This course introduces electric load forecasting from both statistical and practical aspects using language and examples from the power industry. Through conceptual and hands-on exercises, participants experience load forecasting for a variety of horizons from a few hours ahead to 30 years ahead. The overall aims are to prepare and sharpen the statistical and analytical skills of participants in dealing with real-world load forecasting problems and improve their ability to design, develop, document, and report sound and defensible load forecasts.
According to statistics gathered on the first five offerings, this course was highly rated by students who ranged from new graduates with no industry or SAS experience to forecasting experts with over 30 years of industry experience and over 20 years of SAS programming background. The students represented all sectors of the industry: G&T, ISO, distribution companies, REPs, IOU, co-op, municipal, regulatory commission, and consulting firm. Titles of the participants ranged from analyst, engineer, manager, to director and vice president.
For advanced topics, pair this course with Electric Load Forecasting: Advanced Topics and Case Studies The two courses are offered on contiguous days.
classify load forecasts
use basic graphic methods to discover the salient features of load profiles
build a benchmark model for a wide range of utilities
capture special effects for a local utility
forecast loads for both small and large utilities
improve very short-term forecasting accuracy
perform weather normalization
use macroeconomic indicators for long-term load forecasts
continue improving forecasting practice
avoid making frequently made mistakes.
Who Can Benefit
Load/price forecasters, energy traders, quantitative/business analysts in the utility industry, power system planners, power system operators, load research analysts, and rate design analysts
Before attending this course, you should
have a basic knowledge of the utility industry
have a basic understanding of forecasting.
Introduction to Electric Load Forecasting
overview of the electric power industry
business needs of load forecasts
driving factors of electricity consumption
classification of load forecasts
Salient Features of Electric Load Series
a general approach to electric load forecasting
overview of the data pool
trend and seasonality
more salient features
Multiple Linear Regression
A Naive Benchmark for Short-term Load Forecasting
a naive MLR benchmark
two more salient features
Customizing the Benchmarking Model
two more salient features
Very Short-Term Load Forecasting
hour ahead load forecasting
weighted least squares regression
Medium/Long-Term Load Forecasting
forecasting with weather variation
forecasting with cross scenarios
Variables, Methods, Techniques, and Further Readings
load, weather, calendar, macroeconomic indicator, etc.
https://www.exitcertified.com/training/sas/advanced-analytics/forecasting-econometrics/elect-fore-fund-39046-detail.htmlBELFElectric Load Forecasting: Fundamentals and Best Practiceshttps://assets.exitcertified.com/assets/CourseImages/e7cac5873b/AdobeStock_249826261__FitMaxWzEwMDAsMTAwMF0.jpg1650.00USDInStock/Training/SAS/Advanced Analytics/Forecasting and EconometricsThis course introduces electric load forecasting from both statistical and practical aspects using language and examples from...1650.00SASClassroom2015-06-15T15:34:27+00:00USD