Self Paced

Artificial Intelligence for Smart Energy Grids

“Empowering Smart Energy Grids with Artificial Intelligence for a Sustainable Future”

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Early access to e-LMS included

  • Mode: Online/ e-LMS
  • Type: Self Paced
  • Level: Moderate
  • Duration: 4 Weeks

About This Course

Transform your career with the future of energy technology!
This one-month intensive online certification program empowers you to master the use of Artificial Intelligence (AI) in smart energy grids — the next frontier in sustainable energy management.
Participants will explore AI applications for real-time energy monitoring, machine learning algorithms for demand forecasting, and techniques to integrate renewable sources like solar and wind into intelligent grids. The course highlights how AI optimizes power distribution, reduces energy wastage, and enhances the resilience of smart grids.
Designed for energy sector professionals, engineers, and AI enthusiasts, this program offers actionable insights into building a sustainable, efficient, and smart energy future.

Aim

To provide participants with industry-ready skills in applying AI and machine learning for optimizing smart energy grids, energy forecasting, load management, and renewable energy integration, contributing to clean energy innovations and climate goals.

Program Objectives

  1. Understand AI fundamentals and their transformative role in energy management systems.
  2. Learn real-time energy monitoring, predictive analytics, and load forecasting techniques.
  3. Master AI-driven solutions for solar and wind energy integration.
  4. Analyze real-world case studies of AI-enhanced smart grid deployments.
  5. Build skills to address energy variability, storage challenges, and grid resilience.

Program Structure

Week 1: AI in Energy Systems

  • AI in Smart Grids: Fundamentals and Key Concepts
  • Energy Analytics and Efficiency Monitoring
  • Automation and Predictive Maintenance using AI

Week 2: Machine Learning for Demand Forecasting and Load Optimization

  • Time-Series Forecasting of Energy Consumption
  • Load Balancing and Peak Demand Reduction Techniques
  • Energy Data Collection, Processing, and Visualization

Week 3: Renewable Energy Integration with AI

  • Smart Integration of Solar and Wind Power
  • AI for Energy Storage Optimization and Load Management
  • Addressing Challenges: Variability, Reliability, and Scaling Renewable Grids

Week 4: Global Case Studies and Emerging Trends

  • Case Studies: Smart Grids in USA, Europe, and Asia
  • Sustainable Energy Systems Powered by AI
  • Innovations in Smart Grid Cybersecurity and Energy Markets

Who Should Enrol?

  • Students or graduates in Electrical Engineering, Environmental Science, Computer Science, or related fields.
  • Professionals in energy sector, smart grid companies, renewable energy firms, and utility services.
  • Researchers, consultants, and tech enthusiasts interested in AI and green energy solutions.

Program Outcomes

  • Expertise in AI-powered smart grid optimization
  • Skills in machine learning for energy demand forecasting
  • Practical knowledge of solar and wind energy integration with AI
  • Ability to build and interpret smart energy models
  • Preparation for leadership roles in sustainable energy systems and renewable energy industries

Fee Structure

Standard: ₹8,998 | $198

Discounted: ₹4499 | $99

We accept 20+ global currencies. View list →

What You’ll Gain

  • Full access to e-LMS
  • Real-world dry lab projects
  • 1:1 project guidance
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate & e-Marksheet

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