Electric load forecasting: fundamentals and best practices

Primary tabs


A printed copy of this book is not yet available.


Load forecasting is a fundamental business problem of the electric power industry. Although many advanced models and techniques have been tried to forecast electric load over the past many decades, few were adopted in practice by the industry. This book is based on over 40 years of research, teaching and consulting experience on time series forecasting and electric load forecasting with thousands of students and utility professionals. It offers the current and future utility load forecasting analysts a comprehensive, useful and up-to-date reference for today's competitive and dynamic environment.

Authors

Tao Hong
David A. Dickey

Table of contents

Electric load forecasting: fundamentals and best practices
Introduction
Describing the data
Regression analysis
Model selection
Short term load forecasting
Very short term load forecasting
Medium/long term load forecasting
Load forecasting techniques and combined forecasting
Hierarchical load forecasting
Outlier detection and data cleansing
Load settlement
Demand response forecasting
Retail energy forecasting
Frequently made mistakes
The art of load forecasting

Recently updated pages

Classification of load forecasts - 06 Mar 2014
Driving factors of electricity consumption - 06 Mar 2014
Six must-know basics of forecasting - 28 Feb 2014
Electric power industry - 24 Dec 2013
Introduction - 23 Dec 2013
Electric load forecasting: fundamentals and best practices - 05 Oct 2013
Retail energy forecasting - 23 Sep 2013
Cross validation - 09 Sep 2013
Ex ante and ex post forecasting - 09 Sep 2013
Implementation - 09 Sep 2013

Statistics : Total views

Electric load forecasting: fundamentals and best practices - 6,297 Very short term load forecasting - 1,133
Introduction - 2,047 Load forecasting techniques and combined forecasting - 1,076
Six must-know basics of forecasting - 1,725 Simple linear regression - 991
Electric power industry - 1,636 Medium/long term load forecasting - 983
Short term load forecasting - 1,486 Regression analysis - 782
Classification of load forecasts - 1,379 Numerical methods - 719
Overview of the data pool - 1,319 Outlier detection and data cleansing - 714
Driving factors of electricity consumption - 1,300 Model selection - 712
Describing the data - 1,207 Hierarchical load forecasting - 708
Software packages - 1,169 The art of load forecasting - 670