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.

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Publication Details

Journal
International journal of research and scientific innovation
Published
2025-10-14
DOI
https://doi.org/10.51244/ijrsi.2025.120800351
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
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article

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

Abdul Momin, Md. Anisur Rahman, Mehedi Hassan, Badhan Gain et al.
International journal of research and scientific innovation
Power System Optimization and Stability
article

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

Abdul Momin, Md. Anisur Rahman, Mehedi Hassan, Badhan Gain, Shoeb Rahman Jisan
article en

Abstract

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.

International journal of research and scientific innovationVol. 12(9)
University of Barishal (BD)
Openalex Percentile: Top 71%
Power System Optimization and Stability
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