Syllabus
Evolution of Renewable Energy Systems. Role of AI in Energy Forecasting, Optimization, and Control. Types of AI Techniques: Machine Learning, Deep Learning, Reinforcement Learning. Overview of Solar, Wind, Hydro, and Hybrid Renewable Energy Systems. Challenges in Integrating AI with Renewable Energy.
Time Series Forecasting Models: ARIMA, SARIMA, LSTM, GRU. Solar Power Forecasting Using AI. Wind Power Forecasting and Uncertainty Handling. Demand Forecasting and Load Management. Machine learning techniques in Wind/Solar Forecasting, Integration ML strategies techniques – Standalone Wind/Solar, Microgrid/EV for small/medium and industrial consumers, Reinforcement Learning for Energy Storage and Grid Integration.
AI in Smart Grids: Monitoring, Protection, and Control. Digital Twins for Renewable Energy Systems. Optimization Algorithms. AI-Based Fault Detection and Predictive Maintenance. Edge Computing and IoT for Intelligent Energy Management. Ethical and Environmental Considerations in AI Deployment.