Comparison of strategies for model predictive control for home heating in future energy systems

Research output: Research - peer-reviewArticle in proceeding

Abstract

Model predictive control is seen as one of the key future enabler in increasing energy efficiency in buildings. This paper presents a comparison of the performance of the control for different formulations of the objective function. This comparison is made in a simulation study on a single building using historical weather and power system data from Denmark. Trade-offs between energy consumption, comfort and incurred CO2 emissions depending on the chosen objective function are quantified, highlighting the need to carefully select the strategy used in future design and implementation, rather than simply operating energy or SPOT price optimisation.
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Model predictive control is seen as one of the key future enabler in increasing energy efficiency in buildings. This paper presents a comparison of the performance of the control for different formulations of the objective function. This comparison is made in a simulation study on a single building using historical weather and power system data from Denmark. Trade-offs between energy consumption, comfort and incurred CO2 emissions depending on the chosen objective function are quantified, highlighting the need to carefully select the strategy used in future design and implementation, rather than simply operating energy or SPOT price optimisation.
Original languageEnglish
Title of host publication2017 IEEE Manchester PowerTech
Number of pages6
Place of PublicationManchester, GB
PublisherIEEE
Publication dateJun 2017
ISBN (Electronic)978-1-5090-4237-1
DOI
StatePublished - Jun 2017
Publication categoryResearch
Peer-reviewedYes
Event12th IEEE PES PowerTech Conference - Manchester, United Kingdom
Duration: 18 Jun 201722 Jun 2017
http://ieee-powertech.org/

Conference

Conference12th IEEE PES PowerTech Conference
LandUnited Kingdom
ByManchester
Periode18/06/201722/06/2017
Internetadresse
SeriesIEEE PowerTech proceedings

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ID: 261085150