Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

Externe Organisationen

  • Hochschule Hannover (HsH)
  • Siemens AG
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Details

OriginalspracheEnglisch
Titel des SammelwerksCANDO-EPE 2023 - Proceedings
UntertitelIEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten237-242
Seitenumfang6
ISBN (elektronisch)9798350328752
ISBN (Print)979-8-3503-2876-9
PublikationsstatusVeröffentlicht - 2024
Veranstaltung6th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2023 - Budapest, Ungarn
Dauer: 19 Okt. 202320 Okt. 2023

Publikationsreihe

NameProceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering
ISSN (Print)2831-4492
ISSN (elektronisch)2831-4506

Abstract

As simulation studies play a significant role in the development of gas turbine plants and their control systems, it is important to validate their results and adapt the data from real plants. In this paper, two examples are presented on how the interaction between real plant data and the corresponding models can be used efficiently. The first example shows that the accuracy in simulating a load rejection event can be improved significantly by using real world data for identification of model parameters. Instead of developing simplified models as presented in related work, a detailed existing model is object of this identification. For the second example, the opposite direction is illustrated: to possibly support the commissioning progress, a reduced model is utilized to optimize the parameters defining the primary frequency response of a gas turbine plant. The same black-box optimization algorithm is used and its capability to perform different optimization tasks is shown.

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Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization. / Peters, Lukas; Schafer, Marc; Kastner, Tim Cedrik et al.
CANDO-EPE 2023 - Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering. Institute of Electrical and Electronics Engineers Inc., 2024. S. 237-242 (Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Peters, L, Schafer, M, Kastner, TC, Kutzner, R & Lutz Hofmann, H 2024, Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization. in CANDO-EPE 2023 - Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering. Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering, Institute of Electrical and Electronics Engineers Inc., S. 237-242, 6th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2023, Budapest, Ungarn, 19 Okt. 2023. https://doi.org/10.1109/CANDO-EPE60507.2023.10418001
Peters, L., Schafer, M., Kastner, T. C., Kutzner, R., & Lutz Hofmann, H. (2024). Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization. In CANDO-EPE 2023 - Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering (S. 237-242). (Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CANDO-EPE60507.2023.10418001
Peters L, Schafer M, Kastner TC, Kutzner R, Lutz Hofmann H. Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization. in CANDO-EPE 2023 - Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering. Institute of Electrical and Electronics Engineers Inc. 2024. S. 237-242. (Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering). Epub 2024 Feb 7. doi: 10.1109/CANDO-EPE60507.2023.10418001
Peters, Lukas ; Schafer, Marc ; Kastner, Tim Cedrik et al. / Efficient Identification and Tuning of Gas Turbine Models Using Black-Box Optimization. CANDO-EPE 2023 - Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering. Institute of Electrical and Electronics Engineers Inc., 2024. S. 237-242 (Proceedings: IEEE 6th International Conference and Workshop Obuda on Electrical and Power Engineering).
Download
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AU - Schafer, Marc

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AU - Kutzner, Rudiger

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