多重不确定性下的虚拟电厂参与电能量和需求响应市场鲁棒优化调度策略  

Robust Optimal Scheduling Strategy for Virtual Power Plant Participation in Electric Energy and Demand Response Markets Under Multiple Uncertainties

作　　者：王宇绅 陈皓勇[1] 黄宇翔 吴晓彬 朱彦瑾 张健彬 WANG Yushen;CHEN Haoyong;HUANG Yuxiang;WU Xiaobin;ZHU Yanjin;ZHANG Jianbin(School of Electric Power Engineering,South China University of Technology,Guangzhou 510610,Guangdong Province,China;Guangdong U&P Thinktank Energy Science and Technology Development Co.,Ltd.,Guangzhou 511458,Guangdong Province,China)

机构地区：[1]华南理工大学电力学院,广东省广州市510610 [2]广东博慎智库能源科技发展有限公司,广东省广州市511458

出　　处：《发电技术》2024年第6期1173-1185,共13页Power Generation Technology

基　　金：国家自然科学基金项目(51937005)。

摘　　要：【目的】为应对虚拟电厂(virtual power plant,VPP)在参与电能量和需求响应市场时所面临的新能源出力和负荷不确定性问题,提出一种考虑多重不确定性的鲁棒优化调度策略,旨在降低鲁棒优化的保守性并提高VPP的经济效益。【方法】构建基于条件风险价值(conditional value at risk,CVaR)的多面体不确定性集,在此基础上,考虑风电、光伏出力和负荷的不确定性,建立VPP参与电能量和需求响应市场策略的日前两阶段鲁棒优化模型。基于行列生成(column-and-constraint generation,C&CG)算法和拉格朗日对偶理论,将所建模型分为可利用求解器求解的主问题和子问题。最后,利用蒙特卡罗方法生成大量风电、光伏和负荷数据,对所提策略进行仿真分析,并与其他方案的优化结果进行对比。【结果】所提策略采用基于CVaR的多面体不确定性集,能够充分利用历史数据,相比于采用传统不确定性集的方案,VPP的总成本降低了约2%。【结论】所提策略可以显著降低鲁棒优化结果的保守性,并在多重不确定性条件下提升VPP参与市场的经济性。[Objectives]To address the uncertainties of renewable energy output and load faced by virtual power plant(VPP)when participating in electric energy and demand response markets,a robust optimal scheduling strategy considering multiple uncertainties was proposed to reduce the conservativeness of robust optimization and improve the economic benefits of VPP.[Methods]A polyhedral uncertainty set based on conditional value at risk(CVaR)was constructed.On this basis,considering the uncertainties of wind power,photovoltaic output and load,a day-ahead twostage robust optimization model of VPP participating in electric energy and demand response markets was established.Then,using a column-and-constraint generation(C&CG)algorithm and Lagrangian dual theory,the model was divided into a master problem and a sub-problem that can be solved by a solver.Finally,Monte Carlo method was used to generate a large number of wind power,photovoltaic and load data.The proposed strategy was simulated and analyzed,and compared with the optimization results of other schemes.[Results]The proposed strategy adopting a polyhedral uncertainty set based on CVaR can make full use of historical data.Compared with the scheme using traditional uncertainty set,the total cost of VPP is reduced by about 2%.[Conclusions]The proposed strategy can significantly reduce the conservativeness of robust optimization results and enhance the economy of VPP participation in the market under multiple uncertainties.

关 键 词：虚拟电厂(VPP) 风电 光伏 电能量 需求响应市场 条件风险价值(CVaR) 鲁棒优化 调度策略 

分 类 号：TK01[动力工程及工程热物理] TM73[电气工程—电力系统及自动化]