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Automated Statistical Methods for Fault Detection in District Heating Customer Installations

Månsson, Sara LU ; Davidsson, Kristin ; Lauenburg, Patrick LU and Thern, Marcus LU (2018) In Energies 12(113).
Abstract
In order to develop more sustainable district heating systems, the district heating sector is currently trying to increase the energy efficiency of these systems. One way of doing so is to identify customer installations in the systems that have poor cooling performance. This study aimed to develop an algorithm that was able to detect the poorly performing installations automatically using meter readings from the installations. The algorithm was developed using statistical methods and was tested on a data set consisting of data from 3000 installations located in a district heating system in Sweden. As many as 1273 installations were identified by the algorithm as having poor cooling performance. This clearly shows that it is of major... (More)
In order to develop more sustainable district heating systems, the district heating sector is currently trying to increase the energy efficiency of these systems. One way of doing so is to identify customer installations in the systems that have poor cooling performance. This study aimed to develop an algorithm that was able to detect the poorly performing installations automatically using meter readings from the installations. The algorithm was developed using statistical methods and was tested on a data set consisting of data from 3000 installations located in a district heating system in Sweden. As many as 1273 installations were identified by the algorithm as having poor cooling performance. This clearly shows that it is of major interest to the district heating companies to identify the installations with poor cooling performance rapidly and automatically, in order to rectify them as soon as possible (Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
automatiserad felhantering, fjärrvärme, fjärrvärmecentraler
in
Energies
volume
12
issue
113
article number
113
pages
18 pages
publisher
MDPI AG
external identifiers
  • scopus:85060032498
ISSN
1996-1073
DOI
10.3390/en12010113
language
English
LU publication?
yes
id
57ca60ac-e28c-4a6f-b912-2d8f86ad2a56
date added to LUP
2019-01-29 14:35:22
date last changed
2021-09-22 04:03:36
@article{57ca60ac-e28c-4a6f-b912-2d8f86ad2a56,
  abstract     = {In order to develop more sustainable district heating systems, the district heating sector is currently trying to increase the energy efficiency of these systems. One way of doing so is to identify customer installations in the systems that have poor cooling performance. This study aimed to develop an algorithm that was able to detect the poorly performing installations automatically using meter readings from the installations. The algorithm was developed using statistical methods and was tested on a data set consisting of data from 3000 installations located in a district heating system in Sweden. As many as 1273 installations were identified by the algorithm as having poor cooling performance. This clearly shows that it is of major interest to the district heating companies to identify the installations with poor cooling performance rapidly and automatically, in order to rectify them as soon as possible},
  author       = {Månsson, Sara and Davidsson, Kristin and Lauenburg, Patrick and Thern, Marcus},
  issn         = {1996-1073},
  language     = {eng},
  month        = {12},
  number       = {113},
  publisher    = {MDPI AG},
  series       = {Energies},
  title        = {Automated Statistical Methods for Fault Detection in District Heating Customer Installations},
  url          = {http://dx.doi.org/10.3390/en12010113},
  doi          = {10.3390/en12010113},
  volume       = {12},
  year         = {2018},
}