AI in Energy & Utilities
Overview
Energy and utility companies face rising demand, ageing networks and the integration of renewable sources. This course reviews how AI supports load forecasting, grid and network management, asset maintenance, loss reduction and customer services, and what utilities need in place to use it effectively.
Who should attend
Engineers and managers in electricity, water and gas utilities, energy planners, and regulators.
Training methodology
Facilitated discussion, practical frameworks, case studies from different sectors, group exercises, short demonstrations of AI tools, and an action plan for each participant's organisation.
Objectives
By the end of this course, participants will be able to:
- Review AI applications across energy and utilities
- Apply AI to demand and load forecasting
- Use AI for network monitoring and loss reduction
- Support asset management with AI
- Plan AI adoption in a utility
Course outline
Day 1AI in Energy and Utilities
- Sector challenges
- AI use cases overview
- Data from meters and networks
- Examples
- Smart meters
- Regulatory context
Day 2Forecasting Demand
- Load forecasting methods
- Renewable generation forecasting
- Planning for peaks
- Forecasting lab
- Weather data
- Demand response
Day 3Networks and Losses
- Network monitoring
- Detecting technical and commercial losses
- Outage prediction
- Case study
- Theft detection
- Restoration planning
Day 4Assets and Customers
- Predictive asset maintenance
- Customer service automation
- Billing analytics
- Exercise
- Field crew scheduling
- Customer communication
Day 5Adoption Roadmap
- Data and IT foundations
- Skills and partners
- Regulation and cybersecurity
- Roadmap
- Funding options
- Pilot selection
