基于竞价空间预测的虚拟电厂日前竞价策略  

Day-ahead Bidding Strategy of Virtual Power Plant Based on Bidding Space Prediction

作　　者：张国基 贾燕冰 韩肖清 张泽[1] ZHANG Guoji;JIA Yanbing;HAN Xiaoqing;ZHANG Ze(Key Laboratory of Cleaner Intelligent Control on Coal&Electricity(Taiyuan University of Technology),Ministry of Education,Taiyuan 030024,Shanxi Province,China)

机构地区：[1]煤电清洁控制教育部重点实验室(太原理工大学),山西省太原市030024

出　　处：《电网技术》2024年第9期3724-3734,I0059-I0064,共17页Power System Technology

基　　金：国家自然科学基金青年基金项目(51807129);国家自然科学基金重点项目(U1910216)。

摘　　要：“双碳”背景下,虚拟电厂作为聚合管理电动汽车、新能源、储能的有效途径,将是电力现货市场的重要主体,而虚拟电厂内部聚合资源的运行特性决定其竞价空间,是其报价策略的重要影响因素。针对电动汽车、光、储构成的虚拟电厂,提出了基于高斯过程回归的竞价空间预测方法,将虚拟电厂竞价空间的时间序列拓宽形成相空间以挖掘历史数据中的隐含信息,并运用高斯过程回归预测虚拟电厂的竞价空间;然后将竞价空间作为虚拟电厂竞价时的电量及功率约束,基于节点边际电价机制提出了基于竞价空间的虚拟电厂日前竞价方法及市场优化出清方法。最后通过RBTS 38节点配电系统进行仿真验证,结果表明基于相空间重构的高斯过程能够提升竞价空间预测准确性,减少竞价电量与出清电量的偏差,从而提升虚拟电厂收益。Under the background of"Peak Carbon Emissions and Carbon Neutrality",as an effective way to aggregate and manage electric vehicles,new energy,and energy storage,a virtual power plant will be an essential main body of the power spot market,and the operation characteristics of aggregate resources in virtual power plant determine its bidding space.Is an important factor affecting its bidding strategy.Aiming at the virtual power plant composed of electric vehicles,photovoltaic,and energy storage,this paper puts forward a bidding space prediction method based on Gaussian process regression,which broadens the time series of the bidding space of virtual power plant to form phase space to mine the hidden information in historical data.Gaussian process regression is used to predict the bidding space of a virtual power plant.Then,taking the bidding space as the electricity and power constraint of VPP bidding,the day-ahead bidding strategy and market optimization clearing model of a virtual power plant based on bidding space are proposed based on the node marginal price mechanism.Finally,through the simulation verification of the RBTS 38-node distribution system,the results show that the Gaussian process based on phase space reconstruction can improve the prediction accuracy of bidding space,reduce the deviation between bidding electricity and clearing electricity,and thus improve the revenue of virtual power plant.

关 键 词：虚拟电厂 竞价空间 高斯过程 竞价策略 

分 类 号：TM73[电气工程—电力系统及自动化]