Research on Optimal Scheduling of VPP Based on Latin Hypercube Sampling and K-Means Clustering

Abstract

Based on the classical scenario set, the VPP economic dispatch model is proposed taking into account the uncertainty factors of distributed power sources. The basic model of the VPP is first analyzed, followed by the proposed operation strategy of the VPP based on the basic model, while considering the impact of the time-of-use electricity price on the economics of the VPP. Latin hypercube sampling combined with K-means clustering is used to generate the classical scene set; at the same time, the model is solved using an algorithm that incorporates a genetic mechanism in an improved particle swarm algorithm (PSO). Finally, according to the established model, a calculation example is used to verify. The design is based on two scenarios of the classic scene set and general scene. The optimization configuration results are compared and analyzed. It is confirmed that the VPP optimization configuration under the classic scene set can improve the net income of the VPP.