Please wait a minute...
Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  2018, Vol. 12 Issue (4): 540-549   https://doi.org/10.1007/s11708-018-0597-4
  本期目录
基于能质系数的综合能源系统解耦优化研究
马世喜, 孙胜楠, 吴航, 周登极, 张会生(), 翁史烈
上海交通大学机械动力学院,中国上海200240
Decoupling optimization of integrated energy system based on energy quality character
Shixi MA, Shengnan SUN, Hang WU, Dengji ZHOU, Huisheng ZHANG(), Shilie WENG
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
 全文: PDF(464 KB)   HTML
摘要:

随着可再生能源、燃气发电厂、电驱压缩机组等各类能源装备的广泛应用,各种能源系统的耦合和联系日益紧密,由其构成的综合能源系统引起了广泛关注。为满足综合能源系统优化调度和能量管理的需求,构建面向多系统耦合的最优调度体系,本文建立了详细的气-电联合调度模型,考虑到各子系统能量损失的品位差异,提出了基于能质系数的系统评价指标,结合最优化方法构建综合能源系统联合运行的最优调度方法。此外,利用商业用户和居民用户典型负载特征,对由IEEE 39节点电力系统和10节点天然气输送系统构成的综合能源系统进行了优化调度分析,结果证明了本文所提方法的可行性和有效性。

Abstract

Connections among multi-energy systems become increasingly closer with the extensive application of various energy equipment such as gas-fired power plants and electricity-driven gas compressor. Therefore, the integrated energy system has attracted much attention. This paper establishes a gas-electricity joint operation model, proposes a system evaluation index based on the energy quality character after considering the grade difference of the energy loss of the subsystem, and finds an optimal scheduling method for integrated energy systems. Besides, according to the typical load characteristics of commercial and residential users, the optimal scheduling analysis is applied to the integrated energy system composed of an IEEE 39 nodes power system and a 10 nodes natural gas system. The results prove the feasibility and effectiveness of the proposed method.

Key wordsintegrated energy system    energy quality character    optimization    electric power system    natural gas system
收稿日期: 2018-08-05      出版日期: 2018-12-21
通讯作者: 张会生     E-mail: zhslm@sjtu.edu.cn
Corresponding Author(s): Huisheng ZHANG   
 引用本文:   
马世喜, 孙胜楠, 吴航, 周登极, 张会生, 翁史烈. 基于能质系数的综合能源系统解耦优化研究[J]. Frontiers in Energy, 2018, 12(4): 540-549.
Shixi MA, Shengnan SUN, Hang WU, Dengji ZHOU, Huisheng ZHANG, Shilie WENG. Decoupling optimization of integrated energy system based on energy quality character. Front. Energy, 2018, 12(4): 540-549.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-018-0597-4
https://academic.hep.com.cn/fie/CN/Y2018/V12/I4/540
Fig.1  
Fig.2  
Fig.3  
Fig.4  
Categories Nodes
Commercial load 1, 3, 4, 7, 8, 9, 18, 25, 31, 39
Resident load 12, 15, 16, 20, 21, 23, 24, 26, 27, 28, 29
Tab.1  
No. Rated power Efficiency
Rated active power/MW Rated reactive power/Mvar
Gas-fired power plant 1 500 200 0.4
2 600 300 0.4
3 650 300 0.4
4 600 250 0.4
5 450 150 0.4
6 650 300 0.4
7 550 240 0.4
8 500 250 0.4
9 450 –150 0.4
10 350 –100 0.4
Compressor A 15 0.85
B 5 0.85
C 5 0.85
Wind power plant 100
Solar power plant 100
Tab.2  
Fig.5  
Fig.6  
Fig.7  
Fig.8  
Method 1 Method 2
Power output of gas power plants/MWh 86032.5 86381.3
Total energy consumption of compressor/MW 255.3 336.2
Loss of electric network WE/MWh 341.1 289.93
Loss of gas network WG/MWh 295.33 386.4
System loss IIES/MWh 636.43 676.33
Loss reduction/MWh 39.9
Tab.3  
Fig.9  
Fig.10  
Fig.11  
Fig.12  
1 L QBai, F X Li, H T Cui, T Jiang, H BSun, J XZhu. Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty. Applied Energy, 2016, 167: 270–279
https://doi.org/10.1016/j.apenergy.2015.10.119
