Optimal placement and sizing of plug in electric vehicles charging stations within distribution networks with high penetration of photovoltaic panels

Abstract

This paper proposes a scenario optimization based algorithm in order to allocate charging station of plug in electric vehicles (PEVs) within a commercial area with the aim of increasing penetration level of photovoltaic (PV) panels as well as decreasing side effects of vehicular loads. A multivariate stochastic modeling methodology based on the notion of copula is provided in order to develop a probabilistic model of the load demand due to PEVs. The suggested method considers the correlation issue among the related random variables of the PEVs. This model, in addition to the models provided for PV generation and commercial loads, is utilized to construct synthetic data required for the optimal allocation of the station. Considering the prepared scenarios, particle swarm optimization (PSO) algorithm is utilized to minimize energy loss as well as voltage deviation in the distribution system. The proposed methodology has been applied on a test distribution network in order to demonstrate its efficiency in simultaneous integration of vehicular loads and PV generations.