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Forecast of heat demand according the Box-Jenkins methodology for specific locality

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dc.title Forecast of heat demand according the Box-Jenkins methodology for specific locality en
dc.contributor.author Chramcov, Bronislav
dc.relation.ispartof International Conference on Systems - Proceedings
dc.identifier.issn 1792-4235 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-960-474-214-1
dc.identifier.isbn 978-960-474-199-1
dc.date.issued 2010
utb.relation.volume 1
dc.citation.spage 252
dc.citation.epage 256
dc.event.title 14th WSEAS International Conference on Systems, Part of the 14th WSEAS CSCC Multiconference
dc.event.location Corfu Island
utb.event.state-en Greece
utb.event.state-cs Řecko
dc.event.sdate 2010-07-22
dc.event.edate 2010-07-24
dc.type conferenceObject
dc.language.iso en
dc.publisher World Scientific and Engineering Academy and Society (WSEAS)
dc.relation.uri http://www.wseas.us/e-library/conferences/2010/Corfu/SYSTEMS/SYSTEMS1-39.pdf
dc.subject Box-Jenkins en
dc.subject Control algorithms en
dc.subject District heating control en
dc.subject Prediction en
dc.subject Time series analysis en
dc.description.abstract In order to improve the control level of district-heating systems, it is necessary for the energy companies to have reliable optimization routines, implemented in their organizations. However, before a plan of heat production, a prediction of the heat demand first needs to be determined. Forecast of this heat demand course is significant for shortterm and long-term planning of heat production. This forecast is most important for technical and economic consideration. In this paper we propose the forecast model of heat demand based on the Box-Jenkins methodology. The model is based on the assumption that the course of DDHD can be described sufficiently well as a function of the outdoor temperature and the weather independent component (social components). Time of the day affects the social components. The time dependence of the load reflects the existence of a daily heat demand pattern, which may vary for different week days and seasons. Forecast of social component is realized by means of Box-Jenkins methodology. This model is used for prediction of heat demand in different locality. The results of heat demand prediction in specific locality and conclusions are presented. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1004068
utb.identifier.obdid 43863813
utb.identifier.scopus 2-s2.0-79958763451
utb.source d-scopus
dc.date.accessioned 2015-01-15T13:20:21Z
dc.date.available 2015-01-15T13:20:21Z
utb.contributor.internalauthor Chramcov, Bronislav
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