Two-stage and multi-stage stochastic unit commitment under wind generation uncertainty

Yang Lu, Chaoyue Zhao, Jean Paul Watson, Kai Pan, Yongpei Guan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Although wind power is considered green energy and free, its intermittent nature causes the instability issues for the current power grid system. The two-stage stochastic optimization approach has been explored recently and justified as an effective approach to achieve cost efficiency while ensuring system reliability. This approach can fit well for most independent system operators (ISOs) today, performing reliability unit commitment (RUC) runs to ensure the sufficient thermal generation capacity to accommodate the wind output fluctuation. In this paper, we propose a multistage stochastic optimization unit commitment model and compare its performance with the two-stage stochastic optimization model, in terms of total expected cost and computational complexity. For the multi-stage stochastic optimization model, the unit commitment and economic dispatch decisions are made sequentially as more information is realized, which can take advantage of more realized information and provide more flexibility for unit commitment decisions to accommodate the uncertainty. The stochasticity of wind power output is represented by a scenario tree and the final computational results verify the value of the multi-stage stochastic optimization approach.
Original languageEnglish
Title of host publicationIIE Annual Conference and Expo 2014
PublisherInstitute of Industrial Engineers
Pages4148-4155
Number of pages8
ISBN (Electronic)9780983762430
Publication statusPublished - 1 Jan 2014
Externally publishedYes
EventIIE Annual Conference and Expo 2014 - Palais des Congres de Montreal, Montreal, Canada
Duration: 31 May 20143 Jun 2014

Conference

ConferenceIIE Annual Conference and Expo 2014
CountryCanada
CityMontreal
Period31/05/143/06/14

Keywords

  • Mixed-integer linear programming
  • Multistage stochastic programming
  • Two-stage stochastic programming
  • Unit commitment
  • Wind power output

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Control and Systems Engineering

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