issues and are subject to discussion. The aspect presented in this paper of the assessment of active and reactive power output capacity of a 30 MW wind farm with power electronic systems of flexible power control remains in confrontationwith the grid code applicable requirements of power factor tgφ maintenance at the level of 0.4. Meeting these requirements greatly limits the available flexible reactive power control options. Consideration of participationof wind farms smaller than 50 MW in the system regulating processes would require development of a power factor adjustment strategy. These issues discussed in this paper contribute to a widespread discussion on intelligent power grids, particularly with regard to active inclusion of distributed sources to the power system in the form of so-called virtual power plants.

1. Instrukcja Ruchu i Eksploatacji Sieci Dystrybucyjnej (IRiESD) PGE Dystrybucja Łódź-Teren SA., approved by Resolution No. 154/2008 of 11.06.2008, in particular Attachment 3: Szczegółowe wymagania techniczne dla jednostek wytwórczych przyłączanych do sieci dystrybucyjnej along with point 7 of Attachment: Dodatkowe wymagania dla elektrowni wiatrowych. PGE Dystrybucja Łódź-Teren SA.

2. Instrukcja Ruchu i Eksploatacji Sieci Przesyłowych (IRiESP) – Warunki korzystania, prowadzenia ruchu, eksploatacji i planowania rozwoju sieci (revision 1.2. of 17.03.2007 takes into account the amendments implemented by way of update cards K/1/2007, K/2/2007), and in particular point II.B.3.3.3. Wymagania techniczne i warunki pracy farm wiatrowych, PSE SA Operator.

3. Gawdzik M., Rumik A., Elektrownia Wiatrowa Kamieńsk – information bulletin4. Kamieńsk Wind Power Plant web page http://www.ewk.pl.5. Grid integration and wind farm management – folder, http://www.enercon.de.6. Lubośny Z., Farmy wiatrowe w systemie elektroenergetycznym, WNT, Warsaw 2009.7. Grządzielski I., Sposoby kompensacji mocy biernej farm wiatrowych, Nowoczesne elementy układów przyłączenio

wych do systemu elektroenergetycznego – przyłączanie farm wiatrowych, Expopower International Power Industry Exhibition, Poznań 2010.

8. Hartge S., Wachtel S., Technical and economic benefits of wind energy converters with FACTS capabilities for thepower system and the grid integration of wind power, EWEC Conference 2007.

9. Wachtel S., Wind energy converters with FACTS capabilities and their options for the grid integration of wind power into power systems, NZ Wind Energy Conference 2010.

10. Pudjianto D, Ramsay C, Strbac G., Microgrids and virtual power plants: concepts to support the integration of distributed energy resources, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, Volume 222, nr 7, 2008.

11. www.encorp.com – Encorp Corporation: Virtual Power Plant – Product and Technical Data Sheet.


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Wiesław NowakKraków / Poland

A graduate of AGH University of Science and Technology. He received his M.Sc. degree in engineering (1988), then PhD (1995) and postdoctoral degree (2006) in the field of electrical engineering atthe Faculty of Electrical Engineering, Automatics, Computer Science and Electronics of AGH University of Science and Technology. He has worked at AGH University of Science and Technology since 1987, now as an associate professor. He specializes in power system engineering, and his main scientific interests are related tocomputer modelling and analysis of dynamic states in power systems

Rafał TarkoKraków / Poland

Received his Master’s degree in electrical engineering, specialization in electrical engineering, at the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics of AGH University of Science and Technology (2001). PhD received at the same faculty (2007). He has been working at the Department of Electrical and Power Engineering of University of Science and Technology since 2001. His main research interests include the analysis of operational and electromagnetic stress related to transient states in power systems.

Waldemar SzpyraKraków / Poland

Graduated in electrical engineering from the Faculty of Electrical Engineering of Mining and Metallurgy of AGH University of Science and Technology (1975). His PhD obtained at the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics of the same University (1998). Now an assistant professor at the Department of Electrical and Power Engineering of his alma mater. His interests include modelling, operating condition estimation, and optimization of distribution grids, application of artificial intelligencemethods in electric power engineering, and electric power economics.

