Toward scalable, parallel progressive hedging for stochastic unit commitment Ryan, Sarah Wetts, Roger Ryan, Sarah Woodruff, David
dc.contributor.department Industrial and Manufacturing Systems Engineering 2018-02-18T14:11:13.000 2020-06-30T04:47:24Z 2020-06-30T04:47:24Z Tue Jan 01 00:00:00 UTC 2013 2017-06-22 2013-01-01
dc.description.abstract <p>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).</p>
dc.description.comments <p>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 <em>Power and Energy Society General Meeting (PES), 2013 IEEE</em>, pp. 1-5. IEEE, 2013.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 1097
dc.identifier.contextkey 10337309
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath imse_conf/96
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 02:35:23 UTC 2022
dc.source.uri 10.1109/PESMG.2013.6673013
dc.subject.disciplines Industrial Engineering
dc.subject.disciplines Systems Engineering
dc.subject.keywords Wind energy
dc.subject.keywords Computation time
dc.subject.keywords Optimization methods
dc.subject.keywords Parallel algorithms
dc.subject.keywords Power generation scheduling
dc.title Toward scalable, parallel progressive hedging for stochastic unit commitment
dc.type article
dc.type.genre conference
dspace.entity.type Publication
relation.isAuthorOfPublication 22d808f1-c309-4cb1-8d3e-14c57a6b96a9
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
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