By Topic

Geotypical Growth-based Load Forecasting: An introduction to an innovative approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Penton, H.S. ; Distrib. Planning Dept., Idaho Power Co., Boise, ID, USA ; McKinney, E.

An introduction to Geotypical Growth-based Load Forecasting (GGLF), long-term power distribution load forecasting based on biological concepts and segmented geographies, is presented. Using load data obtained from 165 substations in Southern Idaho and Southeastern Oregon, this document (1) describes the reasoning for using Living Systems Theory (LST) as a basis for long-term distribution load forecasting, (2) shows the relationship between the MW growth rates of the substations to their observed peak loads, (3) provides the rationale for segmenting the substations into their various geographical characteristics (geotypes), and (4) discusses a logistical regression curve-fitting model that represents the load characteristics of five example geotypes. Example geotypes discussed in the document are those common to a high plains geography, semi-arid climate type. Recommendations for additional research that applies GGLF to other climate types and to other MW load densities are also suggested.

Published in:

Transmission and Distribution Conference and Exposition (T&D), 2012 IEEE PES

Date of Conference:

7-10 May 2012