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    A unified robust hybrid optimized Takagi-Sugeno fuzzy control for hydrogen fuel cell-integrated microgrids
    (Pergamon-Elsevier Science Ltd, 2025) Ozcan, Omer Faruk; Kilic, Heybet; Ozguven, Omerul Faruk
    Microgrids integrating renewable energy sources, hydrogen fuel cells, battery-based energy storage systems (ESS), and various loads have become essential for the seamless incorporation of distributed energy into the grid. Hydrogen fuel cells, in particular, are crucial for providing reliable, clean electricity, especially during periods of reduced renewable energy availability. This paper presents a unified control solution for converters and inverters, utilizing a hybrid optimized Takagi-Sugeno-Kang (TSK) fuzzy-based approach to manage ESS operation, with a strong focus on hydrogen fuel cells. The strategy dynamically controls the power generated or stored in the ESS, prioritizing hydrogen fuel cells based on grid demand, available renewable power, and the battery's state of charge (SOC). This method reduces active power exchange at the point of common coupling during grid-connected mode and supports frequency regulation during island mode operations, thereby improving system stability and efficiency. To enhance Fuzzy System (FS) design, a hybrid genetic algorithm (GA) and grey wolf optimizer (GWO) approach is applied, accelerating rule generation and optimizing system performance. Simulation results demonstrated that the proposed hybrid GGWO-TSK control strategy achieved 97.58% PV and 98.56% wind tracking efficiency, while optimizing hydrogen fuel cell utilization to maintain a 98.88% fuel cell tracking efficiency. This method effectively minimized power exchange, improved frequency regulation, and enhanced microgrid stability, ensuring efficient energy management in both grid-connected and islanded modes. The proposed framework proves to be a robust and scalable solution for hydrogen fuel cell-integrated microgrids, contributing to a more resilient and sustainable energy system under diverse operating scenarios.
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    Intelligent optimized load shedding under renewable and load uncertainties in fuel cell-integrated islanded microgrids\
    (Pergamon-Elsevier Science Ltd, 2026) Ozcan, Omer Faruk; Kilic, Heybet; Ozguven, Omerul Faruk
    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, shortterm 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 = 59.397 Hz). 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.