smartgrid - nano-tera 2016

8/18/2019 SmartGrid - Nano-Tera 2016

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S3

SmartGridReal time monitoring and management ofsmart grids with validation in the EPFLcampus

Lausanne, 26 of April 2016


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Real-Time State Estimation of Active Distribution Networks(ADNs)

Network

monitoring

Optimal

V/P control Congestionmanagement

Losses

minimization

Optimal dispatch

of DERs

Islanding

operation

a!lt detection

and location

Real"#ime $tate

Estimation of %DNsacc!raterelia&lefast (sub-second)low latenc'

!


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Power sstem state estimation

"tate estimation of power s#stems refers to a statistical

!rocedure that processes the measurements together with thenetwork model in order to provide the most li$el# network

state%Statistical !rocedure & e%g% 'eighted Least "(uares or )alman *lter%Network model& networ$ topolog# and line electrical parameters%

Network state & phase+to+ground nodal voltages%

State EstimationEstimate

dstate "

etwor$ model

-easurements. /ncertainties

Real+time state estimation& state estimation at #i$# refres#

rate several tens of frames+per+second, e%g% enaled # the

use of snc#ro!#asor measurements provided # P%&s%


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6

ower sstem state est mat on'vs* +,(eighted Least $)!ares

• static algorithm: uses only

meas!rements and network model• widely-used in power systems

*alman filter

• rec!rsi+e algorithm, i.e. it uses also aprocess model to represent the time-evolution of the system

• we ha+e de+eloped and +alidated aprocess model s!ita&le for powers'stems state estimation

Concl!sions

* has &etter acc!rac' than (L$ when the

system is in normal operating conditions

Numerical results:

Time evolution of the state

Estimation errors

[1] Sarri, Zanni, Popovic, Paolone, Le Boudec, “ Performance

Assessment of Linear State Estimators using

Synchrophasor Measurements”, EEE Trans! on

nstrumentation and "easurement!

.P


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uplicated networ!

stem arc tecture .Pcommunication

Dedicated communication networ$, resilient topower outages% Reliabilit through an innovative pac$et duplication

method& iPRP' internet Parallel Redundanc# Protocol% E3isting P-/s and P45s ta$e advantage of

redundant networ$s without eing aware of pac$etreplication% "upports P routed networ$s and multicast% o changes in the applications that run on P45 and P-/s% o changes in the networ$ devices%

ADN Communication Network: Reliability with

iPRP

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%ulticast aut#entication& per P-/ authentication withno shared secret is re(uired for an A48 we evaluated

state+of+the art schemes and found that E54"A with pre+computed to$ens is feasile%

"ecurit# of the time snc#roni/ation !rotocol remainsan issue, even with cr#ptograph# and authentication,

ecause of dela attacks* 'e demonstrated that a dela#attac$ is possile and, so far, undetectale%

Securit for ADNs

9

"y inserting asymmetric delays

in lin!s to appropriately chosen

pairs of #$%, we can modify

the measured phasor angles in

ways that are undetectable. &e

induce the grid operator intounder- or over-estimating

power flows.

t


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' - ase mon tor n$sstems

:

'ith the infrastructure deplo#ed in the EPFL campus&

-onitoring of the state of the s#stem voltage levels with highrefresh rate and low latenc#8

4evelopment of the *rst application& ,ault Detection and,aulted ine .denti3cation*

4etects the e"istence of a fault8 denti*es the faulted line, fault t!e and estimate the fault

current4

5ompatile with real-time !rotection*


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P%&-based monitorin$ sstems

'pplication: ault etection and aulted ine *dentification

using #$%-based +eal-ime State stimation

mplemented # using& Real-time simulator reproduces real+networ$

ehavior in real+time Real P%& al$orit#m used in EPFL to generate the

measurements Real measurement noise model otained in EPFL


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P%&-based monitorin$ sstems

E3tensivel# tested for several scenarios&• Real distribution or transmission test networ$8

• Low, high or ver# high im!edance faults 1 ;, 10 ;, 1000 ;8• "everal fault t!es and fault locations4• Earthed or unearthed neutral4• Large presence of distributed $eneration and di


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Smart buildin$ environment

1

• oads are organied in

clusters for management

purposes.

• Intelligent Loads (iLoad )• oads identification/• Specific loads

monitoring 0 control/

• 1entralied low powercommunication layer.


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owPowe

r

Smart 5uildin$ Environment

1

2 3 3 2 2 3

3 3 2 3

2 3 2

222

ioads :• agging• $onitoring• 1ontrol

nergy $anagement System:• aily forecasting• Smart-4rid dialog

E-"

'5

#sers

"uilding $anagement System:• ' representative segment of

the unifying database model• ata mining 0 users interface

"$S

$iddleware:• istributed messaging• 6irtual emulator for

"uilding

owatenc

6uman5asedearni

n$


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Distributed-Scalable Arc#itecture

1

e"mart=s

eplugs

• iLoads• HES-S

sensors

>"4? speciali@ed for

storing time var#ingdata&

• "pace ecient• "amples (ueries

optimi@ed

Hermes: !he "istribute" messagingmi""leware

"olution for&• Latenc#• Reduced Power• 4istriuted message dispatching B

processing

openBMS: !he centrali#e"

management ser$er "calale solution

• Cigh+Level integration of allinfrastructure

• "ervice provides AP . 'esoc$ets

>he actual applications and interfacingwith the 4D, C4, E-" and general the

e%ternal stakehol"ers


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P7' .nte$rated c#i! desi$n

Transient Simulation 6ardware

Arc#itecture


Arc#itecture .8 Desi$n


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P7' .nte$rated c#i! desi$n


Arc#itecture .8 Desi$n

AS.8 Part (2nodes)

Si/e

>ERFA5E

DR4

"/PPL >RA5)"

T9TA

AS.8 Part (2nodes)

Si/e

>ERFA5E

DR4

"/PPL >RA5)"

T9TA

AS.8AR86.TE8T&RE

AS.8 A:9&T


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8onclusion

+eal-time monitoring system for one feeder of the mediumvoltage networ! of the # campus.

evelopment of the first application: a!lt Detection and

a!lted Line Identification,

1ommunication layer with strong reliable and secure

mechanism.

"ottom-up approach for Smart-"uilding environment usingioad technology with dedicated environment for human

interaction with large granularity monitoring and control.

smart$rid*e!;*c#

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smartgrid - nano-tera 2016

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