IIARD International Institute of Academic Research and Development

International Journal of Engineering and Modern Technology (IJEMT )

E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 11 NO. 3 2025
DOI: 10.56201/ijemt.vol.11.no3. 2025.pg81.102

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Artificial intelligence-Driven Renewable Energy Solutions for Rural Electrification in Africa

Sodiq Abiodun Muraina, Bamidele Paul Akinbamiwa, Dauda Sulaimon Abiola, Sanni Isikilu Charles

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Abstract

This research examines the role of Artificial Intelligence (AI) in advancing renewable energy solutions for rural electrification in Africa, where energy access remains a critical challenge. The study adopts a qualitative research approach, utilizing secondary data from academic journals, industry reports, and case studies. Comparative analysis is applied to assess AI-driven electrification projects and their effectiveness in rural settings. The paper explores AI technologies such as machine learning, predictive analytics, and smart grid optimization in renewable energy applications like energy demand forecasting, smart grid management, and predictive maintenance. Case studies from Nigeria, Kenya, and South Africa highlight successful implementations of AI in solar mini-grids, wind energy projects, and battery storage solutions. In Nigeria, AI-powered mini-grids optimize energy generation and storage, ensuring consistent power supply in off-grid areas. In Kenya, AI supports wind forecasting and grid management, increasing the efficiency of the Lake Turkana Wind Power Project. In South Africa, AI-driven battery storage systems enhance the reliability of energy distribution by predicting optimal charging and discharging cycles. Despite these advancements, the study identifies challenges such as high initial costs, technical expertise gaps, and regulatory barriers, which hinder scalability. The paper offers recommendations for addressing these challenges, including investment in AI research and development, capacity building, public-private partnerships, and the development of regulatory frameworks. The findings suggest that with targeted investments, policy support, and technological advancements, AI-driven renewable energy solutions can drive rural electrification, contributing to socio-economic development and sustainable energy access in Africa's underserved communities.

keywords:

Artificial intelligence, Renewable energy, Rural electrification, Smart grids, Energy

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