Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network ...

Summary

The article discusses optimizing a Hybrid Microgrid (HMG) system using machine learning. The HMG integrates photovoltaic (PV), wind turbines (WT), and battery energy storage (BES), while the machine learning model (MLP-ANN) predicts load and weather conditions to improve energy losses, voltage deviations, and power costs. This aligns with the key concept of "Machine learning" and involves tags like "Electric power," "AC power," and "Evidence lower bound," indicating the role of information theory and channel capacity in optimizing power systems.