LAPSE:2023.8036v1
Published Article

LAPSE:2023.8036v1
Tuning Model Predictive Control for Rigorous Operation of the Dalsfoss Hydropower Plant
February 24, 2023
Abstract
Model predictive control is considered an attractive control strategy for the operation of hydropower station systems. It is due to the operational constraints or requirements of the hydropower system for safe and eco-friendly operation. However, it is mandatory to tune the model predictive control to achieve its best and most efficient performance. This paper determines the appropriate tunning on the weight parameters and the length of the prediction horizon for implementing model predictive control on the Dalsfoss hydropower system. For that, several test sets of the weight parameter for the optimal control problem and different lengths of the prediction horizon are simulated and compared.
Model predictive control is considered an attractive control strategy for the operation of hydropower station systems. It is due to the operational constraints or requirements of the hydropower system for safe and eco-friendly operation. However, it is mandatory to tune the model predictive control to achieve its best and most efficient performance. This paper determines the appropriate tunning on the weight parameters and the length of the prediction horizon for implementing model predictive control on the Dalsfoss hydropower system. For that, several test sets of the weight parameter for the optimal control problem and different lengths of the prediction horizon are simulated and compared.
Record ID
Keywords
control application, flood management, Model Predictive Control, process control, rigorous operation, tuning
Subject
Suggested Citation
Jeong C, Sharma R. Tuning Model Predictive Control for Rigorous Operation of the Dalsfoss Hydropower Plant. (2023). LAPSE:2023.8036v1
Author Affiliations
Jeong C: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, N-3918 Porsgrunn, Norway [ORCID]
Sharma R: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, N-3918 Porsgrunn, Norway
Sharma R: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, N-3918 Porsgrunn, Norway
Journal Name
Energies
Volume
15
Issue
22
First Page
8678
Year
2022
Publication Date
2022-11-18
ISSN
1996-1073
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Original Submission
Other Meta
PII: en15228678, Publication Type: Journal Article
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LAPSE:2023.8036v1
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https://doi.org/10.3390/en15228678
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Feb 24, 2023
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