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AI-Driven Microgrid Solutions for Enhancing Energy Access and Reliability in Rural and Remote Areas: A Comprehensive Review Ahmed, Faisal; Uzzaman, Asif; Adam, Md Ibrahim; Islam, Monirul; Rahman, Md Moklesur; Islam, Asm Mohaimenul
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.183

Abstract

As localized energy systems, microgrids provide a viable way to solve problems with energy dependability and access in rural and isolated locations. These regions often have inadequate and unstable grid infrastructure, which restricts their access to energy. Artificial Intelligence (AI) improves the overall performance, flexibility, and efficiency of microgrid systems. AI ensures a steady and dependable power supply by enabling predictive maintenance, optimal load forecasting, energy storage management, and renewable energy resource optimization. AI may help microgrids anticipate system faults, better control energy consumption, and prolong the life of vital parts. Additionally, AI ensures the sustainability of microgrids in resource-constrained places by optimizing the usage of renewable energy sources like solar and wind. Successful case studies from places like the US, India, and Africa have shown the promise of AI-enhanced microgrids in raising the standard of living for marginalized areas, despite obstacles like data infrastructure and upfront installation costs. Microgrids have a bright future thanks to developments in artificial intelligence (AI), which might increase electricity availability and promote economic growth in rural and isolated regions of the world.