Multi-objective optimal sizing of EV charging stations and PV systems in residential buildings

Rapid growth of the electric vehicle (EV) market has made the widespread development of residential charging stations inevitable. Simultaneously, integrating a photovoltaic (PV) system into a residential parking facility not only reduces charging-related electricity costs but also alleviates stress on the main power grid. In this study, a new sizing strategy was developed to optimize both electric vehicle charging stations (EVCS) and PV systems for residential parking, addressing the critical challenge of aligning the infrastructure supply with the evolving demand for EV charging. A multi-objective optimization approach was employed: (1) incorporating one objective function to minimize the combined energy bill and investment costs; (2) to quantify and reduce the mismatch between EV power demand and charging station supply, which was a novel metric introduced as part of this work; (3) to enhance the quality of service (QoS) for EV users. Specific residential constraints, including limited parking space and contracted power capacity, are also considered. To solve the complex multi-objective problem, a metaheuristic method was used, and clustering analysis was applied to support stakeholder decision making. The proposed strategy was evaluated using a QoS-constrained sizing optimization method. It achieves approximately 27% lower energy and infrastructure costs. In addition, significant reductions in global greenhouse gas (GHG) emissions were obtained owing to PV integration, amounting to a 31% decrease compared to the reference method. Furthermore, a more strategic charger allocation was enabled by combining slow and fast chargers to improve