A Forecast-Guided Battery Energy Management Strategy for Peak Load Shaving in Renewable Community Microgrids

This study develops a forecast-guided battery energy management strategy, FG-BEMS, for peak load shaving in a PV–wind–BESS community microgrid. The proposed controller uses only causal information, including recent net-load measurements and previous-day demand patterns, to prepare the battery before the evening peak period without relying on future measured data. It coordinates pre-peak charging and selective discharge while maintaining battery SOC and power limits. The strategy is evaluated against an uncontrolled Typical case and a conventional rule-based controller under the same operating conditions. FG-BEMS reduces the peak net load from 190.686 kW to 150.686 kW, achieving a 20.98% peak reduction and a 97.00% reduction in threshold violation energy. It also provides higher net operating savings while maintaining safe SOC reserve operation, demonstrating its effectiveness for practical peak shaving in renewable community microgrids.