Advancements in Optimizing Smart Energy Systems Through Smart Grid Integration, Machine Learning, and IoT
Sampath Boopathi
Abstract
The convergence of smart energy, smart grid, machine learning, and the internet of things (IoT) is revolutionizing energy management. This chapter explores the evolution of energy management, challenges, and opportunities in smart energy systems. The integration of IoT devices with smart grid infrastructure enables real-time data collection, informed decision-making, and enhanced energy optimization. Case studies demonstrate practical implementation in demand response management, microgrid operation, and electric vehicle grid integration. Results show significant energy consumption reduction, improved grid stability, and enhanced efficiency. Challenges include data privacy, interoperability, and regulatory adaptation. Future directions include edge computing, AI expansion, and decentralized energy systems. The transformative potential of smart energy systems is highlighted, emphasizing sustainable energy consumption and grid stability.