Aim
To provide PhD scholars and academicians with advanced skills in applying AI for optimizing energy sector operations, including renewable energy forecasting, smart grid management, and energy storage. This course equips learners with the knowledge to use AI for improving energy efficiency, optimizing storage, and making data-driven energy market predictions.
Workshop Objectives
- Understand the role of AI in optimizing the energy sector.
- Use AI for forecasting and managing renewable energy sources.
- Apply AI for smart grid management and fault detection.
- Implement AI solutions for optimizing energy storage systems.
- Analyze energy market trends using AI-based models.
Workshop Structure
- Introduction to AI in the Energy Sector
- Importance and benefits of AI in energy
- Key applications and future trends
- AI in Renewable Energy Forecasting
- AI for solar, wind, hydropower forecasting
- Weather prediction for renewable energy
- AI for Energy Distribution through Smart Grids
- AI in smart grids, load balancing, and fault detection
- AI for Energy Storage Optimization
- AI-driven battery management and grid-scale storage
- Predictive maintenance for energy storage
- AI in Energy Market Trading and Policy Modeling
- AI for real-time pricing, demand prediction, and carbon trading
- AI for Optimizing Energy Efficiency in Industrial and Commercial Sectors
- AI-driven energy management systems and smart building technologies
Participant’s Eligibility
AI researchers, data scientists, energy professionals, sustainability experts, and academicians in energy-related fields.
Workshop Outcomes
- Build AI models for renewable energy forecasting and grid management.
- Optimize energy storage and distribution systems using AI.
- Predict energy demand and market trends with AI-based tools.
- Enhance energy efficiency in industrial and commercial settings.
Reviews
There are no reviews yet.