Statistical energy-based sizing of electric vehicle charging infrastructure for workplace parking facilities: case study of Polytechnic University of Valencia, Spain

The accelerating electrification of transport is a cornerstone of global decarbonization strategies, yet it poses challenges for energy systems dominated by intermittent renewable sources. In this context, workplace parking facilities offer an opportunity to integrate Electric Vehicle (EV) charging with on-site renewable generation, benefiting from extended dwell times and predictable user behavior. This study proposes a scalable methodology for the characterization and optimal sizing of EV charging infrastructure integrated with renewable energy sources, explicitly accounting for uncertainty in vehicle characteristics, user behavior, mobility patterns, and solar generation. The methodology combines stochastic demand modeling with a Best Estimate Plus Uncertainty (BEPU) framework and Wilks’ order statistics to derive confidence bounds for energy demand, peak power requirements, and infrastructure sizing. It is applied to a large underground parking facility serving a research campus at the Polytechnic University of Valencia (UPV), accommodating over 600 vehicles and supported by up to 0.6 MW of rooftop and canopy-mounted PhotoVoltaic (PV) generation. Results show that modeling commuting patterns and occupancy reduces annual charging demand estimates to 1,200–1,580 MWh. Although the PV system can theoretically generate energy equivalent to 80% of the annual charging demand, temporal mismatches between generation and load limit direct self-consumption without storage. The analysis shows that moderate charging power (7.4 kW) combined with smart charging can reduce infrastructure requirements. Battery energy storage markedly improves self-consumption, demand coverage, and grid interaction, particularly under favorable seasonal conditions. The framework supports planning resilient, cost-effective, renewable-driven EV charging systems in institutional and urban environments.