Planning Smart EV Charging Infrastructure Around Metro Transit Hubs in Riyadh

Abstract

This study presents an integrated framework for planning electric vehicle (EV) charging infrastructure around metro transit hubs in Riyadh, combining renewable energy, smart grid interaction, and advanced simulation techniques. The approach incorporates spatial demand forecasting, photovoltaic (PV) system sizing, M/M/c queuing analysis, and agent-based modeling (ABM) to evaluate both wired and wireless EV charging strategies. Real demographic and mobility data from ten Riyadh Metro station zones are used to estimate daily EV arrival rates and charging demand, enabling location-specific infrastructure planning. Photovoltaic-powered wireless charging is introduced as a demand-shaping mechanism to relieve fast-charging congestion and reduce grid dependency. The model shows that serving 40 % of the daily EV load wirelessly can reduce charger requirements by up to 60 % and lower average queue delays by more than 80 %. A PV system sizing analysis based on Riyadh’s solar insolation estimates annual energy yields up to 860 MWh per station and total carbon emission avoidance exceeding 1,000 tons CO2 per year. The queuing analysis highlights the critical role of wireless load share and session duration in maintaining system stability, while the agent-based simulation models user behavior under real-time pricing and charger constraints. Together, these tools provide a robust, data-driven planning framework that aligns with Saudi Arabia’s Vision 2030 goals by enabling clean energy integration, reducing emissions, and enhancing smart urban mobility through resilient and scalable EV infrastructure.