A model for predicting the yearly load in district heating systems
This paper presents a model that can be used to predict the yearly load in district heating systems some years ahead. To demonstrate the model, data from Reykjavik, Iceland, were used in the analysis. The model is based on the three main factors affecting the consumption. The first factor is the inc...
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Online Access: | http://dx.doi.org/10.1243/095765002320183595 http://journals.sagepub.com/doi/pdf/10.1243/095765002320183595 |
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crsagepubl:10.1243/095765002320183595 2023-05-15T16:51:04+02:00 A model for predicting the yearly load in district heating systems Jónsson, G. R. 2002 http://dx.doi.org/10.1243/095765002320183595 http://journals.sagepub.com/doi/pdf/10.1243/095765002320183595 en eng SAGE Publications http://journals.sagepub.com/page/policies/text-and-data-mining-license Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy volume 216, issue 3, page 277-281 ISSN 0957-6509 2041-2967 Mechanical Engineering Energy Engineering and Power Technology journal-article 2002 crsagepubl https://doi.org/10.1243/095765002320183595 2022-04-14T04:41:00Z This paper presents a model that can be used to predict the yearly load in district heating systems some years ahead. To demonstrate the model, data from Reykjavik, Iceland, were used in the analysis. The model is based on the three main factors affecting the consumption. The first factor is the increase in the number of houses, called the connected volume, that need to be heated. The trend in the volume during the last decade forms the basis for predicting future values using regression analysis. The second factor is the climate, which is an important factor since approximately 85-90 per cent of the hot water consumption is weather dependent. The estimated variability in the weather is based on data for the period from 1949 to 1999 using bootstrap techniques. The third factor is the behaviour of the consumers, which is analysed by looking at past consumption values after isolating the effect of the first two factors from the consumption. A prediction of the consumption is obtained given some values of each of the three factors. This process is repeated several hundred times, and from those values an estimate of the expected consumption is obtained. Furthermore, the two-sided (100 — α) per cent confidence interval for the consumption is determined by cutting off α/2 per cent of the lowest and highest predicted consumption values. Article in Journal/Newspaper Iceland SAGE Publications (via Crossref) Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 216 3 277 281 |
institution |
Open Polar |
collection |
SAGE Publications (via Crossref) |
op_collection_id |
crsagepubl |
language |
English |
topic |
Mechanical Engineering Energy Engineering and Power Technology |
spellingShingle |
Mechanical Engineering Energy Engineering and Power Technology Jónsson, G. R. A model for predicting the yearly load in district heating systems |
topic_facet |
Mechanical Engineering Energy Engineering and Power Technology |
description |
This paper presents a model that can be used to predict the yearly load in district heating systems some years ahead. To demonstrate the model, data from Reykjavik, Iceland, were used in the analysis. The model is based on the three main factors affecting the consumption. The first factor is the increase in the number of houses, called the connected volume, that need to be heated. The trend in the volume during the last decade forms the basis for predicting future values using regression analysis. The second factor is the climate, which is an important factor since approximately 85-90 per cent of the hot water consumption is weather dependent. The estimated variability in the weather is based on data for the period from 1949 to 1999 using bootstrap techniques. The third factor is the behaviour of the consumers, which is analysed by looking at past consumption values after isolating the effect of the first two factors from the consumption. A prediction of the consumption is obtained given some values of each of the three factors. This process is repeated several hundred times, and from those values an estimate of the expected consumption is obtained. Furthermore, the two-sided (100 — α) per cent confidence interval for the consumption is determined by cutting off α/2 per cent of the lowest and highest predicted consumption values. |
format |
Article in Journal/Newspaper |
author |
Jónsson, G. R. |
author_facet |
Jónsson, G. R. |
author_sort |
Jónsson, G. R. |
title |
A model for predicting the yearly load in district heating systems |
title_short |
A model for predicting the yearly load in district heating systems |
title_full |
A model for predicting the yearly load in district heating systems |
title_fullStr |
A model for predicting the yearly load in district heating systems |
title_full_unstemmed |
A model for predicting the yearly load in district heating systems |
title_sort |
model for predicting the yearly load in district heating systems |
publisher |
SAGE Publications |
publishDate |
2002 |
url |
http://dx.doi.org/10.1243/095765002320183595 http://journals.sagepub.com/doi/pdf/10.1243/095765002320183595 |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy volume 216, issue 3, page 277-281 ISSN 0957-6509 2041-2967 |
op_rights |
http://journals.sagepub.com/page/policies/text-and-data-mining-license |
op_doi |
https://doi.org/10.1243/095765002320183595 |
container_title |
Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy |
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216 |
container_issue |
3 |
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277 |
op_container_end_page |
281 |
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1766041178055114752 |