Architectural frameworks for AI in renewable energy systems

Artificial intelligence (AI) is revolutionizing energy management by merging it with renewable energy systems, enhancing efficiency, sustainability, and real-time decision-making. Traditional cloud-based energy systems face multiple challenges, such as limited real-time control, security vulnerabilities, dependence on the continuous infrastructure of the network, and high latency. This chapter explores architectural constructs by using AI with edge computing, blockchain, and federated learning aimed at optimizing distributed renewable energy management systems. These systems allow for real-time forecasting of energy use, enhanced stability of grids, and decreased reliance on central infrastructure by deploying edge devices. This chapter also explores the AI-based microgrid optimization, drone-supported wind energy predictions, and blockchain-supported secure transactions in smart grids. It also discusses prevailing concerns over scalability, security, and interoperability. It offers insights into the future, such as the role of 5G-powered edge networks and quantum computing in energy optimization. AI-driven architectural frameworks would help the renewable energy industry reach higher resilience, efficiency, and sustainability levels, opening the path for an intelligent and flexible energy environment.