IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v120y2017icp488-497.html
   My bibliography  Save this article

Dynamic model linearization of two shafts gas turbine via their input/output data around the equilibrium points

Author

Listed:
  • Hadroug, Nadji
  • Hafaifa, Ahmed
  • Kouzou, Abdellah
  • Chaibet, Ahmed

Abstract

The present paper deals with a linearization strategy of the non-linear model presenting a gas turbine with two shafts. Indeed, being able to describe and to explain the various phenomena involved and interacted in the dynamics of the turbines has a great impact in practice. Whereas; the modeling of the gas turbine using real data allows to approximate the variables of this nonlinear system based on a linearization approach. It is obvious that the advantage of this approach is to ensure the prediction and the monitoring of the gas turbine behavior to assess its optimized control. In this paper the obtained results based on real data of onsite measurements allow to understand and to analyze the phenomena interacting in the gas turbine system, and therefore the prediction of its dynamic behavior can be ensured.

Suggested Citation

  • Hadroug, Nadji & Hafaifa, Ahmed & Kouzou, Abdellah & Chaibet, Ahmed, 2017. "Dynamic model linearization of two shafts gas turbine via their input/output data around the equilibrium points," Energy, Elsevier, vol. 120(C), pages 488-497.
  • Handle: RePEc:eee:energy:v:120:y:2017:i:c:p:488-497
    DOI: 10.1016/j.energy.2016.11.099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216317388
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.11.099?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Duan, Jiandong & Sun, Li & Wang, Guanglin & Wu, Fengjiang, 2015. "Nonlinear modeling of regenerative cycle micro gas turbine," Energy, Elsevier, vol. 91(C), pages 168-175.
    2. Nikpey, H. & Assadi, M. & Breuhaus, P. & Mørkved, P.T., 2014. "Experimental evaluation and ANN modeling of a recuperative micro gas turbine burning mixtures of natural gas and biogas," Applied Energy, Elsevier, vol. 117(C), pages 30-41.
    3. Zhu, Sipeng & Deng, Kangyao & Liu, Sheng, 2015. "Modeling and extrapolating mass flow characteristics of a radial turbocharger turbine," Energy, Elsevier, vol. 87(C), pages 628-637.
    4. Liu, Ji-Zhen & Yan, Shu & Zeng, De-Liang & Hu, Yong & Lv, You, 2015. "A dynamic model used for controller design of a coal fired once-through boiler-turbine unit," Energy, Elsevier, vol. 93(P2), pages 2069-2078.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guo, Huan & Xu, Yujie & Kang, Haoyuan & Guo, Wenbing & Liu, Yu & Zhang, Xinjing & Zhou, Xuezhi & Chen, Haisheng, 2023. "From theory to practice: Evaluating the thermodynamic design landscape of compressed air energy storage systems," Applied Energy, Elsevier, vol. 352(C).
    2. Hou, Guolian & Gong, Linjuan & Huang, Congzhi & Zhang, Jianhua, 2020. "Fuzzy modeling and fast model predictive control of gas turbine system," Energy, Elsevier, vol. 200(C).
    3. Rahmoune, Mohamed Ben & Hafaifa, Ahmed & Kouzou, Abdellah & Chen, XiaoQi & Chaibet, Ahmed, 2021. "Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 179(C), pages 23-47.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zong, Chao & Ji, Chenzhen & Cheng, Jiaying & Zhu, Tong & Guo, Desan & Li, Chengqin & Duan, Fei, 2022. "Toward off-design loads: Investigations on combustion and emissions characteristics of a micro gas turbine combustor by external combustion-air adjustments," Energy, Elsevier, vol. 253(C).
    2. Kim, Jeong Ho & Kim, Tong Seop, 2019. "A new approach to generate turbine map data in the sub-idle operation regime of gas turbines," Energy, Elsevier, vol. 173(C), pages 772-784.
    3. Zheng, Bingle & Wu, Xiao, 2022. "Integrated capacity configuration and control optimization of off-grid multiple energy system for transient performance improvement," Applied Energy, Elsevier, vol. 311(C).
    4. Liu, Zheng & Copeland, Colin, 2018. "New method for mapping radial turbines exposed to pulsating flows," Energy, Elsevier, vol. 162(C), pages 1205-1222.
