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  4. Optimal CAM Computation of Kaplan Turbines Accounting for Wear and Tear Originated by Frequency Control
 
conference paper

Optimal CAM Computation of Kaplan Turbines Accounting for Wear and Tear Originated by Frequency Control

Gerini, Francesco  
•
Vagnoni, Elena  
•
Cherkaoui, Rachid  
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July 29, 2021
Proceedings of the 2021 IEEE Madrid PowerTech
2021 IEEE Madrid PowerTech

Nowadays, the importance of providing frequency stability to power systems with hydropower units is significantly increasing due to the growing proportion of volatile renewable energy sources. However, the provision of such services, as frequency containment reserve, inevitably increases the wear and tear, decreasing the performance of the hydraulic machines, especially the Kaplan ones. In view of a growing demand for frequency containment reserve, it is important to quantify the performance decline and occasionally recompute the characteristic curves of the hydraulic machine to update the control system and reduce the efficiency loss. Since this process is usually expensive, as it requires off-line tests, this paper proposes a data-driven method to estimate the performance decrease of Kaplan turbines by leveraging operational recorded data. The proposed approach is applied to compute a new CAM relation for the run-of-river power plant of Vogelgrun. The new CAM, obtained with the proposed method is finally compared with real operational data.

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Type
conference paper
DOI
10.1109/PowerTech46648.2021.9495080
Author(s)
Gerini, Francesco  
Vagnoni, Elena  
Cherkaoui, Rachid  
Paolone, Mario  
Date Issued

2021-07-29

Publisher

IEEE

Published in
Proceedings of the 2021 IEEE Madrid PowerTech
ISBN of the book

978-1-665435-97-0

Total of pages

6

Start page

1

End page

6

Subjects

Hydroelectric power generation

•

Frequency containment reserve

•

Kaplan turbine

•

Optimal control

•

Wear and tear

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
DESL  
DESL  
Event nameEvent placeEvent date
2021 IEEE Madrid PowerTech

Madrid, Spain

28 June-2 July 2021

Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/188174
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