Andrzej MakuchKraków / Poland

He received his Master’s degree in electrical engineering, specialization in electric power engineering, at the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics of AGH University of Science and Technology (2010). He has been working at the Department of Electrical and Power Engineering of AGH University of Science and Technology since 2010. His main interests include computer modelling of automatic controls.

Mariusz BeneszKraków / Poland

Received his Master’s degree in electrical engineering, specialization in electric power engineering, at the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics of AGH University of Science and Technology (2006). He has been working at the Department of Electrical and Power Engineering of AGH University of Science and Technology since 2008. His interests include various issues of the operational exposure in electrical power systems

Rafał Tarko, Wiesław Nowak, Waldemar Szpyra, Mariusz Benesz, Andrzej Makuch / AGH University of Science and Technology in Kraków

75

FERRORESONANCE AS A SOURCE OF DISTURBANCES AND FAILURES IN MEDIUM VOLTAGE DISTRIBUTION GRIDS

Rafał Tarko / AGH University of Science and Technology in KrakówWiesław Nowak / AGH University of Science and Technology in Kraków

Waldemar Szpyra / AGH University of Science and Technology in KrakówMariusz Benesz / AGH University of Science and Technology in Kraków

Andrzej Makuch / AGH University of Science and Technology in Kraków

1. INTRODUCTION

Ferroresonance phenomenon occurs when a ferromagnetic core inside an electrical device – primarily a voltage transformer or an unloaded power transformer – operates in the saturated condition, under which inductance has become a non-linear element. In practice ferroresonance can be triggered even by a temporary introduction of core into saturation, e.g. resulting from switching operations or a change in voltage resulting from an earth fault. Although this phenomenon is known in electric power engineering since the 1930s, neither effective criteria for diagnosing the possibility of its occurrence, nor means to counteract it have been specifiedto date [1, 2].

Ferroresonance as a source of disturbances and failures in medium voltage distribution networks, e.g. [3], is dangerous in its consequences for the following two main reasons:

• significant saturation of the core, which can lead to, for instance, thermal damage of voltage transformer’sprimary winding

• development of (often lengthy) ferroresonance overvoltages.Furthermore, the neutral point’s increased potential also makes the zero sequence voltage appear in the

system, which can falsify the operation of ground fault protection [4].The paper presents an analysis of ferroresonance that occurred in a 6 kV distribution grid and disrupted

its operation. The analysis was based on grid system models developed for the EMTP-ATP programme, and on results of simulation studies designed to determine the ferroresonance occurrence conditions and consequences, as well as means to eliminate it.

2. ANALYSED SYSTEM CHARACTERISTICS – PROBLEM ORIGINS

Subject to the analysis is a part of 6kV power grid supplied form 110/6 kV substation (MSP – Main Supply Points) and cogeneration plant (CHP). A simplified diagram of MV switchgear is shown in Figure 1. The MSP ispowered by two 16 MVA transformers: 115 ± 10% / 6.3 kV (TR-1) and 115 ± 10% / 6.6 kV (TR-2). The CHP is equipped with a 11. 4 MVA generator. The total length of MV cable lines in the system is over 60 km. The analysed grid operates with an insulated neutral point, and the ground fault current in the grid, in the normal regime supplied from transformer TR1 is Ic1 = 52.05 A, whereas in the grid supplied from transformer TR2 the ground fault current is Ic2 = 40.99 A.

Ferroresonance as a Source of Disturbances and Failures in Medium Voltage Distribution Grids

Abstract

The article reports a medium voltage power grid analysis carried out to identify the grid’s operating conditions in the aspect of ferroresonance occurrence. A documented ferroresonance instance is presented, which led to the voltage transformers’ damage. The analysis

was based on an original grid system model and on results of simulation studies designed to determine the ferroresonance occurrence conditions and consequences, as well as means to eliminate it.

