AI-Based Control Strategy And Systematic Review For Industrial Peak Shaving Using Hybrid Solar PV And Battery Energy Storage Systems (BESS) In Uzbekistan
Abstract
Rapid industrialization and evolving energy policies in Uzbekistan require sustainable solutions to manage electricity demand, especially during peak periods. This study explores the potential of hybrid solar photovoltaic (PV) and battery energy storage systems (BESS) to implement effective peak shaving in large industrial plants. Through detailed statistical analysis of minute-by-minute load profiles, this study identifies key demand characteristics and develops an AI-based control strategy to optimize BESS operations. The proposed system integrates external factors such as solar radiation, temperature, and dynamic tariffs with internal operational parameters to enable intelligent scheduling of battery charging and discharging. The results demonstrate significant improvements in load management, including a 400 kWh reduction in daily peak-period consumption and a 44% decrease in peak-hour electricity payments, compared with the base case. Furthermore, this study contributes to a replicable methodology for optimizing industrial energy in developing countries transitioning to decarbonization and renewable energy integration.