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Heat demand model for district heating simulation

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dc.title Heat demand model for district heating simulation en
dc.contributor.author Dolinay, Viliam
dc.contributor.author Vašek, Lubomír
dc.contributor.author Novák, Jakub
dc.contributor.author Chalupa, Petr
dc.contributor.author Král, Erik
dc.relation.ispartof MATEC Web of Conferences
dc.identifier.issn 2261-236X OCLC, Ulrich, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 210
dc.event.title 22nd International Conference on Circuits, Systems, Communications and Computers, CSCC 2018
dc.event.location Majorca
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2018-07-14
dc.event.edate 2018-07-17
dc.type conferenceObject
dc.language.iso en
dc.publisher EDP Sciences
dc.identifier.doi 10.1051/matecconf/201821002044
dc.description.abstract Demand for affordable and sustainable energy is growing. Even though the technology of construction and insulation of buildings is continuously improving, heating is still a significant issue for large part of Europe. Building modern heating systems as well as upgrading existing ones requires incorporating new technology and smart control systems with sophisticated control algorithms. An essential part of the control systems are models that allow the simulation to verify proposed actions or use series of simulation experiments to find the optimal solution. Several simulation tools are specializing in the field of energy already, and some general tools can also be used. This article shows two methods of own prediction mechanism of the heat demand of individual consumers (buildings). Modelling of individual buildings is the basis of the simulation model of district heating which is being developed. The fundamental idea is to build a modular model for specific district heating and start from the endpoints-from the individual consumption objects that will be interconnected through the distribution model with other parts of district heating system such as other consumers and producers. It is assumed that the heat demand is the most challenging part of the prediction, and therefore the accuracy and quality of these models will be the most significant to the accuracy of the entire future result. © 2018 The Authors, published by EDP Sciences. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008314
utb.identifier.scopus 2-s2.0-85055579878
utb.source d-scopus
dc.date.accessioned 2019-01-03T12:31:44Z
dc.date.available 2019-01-03T12:31:44Z
utb.contributor.internalauthor Dolinay, Viliam
utb.contributor.internalauthor Vašek, Lubomír
utb.contributor.internalauthor Novák, Jakub
utb.contributor.internalauthor Chalupa, Petr
utb.contributor.internalauthor Král, Erik
utb.scopus.affiliation Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin, 760-05, Czech Republic
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