Tuning Model Predictive Control for Rigorous Operation of the Dalsfoss Hydropower Plant

Changhun Jeong () and Roshan Sharma
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Changhun Jeong: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, N-3918 Porsgrunn, Norway
Roshan Sharma: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, N-3918 Porsgrunn, Norway

Energies, 2022, vol. 15, issue 22, 1-11

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.

Keywords: model predictive control; process control; control application; flood management; rigorous operation; tuning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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