电子科技2025，Vol.38Issue(11)：25-33,9.DOI:10.16180/j.cnki.issn1007-7820.2025.11.004
计及源荷不确定性的虚拟电厂日前优化调度方法
A Day Ahead Optimization Scheduling Method for Virtual Power Plant Considering Source Load Uncertainty
摘要
Abstract
In view of the problems in characterizing the uncertainty fluctuations of scenery and the high carbon e-missions of traditional power systems,a virtual power plant day-ahead optimal scheduling model considering the uncer-tainty of source load is proposed.On the source side,the exponential function method is used to establish the multivari-ate covariance matrix of the landscape,and the Frank-Copula function is used to measure the nonlinear correlation be-tween the landscape output,and the joint probability distribution model is constructed.The typical scenes of scenery output are obtained by inverse sampling and K-means clustering reduction to achieve accurate characterization of scen-ery output.A flexible user 2D incentive demand response model is established on the load side to realize the collabora-tive optimization of source load and improve energy utilization efficiency.In the system side,carbon capture and stor-age,power to gas device coupled with cogeneration unit,realize the low-carbon flexible operation of virtual power plant.To solve the difficult problem of complex multi-objective model,the trapezoidal membership function is used to fuzzy the problem into a single objective problem,and the CPLEX solver is called to solve it.The simulation results show that the proposed method can effectively reduce the wind and light abandonment of the system and improve the low-carbon economic benefits of dispatching operation.关键词
虚拟电厂/源荷不确定性/指标函数法/Frank-Copula函数/碳捕集与封存/优化调度Key words
virtual power plant/source load uncertainty/indicator function method/Frank-Copula function/car-bon capture and storage/optimal dispatch分类
动力与电气工程引用本文复制引用
孙启宸,张靖,何宇,王志杨,曹国强,杨志..计及源荷不确定性的虚拟电厂日前优化调度方法[J].电子科技,2025,38(11):25-33,9.基金项目
黔科合支撑([2022]一般013) （[2022]一般013）
黔科合平台人才(GCC[2022]016-1) （GCC[2022]016-1）
黔教技([2022]043) Qiankehe Support Project([2022]General013) （[2022]043）
Qiankehe Platform Talents(GCC[2022]016-1) （GCC[2022]016-1）
Educational Technology Foundation of Guizhou([2022]043) （[2022]043）
