Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models
Most buildings are not continuously occupied, such as office buildings, schools, churches and many residential buildings. Maintaining comfortable conditions only during the occupied periods reduces the energy costs. This can be done by lowering the temperature as much as possible during unoccupied p...
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Online Access: | http://www.mdpi.com/2075-5309/6/1/10 |
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doaj-9614e01402c64e95840256c841ae4da92020-11-24T21:07:22ZengMDPI AGBuildings2075-53092016-03-01611010.3390/buildings6010010buildings6010010Estimation of the Heating Time of Small-Scale Buildings Using Dynamic ModelsDegurunnehalage Wathsala Upamali Perera0Nils-Olav Skeie1University College of Southeast Norway, Kjølnes Ring 56, 3918 Porsgrunn, NorwayUniversity College of Southeast Norway, Kjølnes Ring 56, 3918 Porsgrunn, NorwayMost buildings are not continuously occupied, such as office buildings, schools, churches and many residential buildings. Maintaining comfortable conditions only during the occupied periods reduces the energy costs. This can be done by lowering the temperature as much as possible during unoccupied periods and at nights and then raising the temperature for occupation. More energy can be saved by using this method. The estimation of the time taken for the temperature increase is important in determining the optimal time for switching the heating equipment on. A dynamic model for single-zone buildings is developed for estimating the heating time, and the model is validated using four case studies with real measurements. The model computes the heating time with an error of less than 3%. It can also be used to obtain a rough prediction of the space heating energy use. Further, it was observed that starting the heating at the right time returns the lowest energy cost with the introduction of usage-based energy tariff systems. The model is quick in predicting the results, and hence, physics-based models can play an influential role in building system control with advanced control strategies.http://www.mdpi.com/2075-5309/6/1/10building simulationdynamic modelheating timesingle-zone buildings |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Degurunnehalage Wathsala Upamali Perera Nils-Olav Skeie |
spellingShingle |
Degurunnehalage Wathsala Upamali Perera Nils-Olav Skeie Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models Buildings building simulation dynamic model heating time single-zone buildings |
author_facet |
Degurunnehalage Wathsala Upamali Perera Nils-Olav Skeie |
author_sort |
Degurunnehalage Wathsala Upamali Perera |
title |
Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models |
title_short |
Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models |
title_full |
Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models |
title_fullStr |
Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models |
title_full_unstemmed |
Estimation of the Heating Time of Small-Scale Buildings Using Dynamic Models |
title_sort |
estimation of the heating time of small-scale buildings using dynamic models |
publisher |
MDPI AG |
series |
Buildings |
issn |
2075-5309 |
publishDate |
2016-03-01 |
description |
Most buildings are not continuously occupied, such as office buildings, schools, churches and many residential buildings. Maintaining comfortable conditions only during the occupied periods reduces the energy costs. This can be done by lowering the temperature as much as possible during unoccupied periods and at nights and then raising the temperature for occupation. More energy can be saved by using this method. The estimation of the time taken for the temperature increase is important in determining the optimal time for switching the heating equipment on. A dynamic model for single-zone buildings is developed for estimating the heating time, and the model is validated using four case studies with real measurements. The model computes the heating time with an error of less than 3%. It can also be used to obtain a rough prediction of the space heating energy use. Further, it was observed that starting the heating at the right time returns the lowest energy cost with the introduction of usage-based energy tariff systems. The model is quick in predicting the results, and hence, physics-based models can play an influential role in building system control with advanced control strategies. |
topic |
building simulation dynamic model heating time single-zone buildings |
url |
http://www.mdpi.com/2075-5309/6/1/10 |
work_keys_str_mv |
AT degurunnehalagewathsalaupamaliperera estimationoftheheatingtimeofsmallscalebuildingsusingdynamicmodels AT nilsolavskeie estimationoftheheatingtimeofsmallscalebuildingsusingdynamicmodels |
_version_ |
1716763158336503808 |