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Fig. 1. Simplified diagram of MV switchgear in the grid

A disturbance occurred in the 6 kV network that led to a failure (explosion) of voltage transformers in the measurement bays (bays 0 and 16) of the 6 kV MSP distribution substations and in the CHP switchgear (bays 12 and 17).

The disturbance was caused by a short circuit in the cable line powered from the MSP (bay 24) and opening of the circuit breaker in the bay resulting from tripping of the over-current and ground fault protection. A few minutes after switching off the line transformer No. 2 was switched off as a result of tripping of the ground fault and over-current protection. The grid was switched over by the Automatic Transfer Switch Equipment (ATSE) to supply from transformer TR1.

On the basis of this string of events a hypothesis may be formulated that in the initial line-to-earth short circuit subsequently developed to the two-phase-to-earth fault. Immediately after the damaged cable line’s switch off in the grid an unsuppressed (sustained) ferroresonance developed, which caused severe overload of the voltage transformers’ grounded primary windings, and consequently their damage. The voltage transformers rupture in the MSP substation’s 6 kV switchgear (a few minutes after disconnecting the damaged cable line) led to a short circuit of the buses in the measurement bay, and to actuation of the ATSE automatics, which changed the switchgear’s operating regime from normal to emergency (supply from transformer TR-1).

The presented analysis of simulation calculations results shows that the above hypothesis of the origins of the 6 kV grid failure is true.

3. COMPUTER MODEL OF THE ANALYSED 6 KV GRID

The model of the analysed 6 kV grid was developed in the simulation EMTP-ATP ElectroMagnetic Transients Program. Since the preliminary analysis of the MSP disturbance pointed to a ferroresonance phenomenon as the cause of the voltage transformers damage, therefore in the model’s development a non-linear dependence was taken into account of the voltage transformer core magnetizing currents on voltage. On the basis of the actual grid’s details and on the basis of prepared models of the voltage transformers, a model of the 6 kV system was developed (Fig. 2), consisting of:

• MSP• 6 kV cable lines outgoing from MSP• 6 kV switchgear of CHP power plant.

open circuit breaker

closed circuit breaker

open disconnector

oclosed disconnector

Legend


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Fig. 2. ATPDraw model of analysed 6 kV grid

Voltage measurement

Voltage measurement

Voltage measurement

Voltage measurement


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The mapped system components’ parameters were implemented on the basis of detailed plans of the power grid, catalogue cards of the devices installed, and laboratory measurements of the voltage transformer in the analyzed MV grid. Accomplishment of the analysis’ objective required accurate mapping of all grid elements, which might have affected the voltage and current waveforms in transient states, and thus were likely to cause the voltage transformer failure. The system components mapped in the model include in particular:

• 110 kV power system• 110/6 kV transformers installed in the MSP and mapped in BCTRAN procedure• cable lines that connect the individual substations supplied from the MSP and mapped in CABLE CON-

STANTS procedure• voltage transformers• ferroresonance suppression system.Based on the results of the 6 kV voltage transformers’ measurements a computer model was developed

as the basis for further analysis of the grid operation and simulation studies. For the purpose of the model development measurements were taken of the magnetization characteristics and short-circuit voltages of a 6 kV voltage transformer (of the same type as the transformers installed in the substation) with the following rated specification:

• primary winding rated voltage U1: 6000/√3V• secondary winding rated voltage U: 100/√3V• additional winding rated voltage U2n: 100/3 V• class: 0,5• rated power: 50 VA.Tab. 1 presents measurement results of a test of short circuit between pairs of windings. The voltage

transformer’s magnetization characteristics measured from the secondary winding is presented in Fig. 3.

