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Thermodynamic information system for diagnosis and prognosis of power plant operation condition

Author

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  • Silva, J.A.M.
  • Venturini, O.J.
  • Lora, E.E.S.
  • Pinho, A.F.
  • Santos, J.J.C.S.

Abstract

A thermodynamic information system for diagnosis and prognosis of an existing power plant was developed. The system is based on an analytic approach that informs the current thermodynamic condition of all cycle components, as well as the improvement that can be obtained in the cycle performance by the elimination of the discovered anomalies. The effects induced by components anomalies and repairs in other components efficiency, which have proven to be one of the main drawbacks in the diagnosis and prognosis analyses, are taken into consideration owing to the use of performance curves and corrected performance curves together with the thermodynamic data collected from the distributed control system. The approach used to develop the system is explained, the system implementation in a real gas turbine cogeneration combined cycle is described and the results are discussed.

Suggested Citation

  • Silva, J.A.M. & Venturini, O.J. & Lora, E.E.S. & Pinho, A.F. & Santos, J.J.C.S., 2011. "Thermodynamic information system for diagnosis and prognosis of power plant operation condition," Energy, Elsevier, vol. 36(7), pages 4072-4079.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:7:p:4072-4079
    DOI: 10.1016/j.energy.2011.04.040
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    Cited by:

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    2. Amorim Lorenzoni, Raphael & Conceição Soares Santos, José Joaquim & Barbosa Lourenço, Atilio & Marcon Donatelli, João Luiz, 2020. "On the accuracy improvement of thermoeconomic diagnosis through exergy disaggregation and dissipative equipment isolation," Energy, Elsevier, vol. 194(C).
    3. Nguyen, Tuong-Van & Barbosa, Yuri M. & da Silva, Julio A.M. & de Oliveira Junior, Silvio, 2019. "A novel methodology for the design and optimisation of oil and gas offshore platforms," Energy, Elsevier, vol. 185(C), pages 158-175.
    4. Barbosa, Yuri M. & da Silva, Julio A.M. & Junior, Silvio de O. & Torres, Ednildo A., 2019. "Deep seawater as efficiency improver for cogeneration plants of petroleum production units," Energy, Elsevier, vol. 177(C), pages 29-43.
    5. Barbosa, Yuri M. & da Silva, Julio A.M. & Junior, Silvio de O. & Torres, Ednildo A., 2018. "Performance assessment of primary petroleum production cogeneration plants," Energy, Elsevier, vol. 160(C), pages 233-244.
    6. Zhou, Dengji & Zhang, Huisheng & Weng, Shilie, 2014. "A novel prognostic model of performance degradation trend for power machinery maintenance," Energy, Elsevier, vol. 78(C), pages 740-746.
    7. Centeno González, Felipe O. & Mahkamov, Khamid & Silva Lora, Electo E. & Andrade, Rubenildo V. & Jaen, René Lesme, 2013. "Prediction by mathematical modeling of the behavior of an internal combustion engine to be fed with gas from biomass, in comparison to the same engine fueled with gasoline or methane," Renewable Energy, Elsevier, vol. 60(C), pages 427-432.

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