Markov Model of Renewable Resources for ‎Reliability Assessment of Distribution Systems

Hesam Khazraj, Filipe Miguel Faria da Silva, Claus Leth Bak, Mazaher Haji Bashi

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

A daily operation of distribution network with the integration of wind power generation (WPG) is presented in this paper. In this study is considered reliability assessment of distribution network, which is one of the key indices to measure the impact of the renewable units' outage such as WPG. The proposed framework maximizes the distribution network operator (DNO) benefits in short-term scheduling model. A Markov model is proposed to a comprehensive reliability assessment of WPG and battery storage system (BSS). The properties of the main parts of the BSS and WPG and their effects on the distribution system reliability is also provided by the Markov model. A scenario-based method is employed to model the uncertainties of WPG and load value. The suggested model is successfully examined on the 9-bus standard system.
Original languageEnglish
Title of host publicationProceedings of the IEEE 18th International Conference on Environment and Electrical Engineering and 2nd Industrial and Commercial Power Systems Europe
Number of pages6
Place of PublicationPalermo, Italy
PublisherIEEE Press
Publication dateJun 2018
Pages1-6
Article number8493814
ISBN (Print)978-1-5386-5187-2
ISBN (Electronic)978-1-5386-5186-5
DOIs
Publication statusPublished - Jun 2018
EventIEEE 18th International Conference on Environment and Electrical Engineering and 2nd Industrial and Commercial Power Systems Europe - Palermo, Italy
Duration: 12 Jun 201815 Jun 2018
https://www.eeeic.net/eeeic/

Conference

ConferenceIEEE 18th International Conference on Environment and Electrical Engineering and 2nd Industrial and Commercial Power Systems Europe
CountryItaly
CityPalermo
Period12/06/201815/06/2018
Internet address

Keywords

  • reliability assessment
  • Markov model
  • wind power generation
  • battery storage

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