Coati Optimization based ANFIS MPPT for PV-Battery Integrated System to Improve Power Quality
1Department of Electronics & Communication, Shivalik College of Engineering, India
2Electrical Cluster, School of Advanced Engineering, University of Petroleum & Energy Studies, India
3Miyan Research Institute, International University of Business, Agriculture and Technology, Bangladesh
*Author to whom correspondence should be addressed:
E-mail: rpachauri@ddn.upes.ac.in (RKP)
E-mail: rpachauri@ddn.upes.ac.in (RKP)
Received: January 26, 2025 | Revised: September 18, 2025 | Accepted: October 28, 2025 | Published: March 2026
Abstract
This research presents an innovative method to improve photovoltaic (PV) systems integrated with batteries, emphasizing efficient power extraction and enhanced power quality. It combines the Coati optimization algorithm, inspired by coati foraging behavior, with Adaptive Neuro Fuzzy Inference Scheme (ANFIS) for precise maximum power point tracking (MPPT) under fluctuating solar conditions. The Coati algorithm ensures optimal energy harvesting, while battery storage mitigates solar energy intermittency. The system also addresses power quality challenges, reducing harmonic distortion and improving voltage stability. Simulations demonstrate its superiority over traditional MPPT methods, promoting efficient, reliable, and sustainable PV-battery systems for modern power grids.
Keywords
Coati algorithm; Maximum Power point; Power quality; PV system
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