Techno-Economic Sizing and Optimization of a Grid-Connected Photovoltaic Electric Vehicle Charging Station Using HOMER: A Case Study of Palestine

The rapid growth of electric vehicle (EV) adoption has intensified the need for cost‑effective and sustainable fast‑charging infrastructure. Integrating photovoltaic (PV) systems with electric vehicle charging stations (EVCSs) offers significant environmental and economic advantages; however, proper system sizing and techno‑economic optimization are critical to ensure feasibility and long‑term performance. This paper presents a comprehensive techno‑economic sizing and optimization study of a grid‑connected photovoltaic‑based fast electric vehicle charging station using HOMER Pro software. A real case study located in Hebron, Palestine, is investigated due to its high solar potential and increasing EV charging demand. The proposed charging station is designed to supply an average EV load of approximately 7 MWh/day. A detailed load assessment is conducted, followed by optimal sizing of the PV system, power converters, and grid interaction strategy. The analysis includes land utilization requirements, energy balance evaluation, and economic performance indicators such as Net Present Cost (NPC), Levelized Cost of Energy (LCOE), and renewable energy penetration. Simulation results indicate that a 1.75 MW photovoltaic system meets the charging demand through optimal sizing, achieving a PV penetration exceeding 100% and permitting substantial surplus energy export to the utility grid during periods of high solar irradiance. The levelized cost of PV generation is found to be approximately 0.034 USD/kWh, and the blended levelized cost of the delivered EV charging service, inclusive of grid backup, is approximately 0.072 USD/kWh, both well below the 0.20 USD/kWh grid tariff, demonstrating strong economic viability compared to conventional grid‑supplied charging stations. The outcomes confirm that PV‑based fast EV charging stations, when properly sized and optimized, represent a sustainable and economically attractive solution for future transportation infrastructure. The underlying sizing problem is further formulated as an explicit cost-minimization program; its solution algorithm is examined analytically, closed-form sensitivity relationships for the discount rate, PV derating factor, and grid sellback price are derived and validated against the simulation outputs, and a stochastic model of EV arrivals is proposed as a probabilistic complement to the deterministic load profile.