By Topic

Domestic Heat Demand Prediction Using Neural Networks

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

4 Author(s)
Bakker, V. ; Dept. of EEMCS, Twente Univ., Enschede ; Molderink, A. ; Hurink, J.L. ; Smit, G.J.M.

By combining a cluster of microCHP appliances, a virtual power plant can be formed. To use such a virtual power plant, a good heat demand prediction of individual households is needed since the heat demand determines the production capacity. In this paper we present the results of using neural networks techniques to predict the heat demand of individual households. This prediction is required to determine the electricity production capacity of the large fleet of microCHP appliances. All predictions are short-term (for one day) and use historical heat demand and weather influences as input.

Published in:

Systems Engineering, 2008. ICSENG '08. 19th International Conference on

Date of Conference:

19-21 Aug. 2008