计及源荷不确定性的虚拟电厂日前优化调度方法OA

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.