Domestic Heat Demand Prediction using Neural Networks

Vincent Bakker, Albert Molderink, Johann L. Hurink, Gerardus Johannes Maria Smit

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

24 Citations (Scopus)
97 Downloads (Pure)

Abstract

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.
Original languageUndefined
Title of host publicationProceedings of Nineteenth International Conference on Systems Engineering
Place of PublicationLos Alamitos
PublisherIEEE Computer Society
Pages189-194
Number of pages6
ISBN (Print)978-0-7695-3331-5
DOIs
Publication statusPublished - 19 Aug 2008
Event19th International Conference on Systems Engineering, ICSENG '08 - Las Vegas, Nevada, USA
Duration: 19 Aug 200821 Aug 2008

Publication series

Name
PublisherIEEE Computer Society Press
NumberSupplement

Conference

Conference19th International Conference on Systems Engineering, ICSENG '08
Period19/08/0821/08/08
Other19-21 August 2008

Keywords

  • EWI-13435
  • METIS-251181
  • IR-64981

Cite this