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Data reconciliation of the thermal system of a double reheat power plant for thermal calculation

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  • Yu, Jianxi
  • Liu, Pei
  • Li, Zheng

Abstract

Double reheat is a cutting-edge technology of thermal power generation at the current material level. There is a lack of research on the performance analysis and monitoring of in-service power plants with double reheat, and accurate thermal calculation is the prerequisite for these studies. However, the measurement data of power plants usually contain measurement errors, especially flow rate measurements. Data reconciliation is a method of using measurement redundancy to reduce measurement errors, which has been applied in various industrial systems. In the domain of power plants, there is still a lack of data reconciliation research on the thermal system of double reheat units. We develop a data reconciliation model for the overall thermal system of a double reheat power plant, which realizes the overall mass balance of the thermal system and the full utilization of measured data of wet steam. Then operation data of an in-service 660 MW ultra-supercritical power plant with double reheat are reconciled through the proposed model. Gross errors of flow rate measurements are detected and eliminated, and thermal calculation is completed over the full working ranges. Results show that the data reconciliation model improves the accuracy of thermal calculations. Uncertainties of flow rate measurements are reduced by 23.4–75.5%, and uncertainties of wet steam enthalpy and heat rate calculations are reduced by 25.5–43.9%, which lays a foundation for performance monitoring and operation optimization for in-service power plants with double reheat.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:rensus:v:148:y:2021:i:c:s1364032121005700
    DOI: 10.1016/j.rser.2021.111283
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Yu, Jianxi & Petersen, Nils & Liu, Pei & Li, Zheng & Wirsum, Manfred, 2022. "Hybrid modelling and simulation of thermal systems of in-service power plants for digital twin development," Energy, Elsevier, vol. 260(C).

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