Power Quality Enhancement of Solar Based Microgrids Using ML and AI

Solar-powered micro grids are gaining popularity as a cost-effective and environmentally friendly way to provide localized electricity. Microgrids struggle with solar power's fluctuation and intermittent nature. Sun-based microgrids' power quality is improved via machine learning (ML) and synthetic intelligence (AI). The recommended solution employs modern ML algorithms to predict solar power generation and micro grid energy output variations. ML models can accurately forecast changes in solar irradiance, temperature, and other crucial aspects by evaluating ancient and real-time data, enabling proactive micro grid power float management. The proposed ML and AI-based technology offers superior power best, proactive power control, and better predictions than standard management methods. Simulation and experimental results show that the technique reduces load interruptions, improves balance, and reduces solar energy oscillations on the micro grid. Its capabilities are excellent. to provide reliable and excellent power supply, large-scale renewable energy adoption, and sustainable power ecosystems with ML and AI in solar-based micrgarids.