Renewable energy sources planning considering approximate dynamic network reconfiguration and nonlinear correlations of uncertainties in distribution network

Abstract

With the development and application of renewable energy sources (RESs) into distribution networks, how to handle the correlations of uncertainties and the network reconfiguration in the RESs planning procedure is a significant challenge. Different from the conventional methods which assume that the uncertainties are linear correlation, the nonlinear correlations of uncertainties are modeled by applying copula theory. The joint probability density functions (PDFs) of wind speed-load and irradiance-load are developed. Based on the scenarios generated by Monte Carlo sampling (MCS), a chance constrained RESs planning model is established. The approximate dynamic network reconfiguration (ADNR) instead of static network reconfiguration is incorporated in the particle swarm optimization (PSO)-based solution algorithm process, which can get a better solution. Numerical simulations on an actual distribution network show the superiority of the proposed algorithm over the existing methods.