| 引用本文: | 王树东,杜巍,林莉,等.基于合作博弈的需求侧响应下光储微电网优化配置[J].电力系统保护与控制,2018,46(1):129-137.[点击复制] |
| WANG Shudong,DU Wei,LIN Li,et al.Optimal allocation of photovoltaic energy storage microgrid under the demand side response based on cooperative game[J].Power System Protection and Control,2018,46(1):129-137[点击复制] |
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| 摘要: |
| 在电力市场环境下，考虑需求侧响应和储能系统对微电网的影响，通过合作博弈的方式进行系统联合优化配置。提出一种在需求侧用户适当转移负荷的情况下实行分时电价的微电网运行策略，用于实现微电网收益最大化和最优可靠性。首先，建立了转移负荷的用户、分时电价下进行负荷响应的用户和储能系统的目标函数和模型。其次，利用合作博弈的方式将三方进行联合优化配置，采用迭代算法求出了三方联合优化纳什(Nash)均衡点(最优配置方案)。基于此提出系统联合优化运行策略。将该模型和算法应用于甘肃某一实际光伏微网系统，验证了其有效性。 |
| 关键词: 光储微电网 合作博弈 可转移负荷 分时电价 Nash均衡 |
| DOI：10.7667/PSPC162051 |
| 投稿时间：2016-12-14修订日期：2017-01-04 |
| 基金项目:甘肃省科技计划项目(1309RTSF043);甘肃省教育厅高校科研项目(2015A-211);2015年酒泉市科技支撑计划项目 |
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| Optimal allocation of photovoltaic energy storage microgrid under the demand side response based on cooperative game |
| WANG Shudong,DU Wei,LIN Li,LI Jianhua,CHEN Weiqian,GAO Xiang |
| (College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China;National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China;Gansu Key Laboratory of Solar Power Systems Engineering, Jiuquan Vocational and Technical College, Jiuquan 735000, China;Gansu Army Reserve Antiaircraft Artillery Division Command Automation Station, Lanzhou 730050, China) |
| Abstract: |
| In the electricity market environment, thinking about the influence of demand side response and energy storage system on microgrid, it jointly optimizes the configuration of the system through cooperative game mode. A microgrid operation strategy of implementing time-of-use price when demand side user appropriately transfers load is proposed, which is used to achieve maximum revenue and optimal reliability of microgrid. Firstly, this paper establishes the objective function and model of the users of the transferring load, the users of implementing load response under time-of-use price and the energy storage system. Second, the cooperative game method is used to optimize the allocation of three parties and an iterative algorithm is used to find joint optimization Nash equilibrium point of three parties (the optimal allocation scheme). On this basis, system joint optimization operation strategy is put forward. The model and algorithm are applied to a practical PV microgrid system in Gansu, verifying their validity. |
| Key words: photovoltaic energy storage microgrid cooperative game transferrable load time-of-use price Nash equilibrium |
