Adaptive Fuzzy Load Prioritization for Energy Management in Hybrid Wind-Solar Microgrids - Arunava Chatterjee (Peneliti Teknologi Teknik Indonesia, 2026)
Hybrid renewable microgrids are increasingly becoming popular among renewable energy generation schemes for small-scale power. However, the intermittent nature of both these sources leads to frequent power imbalances between generation and load demand. Conventional control strategies often rely on battery storage for compensation in these cases or employ advanced controls. This paper presents an adaptive Fuzzy logic-based load prioritization strategy for better energy management in such microgrids. The proposed method adjusts the non-critical loads dynamically based on real-time power availability instead of relying on storage only. A fuzzy-based decision technique is used to determine load shedding levels using inputs such as power mismatch, system voltage deviation, and state-of-charge (SOC) of the battery. The proposed control improves system stability and reduces dependency on battery storage. Suitable simulations backed by laboratory-scale experiments demonstrate that the proposed method improves voltage regulation and minimizes load disruption. It significantly reduces voltage deviation by almost 66%, battery current by 43%, and improves power utilization to 97% compared to conventional control systems.