Multi-Objective Capacity Configuration of PV-Energy Storage Systems in Low-Carbon Buildings with Electric Vehicles: A Bi-Level Optimization Approach

To support low-carbon smart buildings, this study proposes a multi-objective capacity optimization method for PV-energy storage systems considering the flexibility potential of orderly electric vehicle (EV) charging loads. First, an orderly EV charging model based on price-guided charging quantifies the flexibility potential of EV charging loads. Then, a bi-level multi-objective capacity configuration model is proposed. In the upper level, the building operator minimizes both economic and carbon emission costs, jointly optimizing PV-energy storage capacity configuration and EV charging prices. In the lower level, EV users optimize their charging schedules to minimize their charging costs in response to the charging prices. To solve this bi-level multi-objective problem, the two objectives are normalized and weighted into a single-objective function, and then a heuristic solution method based on a genetic algorithm is developed. Case study results show that the proposed mode reduces building economic cost and electricity-related carbon emissions, demonstrating the benefits of incorporating carbon emissions into demand-side optimization under the “dual-carbon” targets.