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Mentor Based

AI for Clean Energy, Utilities & Smart Grid Systems

Energy engineers, AI researchers, and data scientists focused on energy management and utilities optimization.

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Early access to the e-LMS platform is included

  • Mode: Online/ e-LMS
  • Type: Mentor Based
  • Level: Moderate
  • Duration: 3 Weeks

About This Course

This program explores how AI is transforming the energy and utilities sector by optimizing operations, enhancing renewable energy forecasting, and supporting smart grid management. Participants will learn to implement AI for predictive maintenance, energy trading, and efficient use of renewable resources.

Aim

To provide advanced knowledge on the integration of AI in the energy sector, covering renewable energy management, grid optimization, and predictive maintenance. This course enables participants to use AI to improve efficiency, reduce costs, and enhance sustainability in energy production, distribution, and consumption.

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.

Program Structure

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

Who Should Enrol?

Energy engineers, AI researchers, and data scientists focused on energy management and utilities optimization.

Program Outcomes

  • Ability to implement AI models for optimizing renewable energy management and smart grids.
  • Proficiency in predictive maintenance and fault detection using AI.
  • Skills to optimize energy consumption and participate in AI-driven energy trading markets.
  • Hands-on experience with AI applications for sustainable and efficient energy management.

Fee Structure

Discounted: ₹8499 | $112

We accept 20+ global currencies. View list →

What You’ll Gain

  • Full access to e-LMS
  • Real-world dry lab projects
  • One-on-one project guidance
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate & e-Marksheet

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