AI-Based Fuzzy Logic Approach for Load Shedding Scheme for Enhanced Power System Stability in the Barishal, Bangladesh

One of Bangladesh's most urgent problems is still load-shedding, especially in the Barishal region, where frequent outages are frequently caused by an imbalance between the supply and demand for electricity. The majority of traditional load shedding techniques are reactive, manual, and unable to adjust to changing operating conditions. In order to optimize load shedding decisions, this paper suggests an Artificial Intelligence (AI) method based on fuzzy logic. The approach incorporates a number of variables into a fuzzy inference engine, such as the supply-demand ratio, system frequency, and meteorological conditions. A MATLAB/Simulink model was created and evaluated in a variety of real-world situations, including weather disruptions, supply shortages, and generator failure. According to the results, the AI-controlled method outperforms classical methods in terms of frequency and voltage stability, outage duration, and response time to disturbances. The suggested plan has a great deal of potential to improve Barishal's power system dependability and can be expanded to other parts of Bangladesh.

hybrid Load shedding, fuzzy logic, artificial intelligence, power system stability, Barishal, Bangladesh.

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