Revolutionizing Energy Management and Sustainability
Abstract
This paper explores the revolutionary impact of AI-driven engineering on energy management and sustainability. Through case studies and research insights, it investigates how artificial intelligence is transforming traditional energy management practices, including demand forecasting, optimization, and renewable energy integration. The study highlights the application of AI techniques such as machine learning, optimization algorithms, and predictive analytics in enhancing the efficiency, reliability, and environmental sustainability of energy systems. Additionally, it discusses the integration of AI with smart grids, energy storage systems, and distributed energy resources to enable real-time monitoring, control, and optimization of energy networks. The paper also addresses challenges such as regulatory barriers, grid integration, and cybersecurity in the deployment of AI-driven engineering solutions in energy management. It emphasizes the importance of collaboration among energy stakeholders, technology providers, and policymakers to harness AI's potential in advancing energy transition and achieving sustainable development goals.
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References
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