Smart Energy Networks and Artificial Intelligence for Future Power Systems

Karen H. Seal

Smart Energy Networks and Artificial Intelligence for Future Power Systems

Author(s)	Karen H. Seal
Country	United States
Abstract	The rapid growth of renewable energy, distributed generation, electric vehicles, energy storage, and digital infrastructure is transforming conventional electricity networks into increasingly intelligent and decentralised power systems. Smart energy networks combine advanced communication technologies, sensors, automation, distributed energy resources, and data analytics to improve the reliability, flexibility, and efficiency of electricity supply. Artificial Intelligence (AI) further strengthens these capabilities by enabling demand forecasting, renewable-energy prediction, fault detection, predictive maintenance, energy optimisation, and autonomous decision support. This study examines the role of smart energy networks and AI in the development of future power systems. A qualitative and conceptual research methodology based on secondary literature is adopted to analyse smart-grid architecture, AI applications, renewable-energy integration, demand-side management, energy storage, electric vehicles, cybersecurity, and system resilience. The analysis indicates that AI-enabled smart networks can improve forecasting accuracy, optimise energy flows, support real-time decision-making, and facilitate the integration of intermittent renewable resources. However, challenges related to data quality, cybersecurity, interoperability, computational complexity, infrastructure investment, regulatory frameworks, and algorithmic reliability remain significant. The study proposes an integrated AI-enabled smart-energy framework combining sensing infrastructure, edge and cloud computing, machine learning, distributed energy resources, intelligent control, and human oversight. The study concludes that future power systems will increasingly depend on intelligent, flexible, decentralised, and resilient energy networks capable of responding dynamically to changing supply and demand conditions.
Keywords	Smart Energy Networks, Artificial Intelligence, Smart Grid, Future Power Systems, Renewable Energy, Energy Storage, Demand Response, Machine Learning, Distributed Energy Resources, Energy Management.
Field	Engineering
Published In	Volume 4, Issue 5, September-October 2022
Published On	2022-09-13

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American Journal of Advanced Multidisciplinary Research and Innovation

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Smart Energy Networks and Artificial Intelligence for Future Power Systems

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