基于AHP-EWM综合赋权和TOPSIS法的多能互补系统综合评价

doi:10.11930/j.issn.1004-9649.202212004

摘要/Abstract

摘要： 多能互补系统的运行策略直接影响系统的经济性、环保性和能源利用效率。针对多能互补系统的最优运行策略选取问题，首先基于层次分析法以及熵权法结合的综合赋权法确定指标权重，并引入理想逼近排序法实现运行方式的优劣排序；其次分析了以热定电、以电定热以及遵循运营成本策略下的运行方式；最后通过优化一个电气耦合的多能互补系统确定出6个典型日的最佳运行方式并得出全年混合运行策略。结果表明：供热季遵循以电定热策略较优，供冷季以及过渡季遵循运营成本策略较优。从基于此结果的全年运行周期分析可知：混合运行策略比单一运行策略具有更好的综合性能。

关键词: 多能互补系统, 运行策略, 层次分析法, 熵权法, 理想逼近排序法

Abstract: The operation strategy of multi-energy complementary system affects the economy, environment and energy utilization efficiency of power system. To select an optimal operation strategy of the multi-energy complementary system, firstly, the index weights were determined by the integrated weight method combining the analytic hierarchy process and the entropy weight method, and the TOPSIS was introduced to rank the operation strategies. Secondly, the operation strategies of the following thermal load (FTL), following electric load (FEL), and following operation cost (FOC) were analyzed. Finally, the optimal operation strategy of six typical days was determined and a year-round optimum hybrid operation strategy was obtained by optimizing an electricity-gas coupling multi-energy complementary system. The results show that it is better to choose the FEL in the heating season, while it is better to choose the FOC in the cooling season and transition season. It can be concluded from analysis of the annual operation cycle that the hybrid operation strategy has better comprehensive performance than the single operation strategy.

Key words: multi-energy complementary system, operation strategy, analytic hierarchy process, entropy weight method, TOPSIS

贾开华, 于云霞, 范秀波, 李茂轩, 王东, 唐翠翠, 冀章. 基于AHP-EWM综合赋权和TOPSIS法的多能互补系统综合评价[J]. 中国电力, 2023, 56(7): 228-238.

JIA Kaihua, YU Yunxia, FAN Xiubo, LI Maoxuan, WANG Dong, TANG Cuicui, JI Zhang. Multi-criteria Comprehensive Evaluation of Multi-energy Complementary System Based on AHP-EWM and TOPSIS Method[J]. Electric Power, 2023, 56(7): 228-238.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202212004

