AI-Optimized Smart Grids for Renewable Integration & Grid Stability
From renewables to reliability—driven by AI
About This Course
This 3-day online workshop focuses on using AI and Machine Learning for smart grids, renewable integration, and grid stability. Through expert sessions and hands-on labs in Google Colab and Jupyter Notebook, participants will learn practical methods for forecasting, optimization, predictive maintenance, microgrids, and grid cybersecurity, preparing them to work on resilient, renewable-ready power systems.
Aim
To train participants to apply AI and Machine Learning for renewable energy integration, grid stability, and smart grid optimization, through focused concepts and hands-on exercises.
Workshop Objectives
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Introduce the basics of smart grids, grid modernization, and renewable integration.
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Show how AI/ML support forecasting, grid optimization, and real-time operation.
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Build skills in predictive maintenance and fault/failure detection for smart grids.
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Explain the role of energy storage, microgrids, and autonomous control in grid stability.
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Enable participants to implement AI-based smart grid simulations using Google Colab/Jupyter Notebook.
Workshop Structure
Day 1 – AI-Optimized Smart Grids & Renewable Energy Integration
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Introduction to Smart Grids & Grid Modernization
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AI and Machine Learning for Grid Optimization
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Challenges in Renewable Energy Integration
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Real-time Grid Monitoring & Scheduling Using AI
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Hands-on (Google Colab): Renewable Energy Forecasting using AI
Day 2 – Advanced AI for Grid Stability & Optimization
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Predictive Maintenance & Fault Detection in Smart Grids
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Machine Learning for Energy Storage Optimization
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Microgrids & Autonomous Grid Operations
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Hands-on (Google Colab): Fault Detection and Predictive Maintenance with ML
Day 3 – Future Directions in AI-Optimized Smart Grids
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AI in Grid Cybersecurity & Resilience
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Regulatory & Policy Considerations for AI in Smart Grids
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Future Technologies: Quantum Computing, Blockchain, and IoT for Smart Grids
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Hands-on (Jupyter Notebook): Microgrid Simulation and AI-Based Optimization
Who Should Enrol?
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UG/PG students in Electrical, Electronics, Energy, CS, AI/ML and related fields
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Researchers, PhD scholars, and faculty working on smart grids, renewables, or AI in energy
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Industry professionals/engineers from utilities, DISCOMs, transmission, renewable and energy startups
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Data scientists / AI-ML practitioners interested in power systems and energy analytics
Important Dates
Registration Ends
12/07/2025
IST 4:30 PM
Workshop Dates
12/07/2025 – 12/09/2025
IST 5: 30PM
Workshop Outcomes
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Understand smart grids, renewable integration, and grid stability basics.
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Use AI/ML for forecasting, grid optimization, and scheduling.
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Design simple predictive maintenance and fault detection workflows.
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Gain insight into energy storage, microgrids, and autonomous operations.
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Work with hands-on AI simulations in Google Colab/Jupyter Notebook for smart grid applications.
Fee Structure
Student
₹5000 | $100
Ph.D. Scholar / Researcher
₹5000 | $100
Academician / Faculty
₹5000 | $100
Industry Professional
₹5000 | $100
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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