Techno-Economic Analysis and Optimization of Renewable Energy Integrated DC Fast Charging Stations for Electric Vehicles

Author

Terapalli Sandeep, Prof. G.V.Siva Krishna Rao

Abstract

  The increasing adoption of electric vehicles has created a growing demand for fast-charging infrastructure capable of delivering reliable charging services while maintaining economic feasibility. This paper presents an optimization-based approach for designing a renewable energy-integrated DC fast-charging station supported by photovoltaic (PV) generation, a battery energy storage system (BESS), and a bidirectional grid connection. The main objective is to identify a suitable station configuration that maximizes the net present value (NPV) over a 20-year evaluation period. The proposed framework considers the optimal selection of the number of charging units, charger power rating, PV installation area, battery storage capacity, and maximum grid power requirement. To represent practical charging conditions, EV demand is modeled using different vehicle battery-capacity categories, a lognormal distribution of arrival state of charge (SOC), and an Erlang-B-based vehicle arrival model. A balking mechanism is also incorporated to account for vehicles that leave the station when all charging units are occupied. The energy balance and BESS state-of-charge constraints are considered to ensure feasible system operation. Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA) are implemented in MATLAB to determine the optimal station configuration and evaluate its economic performance. The simulation results indicate that PSO achieves a higher NPV of $1,428,997.71 compared with $1,417,521.00 obtained using SSA. These findings demonstrate the effectiveness of metaheuiristic optimization in determining economically attractive configurations for integrated EV fast-charging stations, with PSO providing the better financial outcome among the two methods considered.

Keywords

Vehicle charging station, net present value, particle swarm optimization, salp swarm algorithm, battery energy storage system, photovoltaic generation, techno-economic design station sizing are the core topics, for this project.

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