基于混合博弈与电动汽车共享储能特性的园区综合能源系统协调优化运行  

Coordinated and Optimized Operation of Park Integrated Energy Systems Based on Hybrid Gaming and Electric Vehicle Shared Energy Storage Characteristics

作　　者：王义 靳梓康 王要强[1] 吴坡 刘明洋 梁军[1,4] WANG Yi;JIN Zikang;WANG Yaoqiang;WU Po;LIU Mingyang;LIANG Jun(School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China;State Key Laboratory of Intelligent Agricultural Power Equipment,Luoyang 471099,China;State Grid Henan Electric Power Research Institute,Zheng-zhou 450052,China;School of Engineering,Cardiff University,Cardiff CF243AA,UK)

机构地区：[1]郑州大学电气与信息工程学院,郑州450001 [2]智能农业动力装备全国重点实验室,洛阳471099 [3]国网河南省电力公司电力科学研究院,郑州450052 [4]卡迪夫大学工程学院,卡迪夫CF243AA

出　　处：《高电压技术》2025年第1期135-145,I0009-I0012,共15页High Voltage Engineering

基　　金：国家自然科学基金(62203395);河南省自然科学基金(242300421167);中国博士后科学基金(2023TQ0306);河南省博士后科研项目(202101011).

摘　　要：针对园区综合能源系统中存在多利益主体且收益分配不均的实际情况,提出一种基于混合博弈的双层能量管理模型。首先,建立园区综合能源系统的运行框架,分析上层微网运营商与下层用户聚合商的利益关系。其次,为使园区各主体利益最大化,构建了多用户与微网运营商多方参与的混合博弈模型。其中,运营商通过主从博弈制定向用户的售能价格,用户聚合商在接收价格后基于纳什-海萨尼理论进行利益分配。然后,针对储能设备前期投入较高的实际情况,充分挖掘电动汽车的集群可调度潜力,通过卷积神经网络-双向长短期记忆网络(convolutional neural networks and Bi-directional long short-term memory,CNN-BiLSTM)法处理电动汽车的历史数据以降低不确定性,并制定了利用电动汽车共享储能特性作为储能设备的运行策略。最后,以某市园区综合能源系统为研究对象进行分析。结果表明,所建立的模型可以有效减少碳排放,实现运营商与多用户共赢。In accordanc with multiple stakeholders and uneven income distribution in the park-integrated energy system,a two-layer energy management model based on a hybrid game theory is proposed.Firstly,the operational framework of the park-integrated energy system is established,and the interests of the upper-layer microgrid operators and the lower-level user aggregators are analyzed.Secondly,to maximize the interests of all stakeholders in the park,a hybrid game model is developed,allowing for multi-user and multi-party participation of microgrid operators.The operator formulates the price of energy and sell to users through the Stackelberg game,while the user aggregator distributes the benefits based on the Nash-Harsanyi theory after receiving the price.In light of the substantial initial investment in energy storage equipment,the potential for using electric vehicles as a cluster dispatchable resource is thoroughly investigated.Historical data from electric vehicles are analyzed by using the CNN-BiLSTM method,which combines convolutional neural networks and Bi-directional long short-term memory,to mitigate uncertainty.The strategy has been developed to utilize the shared en-ergy storage capabilities of electric vehicles as energy storage devices.Finally,an integrated energy system of a city is taken for example to perform analyses.The results show that the established model can effectively decrease carbon emis-sions and create a win-win situation for operators and multiple users.

关 键 词：电动汽车 集群可调度潜力 混合博弈 纳什-海萨尼理论 CNN-BiLSTM 需求响应 

分 类 号：U491.8[交通运输工程—交通运输规划与管理] TM73[交通运输工程—道路与铁道工程] TK01[电气工程—电力系统及自动化]