Load-Frequency Control with Mountain Gazelle Optimization Algorithm for Improving Energy Quality

The rising energy demand driven by population growth, industrialization, and modern living necessitates sustainable and efficient energy management strategies. This research focuses on the load-frequency control of an islanded microgrid consisting of components such as a diesel generator, wind turbine, solar panel, energy storage system, fuel cell, electrolyzer, and electric vehicles. To ensure system stability, four controller types—PI, PID, 2-DOFPI, and 2-DOFPID are designed. The Mountain Gazelle Optimization Algorithm (MGO) is utilized to fine-tune the parameters of these controllers.