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Efficient importance sampling technique for estimating operating risks in power systems with large amounts of wind power
KTH Royal Institute of Technology.
KTH Royal Institute of Technology. (Waves signals and systems)ORCID iD: 0000-0003-3111-4820
KTH Royal Institute of Technology.
2014 (English)In: Proceedings of the 13th International Workshop on Large-scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants / [ed] Uta Betancourt, Thomas Ackermann, Energynautics GmbH, 2014Conference paper (Refereed)
Abstract [en]

Uncertainties faced by operators of power systems are expected to increase with increasing amounts of wind power. This paper presents a method to design efficient importance sampling estimators to estimate the operating risk by Monte-Carlo simulations given the joint probability distribution describing the wind power and load forecasts. The operating risk is defined as the probability of violating stability and / or operating constraints. The method relies on an exisiting framework for rare-event simulations but takes into account the peculiarities of power systems. In case studies, it is shown that the number of Monte-Carlo runs needed to achieve a certain accuracy on the estimator can be reduced by up to three orders of magnitude.

Place, publisher, year, edition, pages
Energynautics GmbH, 2014.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:lnu:diva-61549OAI: oai:DiVA.org:lnu-61549DiVA: diva2:1083509
Conference
13th Wind Integration Workshop,22 - 24 October 2013, London, UK
Available from: 2017-03-21 Created: 2017-03-21 Last updated: 2017-04-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
  • html
  • text
  • asciidoc
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