Model predictive control of district heating system

Lie-Jensen, Frode; Aannø, Andreas; Aleksandrova, Elena; Westli, Anders; Nielsen, Morten; Komulainen, Tiina M.

dc.contributor.author	Lie-Jensen, Frode
dc.contributor.author	Aannø, Andreas
dc.contributor.author	Aleksandrova, Elena
dc.contributor.author	Westli, Anders
dc.contributor.author	Nielsen, Morten
dc.contributor.author	Komulainen, Tiina M.
dc.date.accessioned	2019-01-18T14:56:02Z
dc.date.accessioned	2019-01-21T10:23:55Z
dc.date.available	2019-01-18T14:56:02Z
dc.date.available	2019-01-21T10:23:55Z
dc.date.issued	2018-11-19
dc.identifier.citation	Lie-Jensen, Aannø, Aleksandrova, Westli, Nielsen M, Komulainen TMK. Model predictive control of district heating system. Linköping Electronic Conference Proceedings. 2018	en
dc.identifier.issn	1650-3686
dc.identifier.issn	1650-3686
dc.identifier.issn	1650-3740
dc.identifier.uri	https://hdl.handle.net/10642/6528
dc.description.abstract	District heating system (DHS) is a widely used and increasingly popular energy source in cities. The uncertainty in the heat load (HL) due to customer demand ﬂuctuations makes unit commitment (UC) and heat production unit (HPU) control a complex task. This case study of the DHS at Fortum Oslo Varme AS (FOV) aims to ﬁnd a strategy to optimize and fully automate UC and HPU. Our results suggests this can be accomplished by using model predictive control (MPC) to control HPU power and ﬂow rate, mixed integer linear programming (MILP) optimization to solve UC problem, and multiple linear regression (MLR) model to predict the HL. We also show that the fuel cost can be reduced signiﬁcantly.	en
dc.language.iso	en	en
dc.publisher	Linköping University Electronic Press	en
dc.relation.ispartofseries	Linköping Electronic Conference Proceedings;153:007
dc.rights	LiU E-Press publish open access under the Creative Commons license: BY-NC Attribution-Non-commercial.	en
dc.rights.uri	https://creativecommons.org/licenses/by-nc/4.0/
dc.subject	District heating	en
dc.subject	Model predictive controls	en
dc.subject	System identiﬁcations	en
dc.subject	Unit commitment problems	en
dc.subject	Heat load predictions	en
dc.title	Model predictive control of district heating system	en
dc.type	Journal article
dc.type	Journal article	en
dc.type	Peer reviewed	en
dc.date.updated	2019-01-18T14:56:02Z
dc.description.version	publishedVersion	en
dc.identifier.doi	http://dx.doi.org/10.3384/ecp1815343
dc.identifier.cristin	1660591
dc.source.journal	Linköping Electronic Conference Proceedings

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LiU E-Press publish open access under the Creative Commons license: BY-NC Attribution-Non-commercial.

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