Simulation of
Cogeneration System in Smart Energy Networks
using TRNSYS
스마트에너지 환경에서 TRNSYS를 활용한 열병합발전계통 모의분석
30th January 2015
Prepared
by
Dong Sig (Daniel) Chai
PEng. Canada
Training or Introduction Purpose Only. Do not distribute this paper and the relative articles without written permit by author or original sources. 1
Simulation of Cogeneration System in Smart Energy Networks using TRNSYS
Daniel (Dong Sig) Chai PEng. (Ontario, Canada)
2014~ PhD. Candidate ,Energy System Engineering in Seoul National University
2012. MASc. Mechanical Engineering in University of Waterloo, ON, Canada
1984. B.Eng. Mechanical Engineering in Ulsan University, Korea
2012-Pres. Director/ Senior Project Advisor at Korea Kumho Petrochemical Co., Ltd. Korea
2002-2009 Project Developer/ Gan Rim Corporation, Canada
1991-2000 Manager of Mech. Engineering Dep’t at Korea District Heating Engineering Co., Korea
1984-1991 Engineer at Korea Electric Power Co., E&C (former, KOPEC)
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Table of Contents
Simulation of Cogeneration System in Smart Energy Networks using TRNSYS
1. Introduction
Goals
Changing Energy Policy
Emerging Renewable Energy
2. Basic Concept of Energy System
Cogeneration
Smart Energy Networks
3. Simulation of Cogeneration Model using TRNSYS
Proposed Area & Applied Model
Energy Peak Loads & Load Duration Curve
System Configuration
System Modeling using TRNSYS Software
Outputs
4. Conclusion and Recommendations
References 3
Goals
1. Introduction
* SEN: Smart Energy Networks
Reducing
Greenhouse
Gases
Emerging
Renewable
Energy
Concerning
Nuclear Power
Safety
Finding
Sustainable Energy
Solutions
Changing
Energy Polices
Development of
Energy Technologies
Improvement of
Energy Efficiency, Security, Reliability,
& Environmental performance
SEN*
Cogeneration
Economic &
Environmental
Benefits
Others
▶ Finding Sustainable Energy Solutions in Variable Environmental Conditions
4
Changing
Energy
Polices
1. Introduction
* Energy policy in Korea is shown instead of that in Canada for this presentation only * RPS: Renewable Portfolio Standard, 신.재생에너지 공급 의무와 한 제도. ** REC : '신.재생 공급인증서 *** ETS (Emission Trading Scheme) : 배출권 거래제
Changing Energy Policy *
Reducing
Greenhouse Gas (Electricity Ind. Sector)
• Reduce Amount by 7.6% (1):
11.5 10^6 CO2te BAU @2020
10.6 10^6 CO2te Target
Changing
Energy Mix (Renewables)
• Increase Ratio by 11.6% (2) : 8.6%(9,277MW) in 2015
20.2%(32,014MW) in 2027
Increasing
RPS*
• Increase Duty by 6.5% (3) :
3.5% in 2015
10.0% in 2020 and after
Trading
REC**
• KPX Trading in 2014 (4) :
Trade total 344,000 REC
Price avg. 114,000 Won/REC
Trading
Cap & Trade
• Open Market (ETS***,KRX) :
9,800 KRW/CO2te in 12th Jan. 2015(5)
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1. Introduction
1) Sources: Lecture Note of Energy & the Environment, by Prof. Dr. John Wen, University of Waterloo
Emerging Renewable Energy
Renewable
Energy
Conventional
Energy
Energy Useful
Foams
End Users
Legend
6
▶Cogeneration (or CHP) ? CHP is the sequential or simultaneous generation of multiple forms of useful energy (usually mechanical and thermal) in a single, integrated system.
▶Cogeneration (or CHP) Efficiency ? Efficiency advantage of CHP compared with conventional central station power generation and onsite boilers
2. Basic Concept of Energy System
Cogeneration or CHP *
* CHP (Combined Heat & Power)
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2. Basic Concept of Energy System
Smart Energy Networks (6)
Sources: Dong Sig Chai , John Z. Wen , Jatin Nathwani, “Simulation of Cogeneration System within Smart Energy Network”, 2013, Energy Conversion Management 75 (2013),
Concept
8
2. Basic Concept of Energy System S
mart
En
erg
y N
etw
ork
s (6
)
Mo
de
l u
sin
g T
RN
SY
S
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3. Simulation of Model using TRNSYS
Proposed Site & Applied Model **
• Proposed site : David Johnston Research and Technology Park (R+T Park) &
neighborhood areas in Waterloo, Ontario, Canada
• Applied Model : Community Cogeneration Model
Waterloo, ON, Canada*
* Sources: Wikipedia & Google map
** Sources: Reference No. 6
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Energy Peak Loads & Load Duration Curve
• Peak Loads (2012 year base)
Peak Load Residential Office Building Combined
Electricity (kW) 4,005 6,008 9,507
Heating (kW) 6,546 12,221 18,767
• Load Duration Curve (2012 year base)
Electricity-Residential Electricity-Office Heating-Office
* Sources: Reference No. 6
3. Simulation of Model using TRNSYS
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System Configuration
* Sources: Reference No. 6
3. Simulation of Model using TRNSYS
12
System Modeling using TRNSYS Software (1/2)
* TRNSYS : TRaNsient SYstem Simulation Program ** Sources: Reference No. 6
• Analysis Software : TRNSYS 16* • Major Types (modules) Applied:
3. Simulation of Model using TRNSYS
13
System Modeling using TRNSYS Software (2/2)
* Sources: Reference No. 6
• System Model
3. Simulation of Model using TRNSYS
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Outputs – by Facility
* Sources: Reference No. 6
Name of Facility Generation Consumption Index
Elec. Heat Cool Aux. Power
Utility Load Factor
Eff.
