AI-Driven Energy Management System for Industrial and Commercial Facilities to Enhance Energy Optimization

This Paper presents a comprehensive review of the literature on An AI-powered system that can help commercial facilities cut down on energy consumption. With increasing pressure to enhance the consumption of energy efficiency and reduce costs, businesses are turning to advanced technologies such as artificial intelligence (AI) to optimize energy usage. The abstract begins by highlighting the importance of energy management in industrial and commercial sectors, emphasizing its impact on cost efficiency, environmental sustainability, and operational performance. It then provides an overview of key studies and findings in the field, including research on AI techniques inclusive of optimization algorithms, machine learning, and deep learning, applied to energy management.. The abstract discusses the potential benefits of AI-powered energy management systems, including cost savings, environmental impact reduction, and operational efficiency improvement. It also addresses challenges and future directions for research and development in this area. Overall, the abstract emphasizes the significance of AI-powered energy management systems in achieving sustainable energy solutions for industrial and commercial facilities. At its core, an AI-powered energy management system leverages advanced algorithms to examine vast amount of data collected from the facility’s operational systems, meters, and sensor. Through predictive analytics and real-time monitoring, the system can forecast energy demand, identify inefficiencies, and dynamically adjust energy usage to optimize performance. The ability of these systems to adjust and learn from past data is a major benefit as it enables ongoing optimization and development over time. By integrating with existing infrastructure and control systems, AI-powered energy management systems provide actionable insights and recommendations to facility managers, enabling informed decision-making and proactive energy management strategies.