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A machine learning approach to increase energy efficiency in district heating systems
Gjøvik University College, Norway.ORCID-id: 0000-0001-7520-695x
Gjøvik University College, Norway.
Faculty of Technology and Management, Norway.
2015 (engelsk)Inngår i: Environmental Engineering and Computer Application: Proceedings of the International Conference on Environmental Engineering and Computer Application, ICEECA 2014, Hong kong: CRC Press, 2015, s. 223-226Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Heat demand prediction is an important part of increasing system efficiency within district heating. To achieve this efficiency, the energy provider companies need to estimate how much energy is re quired to satisfy the market demand. In this paper, we propose a method to investigate the application of online ma chine learning algorithm to achieve energy efficiency and optimization in District Heating (DH) systems by predicting the heat demand on the consumer side. To accomplish this, we are planning to use operational data from a Norwegian company (EffektivEnergi AS, Hamar) for a group of buildings that are connected to DH in other places.

sted, utgiver, år, opplag, sider
Hong kong: CRC Press, 2015. s. 223-226
HSV kategori
Forskningsprogram
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:lnu:diva-67840DOI: 10.1201/b18565-44ISBN: 978-1-138-02807-4 (tryckt)ISBN: 978-1-315-68538-0 (digital)OAI: oai:DiVA.org:lnu-67840DiVA, id: diva2:1139235
Konferanse
International Conference on Environmental Engineering and Computer Application (ICEECA 2014, Hong Kong, 25-26 December, 2014
Tilgjengelig fra: 2017-09-07 Laget: 2017-09-07 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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Totalt: 117 treff
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  • de-DE
  • en-GB
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