AI for Grid Optimization & Smart Energy
A two-day program on AI applications for grid optimization, load forecasting, renewable integration, and smart grid operations.
Course Overview
The energy grid is becoming smarter and more dynamic, with AI playing a central role in balancing supply and demand. This program covers AI applications for grid optimization, including load forecasting, renewable generation prediction, grid stability monitoring, and demand response optimization. Participants learn how AI is enabling a more resilient and efficient grid.
Target Audience
Grid engineers, power systems engineers, energy analysts, utility engineers
Prerequisites
EN-101 or equivalent. Power systems or grid operations background.
Learning Objectives
- Apply ML to load and generation forecasting
- Use AI for grid stability monitoring and anomaly detection
- Optimize demand response with AI
- Design smart grid AI architectures
- Evaluate grid AI tools and platforms
Key Modules
- AI for Grid Operations Overview
- Load Forecasting with ML
- Renewable Generation Forecasting
- Grid Stability and Anomaly Detection
- Demand Response Optimization
- Smart Grid AI Architecture
- Case Studies in Grid AI
Learning Outcomes
- Practical understanding of AI in grid operations
- Skills in load and generation forecasting with ML
- A framework for grid anomaly detection
- A smart grid AI architecture design
Your Instructor
Dr. Hussein Mustapha
AITECH Academy Faculty
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