Smart charging strategy for wireless charging electric vehicles in microgrid-integrated multistorey charging carpark with HIL simulation

Optimally scheduling loads from wireless (dis)charging electric vehicles (WCEVs) in the multistorey charging carpark (MCC) has received much attention from both academia and industry recently. WCEVs also have great potential for utilization in the MCC-integrated microgrid, functioning as distributed energy storage systems. However, load-levelling and cost-effective operations in such contexts require thorough investigation. Optimal scheduling of the (dis)charging power and timing of WCEVs via smart charging strategies can alleviate the power load profile and reduce energy costs. Thus, multi-objective optimization is required to achieve these optimal schedules. The dominance-based local search procedure (DBLSP) and clone management principle (CMP) are developed and integrated with the non-dominated sorting genetic algorithm-II (NSGA-II) to form the memetic DBLSP-CMP-NSGA-II method, with the novelty of further coupling with an optimization-to-dispatch hardware-in-the-loop (HIL) validation framework for multi-objective optimization by considering the load profile and charging costs of WCEVs. The proposed approach can achieve solution diversity, enhanced convergence quality, and balance exploration-exploitation while avoiding premature convergence. Its superior performance in load alleviation and charging cost reduction is proven in simulation-based comparative case studies within the MCC scenario and parameter settings considered, and its underlying principles, effectiveness, and implementability of the proposed method are further tested through HIL feasibility demonstration at scaled power with advanced three-level inverter-based bidirectional wireless power transfer systems. The reported improvements are scenario-dependent, whereas the proposed formulation and optimization-to-dispatch workflow are general and can be re-parameterized for other charging sites and tariffs.