Data reconciliation for steam turbine on-line performance monitoring

Abstract In a coal-fired power generation unit, steam turbine performance monitoring relies on steam cycle heat balance analysis, in which the primary flow measurement accuracy is critical. However, in a steam turbine on-line measurement system, the accuracy of most flow metering devices is not satisfactory, and using data measured with these devices could lead to high uncertainty in the heat balance analysis and performance monitoring results. In this work, we propose a data reconciliation approach in steam turbine on-line performance monitoring, with the aim of reducing uncertainty of the primary flow measurements and steam turbine heat rate. The proposed method is based on the establishment of a first-principle mathematical model of a steam turbine unit and optimization of the reconciled values of measurements. Results of a case study carried out on a real-life 1000 MW ultra-supercritical unit show that, after data reconciliation, uncertainties of measured values of the outlet flow rate of the #1 feed water heater, the outlet flow rate of the feed water pump, and the inlet flow rate of condensate water in the deaerator can be reduced by 72.1%, 39.4% and 21.4%, and that uncertainty of the steam turbine heat rate can be reduced by 17.9%, 18.8% and 18.8%, when the unit operates at 100%, 75% and 50% of its design load.

[1]  David I. Wilson,et al.  Scheduling cleaning in a crude oil preheat train subject to fouling: Incorporating desalter control , 2010 .

[2]  Hongwei Tong,et al.  Detection of gross erros in data reconciliation by principal component analysis , 1995 .

[3]  Richard S. H. Mah,et al.  Reconcillation and Rectification of Process Flow and Inventory Data , 1976 .

[4]  Alberto Traverso,et al.  Data Reconciliation for power systems monitoring: Application to a microturbine-based test rig , 2013 .

[5]  James E. Gentle,et al.  Matrix Algebra: Theory, Computations, and Applications in Statistics , 2007 .

[6]  Tiziano Faravelli,et al.  Application of data-reconciliation and optimisation procedure to hydrogen plant , 1995 .

[7]  Bo Li,et al.  Data reconciliation for real-time optimization of an industrial coke-oven-gas purification process , 2006, Simul. Model. Pract. Theory.

[8]  Pen-Chung Chen,et al.  The Implementation of the Data Validation Process in a Gas Turbine Performance Monitoring System , 2005 .

[9]  M. P. Vukalovitch.  Thermodynamic properties of water and steam , 1958 .

[10]  Diego Martinez Prata,et al.  Nonlinear dynamic data reconciliation and parameter estimation through particle swarm optimization: Application for an industrial polypropylene reactor , 2009 .

[11]  R. Schirru,et al.  Simultaneous Model Selection, Robust Data Reconciliation and Outlier Detection with Swarm Intelligence in a Thermal Reactor Power calculation , 2011 .

[12]  Vladimir Mahalec,et al.  Heat exchanger network simulation, data reconciliation & optimization , 2013 .

[13]  Xu Zhigao.  Uncertainty Evaluation of Steam Turbine Performance Tests , 2010 .

[14]  Patrick Hamilton,et al.  Model-Based Data Reconciliation to Improve Accuracy and Reliability of Performance Evaluation of Thermal Power Plants , 2005 .

[15]  Alberto Coronas,et al.  Steady-state data reconciliation for absorption refrigeration systems , 2013 .

[16]  J. Kenneth Salisbury,et al.  Power-Plant Performance Monitoring , 1961 .

[17]  Tao Wu-xin.  DETECTION AND RECONCILIATION ON THE ABNORMAL OPERATION DATA BASED ON REDUNDANCY MEASUREMENT IN A POWER PLANT , 2003 .

[18]  Jose A. Romagnoli,et al.  Data Reconciliation - an Industrial Case Study , 1993 .

[19]  J. Plácido,et al.  Industrial application of data reconciliation , 1998 .

[20]  Magnus Langenstein,et al.  Process data reconciliation in nuclear power plants , 2003 .

[21]  Didier Maquin,et al.  Comparison of gross errors detection methods in process data , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[22]  S. Can Gülen,et al.  A Simple Mathematical Approach to Data Reconciliation in a Single-Shaft Combined Cycle System , 2009 .

[23]  Magnus Langenstein,et al.  Power Recapture and Power Uprate in NPPs With Process Data Reconciliation in Accordance With VDI 2048 , 2006 .

[24]  C. M. Crowe,et al.  Data reconciliation — Progress and challenges , 1996 .

[25]  Richard S. H. Mah,et al.  Generalized likelihood ratio method for gross error identification , 1987 .

[26]  Diego Martinez Prata,et al.  Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial polypropylene reactor , 2010 .

[27]  Shankar Narasimhan,et al.  Data reconciliation & gross error detection: an intelligent use of process data , 1999 .