Neuro-Fuzzy Logic Controller for Switching Capacitor Banks in Power Factor Correction within the Manufacturing Industry
Journal Title: Journal of Intelligent Systems and Control - Year 2024, Vol 3, Issue 2
Abstract
Regulatory bodies in electrical engineering mandate the installation of power factor (PF) improvement systems to elevate PF values to between 0.9 and 0.96. Compliance is enforced by regional or local utility companies through penal rates and incentives for PF values nearing unity. Traditional power factor correction (PFC) systems often utilize microprocessor-based controllers for switching capacitor banks, which can result in under- or over-compensation of reactive power. This study developed an adaptive neuro-fuzzy inference system (ANFIS) utilizing a Sugeno-Takagi inference model based on the sub-clustering method to address the limitations of sensitivity and response time observed in existing microcontroller-based PFC systems. The proposed neuro-fuzzy (NF) controller comprises a five-layered model with two inputs, i.e., kilowatt (KW) and kilovolt-ampere reactive (KVAR), and one output (PF). A 25-rule set performance of the developed program was achieved, with significant improvements observed after 50 epochs, culminating in an error rate of 0.050691 recorded post the second epoch. The results demonstrated that the developed controller exhibits higher sensitivity and faster response time compared to existing PF controllers. Consequently, the implementation of the proposed controller is recommended for optimizing the switching of capacitor banks, thereby enhancing PF in manufacturing industries characterized by variable load conditions.
Authors and Affiliations
Olamide Omolara Olusanya, Gbenga Mufutau Adebajo, Ibrahim Giwa, Kennedy Okokpujie, Samuel Adebayo Daramola, Adenugba Vincent Akingunsoye5
Keywords
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- EP ID EP752424
- DOI https://doi.org/10.56578/jisc030203
- Views 53
- Downloads 1
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