Use of Synthetic Wind Power Time Series for Long-term Voltage Stability Analysis

I. M. Granitsas, T. Souxes, C. Vournas, M. J. Koivisto*, M. Sarkar, P. E. Sorensen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this paper two types of synthetic wind power time series are used to assess the effect of wind variability in the long-term voltage stability assessment of a power system. A wind power time series is generated using the wind simulation tool CorWind, which is based on power spectral density. This time series is then used as input to develop a Markov model for wind power simulation. Both the CorWind time series and randomly generated time series using the Markov model are then applied to a simple power system and the effect of wind variability on the maximum power transfer to a remote load is investigated.
Original languageEnglish
Title of host publicationProceedings of 2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Number of pages6
PublisherIEEE
Publication date2020
ISBN (Electronic)978-1-7281-2822-1
DOIs
Publication statusPublished - 2020
Event2020 International Conference on Probabilistic Methods Applied to Power Systems - Liege, Belgium
Duration: 18 Aug 202021 Aug 2020

Conference

Conference2020 International Conference on Probabilistic Methods Applied to Power Systems
Country/TerritoryBelgium
CityLiege
Period18/08/202021/08/2020
Series2020 International Conference on Probabilistic Methods Applied To Power Systems (pmaps)
ISSN2642-6757

Keywords

  • Markov chain
  • Synthetic time series
  • Wind power
  • Long-term voltage stability
  • Maximum power transfer

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