Fundamentals of Green Energy and AI

The integration of Green Energy Systems (GES) and Artificial Intelligence (AI) has gained increased pace as part of the global shift to sustainable and intelligent energy infrastructures, in order to combat climate change.The global transition from non-sustainable and non-intelligent energy infrastructures to sustainable and intelligent energy infrastructures has accelerated the use of Artificial Intelligence (AI) together with Green Energy Systems (GES) to face climate change.The present chapter proposes the fundamental principles, developments and applications of renewable energy technologies like solar, wind, hydro power, biomass, and geo thermal sources in smart power grid in modern scenario.It underscores the increasing environmental need for clean energy solutions, with the challenges of climate change, carbon emission reduction, energy security and sustainable economic development.In more depth, the chapter discusses the operational problems of intermittency and grid instability of renewable sources, energy models for energy forecasting and the limitations of energy storage.To address these hurdles, the solutions implemented involve advanced AI techniques such as Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL) for renewable energy forecasting, predictive maintenance, smart grid optimization, autonomous energy management and carbon aware operations.The chapter highlights the need for intelligent energy management systems, smart grids, sustainable computing, and AI-based carbon monitoring systems to create resilient, efficient, and environmentally friendly future energy systems.This chapter provides a good illustration of the combination of renewable energy technologies and intelligent computational intelligence, thus setting the groundwork for cleaner, smarter, decentralized and sustainable power systems that can meet future global needs for energy and deliver the objectives of a zero-emission path to a zero-carbon world.