Optimizing Renewable Energy Integration: A Novel PSO-ADP Control Scheme for Enhanced Energy Storage System Performance

Renewable energy sources have become more integrated into power grids, and as they do so the effective operation of Energy Storage Systems (ESSs) becomes a vital factor to address intermittency and ensure grid stability. Our research offers an innovative control system for ESS that integrates Particle Swarm Optimization and Adaptive Dynamic Programming techniques for optimal operation. PSO leverages its strengths to optimize and initialize control parameters in an ADP framework for improved control performance and efficiency. This research stands out for its innovative algorithms and evaluation parameters explicitly designed to meet the unique control needs of ESS systems. An adaptive dynamic programming (ADP) framework fine-tunes control parameters utilizing PSO for pretraining purposes to allow rapid adaptation to changing grid requirements and operational conditions. Novel evaluation parameters have been employed to assess control schemes, considering energy efficiency, response-time impact analysis, lifetime evaluation, and life cycle evaluation for an in-depth assessment of their effectiveness. PSO-based ADP Energy Storage Control Scheme offers an innovative, effective, and practical method for integrating ESS technology in modern power grids. This research advances energy-storage control strategies by creating robust algorithms and comprehensive evaluation methods.