Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Detection and localization of non-technical losses in distribution systems with future smart meters
RISE - Research Institutes of Sweden, Safety and Transport, Measurement Science and Technology.
RISE - Research Institutes of Sweden, Safety and Transport, Measurement Science and Technology.
2019 (English)In: 2019 IEEE Milan PowerTech, PowerTech 2019, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper, Published paper (Refereed)
Abstract [en]

In terms of efficiency, 54 out of 159 Swedish DSOs have higher distribution losses than 4% on an annual basis. If these 54 had made improvements in their power grids and reached an energy loss of 4%, this would mean a reduction of 143 GWh/year overall. Assuming a cost of 5 cent/ kWh this would equivalent to approximately 7.2 million EUR/year. This paper evaluates two different distribution systems, a method for detection of non-technical losses(NTL) and the impact of the detection method on time delays and resolution issues. Furthermore, three different methods for localization is evaluated and their usability discussed, evaluated and tools presented. All three methods prove able to localize NTL at the bus of connection in the cases presented in the paper. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019.
Keywords [en]
Power distribution, Power system analysis computing, Smart grids, Electric power transmission networks, Energy dissipation, Detection and localization, Detection methods, Different distributions, Distribution systems, Non-technical loss, Power distributions, Power system analysis, Smart grid, Smart power grids
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-39978DOI: 10.1109/PTC.2019.8810893Scopus ID: 2-s2.0-85072310852ISBN: 9781538647226 (print)OAI: oai:DiVA.org:ri-39978DiVA, id: diva2:1361664
Conference
2019 IEEE Milan PowerTech, PowerTech 2019, 23 June 2019 through 27 June 2019
Note

Funding details: Swedish Insitute, SI; Funding details: RISE; Funding text 1: ACKNOWLEDGMENT The funding from EnergiForsk through the program of Smart Grids (Smarta Elnät) is greatly acknowledged. This article was partly taken from a report in Swedish (see [8]) for EnergiForsk co-written by the first author, Dr. Claes Sandels and Senior Engineer Andreas Nilsson at Research Institutes of Sweden (RISE). In this report where added values of DSO feedback and AI-methods are presented.

Available from: 2019-10-16 Created: 2019-10-16 Last updated: 2019-10-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus
By organisation
Measurement Science and Technology
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 2 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.35.9