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Transforming Energy Systems for Sustainability
Abstract
This paper explores the transformative impact of AI-driven engineering on energy systems for sustainability. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional energy production, distribution, and consumption practices. The study highlights the application of AI techniques such as predictive maintenance, energy forecasting, and demand-side management in optimizing energy efficiency, reducing costs, and integrating renewable energy sources into the grid. Additionally, it discusses the integration of AI with smart grids, energy storage systems, and decentralized energy platforms to enable real-time monitoring, grid stability, and energy trading in a decentralized manner. The paper also addresses challenges such as cybersecurity, data privacy, and regulatory compliance in the deployment of AI-driven engineering solutions in energy systems. It emphasizes the importance of collaboration among utilities, policymakers, and technology providers in harnessing AI's potential to accelerate the transition to a more sustainable energy future.
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References
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