2 QZeng, J K Fang, J H Li, Z Chen. Steady-state analysis of the integrated natural gas and electric power system with bi-directional energy conversion. Applied Energy, 2016, 184: 1483–1492
https://doi.org/10.1016/j.apenergy.2016.05.060
3 J HZheng, Q H Wu, Z X Jing. Coordinated scheduling strategy to optimize conflicting benefits for daily operation of integrated electricity and gas networks. Applied Energy, 2017, 192: 370–381
https://doi.org/10.1016/j.apenergy.2016.08.146
4 AGhasemi, M Banejad, MRahimiyan. Integrated energy scheduling under uncertainty in a micro energy grid. IET Generation, Transmission & Distribution, 2018, 12(12): 2887–2896
https://doi.org/10.1049/iet-gtd.2017.1631
5 WGu, J Wang, SLu, ZLuo, C Y Wu. Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings. Applied Energy, 2017, 199: 234–246
https://doi.org/10.1016/j.apenergy.2017.05.004
6 Z GPan, Q L Guo, H B Sun. Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow. Applied Energy, 2016, 167: 230–243
https://doi.org/10.1016/j.apenergy.2015.10.095
7 SCollins, J P Deane, K Poncelet, EPanos, R CPietzcker, EDelarue, B PÓ Gallachóir. Integrating short term variations of the power system into integrated energy system models: a methodological review. Renewable & Sustainable Energy Reviews, 2017, 76: 839–856
https://doi.org/10.1016/j.rser.2017.03.090
8 HRashidi, J Khorshidi. Exergoeconomic analysis and optimization of a solar based multigeneration system using multiobjective differential evolution algorithm. Journal of Cleaner Production, 2018, 170: 978–990
https://doi.org/10.1016/j.jclepro.2017.09.201
9 J LLiu, A N Wang, Y H Qu, W H Wang. Coordinated operation of multi-integrated energy system based on linear weighted sum and grasshopper optimization algorithm. IEEE Access: Practical Innovations, Open Solutions, 2018, 6: 42186–42195
https://doi.org/10.1109/ACCESS.2018.2859816
10 J NLiu, H Z Zhong, K W Zeng, H X Fan, Q X Chen. Optimal scheduling of multiple energy system considering power to gas unit. In: 2017 IEEE Conference on Energy Internet and Energy System Integration, Beijing, China, 2017: 58–63
11 Y LWang, H Y Yu, M Y Yong, Y J Huang, F L Zhang, X H Wang. Optimal scheduling of integrated energy systems with combined heat and power generation, photovoltaic and energy storage considering battery lifetime loss. Energies, 2018, 11(7): 1676
https://doi.org/10.3390/en11071676
12 JYe, R X Yuan. Integrated natural gas, heat, and power dispatch considering wind power and power-to-gas. Sustainability, 2017, 9(4): 602
https://doi.org/10.3390/su9040602
13 SChen, Z N Wei, G Q Sun, K W Cheung, D Wang. Identifying optimal energy flow solvability in electricity-gas integrated energy systems. IEEE Transactions on Sustainable Energy, 2017, 8(2): 846–854
https://doi.org/10.1109/TSTE.2016.2623631
14 Y BJiang, J Xu, Y ZSun, C YWei, JWang, S Y Liao, D P Ke, X Li, JYang, X TPeng. Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources. Applied Energy, 2018, 211: 237–248
https://doi.org/10.1016/j.apenergy.2017.10.128
15 X JZhang, G G Karady, S T Ariaratnam. Optimal allocation of CHP-based distributed generation on urban energy distribution networks. IEEE Transactions on Sustainable Energy, 2014, 5(1): 246–253
https://doi.org/10.1109/TSTE.2013.2278693
16 AMartinez-Mares, C R Fuerte-Esquivel. A unified gas and power flow analysis in natural gas and electricity coupled networks. IEEE Transactions on Power Systems, 2012, 27(4): 2156–2166