Tab. 1. 6 kV voltage transformer short-circuit test results

Measurement winding terminals A-N

Measurement winding terminals a-n

Additional winding terminals da-dn

U, V I, A P , W cos

shorted powered open 5. 48 2.93 14.18 0.96

open powered shorted 6.88 3.36 22 0.88

shorted open powered 2.78 1.93 4.76 0.89

Fig. 3. Current-voltage transformer magnetization characteristics of 6 kV voltage transformer (measured on the secondary side)

The voltage transformer model diagram is presented in Fig. 4. The model consists of the following components:

• primary winding dissipation impedance ZH

0

1000

2000

3000

4000

5000

6000

0 20 40 60 80 100 120 140

I, m

A

U, V


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• secondary winding dissipation impedance Z’T transferred to the primary side• additional winding dissipation impedance Z’L transferred to the primary side• resistance RFe representing losses in voltage transformer core• nonlinear reactance Xm mapping magnetization characteristics• ideal transformers TI1, TI2.

Fig. 4. Voltage transformer model diagram Fig. 5. ATPDraw diagram of three voltage transformers’ three-phase system

The above components’ parameters determined on the basis of the measurements are presented in Tab. 1 and in Fig. 3. The ATPDraw diagram of three voltage transformers’ three-phase system is presented in Fig. 5.

The system consists of three VT units, in which were implemented the voltage transformer models presented in Fig. 4.

4. SIMULATION STUDIES OF ANALYSED GRID

The simulation results include current and voltage waveforms relevant to the operation of protective automation and the threat of ferroresonance to the 6 kV grid components. Because of activation (stimulation) during the short circuit of the earth fault as well as overcurrent protections, it was assumed that there was initially a one-phase to earth fault, which eventually evolved into a two-phase to earth fault. The disturbance condition, protection tripping at the MSP, and ferroresonance development were reproduced in the model system subject to the following assumptions:

• the first disturbance (L3 phase earth fault in bay 24) occurs in 15 ms after simulation start• the second disturbance (L2 phase earth fault and the subsequent phase-to-phase short-circuit in bay

24) occurs in 60 ms after simulation start• the circuit breaker in bay 24, where the double fault occurred, opens in 100 ms after simulation start.The resulting waveforms of phase voltages and zero sequence voltage at the 6 kV switchgear busbars in

the MSP substation are shown in Fig. 6. On the other hand in Fig. 7 the waveforms of the currents in the voltage transformers’ primary sides are presented.

VT2A

I U

VT2BI U

VT2CI U

OT2P

OT2K

U


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Fig. 6. Voltage waveforms after switching off the short circuit: a) UL1; b) UL2; c) UL3; d) 3U0

Fig. 7. Current waveforms in voltage transformer primary sides after switching off the short circuit: a) IL1; b) IL2; c) IL3

0,0 0,1 0,2 0,3 0,4 0,5[s]-10

-5

0

5

10[kV]

v:TR2B 0,0 0,1 0,2 0,3 0,4 0,5[s]

-10

-5

0

5

10[kV]

0,0 0,1 0,2 0,3 0,4 0,5[s]-9000

-4500

0

4500

9000[V]

0,0 0,1 0,2 0,3 0,4 0,5[s]-200

-100

0

100

200[V]

0,0 0,1 0,2 0,3 0,4 0,5[s]-10

-5

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10[A]

0,0 0,1 0,2 0,3 0,4 0,5[s]-10

-5

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10[A]

0,0 0,1 0,2 0,3 0,4 0,5[s]-10

-5

0

5

10[A]

a)

b)

c)

d)

a)

b)

c)


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After the short circuit switch off in bay 24 permanent ferroresonance developed. The occurrence of this phenomenon is evidenced by the appearance of the characteristic phase voltage waveforms (Fig. 6a÷6c) and of the zero sequence voltage (Fig. 6d). This is accompanied by a large increase in the voltage transformer primary side currents (Fig. 7). After the ferroresonance occurrence the peak currents reach 10 A. Such a large current is undoubtedly a serious threat to the voltage transformers and could cause damage to them.

Ferroresonance suppression capabilities in the analyzed grid were checked by adding an additional resistance to the voltage transformer additional windings connected in open triangle. The additional resistance was connected in 500 ms after simulation start (Fig. 8). Variants were analysed that assumed adding the following resistances: 5 Ω, 10 Ω, 20 Ω and 50 Ω.

Fig. 8. Voltage waveforms 3U0 after adding the resistor: a) R = 5 Ω; b) R = 10 Ω; c) R = 20 Ω; d) R = 50 Ω

In the analyzed range of added suppression resistances the possibility of the ferroresonance phenomenon suppression in the analyzed grid is revealed. The added resistance’s value, however, affects the time after which ferroresonance is suppressed – the higher the resistance, the later the suppression, and at significant values (R > 50 Ω) ferroresonance may not be suppressed at all. The analysis shows that the optimum added resistance is 10 Ω (suppression time ca. 1 s).

0,5 0,7 0,9 1,1 1,3 1,5[s]-100

-50

0

50

100[V]

0,5 0,7 0,9 1,1 1,3 1,5[s]-200

-100

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200[V]

0,5 0,7 0,9 1,1 1,3 1,5[s]-100

-50

0

50

100[V]

0,5 0,7 0,9 1,1 1,3 1,5[s]-100

-50

0

50

100[V]

a)

b)

c)

d)


82

REFERENCES

5. SUMMARY

Ferroresonance phenomena involving voltage transformers are most common in grids with an insulated neutral point, so the voltage transformers operation in medium voltage distribution grids entails the risk of their damage due to increased current in the primary winding.

The 6 kV grid model developed for the study allowed the simulation testing and analysis, that led to the following conclusions:

• ferroresonance can develop resulting from such disturbance conditions as short-circuits,• ferroresonance can be persistent, eventually resulting in voltage transformers’ damage,• ferroresonance may be suppressed by the use of an appropriate device.Effective ferroresonance suppression with a suppression resistor requires selection of a very small

resistor. Such resistance is often too small from the standpoint of the required voltage transformer immunity to long-term ground fault in the grid. Therefore, in practice resistors in the range of 20 Ωare used that ensure ferroresonance suppression in most typical conditions, but are not 100% effective. In order to solve the problem some manufacturers offer suppression devices, whereby conventional transistors are replaced with systems the resistances of which actively adjust to the actual operating conditions.

Such devices operate in the following way [3]: when zero sequence voltage is small (resulting from asymmetry in normal grid conditions) the device’s resistance is very high. When zero sequence voltage appears in excess of the device’s insensitive zone, the resistance falls to a level that effectively suppresses the ferroresonance condition. When a zero sequence voltage in the open triangle circuit persists for a long time, the device automatically switches over to the high-resistance regime without posing undue burden on voltage transformers. When the cause of asymmetry disappears, the device automatically returns to its initial state.

1. Irvani M.R. et al., Modeling and analysis guidelines for slow transients – Part III, The study of ferroresonance, IEEE Trans. on PWRD, 2000, vol. 15, no 1, pp. 255–265

2. Ben-Tal A., Kirk V., Wake G., Banded chaos in power systems, IEEE Trans. on PWRD, 2001, vol. 16, no 1, pp. 105–110.

3. Piasecki W., Florkowski M., Fulczyk M., Mahonen P. , Luto M., Nowak W., Mitigating Ferroresonance in Voltage Trans-formers in Ungrounded MV Networks, IEEE Trans. on PWRD, 2007, vol. 22, no 4, pp. 2362–2369.

4. Moskwa S., Nowak W., Tarko R., Modelowanie i analiza układu sieci średniego napięcia dla oceny warunków i skutków występowania ferrorezonansu oraz sposobów jego eliminacji, Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej, 2009, No. 26, pp. 101–104.


1. ARTICLE

2. ABSTRACT

ENERGA SA


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