Scenario reduction for stochastic unit commitment with wind penetration

dc.contributor.author Feng, Yonghan
dc.contributor.author Ryan, Sarah
dc.contributor.author Ryan, Sarah
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-02-18T13:20:58.000
dc.date.accessioned 2020-06-30T04:47:18Z
dc.date.available 2020-06-30T04:47:18Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2014
dc.date.embargo 2017-06-06
dc.date.issued 2014-01-01
dc.description.abstract <p>Uncertainties in the day-ahead forecasts for load and wind energy availability are considered in a reliability unit commitment problem. A two-stage stochastic program is formulated to minimize total expected cost, where commitments of thermal units are viewed as first-stage decisions and dispatch is relegated to the second stage. Scenario paths of hourly loads are generated according to a weather forecast-based load model. Wind energy scenarios are obtained by identifying analogue historical days. Net load scenarios are then created by crossing scenarios from each set and subtracting wind energy from load. A new heuristic scenario reduction method termed forward selection in recourse clusters (FSRC) is customized to alleviate the computational burden. Results of applying FSRC are compared with those of a classical scenario reduction method, fast forward selection (FFS) by evaluating the expected dispatch costs when the commitment decisions derived from each subset of scenarios are applied to the whole scenario set. In an instance down-sampled from data of an Independent System Operator in the U.S., the expected dispatch costs for both scenario reduction methods are similar, but FSRC improves reliability.</p>
dc.description.comments <p>This is a manuscript of a proceedings published as Y. Feng and S. M. Ryan, Scenario Reduction for Stochastic Unit Commitment with Wind Penetration <em>IEEE Power and Energy Society General Meeting</em>, July 2014. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/imse_conf/84/
dc.identifier.articleid 1082
dc.identifier.contextkey 10260268
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath imse_conf/84
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/44345
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/imse_conf/84/2014_Ryan_ScenarioReduction.pdf|||Sat Jan 15 02:11:01 UTC 2022
dc.source.uri 10.1109/PESGM.2014.6939138
dc.subject.disciplines Industrial Engineering
dc.subject.disciplines Systems Engineering
dc.subject.keywords Stochastic processes
dc.subject.keywords Sensitivity
dc.subject.keywords Wind energy
dc.subject.keywords Generators
dc.subject.keywords Reliability
dc.subject.keywords Programming
dc.title Scenario reduction for stochastic unit commitment with wind penetration
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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