Multi-Objective Site Selection and Capacity Determination of Distribution Network Considering New Energy Uncertainties and Shared Energy Storage of Electric Vehicles

Abstract

In recent years, the share of renewable energy in the distribution network has been increasing. To deal with high renewable energy penetration, it is important to improve the energy efficiency and stability of the distribution network. In this paper, the optimal configuration of a distribution network with a high proportion of new energy and electric vehicles is investigated. Firstly, based on the copula theory, the clustered new energy data are obtained by optimizing the wind and solar output scenarios. Secondly, the uncertainty of renewable energy output is fully considered in the planning stage of the distribution network. Subsequently, an improved multi-objective particle swarm optimization algorithm is adopted to determine the optimal capacity and location of charging stations. Finally, the IEEE 33-node distribution network is used for case analysis. Through the comparison of network loss, voltage change, and other related parameters, the advantages of shared energy storage characteristics of electric vehicles in smoothing the uncertainty of the high proportion of new energy are verified.