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An optimization of redundant measurements location for thermal capacity of power unit steam boiler calculations using data reconciliation method

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  • Szega, Marcin
  • Nowak, Grzegorz Tadeusz

Abstract

The optimization of a location of redundant measurements under varying loads for steam boiler of a supercritical power unit using the generalized method of data reconciliation has been carried out. The method of weighted objectives has been applied as a method of optimization. This method reduce the weighted multi-criteria optimization task to task one-dimensional. Measurement values have been determined by numerical experiment and the Monte Carlo method for the designed redundant measurements system. For this purpose, a mathematical simulation model of a supercritical steam power unit with power rating of 900 MW in the Thermoflex program has been worked out. In the optimization calculations of location of redundant measurements as an objective functions minimizing the relative standard deviation of a boiler thermal capacity and maximizing the Kullback-Leibler divergence have been accepted. In the calculation the measurements were taken into account, which can be located in the water-steam system of the boiler and in the high-pressure heat recovery steam supercritical power unit. The results of calculations confirm the influence of the number of redundant measurements and places of their location in the thermal system of the boiler on the accepted criteria of optimization. Increasing the number of redundant measurements, in terms of the data reconciliation method, leads to decrease the relative standard deviation of the thermal capacity of the boiler and increase the value of Kullback-Leibler divergence, i.e.; decrease the information entropy of the measuring system.

Suggested Citation

  • Szega, Marcin & Nowak, Grzegorz Tadeusz, 2015. "An optimization of redundant measurements location for thermal capacity of power unit steam boiler calculations using data reconciliation method," Energy, Elsevier, vol. 92(P1), pages 135-141.
  • Handle: RePEc:eee:energy:v:92:y:2015:i:p1:p:135-141
    DOI: 10.1016/j.energy.2015.03.125
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    References listed on IDEAS

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    1. Rusinowski, Henryk & Stanek, Wojciech, 2010. "Hybrid model of steam boiler," Energy, Elsevier, vol. 35(2), pages 1107-1113.
    2. Valero, Antonio & Usón, Sergio, 2006. "Oxy-co-gasification of coal and biomass in an integrated gasification combined cycle (IGCC) power plant," Energy, Elsevier, vol. 31(10), pages 1643-1655.
    3. 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.
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    Citations

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    Cited by:

    1. 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.
    2. Szega, Marcin, 2017. "An improvement of measurements reliability in thermal processes by application of the advanced data reconciliation method with the use of fuzzy uncertainties of measurements," Energy, Elsevier, vol. 141(C), pages 2490-2498.
    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. Plis, Marcin & Rusinowski, Henryk, 2019. "Identification of mathematical models of thermal processes with reconciled measurement results," Energy, Elsevier, vol. 177(C), pages 192-202.
    5. Szega, Marcin & Czyż, Tomasz, 2019. "Problems of calculation the energy efficiency of a dual-fuel steam boiler fired with industrial waste gases," Energy, Elsevier, vol. 178(C), pages 134-144.
    6. 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.
    7. Szega, Marcin, 2018. "Extended applications of the advanced data validation and reconciliation method in studies of energy conversion processes," Energy, Elsevier, vol. 161(C), pages 156-171.
    8. 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).

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