Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Multi-area power system reliability evaluation by application of copula theory
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0002-8189-2420
2016 (English)In: IEEE Power and Energy Society General Meeting, IEEE, 2016Conference paper, (Refereed)
Abstract [en]

Evaluating the risk of capacity deficit in large interconnected power systems is an important task in planning studies in order to supply the demand in the system at a certain risk level. It makes it possible to identify in which parts of the system reinforcements are needed in terms of generating capacity and/or interconnections. In modern power systems, with tie lines interconnecting countries and continents as well as an increasing amount of intermittent renewable resources, areas become dependent on each other for generating capacity not only under rare hazardous operating conditions but also in what can be considered as normal operation. This paper presents a novel way of taking inter-area load correlation into account when calculating the risk of capacity deficit by applying Copula sampling. The Monte Carlo simulation method is applied in addition to a Cross-Entropy based importance sampling technique to reduce computation time. The resulting procedure is a computationally effective general method of evaluating the risk of capacity deficit in a large scale multi-area interconnected power system.

Place, publisher, year, edition, pages
IEEE, 2016.
Keyword [en]
Computation theory, Importance sampling, Intelligent systems, Monte Carlo methods, Reliability theory, Computation time, Generating capacity, Monte Carlo simulation methods, Multi area power systems, Normal operations, Operating condition, Planning studies, Renewable resource, Electric power system interconnection
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-202153DOI: 10.1109/PESGM.2016.7741943ISI: 000399937903107Scopus ID: 2-s2.0-85002406504ISBN: 9781509041688 (print)OAI: oai:DiVA.org:kth-202153DiVA: diva2:1081263
Conference
2016 IEEE Power and Energy Society General Meeting, PESGM 2016, 17 July 2016 through 21 July 2016
Note

QC 20170313

Available from: 2017-03-13 Created: 2017-03-13 Last updated: 2017-06-29Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopushttp://www.pes-gm.org/2016/

Search in DiVA

By author/editor
Tomasson, EgillSöder, Lennart
By organisation
Electric Power and Energy Systems
Energy Systems

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 5 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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