Exploring the Role of Artificial Intelligence in Optimizing Renewable Energy Distribution Networks

Abstract

Opportunities and problems arise for energy distribution networks when renewable energy sources like solar, wind, and hydropower are increasingly used. Although renewable and ecologically beneficial, these energy sources are frequently intermittent and distributed, necessitating creative approaches to integrate them into the grid efficiently. A new weapon in the fight against these problems is artificial intelligence (AI), which provides cutting-edge strategies for improving distribution networks that carry renewable energy. Machine learning, data analytics, and predictive modelling are all examples of AI technologies that can improve the administration of decentralised energy systems by allowing for real-time monitoring, forecasting, and decision-making. how artificial intelligence (AI) may optimise renewable energy distribution by boosting demand response, decreasing energy loss, increasing grid stability, and making better use of distributed energy resources (DERs). One step towards a smarter, more sustainable power grid could be the incorporation of artificial intelligence (AI) into renewable energy systems, which could make them more adaptable, dependable, and economical. highlights the technical, economic, and policy aspects that need to be addressed for a successful application of AI with existing grid infrastructure through case studies and discussions. The results highlight the importance of AI in improving the efficiency, resilience, and capacity of renewable energy distribution networks to meet the increasing demand for clean energy.