By Topic

Application of statistical and neural approaches to the daily load profiles modelling in power distribution systems

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)
Nazarko, J. ; Inst. of Manage. & Marketing, Bialystok Tech. Univ., Poland ; Styczynski, Z.A.

Load modelling is an essential task in the economic analysis, operation and planning of distribution systems. Particularly, when a demand side management system is taken into account on a deregulated energy market, the knowledge of load profiles is of the greatest importance. Forecasting of daily demand, based upon load models, uses comparable load research data for a different customer mix. For the given season and day of the week, the shape of a daily load curve depends mainly on the customer composition. Difficulties in defining objective customer classes significantly complicate the forecasting process. Usage of statistical clustering and neural network approaches makes possible to improve the load modelling accuracy. This paper presents load modelling methods useful for the long-term planning of power distribution systems. The theoretical statement is illustrated by examples which correspond to Polish and German distribution systems

Published in:

Transmission and Distribution Conference, 1999 IEEE  (Volume:1 )

Date of Conference:

11-16 Apr 1999