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Toward scalable, parallel progressive hedging for stochastic unit commitment
Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters
  • Sarah M. Ryan, Iowa State University
  • Roger J.B. Wetts, University of California, Davis
  • David L. Woodruff, University of California - Davis
Document Type
Conference Proceeding
Publication Version
Accepted Manuscript
Link to Published Version
Publication Date
Conference Title
2013 IEEE Power and Energy Society General Meeting
Conference Date
July 21-25, 2013
(49.2827291, -123.12073750000002)
Abstract: Given increasing penetration of variable generation units, there is significant interest in the power systems research community concerning the development of solution techniques that directly address the stochasticity of these sources in the unit commitment problem. Unfortunately, despite significant attention from the research community, stochastic unit commitment solvers have not made their way into practice, due in large part to the computational difficulty of the problem. In this paper, we address this issue, and focus on the development of a decomposition scheme based on the progressive hedging algorithm of Rockafellar and Wets. Our focus is on achieving solve times that are consistent with the requirements of ISO and utilities, on modest-scale instances, using reasonable numbers of scenarios. Further, we make use of modest-scale parallel computing, representing capabilities either presently deployed, or easily deployed in the near future. We demonstrate our progress to date on a test instance representing a simplified version of the US western interconnect (WECC-240).

This is an accepted manuscript of a conference proceeding published as Ryan, Sarah M., Roger J-B. Wets, David L. Woodruff, César Silva-Monroy, and Jean-Paul Watson. "Toward scalable, parallel progressive hedging for stochastic unit commitment." In Power and Energy Society General Meeting (PES), 2013 IEEE, pp. 1-5. IEEE, 2013.

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Citation Information
Sarah M. Ryan, Roger J.B. Wetts and David L. Woodruff. "Toward scalable, parallel progressive hedging for stochastic unit commitment" Vancouver, BC, Canada(2013)
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