Joint Planning of Distributed PV Stations and EV Charging Stations in the Distribution Systems Based on Chance-Constrained Programming

Abstract

Simultaneous deployment of the electric vehicle charging stations (EVCSs) and distributed photovoltaic stations (DPVSs) in the distribution systems is an effective way to reduce greenhouse gas emissions, promote renewable power adoption, and achieve sustainable development in energy utilization. In this context, how to deploy the EVCSs and DPVSs in the distribution systems with a reasonable scheme is of great importance. In this article, a joint planning model is developed to optimize locations and capacities of the EVCSs and DPVSs simultaneously to reduce energy losses in the distribution systems. In the joint planning model, constraints on bus voltage deviations and line currents are both formulated as chance constraints to ensure that the distribution systems are in reasonable operating statues. To quantify these two chance constraints, a scenario-based method is developed to calculate the probabilistic power flow of the distribution systems during a typical planning day, in which random characters of the DPVS generations and the EVCS charging loads are both considered. The joint planning model of the EVCSs and DPVSs developed in this article is difficult to be solved by mathematical optimization methods. Therefore, genetic algorithm (GA) is customized and utilized to solve the joint planning model of the EVCSs and DPVSs. Finally, a case study based on IEEE 33-bus distribution systems validates the joint planning model and its solving algorithm.

Keywords

• Electric vehicle charging station
• distributed photovoltaic station
• joint planning
• genetic algorithm
• chance constraints