LAUSR

With the widespread access of flexible loads and renewable energy, the power flow often exceeds the limit of line, resulting in the blockage of distribution network. Virtual power plant (VPP) can not only integrate multiple forms of energy, but also improve the penetration proportion of renewable energy sources. In view of the excellent ability of VPP in power market, a two-stage congestion management (CM) model involving virtual power plant (VPP) with cascade hydro-photovoltaic-pumped storage hybrid generators is established in this paper. The first stage is congestion management of ISO (Independent System Operator), which aims at minimizing congestion cost and is solved by genetic algorithm. The second stage is power correction model of virtual power plant, which is a multi-objective problem considering water and light curtailment, navigation and ecological needs. An improved hybrid non-dominated sorting genetic algorithm-II (HNSGA-II) is proposed to solve the two-stage model. Case studies show that the participation of virtual power plants in congestion management has certain economic value to power system. The joint dispatch of cascade hydro-photovoltaic-pumped storage hybrid generation in the virtual power plant can make flexible decisions according to the needs of energy saving, navigation and ecology. The improved HNSGA-II algorithm is superior to the traditional NSGA-II algorithm in convergence, uniformity and extensity.