Article | Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden | Flood Management of Lake Toke: MPC Operation under Uncertainty Linköping University Electronic Press Conference Proceedings
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Title:
Flood Management of Lake Toke: MPC Operation under Uncertainty
Author:
Itsaso Menchacatorre: University of South-Eastern Norway, Porsgrunn, Norway Roshan Sharma: University of South-Eastern Norway, Porsgrunn, Norway Beathe Furenes: Skagerak Kraft AS, Porsgrunn, Norway Bernt Lie: University of South-Eastern Norway, Porsgrunn, Norway
DOI:
https://doi.org/10.3384/ecp201709
Download:
Full text (pdf)
Year:
2019
Conference:
Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden
Issue:
170
Article no.:
002
Pages:
9-16
No. of pages:
8
Publication type:
Abstract and Fulltext
Published:
2020-01-24
ISBN:
978-91-7929-897-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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A deterministic reference tracking model predictive control (MPC) is in use at Skagerak Kraft for flood management of Lake Toke in Norway. An operational inflow estimate is used to predict the optimal gate opening at Dalsfos power station, with required constraints set by the Norwegian Water Resource and Energy Directorate (NVE). The operational inflow estimate is based on the meteorological forecast, and is uncertain; this may lead to broken concession requirements and unnecessary release of water through the floodgates. Currently not utilized, the meteorological uncertainty is quantified by an ensemble of possible weather forecasts. In this paper, quantified inflow uncertainty is studied and how this affects the operation of the current, deterministic MPC solution. Next, we develop an alternative, stochastic MPC solution based on multi objective optimization which directly takes the inflow uncertainty into consideration. A comparison of the results from both approaches concludes that the stochastic MPC solution seems to give better control by reducing the amount of water released through the flood gates. Furthermore, with less frequent update of the control signal, the benefit of the stochastic MPC is expected to increase.

Keywords: model predictive control, hydrology, uncertainty, multi objective optimization

Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Author:
Itsaso Menchacatorre, Roshan Sharma, Beathe Furenes, Bernt Lie
Title:
Flood Management of Lake Toke: MPC Operation under Uncertainty
DOI:
10.3384/ecp201709
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Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Author:
Itsaso Menchacatorre, Roshan Sharma, Beathe Furenes, Bernt Lie
Title:
Flood Management of Lake Toke: MPC Operation under Uncertainty
DOI:
https://doi.org10.3384/ecp201709
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Last updated: 2019-11-06