A Bi-Level Optimization Model for Virtual Power Plant Membership Selection Considering Load Time Series

In order to improve the level of new energy consumption and reduce dependence power system on traditional fossil energy, this paper proposed a bi-level optimization model for virtual plant member selection by means coordination complementarity among different sources, aiming at optimizing economy clean capacity combining it with time sequence load consumption. The method comprises following steps: (1) processing load, wind power, photovoltaic data using ordered clustering reflect correlation between (2) uses double-layer model, wherein upper layer calculates configuration thermal storage units in selects participate dispatching considering utility coefficient environmental benefit units. Latin hypercube sampling (LHS) was used generate large number subsequences mixed integer linear programming (MILP) algorithm calculate optimal operation scheme system. simulation results showed that reducing combination establishing reasonable unit allocation average daily VPP revenue increased RMB 12,806 proportion generation 1.8% average, which verified correctness method.