IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v93y2015ip1p923-944.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215012542
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.09.044?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. 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.
    2. 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.
    3. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    4. 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.
    5. 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.
    6. Jiang, Xiaolong & Liu, Pei & Li, Zheng, 2014. "Gross error isolability for operational data in power plants," Energy, Elsevier, vol. 74(C), pages 918-927.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    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. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    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, Sisi & Liu, Pei & Li, Zheng, 2018. "Enhancement of performance monitoring of a coal-fired power plant via dynamic data reconciliation," Energy, Elsevier, vol. 151(C), pages 203-210.
    2. Du, Zhimin & Chen, Ling & Jin, Xinqiao, 2017. "Data-driven based reliability evaluation for measurements of sensors in a vapor compression system," Energy, Elsevier, vol. 122(C), pages 237-248.
    3. Guo, Sisi & Liu, Pei & Li, Zheng, 2016. "Identification and isolability of multiple gross errors in measured data for power plants," Energy, Elsevier, vol. 114(C), pages 177-187.
    4. Markowski, Mariusz & Trzcinski, Przemyslaw, 2019. "On-line control of the heat exchanger network under fouling constraints," Energy, Elsevier, vol. 185(C), pages 521-526.

    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. 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.
    2. Guo, Sisi & Liu, Pei & Li, Zheng, 2016. "Identification and isolability of multiple gross errors in measured data for power plants," Energy, Elsevier, vol. 114(C), pages 177-187.
    3. Guo, Sisi & Liu, Pei & Li, Zheng, 2016. "Data reconciliation for the overall thermal system of a steam turbine power plant," Applied Energy, Elsevier, vol. 165(C), pages 1037-1051.
    4. Jiang, Xiaolong & Liu, Pei & Li, Zheng, 2014. "A data reconciliation based framework for integrated sensor and equipment performance monitoring in power plants," Applied Energy, Elsevier, vol. 134(C), pages 270-282.
    5. Szega, Marcin, 2018. "Issues of an optimization of measurements location in redundant measurements systems of an energy conversion process – A case study," Energy, Elsevier, vol. 165(PA), pages 1034-1047.
    6. Loyola-Fuentes, José & Smith, Robin, 2019. "Data reconciliation and gross error detection in crude oil pre-heat trains undergoing shell-side and tube-side fouling deposition," Energy, Elsevier, vol. 183(C), pages 368-384.
    7. Jesse G. Wales & Alexander J. Zolan & William T. Hamilton & Alexandra M. Newman & Michael J. Wagner, 2023. "Combining simulation and optimization to derive operating policies for a concentrating solar power plant," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 119-150, March.
    8. 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.
    9. Du, Zhimin & Chen, Ling & Jin, Xinqiao, 2017. "Data-driven based reliability evaluation for measurements of sensors in a vapor compression system," Energy, Elsevier, vol. 122(C), pages 237-248.
    10. Łukowicz, Henryk & Rusin, Andrzej, 2018. "The impact of the control method of cyclic operation on the power unit efficiency and life," Energy, Elsevier, vol. 150(C), pages 565-574.
    11. Yu, Jianxi & Han, Wenquan & Chen, Kang & Liu, Pei & Li, Zheng, 2022. "Gross error detection in steam turbine measurements based on data reconciliation of inequality constraints," Energy, Elsevier, vol. 253(C).
    12. Xu, Jing & Bi, Dapeng & Ma, Suxia & Bai, Jin, 2020. "A data-based approach for benchmark interval determination with varying operating conditions in the coal-fired power unit," Energy, Elsevier, vol. 211(C).
    13. Zhang, Hengliang & Xie, Danmei & Yu, Yanzhi & Yu, Liangying, 2016. "Online optimal control schemes of inlet steam temperature during startup of steam turbines considering low cycle fatigue," Energy, Elsevier, vol. 117(P1), pages 105-115.
    14. Wang, Yanhong & Cao, Lihua & Li, Xingcan & Wang, Jiaxing & Hu, Pengfei & Li, Bo & Li, Yong, 2020. "A novel thermodynamic method and insight of heat transfer characteristics on economizer for supercritical thermal power plant," Energy, Elsevier, vol. 191(C).
    15. Yu, Jianxi & Liu, Pei & Li, Zheng, 2021. "Data reconciliation of the thermal system of a double reheat power plant for thermal calculation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    16. Eslick, John C. & Zamarripa, Miguel A. & Ma, Jinliang & Wang, Maojian & Bhattacharya, Indrajit & Rychener, Brian & Pinkston, Philip & Bhattacharyya, Debangsu & Zitney, Stephen E. & Burgard, Anthony P., 2022. "Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application," Applied Energy, Elsevier, vol. 319(C).
    17. Rusin, Andrzej & Bieniek, Michał & Lipka, Marian, 2016. "Assessment of the rise in the turbine operation risk due to increased cyclicity of the power unit operation," Energy, Elsevier, vol. 96(C), pages 394-403.
    18. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    19. 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.
    20. Badur, Janusz & Ziółkowski, Paweł & Sławiński, Daniel & Kornet, Sebastian, 2015. "An approach for estimation of water wall degradation within pulverized-coal boilers," Energy, Elsevier, vol. 92(P1), pages 142-152.

    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:93:y:2015:i:p1:p:923-944. 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.