Spatiotemporal Assessment of Electric Vehicle Charging Strategies and Vehicle-to-Grid Operation in Distribution Networks

Abstract

The increasing penetration of electric vehicles (EVs) poses significant operational challenges for distribution networks due to spatial concentration and temporal variability of charging demand. Existing studies often treat the spatiotemporal evolution of EV adoption separately from network-constrained operation, or rely on single representative operating conditions, limiting the assessment of cumulative network impacts. This paper presents a common spatiotemporal optimization framework to assess the progressive impact of EV integration under different charging strategies, including uncontrolled charging, smart charging, and vehicle-to-grid operation. The proposed approach integrates dynamic zonal EV adoption modeling with a convex network-constrained power flow formulation, enabling scalable multi-period analysis. EV adoption is represented through heterogeneous zonal growth patterns driven by socioeconomic factors, capturing both spatial disparities and temporal evolution of charging demand. The framework is evaluated on the IEEE 70-node radial distribution feeder under increasing EV penetration levels. Results show that uncontrolled charging quickly activates network constraints, while coordinated strategies restore feasibility. Moreover, vehicle-to-grid operation further reduces peak loading and overall network stress, leading to operating conditions closer to the base case.