基于条件风险价值的虚拟电厂参与能量及备用市场的双层随机优化  

Bi-level Stochastic Optimization for A Virtual Power Plant Participating in Energy and Reserve Market Based on Conditional Value at Risk

作　　者：王俊[1] 徐箭[1] 王晶晶[1] 柯德平[1] 廖思阳[1] 孙元章[1] 吴煜晖 WANG Jun;XU Jian;WANG Jingjing;KE Deping;LIAO Siyang;SUN Yuanzhang;WU Yuhui(School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,Hubei Province,China)

机构地区：[1]武汉大学电气与自动化学院,湖北省武汉市430072

出　　处：《电网技术》2024年第6期2502-2510,I0065-I0068,共13页Power System Technology

基　　金：国家重点研发计划项目(2022YFB2403500);国家自然科学基金项目(U2066601)。

摘　　要：为充分发挥虚拟电厂的灵活性价值,提出了虚拟电厂参与电能量及备用辅助服务市场的双层随机优化模型。上层基于条件风险价值理论建立了虚拟电厂参与电能量及备用辅助服务市场的两阶段风险决策模型,其中,第一阶段考虑新能源不确定性的潜在风险,建立了虚拟电厂参与能量和备用辅助服务市场的投标报价模型,第二阶段针对不同场景下的新能源出力建立了以虚拟电厂期望运行成本最小为目标的分布式资源优化调度模型;下层在已知各市场主体的投标报价信息后,开展电能量市场及备用辅助服务市场的联合出清。仿真分析表明,所提方法能够有效指导虚拟电厂规避新能源不确定性的潜在风险,并通过将备用价格提高到下一个边际机组的报价从而增加自身利润。To give full play to the flexibility value of virtual power plants,a bi-level stochastic optimization model is proposed for virtual power plants to participate in the wholesale energy and reserve market.The upper level establishes a two-stage risk-averse decision-making model for a virtual power plant based on conditional value at risk to participate in the electricity market.In the first stage,a bidding model for virtual power plants to participate in the energy and reserve market is established,considering the potential risks of new energy uncertainty.In the second stage,a distributed resource optimization scheduling model is established to minimize the expected operating cost of virtual power plants according to the output of new energy under different scenarios.The lower level is the joint market clearing model of the energy and reserve market based on the bidding information of all participants.Simulation results show that the proposed method can effectively guide virtual power plants to avoid the potential risks of new energy uncertainty and increase their profits by increasing the reserve bidding price to the next marginal generation unit.

关 键 词：虚拟电厂 风险规避 能量市场 备用市场 随机优化 

分 类 号：TM73[电气工程—电力系统及自动化]