The standard course outline is listed below. The course is being customized based on the background and needs of attendees. See THIS BLOG POST for my teaching method.
Course Outline
Introduction
Utility applications
How much is 1% error?
Principles of forecasting
Load forecasting terminologies
Techniques for long term load forecasting
Classical methods
The magic ruler
Regression models with monthly or daily data
S-curve for spatial load forecasting
End use studies
A statistical approach
Golden insights from hourly data
Piecewise or polynomial functions
A large but small model
It's economists' fault
Probabilistic load forecasting
Forecasting methods
Evaluation methods
A series of case studies
A crowd-sourcing approach
Challenges and solutions
Data, data, data
Weather station selection
Forecast reconciliation: when science meets reality
Emerging topics
Distributed generation
Energy efficiency and demand response
Electric vehicles
Forecast override, override what, and how?
(Computer lab session based on MS Excel, MATLAB, R or SAS)
Load forecasting in MS Excel
Software tools and solutions
Spreadsheet based forecasting: five approaches
Understanding the limitations
Building load forecasting models