https://doi.org/10.1109/TPWRS.2012.2191984
17 Z HJiang, X W Yu. Modeling and control of an integrated wind power generation and energy storage system. In: 2009 IEEE Power & Energy Society General Meeting, Calgary, Canada, 2009, 1–8: 2612–2619
18 S XMa, D J Zhou, H S Zhang, Z H Lu. Modeling and optimal operation of a network of energy hubs system with distributed energy resources. In: Proceedings of the ASME Turbo Expo: Turbine Technical Conference and Exposition, 2017
19 EGholamian, P Hanafizadeh, AHabibollahzade, PAhmadi. Evolutionary based multi-criteria optimization of an integrated energy system with SOFC, gas turbine, and hydrogen production via electrolysis. International Journal of Hydrogen Energy, 2018, 43(33): 16201–16214
https://doi.org/10.1016/j.ijhydene.2018.06.130
20 Z SChen, W H Xie, P Hu, LJia, MShi. An effective thermodynamic transformation analysis method for actual irreversible cycle. Science China. Technological Sciences, 2013, 56(9): 2188–2193
https://doi.org/10.1007/s11431-013-5298-y
21 SChen, Z N Wei , G G Sun , Y LSun, H XZang , YZhu. Optimal power and gas how with a limited number of control actions IEEE Transactions on Smart Grid , 2018, 9(5): 5371–5380
https://doi.org/10.1109/TSG.2017.2687621
22 YHu, H Lian, ZBie, BZhou. Unified probabilistic gas and power flow. Journal of Modern Power Systems and Clean Energy, 2017, 5(3): 400–411
https://doi.org/10.1007/s40565-017-0284-1
23 C AKang, A R Brandt, L J Durlofsky. Optimal operation of an integrated energy system including fossil fuel power generation, CO2 capture and wind. Energy, 2011, 36(12): 6806–6820
https://doi.org/10.1016/j.energy.2011.10.015
24 MGranovskii, I Dincer, M ARosen. Exergy and industrial ecology: an application to an integrated energy system. International Journal of Exergy, 2008, 5(1): 52–63
https://doi.org/10.1504/IJEX.2008.016012
25 S XMa, D J Zhou, H S Zhang, Z H Lu. Micro gas turbine/renewable hybrid power system for distributed generation: effects of ambient conditions on control strategy. In: Proceedings of the ASME Turbo Expo: Turbine Technical Conference and Exposition, 2016
26 I GDamousis, A G Bakirtzis, P S Dokopoulos. A solution to the unit-commitment problem using integer-coded genetic algorithm. IEEE Transactions on Power Systems, 2004, 19(2): 1165–1172
https://doi.org/10.1109/TPWRS.2003.821625
27 SAn, Q Li, T WGedra. Natural gas and electricity optimal power flow. In: Proceedings of 2003 IEEE PES Transmission and Distribution Conference & Exposition, Dallas, TX, USA, 2003, 1–3: 138–143
28 S XQi, X L Wang, Y F Wang, S J Tian, R G Wang. Integrated probabilistic energy flow analysis in natural gas and electricity coupled systems considering the randomness of wind power. In: 2017 IEEE Conference on Energy Internet and Energy System Integration, 2017
29 YYuan, J Kubokawa, HSasaki. A solution of optimal power flow with multicontingency transient stability constraints. IEEE Transactions on Power Systems, 2003, 18(3): 1094–1102
https://doi.org/10.1109/TPWRS.2003.814856
30 GChicco, R Napoli, PPostolache, MScutariu, C MToader. Customer characterization options for improving the tariff offer. IEEE Transactions on Power Systems, 2003, 18(1): 381–387
https://doi.org/10.1109/TPWRS.2002.807085
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed