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Transforming Energy Systems with Intelligent Solutions
Abstract
This paper explores the transformation of energy systems through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is reshaping various aspects of energy production, distribution, and consumption. The study highlights the application of AI techniques such as predictive maintenance, demand forecasting, and energy optimization in improving efficiency, reliability, and sustainability in energy systems. Additionally, it discusses the integration of AI with renewable energy sources, smart grids, and energy storage systems to enable decentralized generation, grid balancing, and demand response. The paper also addresses challenges such as grid cybersecurity, regulatory frameworks, and energy equity in the adoption of AI-driven engineering solutions in energy systems. It emphasizes the importance of collaboration, innovation ecosystems, and stakeholder engagement in harnessing AI's potential to accelerate the transition to a more resilient, low-carbon, and inclusive energy future.
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