Two-stage intra-day control strategy of EV charging and air conditioner loads in commercial buildings for system load reshaping

The increasing disparity between system peak and valley loads poses challenges to the economic operation and renewable energy (RE) integration. Addressing this issue while maintaining human comfort and computational efficiency remains a significant challenge. To tackle this, a collaborative framework is proposed to manage the coupled loads of electric vehicle (EV) charging and air conditioner (AC) systems in commercial buildings powered by the grid and/or the RE. At the first stage, the thermal sensation vote is accurately predicted using a sophisticated hybrid method. Then, the study dynamically adjusts the temperature set-point (TS) of the AC unit and evaluates its load control capacity. At the second stage, a multi-objective intra-day control strategy is developed to optimize the operational parameters of the EV charging and AC load regulation. At this stage, a modified heuristic-based approach is employed to resolve the problem. Finally, the novel strategy is validated using real-world distribution system data. Results demonstrate that the proposed method alleviates EV battery degradation costs by 15% when AC systems are integrated. As for the system load management, the method achieves a 43.2% reduction in peak–valley difference and a 20.01% improvement in valley filling compared to the baseline. • A two-stage strategy reshapes system load via coordinated EV and AC scheduling. • Thermal sensation votes (TSV) guide adaptive AC flexibility while preserving comfort. • A modified HBO enhances convergence in multi-objective load optimization. • The strategy achieves 43.2% peak–valley reduction and mitigates EV battery degradation.