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dc.contributor.authorSahu, Reetik Kumar
dc.contributor.authorMcLaughlin, Dennis
dc.date.accessioned2020-06-08T20:16:23Z
dc.date.available2020-06-08T20:16:23Z
dc.date.issued2018-10
dc.date.submitted2018-10
dc.identifier.issn0043-1397
dc.identifier.issn1944-7973
dc.identifier.urihttps://hdl.handle.net/1721.1/125733
dc.description.abstractRevenues from hydropower generation often depend on the operator's ability to provide firm power in the presence of uncertain inflows. The primary options available for optimizing revenue are negotiation of a firm power contract before operations begin and adjustment of the reservoir release during operations. Contract and release strategy optimization are closely coupled and most appropriately analyzed with stochastic real-time control methods. Here we use an ensemble-based approach to stochastic optimization that provides a convenient way to construct nonparametric revenue probability distributions to explore the implications of uncertainty. The firm power contract is a simplified bilateral fixed price agreement that partially insulates operator and buyer from price fluctuations. The release control laws and firm energy target are jointly optimized to maximize the operator's expected revenue. Revenue probability distributions and related spill performance statistics indicate that predictive operating strategies such as stochastic dynamic programming and model predictive control can give significantly better performance than standard deterministic operating rules. The performance obtained from batch optimization with perfect inflow information establishes a convenient upper bound on potential revenue and provides a baseline for assessing the significance of differences between real-time operating strategies. Sensitivity analysis indicates that the benefits of predictive operational strategies are greatest for reservoirs with medium nondimensional residence times and less important for reservoirs with large residence times. Overall, probabilistic analysis of the coupled hydropower contract-operations problem provides a realistic way to assess revenue and risk for reservoirs that must provide firm power when inflows are uncertain. Keywords: optimal control; hydropower; stochastic optimization; contract optimization; real-time controlen_US
dc.language.isoen
dc.publisherAmerican Geophysical Union (AGU)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1029/2018wr022753en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceOther repositoryen_US
dc.titleAn Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real‐Time Reservoir Operating Rulesen_US
dc.typeArticleen_US
dc.identifier.citationSahu, Reetik Kumar and Dennis B. McLaughlin. "An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real‐Time Reservoir Operating Rules." Water Resources Research, 54, 10 (October 2018): 8401-8419.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.relation.journalWater Resources Researchen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-05-28T19:29:23Z
dspace.date.submission2020-05-28T19:29:25Z
mit.journal.volume54en_US
mit.journal.issue10en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusComplete


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