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Robust methodology for steady state measurements estimation based framework for a reliable long term thermal power plant operation performance monitoring

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  • Vazquez, Luis
  • Blanco, Jesús María
  • Ramis, Rolando
  • Peña, Francisco
  • Diaz, David

Abstract

Steady state identification is a process control research approximating the successive values of samples in steady state into its average values. According to the plant-wide control hierarchical model, these results implement monitoring and optimizing functions. Thermal power plant operates into a wide range of mean value active power. Systematic plant-wide slow developing disturbances affect the power plant operation performance through deviations of each process variable between its current true process value and the expected good performance relative value. Supervised records are realizations contaminated with stationary correlated noise carrying successive steady state deviations. Long term thermal power plant operation performance monitoring depending on (i) accuracy and precision of steady state identification method and (ii) fitness approximation per process variable versus mean value active power. This paper bases: (i) a computational experiment design to calibrate a steady state identification before to embed into a real system, and (ii) a solution for curve structure to capture good performance relative value per process variable with few knots availability right after the start-up of the plant at base load regime. A case study tracking the cumulative effects of degradation due to fouling on a heat exchanger was performed.

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  • Vazquez, Luis & Blanco, Jesús María & Ramis, Rolando & Peña, Francisco & Diaz, David, 2015. "Robust methodology for steady state measurements estimation based framework for a reliable long term thermal power plant operation performance monitoring," Energy, Elsevier, vol. 93(P1), pages 923-944.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:923-944
    DOI: 10.1016/j.energy.2015.09.044
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    as
    1. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    2. Fink, Olga & Zio, Enrico & Weidmann, Ulrich, 2014. "Predicting component reliability and level of degradation with complex-valued neural networks," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 198-206.
    3. Jiang, Xiaolong & Liu, Pei & Li, Zheng, 2014. "Data reconciliation and gross error detection for operational data in power plants," Energy, Elsevier, vol. 75(C), pages 14-23.
    4. Strušnik, Dušan & Avsec, Jurij, 2015. "Artificial neural networking and fuzzy logic exergy controlling model of combined heat and power system in thermal power plant," Energy, Elsevier, vol. 80(C), pages 318-330.
    5. Blanco, J.M. & Vazquez, L. & Peña, F. & Diaz, D., 2013. "New investigation on diagnosing steam production systems from multivariate time series applied to thermal power plants," Applied Energy, Elsevier, vol. 101(C), pages 589-599.
    6. Cafaro, S. & Napoli, L. & Traverso, A. & Massardo, A.F., 2010. "Monitoring of the thermoeconomic performance in an actual combined cycle power plant bottoming cycle," Energy, Elsevier, vol. 35(2), pages 902-910.
    7. Mirandola, A. & Stoppato, A. & Lo Casto, E., 2010. "Evaluation of the effects of the operation strategy of a steam power plant on the residual life of its devices," Energy, Elsevier, vol. 35(2), pages 1024-1032.
    8. Shao, Meng & Zhu, Xin-Jian & Cao, Hong-Fei & Shen, Hai-Feng, 2014. "An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system," Energy, Elsevier, vol. 67(C), pages 268-275.
    9. Arriola-Medellín, Alejandro & Manzanares-Papayanopoulos, Emilio & Romo-Millares, César, 2014. "Diagnosis and redesign of power plants using combined Pinch and Exergy Analysis," Energy, Elsevier, vol. 72(C), pages 643-651.
    10. Poma, Christian & Verda, Vittorio & Consonni, Stefano, 2010. "Design and performance evaluation of a waste-to-energy plant integrated with a combined cycle," Energy, Elsevier, vol. 35(2), pages 786-793.
    11. 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.
    12. Stoppato, A. & Mirandola, A. & Meneghetti, G. & Lo Casto, E., 2012. "On the operation strategy of steam power plants working at variable load: Technical and economic issues," Energy, Elsevier, vol. 37(1), pages 228-236.
    13. Soleimani, Hamed & Govindan, Kannan, 2014. "Reverse logistics network design and planning utilizing conditional value at risk," European Journal of Operational Research, Elsevier, vol. 237(2), pages 487-497.
    14. Kiluk, Sebastian, 2012. "Algorithmic acquisition of diagnostic patterns in district heating billing system," Applied Energy, Elsevier, vol. 91(1), pages 146-155.
    15. Blanco, Jesús M. & Vazquez, L. & Peña, F., 2012. "Investigation on a new methodology for thermal power plant assessment through live diagnosis monitoring of selected process parameters; application to a case study," Energy, Elsevier, vol. 42(1), pages 170-180.
    16. Biagetti, Tatiana & Sciubba, Enrico, 2004. "Automatic diagnostics and prognostics of energy conversion processes via knowledge-based systems," Energy, Elsevier, vol. 29(12), pages 2553-2572.
    17. Markowski, Mariusz & Trafczynski, Marian & Urbaniec, Krzysztof, 2013. "Identification of the influence of fouling on the heat recovery in a network of shell and tube heat exchangers," Applied Energy, Elsevier, vol. 102(C), pages 755-764.
    18. Łopata, Stanisław & Ocłoń, Paweł, 2015. "Numerical study of the effect of fouling on local heat transfer conditions in a high-temperature fin-and-tube heat exchanger," Energy, Elsevier, vol. 92(P1), pages 100-116.
    19. Lee, Seongjun & Kim, Jonghoon, 2015. "Discrete wavelet transform-based denoising technique for advanced state-of-charge estimator of a lithium-ion battery in electric vehicles," Energy, Elsevier, vol. 83(C), pages 462-473.
    20. Thurner, Paul W. & Mittermeier, Laura & Küchenhoff, Helmut, 2014. "How long does it take to build a nuclear power plant? A non-parametric event history approach with P-splines," Energy Policy, Elsevier, vol. 70(C), pages 163-171.
    21. Cavalcante, Cristiano A.V. & Lopes, Rodrigo S., 2015. "Multi-criteria model to support the definition of opportunistic maintenance policy: A study in a cogeneration system," Energy, Elsevier, vol. 80(C), pages 32-40.
    22. Jiang, Xiaolong & Liu, Pei & Li, Zheng, 2014. "Gross error isolability for operational data in power plants," Energy, Elsevier, vol. 74(C), pages 918-927.
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    Cited by:

    1. Markowski, Mariusz & Trzcinski, Przemyslaw, 2019. "On-line control of the heat exchanger network under fouling constraints," Energy, Elsevier, vol. 185(C), pages 521-526.
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