Demonstration of heating demand peak shaving in smart homes

Lucas Beltram, Morten Herget Christensen, Rongling Li*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.
Original languageEnglish
Article number012055
Book seriesJournal of Physics: Conference Series (Online)
Volume1343
Issue number1
Number of pages6
ISSN1742-6596
DOIs
Publication statusPublished - 2019
EventCISBAT 2019: Climate Resilient Cities - Energy Efficiency & Renewables in the Digital Era - EPFL Lausanne, Lausanne, Switzerland
Duration: 4 Sep 20196 Sep 2019
https://cisbat.epfl.ch/

Conference

ConferenceCISBAT 2019
LocationEPFL Lausanne
CountrySwitzerland
CityLausanne
Period04/09/201906/09/2019
SponsorSwiss Federal Office of Energy
Internet address

Cite this

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title = "Demonstration of heating demand peak shaving in smart homes",
abstract = "Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.",
author = "Lucas Beltram and Christensen, {Morten Herget} and Rongling Li",
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Demonstration of heating demand peak shaving in smart homes. / Beltram, Lucas; Christensen, Morten Herget; Li, Rongling.

In: Journal of Physics: Conference Series (Online), Vol. 1343, No. 1, 012055, 2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Demonstration of heating demand peak shaving in smart homes

AU - Beltram, Lucas

AU - Christensen, Morten Herget

AU - Li, Rongling

PY - 2019

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N2 - Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.

AB - Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.

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