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多主体联合投资微电网源–储多策略有限理性决策演化博弈容量规划 被引量:37

Multi-agent Joint Investment Microgrid Source-storage Multi-strategy Bounded Rational Decision Evolution Game Capacity Planning
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摘要 针对多主体联合投资单一微电网源–储规划场景中难以平衡多投资主体利益冲突,以及传统博弈方法假设参与人完全理性的局限性,提出一种配电网运营商与微电网运营商联合投资的基于演化博弈微电网源–储容量规划新方法。首先,建立微电网系统及内部源、储模型,并结合峰谷电价确定含储能微电网运行策略。其次,以微电网运营商运行成本及内部经济收益,以及配电网运营商投资微电网成本、配电网网损、延缓配电网升级成本及售购电收益的总经济支付最小为目标,建立参与人支付函数模型。再次,从参与者、策略集、支付函数及复制者动态方程出发,建立计及参与人有限理性的多策略集演化博弈模型,并提出求解多策略集演化稳定策略的方法。最后,通过实际系统算例证明所提出的多策略集演化博弈微电网源–储规划策略的有效性。采用非博弈、传统博弈与演化博弈等不同场景开展对比实验,实验证明演化博弈方法在平衡微电网运营商与配电网运营商的收益方面具有更好的效果。 Aiming at the multi-agent joint investment in a single microgrid source-storage planning scenario,it is difficult to balance the conflicts of multiple investment subjects,and the traditional game theory assumes the limitations of participants’complete rationality,and proposed a new method based on evolutionary game to plan the microgrid source-storage capacity with distribution network operators and microgrid operators jointly invested.Firstly,established a microgrid system and internal source and storage models,and combined the peak and valley electricity prices to determine the operation strategy of the microgrid containing energy storage.Secondly,with the operating costs and internal economic benefits of microgrid operators,as well as the total economic benefits of distribution grid operators investing in microgrid costs,distribution network losses,delaying distribution network upgrade costs and selling electricity revenues,established a multi-participant payment function model.Thirdly,based on the participants,the strategy set,payment function and the dynamic equation of the replicator,a multi-strategy evolutionary game model considering the bounded rationality of the participants was established,and a method for solving the multi-strategy evolutionary stability strategy was proposed.Finally,the effectiveness of the proposed multi-strategy evolutionary game microgrid source-storage planning strategy was illustrated by the actual system.Comparative experiments were carried out in different scenarios such as non-gaming,traditional game and evolutionary game.Experiments show that the evolutionary game method has better effects in balancing the benefits of microgrid operators and distribution network operators.
作者 黄南天 包佳瑞琦 蔡国伟 赵树野 刘德宝 王俊生 王盼盼 HUANG Nantian;BAO Jiaruiqi;CAI Guowei;ZHAO Shuye;LIU Debao;WANG Junsheng;WANG Panpan(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education(Northeast Electric Power University),Jilin 132012,Jilin Province,China;State Grid Inner Mongolia Eastern Electric Power Co.,Ltd.Institute of Economics and Technology,Hohhot City,Inner Mongolia Autonomous Region 010000,China)
出处 《中国电机工程学报》 EI CSCD 北大核心 2020年第4期1212-1225,1412,共15页 Proceedings of the CSEE
基金 国家重点研发计划(2016YFB0900104) 吉林省科技发展项目计划项目(20160411003XH,20160204004GX) 吉林省产业技术研究与开发专项(2019C058-8)。
关键词 微电网 容量规划 多投资主体 演化博弈 多策略 microgrid capacity planning multi-investor evolutionary game multi-strategy
作者简介 黄南天(1980-),男,博士,副教授,主要研究方向为含高比例可再生能源电力系统运行控制与规划等,huangnantian@126.com;包佳瑞琦(1994-),女,硕士研究生,研究方向为博弈论在电力系统应用及微能源网规划等,baohan1019@126.com;蔡国伟(1968-),男,博士,教授,博士生导师,研究方向为含新能源并网的电力系统稳定与控制,caigw@mail.nedu.edu.cn;赵树野(1987-),男,硕士研究生,研究方向为电力系统规划,18547111945@163.com。
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  • 1梁惠施,程林,苏剑.微网的成本效益分析[J].中国电机工程学报,2011,31(S1):38-44. 被引量:77
  • 2王成山,陈恺,谢莹华,郑海峰.配电网扩展规划中分布式电源的选址和定容[J].电力系统自动化,2006,30(3):38-43. 被引量:247
  • 3陈益棠,胡兆银.用海水淡化法解决海岛用水[J].水处理技术,2006,32(6):65-69. 被引量:13
  • 4汤玉东,徐诚,邹云.基于DSM的峰谷分时电价[J].电力需求侧管理,2006,8(6):11-13. 被引量:7
  • 5PEPERMANS G, DRIESEN J, HAESELDONCKX D. Distributed generation: definition, benefits and issues [J]. Energy Policy, 2005, 33(6): 787- 798.
  • 6WANG L, SINGH C. PSO based multi-criteria optimum design of a grid-connected hybrid power system with multiple renewable sources of energy[C]// Proceedings of the 2007 IEEE Swarm Intelligence Symposium (SIS 2007), April 1- 5, 2007, Honolulu, HI, USA.
  • 7YANG H, LU L, ZHOU W. A novel optimization sizing model for hybrid solar-wind power generation system [J ]. Solar Energy, 2007, 81(1): 76-84.
  • 8CHUANG A S, WU F, VARAIYA P. A game-theoretic model for generation expansion planning: problem formulation and numerical comparisons [J].IEEE Trans on Power Systems, 2001, 16(4): 885-891.
  • 9GUAN X, HO Y, PEPYNE D L. Gaming and price spikes in electric power markets [J].IEEE Trans on Power Systems, 2001, 16(3): 402-408.
  • 10SINGH H. Introduction to game theory and its application in electric power markets [J]. IEEE Computer Applications in Power, 1999, 12(4):18-22.

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