Energy storage-empowered multi-type EV charging infrastructure for power-constrained buildings: A two-stage design optimization framework

Large-scale deployment of electric vehicle (EV) charging infrastructure in existing commercial buildings is often constrained by limited transformer capacity, particularly in high-density cities where electrical upgrades are costly and difficult to implement. To address this challenge, this study investigates the technical and economic feasibility of using energy storage systems (ESSs) to support EV charger deployment in power-constrained buildings. A two-stage design optimization framework is proposed to co-optimize EV charger deployment and ESS energy and power capacities. The upper-level design optimization uses a genetic algorithm to search for the optimal configuration of multi-type EV chargers and the ESS while satisfying users' basic commuting requirements. The lower-level operation optimization then determines the optimal ESS scheduling that minimizes operational cost under the transformer capacity constraint. The results show that the proposed framework significantly increases the achievable EV penetration in power-constrained buildings without requiring electrical upgrades, while substantially improving life-cycle economic performance. Compared with conventional single-type charger deployment supported by electrical upgrades, the proposed framework substantially reduces life-cycle cost by 43.1–175.5% while achieving higher charging quality of service. Overall, this study provides a technically feasible and cost-effective planning pathway for enabling high EV penetration in existing power-constrained buildings, thereby facilitating transport electrification in high-density cities.