Hourly Energy Demand Impacts of Battery Electric Vehicle Adoption in Italy: A Grid Simulation and Policy Analysis

Abstract

The rapid adoption of Battery Electric Vehicles (BEVs) poses growing challenges for electricity grid stability and emissions reduction. This study presents a high-resolution, hourly analysis of BEV-driven energy demand in Italy, simulating two 2024 scenarios: 3.5 million BEVs (Scenario 1) and 7 million BEVs (Scenario 2). A Python-based grid model incorporates household and highway fast-charging loads, renewable energy sources (solar, wind, hydro, bioenergy), and 5 GWh of battery storage.Scenario 1 increases daily electricity demand by 19% (1.1 TWh), with peak loads of 47–49 GW, requiring 152 GWh of thermal generation and emitting 76,000 tons of CO₂ per day. Scenario 2 increases demand by 40% (1.25 TWh), with peaks of 50–53 GW, necessitating 224 GWh of thermal generation and resulting in 112,000 tons of daily CO₂ emissions. Battery storage mitigates 20% of peak demand, but remains inadequate for Scenario 2’s 15 GW shortfall.Unlike annual-averaged studies, this work highlights hourly demand spikes and critical grid stress periods. Policy recommendations include time-of-use tariffs, tripling storage capacity, and doubling solar PV—measures that could cut emissions by up to 35% and meet 80% of BEV energy needs during daylight. These findings support the EU Fit for 55 goals and offer a scalable model for sustainable BEV integration. The study underscores the urgency of smart charging, renewable expansion, and advanced storage to enable a resilient energy transition. Future research should explore real-time renewable forecasting and vehicle-to-grid systems for optimized load balancing.

Keywords: Battery Electric Vehicles (BEVs), energy demand, grid management, smart charging, sustainable transportation