AI-Driven Robotics in Solar and Wind Energy Maintenance: A Path toward Sustainability

Abstract

According to this research, AI-driven robots may improve operational efficiency, save costs, and promote sustainability objectives in solar and wind energy system maintenance. The paper examines AI and robotics technology, analyzes their applications in renewable energy maintenance, and identifies difficulties and prospects for maximizing their utilization. Using secondary data, the research synthesizes significant findings and trends from peer-reviewed publications, case studies, and industry reports. Primary results show that AI-driven robots may transform maintenance processes by boosting inspection accuracy, safety, and downtime while meeting sustainability objectives via resource efficiency and waste reduction. High initial costs, technological constraints in severe settings, and regulatory complexity still prevent broad implementation. Policy implications involve focused research and development, consistent rules, and financial incentives to make these technologies more accessible to smaller operators to solve these difficulties. Governments, business leaders, and academics must work together to overcome these challenges and maximize AI-driven robots in renewable energy. This research stresses robots' crucial role in expediting sustainable energy infrastructure transformation.