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基于非合作博弈的冷热电联供微能源网运行策略优化
引用本文:林凯骏,吴俊勇,郝亮亮,刘迪,李德智,闫华光.基于非合作博弈的冷热电联供微能源网运行策略优化[J].电力系统自动化,2018,42(6):25-32.
作者姓名:林凯骏  吴俊勇  郝亮亮  刘迪  李德智  闫华光
作者单位:北京交通大学电气工程学院, 北京市 100044,北京交通大学电气工程学院, 北京市 100044,北京交通大学电气工程学院, 北京市 100044,北京交通大学电气工程学院, 北京市 100044,中国电力科学研究院有限公司, 北京市 100192,中国电力科学研究院有限公司, 北京市 100192
基金项目:国家电网公司科技项目(YDB17201700249)
摘    要:提出了基于非合作博弈的冷热电联供微能源网优化的一般模型与求解方法。基于博弈论,建立了微能源网与用户的博弈模型;证明了该博弈纳什均衡的存在性,并提出了相应的求解流程;利用模糊双目标算法对用户的支付费用和不满意度进行归一化处理,在博弈模式下用户调整自身用电策略,微能源网根据用户的负荷计划调整电价,优化冷热电出力。以某小区夏季典型日负荷与冬季典型日负荷为例,对博弈模型进行求解。仿真结果表明,微能源网在所提出的博弈模式下能更好地消纳可再生能源,实现个体理性情况下的能源最优,且用户能在兼顾用能体验的前提下实现经济最优。

关 键 词:冷热电联供微能源网  非合作博弈  用户不满意度  模糊双目标算法
收稿时间:2017/7/14 0:00:00
修稿时间:2018/1/4 0:00:00

Optimization of Operation Strategy for Micro-energy Grid with CCHP Systems Based on Non-cooperative Game
LIN Kaijun,WU Junyong,HAO Liangliang,LIU Di,LI Dezhi and YAN Huaguang.Optimization of Operation Strategy for Micro-energy Grid with CCHP Systems Based on Non-cooperative Game[J].Automation of Electric Power Systems,2018,42(6):25-32.
Authors:LIN Kaijun  WU Junyong  HAO Liangliang  LIU Di  LI Dezhi and YAN Huaguang
Affiliation:School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China,School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China,School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China,School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China,China Electric Power Research Institute, Beijing 100192, China and China Electric Power Research Institute, Beijing 100192, China
Abstract:The general model and solution algorithm for the optimization of micro-energy grid with combined cooling, heating and power system are proposed by using the non-cooperative game. Based on the game theory, the game model between micro-energy grid and user is established, which proves that the game has the Nash equilibrium(NE)and the simulation method based on the definition of NE is put forward. The fuzzy bi-objective algorithm is used to normalize the payment and the user dissatisfaction. In the game, the user adjusts the power consumption strategy, and the micro-energy grid adjusts the electricity price according to the user''s load plan and optimizes the cooling, heating and power loads. The typical daily loads of a community in summer and in winter are taken as examples to solve the game model. The simulation results indicate that the micro-energy grid has better consumption capacity of renewable energy in the proposed game mode and realizes the energy optimization via the rational action of micro-energy grid individuals, and the user can achieve economic optimality with considering the experience of using energy.
Keywords:micro-energy grid with combined cooling  heating and power system  non-cooperative game  user dissatisfaction  fuzzy bi-objective algorithm
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