闫庆友, 于鹏朔, 张美娟, 林宏宇. 考虑光伏不确定性和碳交易的光储充电站博弈运行优化[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2023.0363
引用本文: 闫庆友, 于鹏朔, 张美娟, 林宏宇. 考虑光伏不确定性和碳交易的光储充电站博弈运行优化[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2023.0363
YAN Qingyou, YU Pengshuo, ZHANG Meijuan, LIN Hongyu. Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2023.0363
Citation: YAN Qingyou, YU Pengshuo, ZHANG Meijuan, LIN Hongyu. Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2023.0363

考虑光伏不确定性和碳交易的光储充电站博弈运行优化

Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading

  • 摘要: 随着双碳目标的推进,光储充电站成为利用清洁能源,满足电动汽车用电需求,并减少碳排放的重要设施。如何在兼顾经济性和低碳性的前提下确定各主体的交易策略,实现利益双方互利共赢,成为亟待解决的课题。基于此,在考虑光伏出力不确定性和电动汽车充电随机性的前提下,构建计及碳交易的光储充电站博弈运行优化模型。首先,通过场景生成和削减技术处理光伏不确定性,随后根据用户行驶习惯建立电动汽车(electric vehicles,EV)随机充电模型。其次,引入阶梯型碳交易机制约束充电站的碳排放。最后,构建充电站-电动汽车主从博弈模型。上层制定充电运营商的定价策略,以保证其运行经济性和低碳性;下层制定电动汽车用户的充电策略,最大化车主的满意度,并利用遗传算法与混合整数线性规划相结合的算法对模型进行求解。仿真结果表明,所提策略能够在有效兼顾各主体利益的同时,减少系统的碳排放量。

     

    Abstract: The determination of the trading strategies for each participant, under the premise of considering the economy and low carbon and realizing mutual benefits and win-win situation, have emerged as an urgent research topic. Based on this, considering the uncertainty of photovoltaic output and the stochastic nature of electric vehicle charging, in this paper we construct a game-based operation optimization model for PVCS, taking into account the carbon trading. Firstly, we deal with photovoltaic uncertainty through scenario generation and reduction techniques. Subsequently, the EV stochastic charging model is established based on users’ driving habits. Secondly, a stepwise carbon trading mechanism is introduced to constrain the carbon emissions of charging stations. Finally, we construct a PVCS-EV Stackelberg game model. The upper layer formulates the pricing strategy for charging operators to ensure its operation economy and low carbon, while the lower one develops the charging strategy for EV users to maximize owners' satisfaction. The model is solved using an algorithm that integrates intelligent algorithms with mixed integer linear programming. The simulation results demonstrate the efficacy of the proposed strategy in reducing the system’s carbon emissions while effectively balancing the interests of all stakeholders.

     

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