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dc.contributor.author
Flamm, Benjamin
dc.contributor.author
Eichler, Annika
dc.contributor.author
Warrington, Joseph
dc.contributor.author
Lygeros, John
dc.date.accessioned
2021-07-16T05:12:30Z
dc.date.available
2020-01-07T11:00:16Z
dc.date.available
2020-01-09T16:01:31Z
dc.date.available
2020-01-15T12:32:21Z
dc.date.available
2020-03-30T08:00:22Z
dc.date.available
2020-12-21T13:43:18Z
dc.date.available
2021-07-15T11:39:37Z
dc.date.available
2021-07-16T05:12:30Z
dc.date.issued
2021-01
dc.identifier.issn
1063-6536
dc.identifier.issn
1558-0865
dc.identifier.other
10.1109/TCST.2019.2961645
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/388081
dc.identifier.doi
10.3929/ethz-b-000388081
dc.description.abstract
We present an approximate method for solving nonlinear control problems over long time horizons, in which the full nonlinear model is preserved over an initial part of the horizon, while the remainder of the horizon is modeled using a linear relaxation. As this approximate problem may still be too large to solve directly, we present a Benders decomposition-based solution algorithm that iterates between solving the nonlinear and linear parts of the horizon. This extends the dual dynamic programming approach commonly employed for optimization of linearized hydro power systems. We prove that the proposed algorithm converges after a finite number of iterations, even when the nonlinear initial stage problems are solved inexactly. We also bound the suboptimality of the split-horizon method with respect to the original nonlinear problem, in terms of the properties of a map between the linear and nonlinear state-input trajectories. We then apply this method to a case study concerning a multiple reservoir hydro system, approximating the nonlinear head effects in the second stage using McCormick envelopes. We demonstrate that near-optimal solutions can be obtained in a shrinking horizon setting when the full nonlinear model is used for only a short initial section of the horizon. For this example, the approach is shown to be more practical than both conventional dynamic programming and a multi-cell McCormick envelope approximation from the literature.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
Two-Stage Dual Dynamic Programming with Application to Nonlinear Hydro Scheduling
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2020-01-23
ethz.journal.title
IEEE Transactions on Control Systems Technology
ethz.journal.volume
29
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
IEEE trans. control syst. technol.
ethz.pages.start
96
en_US
ethz.pages.end
107
en_US
ethz.size
12 p. accepted version
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.grant
Optimal control at large
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
New York, NY
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
en_US
ethz.grant.agreementno
787845
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.date.deposited
2020-01-07T11:00:23Z
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-12-21T13:43:26Z
ethz.rosetta.lastUpdated
2024-02-02T14:20:07Z
ethz.rosetta.versionExported
true
ethz.COinS
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