    5. Rossi, Francesco & Velázquez, David, 2015. "A methodology for energy savings verification in industry with application for a CHP (combined heat and power) plant," Energy, Elsevier, vol. 89(C), pages 528-544.
    6. Jiabao Gu & Hui Wang & Wuquan Li & Ben Niu, 2022. "Adaptive State-Feedback Stabilization for Stochastic Nonlinear Systems with Time-Varying Powers and Unknown Covariance," Mathematics, MDPI, vol. 10(16), pages 1-16, August.
    7. Do, Kyu Hyung & Kim, Taehoon & Han, Yong-Shik & Choi, Byung-Il & Kim, Myungbae, 2017. "Investigation on flow distribution of the fuel supply nozzle in the annular combustor of a micro gas turbine," Energy, Elsevier, vol. 126(C), pages 361-373.
    8. Ma, Zetai & Xie, Wenping & Xiang, Hanchun & Zhang, Kun & Yang, Mingyang & Deng, Kangyao, 2023. "Thermodynamic analysis of power recovery of marine diesel engine under high exhaust backpressure by additional electrically driven compressor," Energy, Elsevier, vol. 266(C).
    9. Wei, Jiangshan & Xue, Yingxian & Deng, Kangyao & Yang, Mingyang & Liu, Ying, 2020. "A direct comparison of unsteady influence of turbine with twin-entry and single-entry scroll on performance of internal combustion engine," Energy, Elsevier, vol. 212(C).
    10. Kim, Min Jae & Kim, Jeong Ho & Kim, Tong Seop, 2018. "The effects of internal leakage on the performance of a micro gas turbine," Applied Energy, Elsevier, vol. 212(C), pages 175-184.
    11. Li, Huijuan & Li, Wuquan & Gu, Jianzhong, 2022. "Decentralized stabilization of large-scale stochastic nonlinear systems with time-varying powers," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    12. Yize Liu & Theoklis Nikolaidis & Seyed Hossein Madani & Mohammad Sarkandi & Abdelaziz Gamil & Muhamad Firdaus Sainal & Seyed Vahid Hosseini, 2022. "Multi-Fidelity Combustor Design and Experimental Test for a Micro Gas Turbine System," Energies, MDPI, vol. 15(7), pages 1-29, March.
    13. Esmaeili, Mohammad & Moradi, Hamed, 2023. "Robust & nonlinear control of an ultra-supercritical coal fired once-through boiler-turbine unit in order to optimize the uncertain problem," Energy, Elsevier, vol. 282(C).
    14. Chen Chen & Lei Pan & Shanjian Liu & Li Sun & Kwang Y. Lee, 2018. "A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control," Sustainability, MDPI, vol. 10(12), pages 1-21, December.
    15. Zhang, Hongfu & Gao, Mingming & Fan, Haohao & Zhang, Kaiping & Zhang, Jiahui, 2022. "A dynamic model for supercritical once-through circulating fluidized bed boiler-turbine units," Energy, Elsevier, vol. 241(C).
    16. Tregenza, Owen & Olshina, Noam & Hield, Peter & Manzie, Chris & Hulston, Chris, 2022. "A comparison of turbine mass flow models based on pragmatic identification data sets for turbogenerator model development," Energy, Elsevier, vol. 247(C).
    17. Wu, Xiao & Wang, Meihong & Shen, Jiong & Li, Yiguo & Lawal, Adekola & Lee, Kwang Y., 2019. "Reinforced coordinated control of coal-fired power plant retrofitted with solvent based CO2 capture using model predictive controls," Applied Energy, Elsevier, vol. 238(C), pages 495-515.
    18. Wu, Zhenlong & Li, Donghai & Xue, Yali & Chen, YangQuan, 2019. "Gain scheduling design based on active disturbance rejection control for thermal power plant under full operating conditions," Energy, Elsevier, vol. 185(C), pages 744-762.
    19. Serrano, José Ramón & Navarro, Roberto & García-Cuevas, Luis Miguel & Inhestern, Lukas Benjamin, 2018. "Turbocharger turbine rotor tip leakage loss and mass flow model valid up to extreme off-design conditions with high blade to jet speed ratio," Energy, Elsevier, vol. 147(C), pages 1299-1310.
    20. Ruitao Wang & Hui Wang & Wuquan Li & Ben Niu, 2022. "Output Tracking Control of Random Nonlinear Time-Varying Systems," Mathematics, MDPI, vol. 10(14), pages 1-13, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:120:y:2017:i:c:p:488-497. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.