Sustainable EV charging via scenario-based optimization of hybrid solar-storage systems: A regionally adaptive approach

Abstract

The rapid expansion of electric vehicle (EV) adoption requires charging infrastructure that is both economically viable and aligned with low-carbon energy transition goals. In this context, carbon taxation and energy storage economics play a decisive role in shaping the performance of renewable-powered EV charging stations (EVCS). This study proposes and evaluates a scenario-based, regionally adaptive optimization framework to assess the techno-economic and environmental performance of EVCS integrated with photovoltaic (PV) systems and energy storage system (ESS) under varying charging demand, carbon tax (CT), spatial constraints, and storage investment costs. The results indicate that although carbon taxation increases total system costs, it substantially reduces grid dependency and accelerates investment recovery by enhancing the economic value of renewable selfconsumption. These effects are most pronounced in high-irradiance regions, where coordinated PV expansion and demand-responsive ESS sizing lead to significant emission reductions and improved financial performance. An effective CT incentive range of 40-60 $/t is identified, beyond which marginal economic gains diminish despite rising costs. The analysis further shows that optimal ESS sizing is driven primarily by temporal mismatches between PV generation and EV charging demand rather than capital cost minimization alone. ESS deployment becomes economically attractive when investment costs fall below approximately 150 $/kWh, enabling curtailment mitigation and higher renewable utilization. Cross-regional comparisons reveal strong location dependency: high-solar regions achieve faster returns, whereas carbon taxation alone remains insufficient in low-irradiance or low-tariff markets. These findings offer quantitative, policy-relevant guidance for region-specific planning of sustainable EV charging infrastructure.