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Optimizing Energy Systems with Intelligent Solutions
Abstract
This paper explores the optimization of energy systems through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is optimizing various aspects of energy production, distribution, and consumption. The study highlights the application of AI techniques such as predictive maintenance, demand forecasting, and energy trading in improving efficiency, reliability, and sustainability in energy systems. Additionally, it discusses the integration of AI with smart grids, energy storage, and renewable energy sources to enable decentralized energy management, grid stability, and carbon footprint reduction. The paper also addresses challenges such as grid cybersecurity, regulatory compliance, and energy transition in the adoption of AI-driven engineering solutions in the energy sector. It emphasizes the importance of stakeholder collaboration, policy support, and technology innovation in leveraging AI's potential to accelerate the transition to a clean and resilient energy future.
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