Stochastic optimization formulations for reliability unit commitment runs

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

Research output: Journal article publicationConference articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.
Original languageEnglish
Article number6939833
JournalIEEE Power and Energy Society General Meeting
Volume2014-October
Issue numberOctober
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2014 IEEE Power and Energy Society General Meeting - National Harbor, United States
Duration: 27 Jul 201431 Jul 2014

Keywords

  • mixed-integer linear programming
  • multi-stage stochastic optimization
  • two-stage stochastic optimization
  • Unit commitment

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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