Energy Storage Expansion Planning Method for Active Distribution Network Based on Improved Particle Swarm Optimization Algorithm

Abstract

Abstract With the increasing proportion of new energy sources such as photovoltaic and wind power in the regional power grid, the unreliable and random problems of new energy generation are magnified, which will cause damage to the security and stability of the power grid. How to improve the reliability and accuracy of active distribution network energy storage expansion planning and ensure the safe, stable and economic operation of the power grid is the research direction of all countries in the world. In this paper, an improved particle swarm optimization algorithm based on particle swarm optimization for adaptive improvement is proposed. Compared with the traditional particle swarm algorithm, the feasibility and superiority of the algorithm are illustrated. The lower-level programming model is solved by using the interior point method of tracking the center trajectory. The dual gap is improved to speed up the convergence of the algorithm. The improved particle swarm optimization algorithm is combined with the interior point method of tracking the center trajectory to solve the established bi-level programming model. The planning model is solved by using the algorithm. Through the analysis of the planning results, the optimal planning and operation scheme of renewable distributed generation in active distribution network is obtained, and the feasibility of the model is verified. In this paper, the active distribution network has the characteristics of active management, which improves the ability of the distribution network to accept the expansion of energy storage, and becomes an important direction of the development of distribution network.