Kontaktujte nás | Jazyk: čeština English
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 |