Adaptive control strategies improve system stability and efficiency in smart microgrids with renewable energy sources, suggesting a novel combined approach using machine learning.
Abstract The growing use of renewable energy sources (RES) in small-scale power systems brings about major obstacles in keeping the power grid steady and dependable because RES naturally fluctuates and is not always available. This study suggests a new approach to control that uses sophisticated machine learning techniques and instant data analysis to better manage RES in intelligent power systems. The goal of this approach is to boost the stability of the system, cut down on running expenses, and increase the efficiency of energy use. This study is different from previous research because it introduces a mixed control system that combines Model Predictive Control (MPC) with Reinforcement Learning (RL) to adjust control settings in response to current conditions and past data trends.
No takes yet. Share an insight, caveat, or question.
patra et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: