Akademik Veri Yönetim Sistemi
International Journal of Hydrogen Energy, cilt.214, 2026 (SCI-Expanded, Scopus)
The stochastic nature of renewable energy sources and load demand poses significant challenges to maintaining voltage and frequency stability in islanded microgrids. To address these challenges, this paper proposes an adaptive voltage–frequency control framework based on a Genetic–Gray Wolf Optimized interval Type-II Sugeno fuzzy logic controller. The proposed system integrates a hydrogen fuel cell into a hybrid microgrid that considers multi-source uncertainties on both the generation and demand sides. In this configuration, short-term fluctuations in renewable energy generation are compensated by the battery energy storage system, while the fuel cell provides long-term power support, ensuring system sustainability and stability. Renewable and load variations are modeled using probabilistic distributions, and a roulette wheel mechanism dynamically selects one of 20 stochastic scenarios to represent various uncertainty conditions. The proposed GGWO–Type II fuzzy controller is evaluated under four operating scenarios, including manual and optimized demand response programs. The simulation results demonstrate that it outperforms conventional P/F and Q/V droop and Type-I fuzzy controllers, achieving superior voltage–frequency regulation and faster transient recovery under uncertainty. In the optimized DRP case, the system achieved the fastest dynamic response and the lowest voltage and frequency deviations (Vmin=0.9685 p.u., fmin=59.397Hz). Compared to the reference uncertainty scenario, the proposed controller improved voltage and frequency regulation by approximately 17% and 19%, respectively, while further improvements of 8% and 10% were observed relative to the manual DRP case. These results confirm that hydrogen fuel cell integration, combined with the optimized control strategy, significantly enhances the dynamic stability and resilience of the islanded microgrid under uncertain operating conditions.