Photovoltaic Array O O O
Electrolysis O O O
Hydrogen tank O O
Fuel cell system O O O O O
Gas turbine system O O O O O O
Steam turbine system O O O O O O
District heaters O O
Absorption chiller O O O O O
DH Pumping systems O O O
Auxiliary Boiler System O O O O O O
• Hourly-based Real-time Operating Data
3. Simulation of Model using TRNSYS
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Outputs – Electricity Production by Facility
* Sources: Reference No. 6
• Hourly-based Real-time Operating Data - Electricity
3. Simulation of Model using TRNSYS
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Outputs – Thermal Product by Facility
* Sources: Reference No. 6
• Hourly-based Real-time Operating Data - Heating
3. Simulation of Model using TRNSYS
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Outputs – System Operating Data (1/2)
* Sources: Reference No. 6
• Heat – to – Power Ratio
• Excessive Power Product
& Unmet Power Load
• Excessive Heating Product
& Unmet Heating Load
3. Simulation of Model using TRNSYS
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* Sources: Reference No. 6
• Renewable & Fossil Contribution
• Efficiency (Separate Heat & Power)
• Efficiency (Cogeneration)
• CEI (Cogeneration Efficiency Index)
• Emissions
Outputs – System Operating Data (2/2)
3. Simulation of Model using TRNSYS
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4. Conclusions & Recommendations
* Sources: Reference No. 6
• Need to find sustainable energy solutions with emerging energy
systems in changing environmental situations.–Goal
• Energy-mix distributed cogeneration systems in SEN environment
could be one of best solutions to reach the goal because they have
their own unique characteristics to cope with the environment
given.
• Before implementing project, a simulation of cogeneration system
using TRNSYS is able to provide suppliers and consumers with
predictable hourly-based real-time operating data, which enables
them to communicate for mutual interests.
• Need to further study in optimization and economic analysis using
the output data and information to be provided by simulation.
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References
1. 국가 온실가스 감축목표 달성을 위한 로드맵, 2014.1, 녹색성장위원회 심의 국무회의보고 (Korean)
2. 제 6차 전력수급 기본계획, 2013-2027, 산업통산자원부 (Korean)
3. 신.재생에너지 공급 의무화제도 (RPS), 2012, 에너지 관리공단 신.재생 에너지 쎈타 (Korean)
4. KPX, 2014, REC Transaction, https://rec.kpx.info/main.jsp?menuId=502&lfsdMenuId=511
5. KRX (Korean Exchange), 2014, Cap & Trade, ETS, 배출권거래
6. Dong Sig Chai , John Z. Wen , Jatin Nathwani, “Simulation of Cogeneration System within Smart
Energy Network”, 2013, Energy Conversion Management 75 (2013)
7. TRNSTS Software Training Manuals
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Simulation of Cogeneration System in Smart Energy Networks using TRNSYS
Q & A
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References
1. Energy-Mix Distributed Generation Models in SEN*
* SEN : Smart Energy Networks
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References
2. Communication Model in SEN*
* SEN : Smart Energy Networks
Consumers
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References
3. TRNSYS Software
• Developed based on component based architecture using FOTRAN & C language by the University of Wisconsin's Solar Energy Lab in 1970s. • Several research contributors such as DLR (German Aerospace Centre), Sun Lab/SANDIA (USA) and IV- TAN (Institute for High Temperatures of the Russian Academy of Science, Russia).
• Can use various external simulation packages such as Excel, Matlab, Fluent, and EES by liking them to components. • Simulation Studio for graphic interface, TRN- Build for creating a building input file, IIS-iBat for a graphical front-end, PREBID for entering building information, TRNSED for share simulations with non-user, & SimCad for building simulation. • Use a successive substitution as a solver.
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Simulation of Cogeneration System in Smart Energy Networks using TRNSYS
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