Renewable Energy Supported Bi-directional Electric-Vehicle Charging Station Allocation in Distribution Network using INBPSO Technique

Abstract

With the sustained growth in the electric-vehicle (EV) industry, the installation of a large number of electric-vehicle charging stations (EVCSs) is the utmost important in recent energy policies of all countries. On the other side, due to the augmented awareness on renewable energy especially the photovoltaic (PV) and wind energies, the installation of renewable energy based EVCSs and their integration into the radial distribution networks have become a promising choice with the feasible bi-directional power flow facility catered by the EVCSs. Bi-directional EVCSs can enable power flow from renewable source/EV to grid and grid to EV to balance power demand for EV as well as distribution network. The optimum allotment of renewable energy powered EVCSs in existing power distribution system is a matter of great significance to maintain the power balance as well as the voltage profile and to minimize the total active power loss of the network. This paper presents a strategy for optimum allocation of renewable energy powered EVCSs in a large distribution network with the focus on power balance, voltage profile improvement, and active power loss minimization. An improved new binary particle swarm optimization (INBPSO) technique is applied in collaboration with a fast and efficient power flow analysis technique for performing dynamic power flow computation. Validation is conducted on IEEE 15-bus system considering different cases of power flow directions and power ratings. Additionally, voltage as well as loss sensitivity analyses are performed to ascertain the acceptability of the optimum locations obtained by the computation approach.