Program Objectives:

• Understand how AI is transforming the energy and utilities sector.
• Implement AI models for renewable energy management and predictive maintenance.
• Explore AI-driven smart grid solutions.
• Learn to optimize energy consumption using AI tools.
• Gain hands-on experience with AI applications in energy trading and fault detection.

What you will learn?

Module 1: Introduction to AI in Energy and Utilities

• Overview of AI Applications in the Energy Sector

• Challenges Facing Modern Energy and Utility Systems

• Key AI Technologies: Machine Learning, IoT, and Big Data

• Benefits of AI in Energy Efficiency and Resource Management

Module 2: AI for Energy Demand Forecasting

• Predictive Analytics for Energy Demand

• Time Series Forecasting with Machine Learning

• AI for Load Balancing and Peak Load Management

• Case Studies in Energy Demand Forecasting

Module 3: AI for Smart Grids

• Concept of Smart Grids and Their Benefits

• AI for Real-Time Monitoring and Control

• Grid Optimization with AI Algorithms

• Applications of AI in Decentralized Energy Systems

Module 4: AI in Renewable Energy Systems

• AI for Solar and Wind Energy Forecasting

• Optimizing Renewable Energy Integration with AI

• AI for Energy Storage Management

• Real-World Examples in Renewable Energy Optimization

Module 5: AI for Predictive Maintenance in Energy Infrastructure

• Condition Monitoring with AI

• Predictive Maintenance for Power Plants and Grids

• Reducing Downtime and Costs with AI-Based Monitoring

• Case Studies in Maintenance Optimization

Module 6: AI for Energy Efficiency and Optimization

• AI for Reducing Energy Waste in Industrial Systems

• AI-Driven Energy Auditing and Smart Metering

• Optimizing Energy Consumption in Buildings with AI

• Real-World Applications in Smart Homes and Cities

Module 7: Ethical and Regulatory Considerations in AI for Energy

• Data Privacy and Security in Energy AI

• Ethical Considerations in Energy Automation

• Regulatory Frameworks for AI in Utilities

• Environmental Impact of AI-Powered Energy Solutions

🔥 Module 8: AI for Energy Trading and Carbon Markets

• AI in Dynamic Pricing and Market Forecasting

• Modeling Volatility and Risk in Energy Markets

• Demand-Supply Balancing with ML

• Emissions Trading Systems and Climate Finance Modeling

🧠 Module 9: Digital Twins for Power Systems

• Concept and Architecture of Digital Twins

• AI for Real-Time Simulation of Grid Operations

• Predictive Control of Power Infrastructure

• Integration of IoT Sensors and Big Data for System Replication

🤖 Module 10: Generative AI & LLMs in Energy Operations

• Leveraging Generative AI for Operational Efficiency

• Auto-generation of Maintenance SOPs and Technical Reports

• Energy Policy Drafting and Scenario Simulation with LLMs

• Prompts and Workflows for Energy Sector Professionals

🔗 Module 11: AI & Blockchain for Decentralized Energy

• Introduction to Blockchain in Energy

• Smart Contracts for Peer-to-Peer Energy Trading

• Blockchain for Carbon Traceability and Grid Transactions

• Use Cases: Community Energy Markets and Tokenization