Peak-Shaving Control Method for Commercial Building Clusters via Source-Storage-Load Coordination

To address the challenges of load regulation and revenue allocation when commercial building clusters participate in grid demand response (DR), this paper proposes an optimized control method for energy storage-assisted multi-building peak shaving. First, we establish detailed load models for offices, malls, and hotels, generating day-ahead load profiles with typical peak-valley characteristics. Second, a dynamic battery charging/discharging strategy based on time-of-use electricity prices is designed to achieve arbitrage and grid DR requirements. Finally, a proportional load-sharing revenue allocation mechanism ensures economic fairness among stakeholders. Simulation results demonstrate that under a 15-minute time resolution, the system reduces the peak load by $12.7 \%$, increases direct DR income by $23.5 \%$, and achieves win-win outcomes through the proposed revenue distribution. This study provides quantifiable decision-making support for distributed energy storage in commercial districts participating in grid interaction.