Electric-vehicle charging facility deployment models for dense-city residential carparks considering demand uncertainty and grid dynamics

Abstract

As the driving range of electric vehicles (EVs) increases, home-based charging has been becoming the dominant strategy for EV users to replenish electricity in urban e-mobility systems. In Asian metropolises with high population density (called dense-cities), the majority of residents live in multi-unit dwellings and share public parking and charging facilities in their residential carparks. This study, therefore, investigates the EV charging facility deployment (CFD) problem for dense-city residential carparks, taking into account charging demand uncertainty and the impact of grid dynamics. To address this problem, we first develop a water-pipe model to minimize the construction cost of the CFD scheme while balancing dynamic charging demand and supply. We then extend our approach to formulate a chance-constraint optimization model that considers more practical factors such as stochastic and dynamic charging demand, multi-type chargers, grid dynamics and the setup time of charging service. Furthermore, we propose a simulation-based method to validate the developed CFD models at the operational level. Our case study in Singapore demonstrates that the chance-constraint optimization model produces effective CFD solutions for all simulated charging scenarios. Our results also reveal the importance of considering grid dynamics and charging demand uncertainty for the residential-carpark CFD problem.