Current power system stabilizer designs, including fuzzy-PID and Lead-Lag compensators, need help with adaptability and complexity in diverse and evolving power system environments. Conventional tuning methods like th...
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Current power system stabilizer designs, including fuzzy-PID and Lead-Lag compensators, need help with adaptability and complexity in diverse and evolving power system environments. Conventional tuning methods like the Newton-Raphson approach and optimization strategies like particle swarm optimization, genetic algorithms, and cuckoo search algorithms face challenges in achieving optimal performance for Fractional Order Proportional Integral Derivative (fopid) controllers. There is a critical need for innovative tuning methods that offer enhanced adaptability and performance in complex power system stability analysis. This research contributes to the advancement of power system stability analysis, specifically in SMIB systems, offering insights into optimizing fopidcontrollers utilizing the innovative Harris Hawks Optimization (HHO) algorithm. The work expects these findings to broaden the implications for power system control and enhance the stability of Single Machine Infinite Bus (SMIB) systems, thus fostering the resilience and reliability of modern electrical infrastructure. The fopidcontroller encompasses fractional order parameters, encompassing proportional, integral, and derivative gain, integral order, and derivative order, each exerting a substantial influence on control responses and stability. This research harnesses HHO, an optimization technique inspired by nature, to fine-tune fopidparameters. The investigation involves initializing the SMIB model, formulating an objective function to minimize control errors, and employing HHO iteratively to refine the fopidcontroller. The outcomes reveal enhanced stability, diminished overshoot, accelerated settling time, and transient response.
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