Abstract
As the demand for energy continues to rise, there is an increasing need for more efficient and intelligent systems to manage energy consumption. AI-powered predictive analytics is emerging as a powerful tool in the development of smart energy management systems. By leveraging machine learning algorithms and big data, these systems can forecast energy usage patterns, optimize energy distribution, and improve overall efficiency. This article explores the role of AI-powered predictive analytics in energy management systems, highlighting its applications in load forecasting, demand response, and renewable energy integration. The article also examines the challenges and future opportunities in the integration of AI technologies in energy management, with a focus on sustainability and cost-effectiveness.
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