A unified acceptance test framework for power plant gas turbine control systems.

Acceptance test Control system Gas turbine Modeling and identification Robust control

Journal

ISA transactions
ISSN: 1879-2022
Titre abrégé: ISA Trans
Pays: United States
ID NLM: 0374750

Informations de publication

Date de publication:
Feb 2019
Historique:
received: 29 06 2018
revised: 20 09 2018
accepted: 08 10 2018
pubmed: 6 11 2018
medline: 6 11 2018
entrez: 3 11 2018
Statut: ppublish

Résumé

Renovation and retrofit of gas turbine control systems yield significant economic savings, enhanced reliability, and improved performance. In recent years, the gas turbine industry is increasingly facing the need to well-established procedures for the acceptance tests of renovated control systems. This paper proposes a unified framework to evaluate the performance of renovated gas turbine control systems. Under a set of assumptions on the ambient and fuel conditions, a low-complexity modular model is presented and identified using optimization-oriented identification techniques. The accuracy of the proposed model is validated through experimental studies in full-load, min-load, and no-load operating conditions. Subsequently, a model-based analysis framework is proposed to determine realistic levels of tracking performance, robustness margin and disturbance attenuation by utilizing the supporting tools in robust control theory. Quantitative and qualitative performance indices are introduced to provide acceptance criteria for the existing control loops as compared to the optimal ones. The proposed procedure is applied to a W251-B2 gas turbine manufactured by Westinghouse company, and the results show that the optimal control system outperforms the existing controllers based on quantitative and qualitative indices. The proposed procedure determines whether the overall performance of the renovated control system sufficiently meets the requirements.

Identifiants

pubmed: 30385036
pii: S0019-0578(18)30389-6
doi: 10.1016/j.isatra.2018.10.010
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

262-273

Informations de copyright

Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Auteurs

Mostafa Eslami (M)

Sharif University of Technology, Tehran, Iran.

Maryam Babazadeh (M)

Sharif University of Technology, Tehran, Iran. Electronic address: babazadeh@sharif.edu.

Classifications MeSH