To reduce energy consumption and cost management, energy performance
goals should be optimised with ease. Artificial Intelligence (AI) and the Internet of
Things (IoT) are crucial for developing predictive management methods and
maintaining renewable energy infrastructure. AI accelerates energy transition and
carbon reduction, which has become a necessity to address the global confront. As
there is a paradigm shift in energy from traditional to cleaner and renewable
alternatives, non-traditional sources like wind, solar, and hydro power become more
obvious. For sustainability, the digital revolution has facilitated better management of
renewable energy sources, enabling more effective consumption and distribution. The
application of renewable energy sources is also vital for the newly emerging concept of
Industry 5.0. AI can easily analyse the energy requirement pattern during the
production process and can switch to available renewable energy sources when the
demand is relatively lower. The present chapter emphasises how AI is commissioned to
unlock extraordinary efficiency, grid stability, and cost optimisation. Nowadays, AI
bridges the gap between the unpredictable nature of renewable sources and the
consistent energy demand and reshapes the energy scenario by paving the path for a
greener, brighter tomorrow. AI applications in renewable energy encompass prognostic
maintenance, energy optimisation, and smart grid management. The present chapter
also focuses on in what way AI acts as a transformative potential for renewable energy
generation. This chapter reviews existing techniques and the incorporation of AI in
energy management systems to meet the flexibility needs of modern energy supply
systems.
Keywords: Artificial intelligence, Blockchain, Climate change, Deep learning, Energy efficiency, Energy Optimisation, Energy storage systems, Green energy, Grid stability, Intelligent processing, IoT.
