Transforming Energy Sector with Intelligent Solutions
Abstract
This paper explores the transformation of the energy sector through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional energy production, distribution, and consumption practices, including renewable energy integration, grid optimization, and energy efficiency management. The study highlights the application of AI techniques such as predictive modeling, smart metering, and demand response in enhancing reliability, sustainability, and affordability in energy systems. Additionally, it discusses the integration of AI with smart grids, energy storage systems, and electric vehicle infrastructure to enable decentralized energy generation, grid resilience, and electrified transportation. The paper also addresses challenges such as regulatory barriers, cybersecurity risks, and societal acceptance in the adoption of AI-driven engineering solutions in the energy sector. It emphasizes the importance of stakeholder engagement, policy support, and technology innovation in leveraging AI's potential to accelerate the transition to a clean, resilient, and equitable energy future.
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References
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