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Predictive, adaptive model of PG 9171E gas turbine unit including control algorithms

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  • Plis, Marcin
  • Rusinowski, Henryk

Abstract

Contemporary thermal diagnostic systems require computational tools, including mathematical models. Because of required short computation time, these models should have a simple structure. Therefore very often, for these purposes, analytical-empirical models are used. Such models encompass both mass and energy balances and additional empirical functions whose coefficients are estimated by using the measurement results. As a result, changing technical conditions are taken into account. This paper presents a simulation model of PG 9171E gas turbine unit by General Electric which contains partial models of an axial compressor, low-emission combustion chambers, and an axial expander. The unknown values of empirical coefficients were estimated based on the operating data using the least squares method. The simulation model allows the calculation of non-measured operating parameters and energy assessment indicators, e.g. efficiency of electricity production. An important advantage of the developed model is that it has the capability of adapting to the changing technical conditions of the machine. The results of calculations were compared to the results of measurements. Model predictive quality was verified with the use of the determination factor and root mean square error.

Suggested Citation

  • Plis, Marcin & Rusinowski, Henryk, 2017. "Predictive, adaptive model of PG 9171E gas turbine unit including control algorithms," Energy, Elsevier, vol. 126(C), pages 247-255.
    • Handle: RePEc:eee:energy:v:126:y:2017:i:c:p:247-255
    DOI: 10.1016/j.energy.2017.03.027
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    Citations

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    Cited by:

    1. Żymełka, Piotr & Szega, Marcin, 2020. "Issues of an improving the accuracy of energy carriers production forecasting in a computer-aided system for monitoring the operation of a gas-fired cogeneration plant," Energy, Elsevier, vol. 209(C).
    2. Szega, Marcin & Żymełka, Piotr & Janda, Tomasz, 2022. "Improving the accuracy of electricity and heat production forecasting in a supervision computer system of a selected gas-fired CHP plant operation," Energy, Elsevier, vol. 239(PE).
    3. Mohammadian, Poorya Keshavarz & Saidi, Mohammad Hassan, 2019. "Simulation of startup operation of an industrial twin-shaft gas turbine based on geometry and control logic," Energy, Elsevier, vol. 183(C), pages 1295-1313.
    4. 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).
    5. Kim, Sangjo, 2021. "A new performance adaptation method for aero gas turbine engines based on large amounts of measured data," Energy, Elsevier, vol. 221(C).

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