https://www.electricpower.com.cn/CN/Y2023/V56/I7/228

参考文献

[1] 周原冰, 杨方, 余潇潇, 等. 中国能源电力碳中和实现路径及实施关键问题[J]. 中国电力, 2022, 55(5): 1–11
ZHOU Yuanbing, YANG Fang, YU Xiaoxiao, et al. Realization pathways and key problems of carbon neutrality in China’s energy and power system[J]. Electric Power, 2022, 55(5): 1–11
[2] 文明, 胡资斌, 龙乙林, 等. 考虑碳排放惩罚因子的综合能源系统优化规划[J]. 电力科学与技术学报, 2021, 36(3): 11–18
WEN Ming, HU Zibin, LONG Yilin, et al. Optimal planning of integrated energy system considering carbon emission penalty factor[J]. Journal of Electric Power Science and Technology, 2021, 36(3): 11–18
[3] 谭俊丰, 杨苹, 张凡, 等. 考虑能量-辅助服务下的园区综合能源系统多时间尺度优化模型[J]. 中国电力, 2022, 55(10): 100–111
TAN Junfeng, YANG Ping, ZHANG Fan, et al. Multi-time scale optimization model of park comprehensive energy system considering energy-auxiliary service[J]. Electric Power, 2022, 55(10): 100–111
[4] 程韧俐, 周保荣, 史军, 等. 面向区域统一电力市场的超大城市虚拟电厂关键技术研究综述[J]. 南方电网技术, 2023, 17(4): 90–100, 131
CHENG Renli, ZHOU Baorong, SHI Jun, et al. Review of key technologies for mega-city virtual power plants upon regional unified power market[J]. Southern Power System Technology, 2023, 17(4): 90–100, 131
[5] 张彼德, 陈颖倩, 李孟洁, 等. 含热泵和相变储能的多能互补微能源网运行优化方法研究[J]. 电力系统保护与控制, 2021, 49(1): 106–114
ZHANG Bide, CHEN Yingqian, LI Mengjie, et al. Research on an operational optimization method of multi-energy complementary micro energy grid with heat pump and phase change energy storage[J]. Power System Protection and Control, 2021, 49(1): 106–114
[6] 姜海洋, 杜尔顺, 金晨, 等. 高比例清洁能源并网的跨国互联电力系统多时间尺度储能容量优化规划[J]. 中国电机工程学报, 2021, 41(6): 2101–2115
JIANG Haiyang, DU Ershun, JIN Chen, et al. Optimal planning of multi-time scale energy storage capacity of cross-national interconnected power system with high proportion of clean energy[J]. Proceedings of the CSEE, 2021, 41(6): 2101–2115
[7] 屈小云, 吴鸣, 李奇, 等. 多能互补综合能源系统综合评价研究进展综述[J]. 中国电力, 2021, 54(11): 153–163
QU Xiaoyun, WU Ming, LI Qi, et al. Review on comprehensive evaluation of multi-energy complementary integrated energy systems[J]. Electric Power, 2021, 54(11): 153–163
[8] 贠保记, 张恩硕, 张国, 等. 考虑综合需求响应与“双碳”机制的综合能源系统优化运行[J]. 电力系统保护与控制, 2022, 50(22): 11–19
YUN Baoji, ZHANG Enshuo, ZHANG Guo, et al. Optimal operation of an integrated energy system considering integrated demand response and a “dual carbon” mechanism[J]. Power System Protection and Control, 2022, 50(22): 11–19
[9] 田福银, 马骏, 王灿, 等. 基于双层主从博弈的综合能源系统多主体低碳经济运行策略[J]. 中国电力, 2022, 55(11): 184–193
TIAN Fuyin, MA Jun, WANG Can, et al. Multi-agent low-carbon and economy operation strategy of integrated energy system based on bi-level master-slave game[J]. Electric Power, 2022, 55(11): 184–193
[10] 冉华军, 祝杰, 张涛. 基于类电磁机制算法的综合能源系统多目标优化调度[J]. 智慧电力, 2022, 50(3): 22–29
RAN Huajun, ZHU Jie, ZHANG Tao. Multi-objective optimal scheduling of integrated energy system based on electromagnetism-like mechanism algorithm[J]. Smart Power, 2022, 50(3): 22–29
[11] LI L X, YU S W, MU H L, et al. Optimization and evaluation of CCHP systems considering incentive policies under different operation strategies[J]. Energy, 2018, 162: 825–840.
[12] 刘高科, 沈国民, 徐新华, 等. 某建筑综合体分布式能源系统模拟分析[J]. 暖通空调, 2018, 48(11): 45–49, 86
LIU Gaoke, SHEN Guomin, XU Xinhua, et al. Simulation and analysis of distributed energy system of a building complex[J]. Heating Ventilating & Air Conditioning, 2018, 48(11): 45–49, 86
[13] ZHAO X, ZHENG W Y, HOU Z H, et al. Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy[J]. Energy, 2022, 238: 121733.
[14] 陈一仁, 邓卓, 王宇辉. 基于层次分析法的综合智慧能源项目风险管理研究[J]. 电工技术, 2022(4): 153–156
CHEN Yiren, DENG Zhuo, WANG Yuhui. Research on risk management of comprehensive intelligent energy project based on AHP[J]. Electric Engineering, 2022(4): 153–156
[15] KAMEL M A, ELBANHAWY A Y, ABO EL-NASR M. A novel methodology to compare between side-by-side photovoltaics and thermal collectors against hybrid photovoltaic thermal collectors[J]. Energy Conversion and Management, 2019, 202: 112196.
[16] 许伟, 韩伟, 金怀章, 等. 基于熵值法的区域综合能源系统综合评价方法[J]. 科技传播, 2022(22): 66–69
[17] 李虹, 段杰, 陈非凡, 等. 基于综合赋权和改进K-means++的DERs区域类型划分研究[J]. 智慧电力, 2020, 48(12): 51–57, 78
LI Hong, DUAN Jie, CHEN Feifan, et al. Research on regional type division of DERs based on comprehensive weight and improved K-means++[J]. Smart Power, 2020, 48(12): 51–57, 78
[18] 董福贵, 张也, 尚美美. 分布式能源系统多指标综合评价研究[J]. 中国电机工程学报, 2016, 36(12): 3214–3223
DONG Fugui, ZHANG Ye, SHANG Meimei. Multi-criteria comprehensive evaluation of distributed energy system[J]. Proceedings of the CSEE, 2016, 36(12): 3214–3223
[19] 张世翔, 吕帅康. 面向园区微电网的综合能源系统评价方法[J]. 电网技术, 2018, 42(8): 2431–2439
ZHANG Shixiang, LÜ Shuaikang. Evaluation method of park-level integrated energy system for microgrid[J]. Power System Technology, 2018, 42(8): 2431–2439
[20] 陈曦, 彭泓华, 曹杰, 等. 基于改进组合赋权-逼近理想解排序法的综合能源系统规划方案综合评价[J]. 重庆理工大学学报(自然科学), 2022, 36(3): 181–190
CHEN Xi, PENG Honghua, CAO Jie, et al. Overall evaluation of integrated energy system planning scheme based on improved combination weighting-TOPSIS[J]. Journal of Chongqing University of Technology (Natural Science), 2022, 36(3): 181–190
[21] 邱伟强, 王茂春, 林振智, 等. “双碳”目标下面向新能源消纳场景的共享储能综合评价[J]. 电力自动化设备, 2021, 41(10): 244–255
QIU Weiqiang, WANG Maochun, LIN Zhenzhi, et al. Comprehensive evaluation of shared energy storage towards new energy accommodation scenario under targets of carbon emission peak and carbon neutrality[J]. Electric Power Automation Equipment, 2021, 41(10): 244–255
[22] 王洲, 魏光明, 海晓燕. 基于逼近理想解排序法的输电网规划方案综合评价[J]. 中国设备工程, 2022(4): 148–149
WANG Zhou, WEI Guangming, HAI Xiaoyan. Comprehensive evaluation of transmission network planning scheme based on approximate ideal solution ranking method[J]. China Plant Engineering, 2022(4): 148–149
[23] CHEN L M, WU J K, WU F, et al. Energy flow optimization method for multi-energy system oriented to combined cooling, heating and power[J]. Energy, 2020, 211: 118536.
[24] JIA J D, CHEN H W, LIU H T, et al. Thermodynamic performance analyses for CCHP system coupled with organic Rankine cycle and solar thermal utilization under a novel operation strategy[J]. Energy Conversion and Management, 2021, 239: 114212.
[25] 杨恒岳, 刘青荣, 阮应君. 基于k-means聚类算法的分布式能源系统典型日冷热负荷选取[J]. 热力发电, 2021, 50(3): 84–90
YANG Hengyue, LIU Qingrong, RUAN Yingjun. Selection of typical daily cooling and heating load of CCHP system based on k-means clustering algorithm[J]. Thermal Power Generation, 2021, 50(3): 84–90