A Review of Load Forecasting Methodologies

Thumbnail Image
Date
1984-06-01
Authors
Oamek, George
English, Burton
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Research Projects
Organizational Units
Organizational Unit
Center for Agricultural and Rural Development

The Center for Agricultural and Rural Development (CARD) conducts innovative public policy and economic research on agricultural, environmental, and food issues. CARD uniquely combines academic excellence with engagement and anticipatory thinking to inform and benefit society.

CARD researchers develop and apply economic theory, quantitative methods, and interdisciplinary approaches to create relevant knowledge. Communication efforts target state and federal policymakers; the research community; agricultural, food, and environmental groups; individual decision-makers; and international audiences.

Journal Issue
Is Version Of
Versions
Series
Abstract

In response to increasing criticisms of their load forecasts and forecasting methods, Iowa's electric utilities sponsored an independent review of past and present load forecasting methodologies. The review was conducted by an Iowa research team and followed two approaches. One was to evaluate various energy and peak demand models used by United States' electrical utilities, with emphasis on models developed during the period 1973 through 1979. The second approach involved construction of econometric energy demand models for an Iowa utility.

Historical energy and peak demand models were classified by methodology (statistical, econometric-end use analysis) and demand class (residential, commercial, and industrial). Statistical and econometric models were examined for forecast and backcast accuracy and parameter stability over time. Econometric-end use simulation models were observed for parameter sensitivity and, when possible, accuracy.

The energy demand models were constructed for the residential and commercial classes with the purpose of incorporating variables considered relevant by economic theory and available literature. These variables, and their various combinations, were tested for statistical significance and logical applicability to Iowa.

The results of this study will provide a foundation on which to begin construction of a comprehensive set of load forecasting models for use by Iowa utilities and legislators.

Comments
Description
Keywords
Citation
DOI
Source
Copyright
Sun Jan 01 00:00:00 UTC 1984
Collections