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Implementation of on-line performance monitoring system at Seoincheon and Sinincheon combined cycle power plant

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  • Kim, Si-Moon
  • Joo, Yong-Jin

Abstract

As a result of the restructuring of the Korean Power Generation Industry, Korean power companies are under increased pressure to increase capacity and lower operating costs. In order to achieve these goals, an on-line real-time performance monitoring system has been introduced to the Seoincheon and Sinincheon combined cycle power plants (CCPP). The on-line real-time performance monitoring and optimization system helps plant personnel operate the plants profitably by tracking plant performance changes based on real-time information. This paper outlines how the on-line performance monitoring system is being used to improve the operational efficiency and optimize equipment maintenance. Case studies showing the benefits provided by the system are presented. This system will be useful for the plants to respond to the competitive electricity market.

Suggested Citation

  • Kim, Si-Moon & Joo, Yong-Jin, 2005. "Implementation of on-line performance monitoring system at Seoincheon and Sinincheon combined cycle power plant," Energy, Elsevier, vol. 30(13), pages 2383-2401.
    • Handle: RePEc:eee:energy:v:30:y:2005:i:13:p:2383-2401
    DOI: 10.1016/j.energy.2005.01.001
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    References listed on IDEAS

    as
    1. Verda, Vittorio & Serra, Luis & Valero, Antonio, 2004. "The effects of the control system on the thermoeconomic diagnosis of a power plant," Energy, Elsevier, vol. 29(3), pages 331-359.
    2. Kwak, H.-Y. & Kim, D.-J. & Jeon, J.-S., 2003. "Exergetic and thermoeconomic analyses of power plants," Energy, Elsevier, vol. 28(4), pages 343-360.
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    Cited by:

    1. Finn, Joshua & Wagner, John & Bassily, Hany, 2010. "Monitoring strategies for a combined cycle electric power generator," Applied Energy, Elsevier, vol. 87(8), pages 2621-2627, August.
    2. 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.
    3. Usón, Sergio & Valero, Antonio & Correas, Luis, 2010. "Energy efficiency assessment and improvement in energy intensive systems through thermoeconomic diagnosis of the operation," Applied Energy, Elsevier, vol. 87(6), pages 1989-1995, June.
    4. Lee, Jae Hong & Kim, Tong Seop & Kim, Eui-hwan, 2017. "Prediction of power generation capacity of a gas turbine combined cycle cogeneration plant," Energy, Elsevier, vol. 124(C), pages 187-197.
    5. Liu, Zuming & Karimi, Iftekhar A., 2020. "Gas turbine performance prediction via machine learning," Energy, Elsevier, vol. 192(C).

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