Reduction of uncertainty of thermal performance calculations in nuclear power plants

Olli Saarela, Emil Wingstedt

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

The OECD Halden Reactor Project (HRP) has taken an active role in facilitating implementation of technology advances and in particular application of condition monitoring techniques for operation support. TEMPO [1] is a system based on physical models for thermal performance monitoring and optimization developed at the HRP. The system aims at satisfying information needs associated with condition monitoring, on-line calibration monitoring of plant measurements, process fault detection and diagnosis. Data reconciliation [2] combines a first principles model and process measurement data to calculate the most likely process state. The use of data reconciliation requires an analytically redundant set of measurements, i.e. that information about measured entities can be deducted from other measurements through the model, e.g. from mass and heat balances. Uncertainties of the computed results depend on both the uncertainties of the measurement data and the inaccuracy and uncertainty of the data reconciliation model. The TEMPO system has been in daily use in the analysis of thermal performance of the secondary side of the Loviisa NPP turbine cycle for several years [3]. This paper presents an approach where distributions of measurement errors are estimated from observed time series data. Principal Component Analysis (PCA) is used to identify process variability modes observable in several measurements, which are then subtracted from observed data to estimate the distributions of measurement errors. Uncertainty estimates for the reconciled values are then computed using Monte Carlo simulation. The approach described above is applied to a turbine section of a nuclear power plant. The estimated distributions of measurement errors are utilized in both reactor power monitoring and sensor drift detection. The results indicate that the measurement uncertainty in the process examined is not too significant a source of uncertainty affecting the results computed with data reconciliation.
Original languageEnglish
Title of host publication9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies
PublisherCurran Associates Inc.
Pages2130-2140
ISBN (Print)978-1-5108-0809-6
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
Event9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC & HMIT  - Charlotte, United States
Duration: 22 Feb 201526 Feb 2015

Conference

Conference9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC & HMIT 
Abbreviated titleNPIC & HMIT
CountryUnited States
CityCharlotte
Period22/02/1526/02/15

Fingerprint

Nuclear power plants
Measurement errors
Condition monitoring
Monitoring
Turbines
Hot Temperature
Uncertainty
Fault detection
Principal component analysis
Failure analysis
Time series
Calibration
Sensors

Keywords

  • thermal performance
  • data reconciliation
  • uncertainty

Cite this

Saarela, O., & Wingstedt, E. (2015). Reduction of uncertainty of thermal performance calculations in nuclear power plants. In 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies (pp. 2130-2140). Curran Associates Inc..
Saarela, Olli ; Wingstedt, Emil. / Reduction of uncertainty of thermal performance calculations in nuclear power plants. 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies. Curran Associates Inc., 2015. pp. 2130-2140
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Saarela, O & Wingstedt, E 2015, Reduction of uncertainty of thermal performance calculations in nuclear power plants. in 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies. Curran Associates Inc., pp. 2130-2140, 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC & HMIT , Charlotte, United States, 22/02/15.

Reduction of uncertainty of thermal performance calculations in nuclear power plants. / Saarela, Olli; Wingstedt, Emil.

9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies. Curran Associates Inc., 2015. p. 2130-2140.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AB - The OECD Halden Reactor Project (HRP) has taken an active role in facilitating implementation of technology advances and in particular application of condition monitoring techniques for operation support. TEMPO [1] is a system based on physical models for thermal performance monitoring and optimization developed at the HRP. The system aims at satisfying information needs associated with condition monitoring, on-line calibration monitoring of plant measurements, process fault detection and diagnosis. Data reconciliation [2] combines a first principles model and process measurement data to calculate the most likely process state. The use of data reconciliation requires an analytically redundant set of measurements, i.e. that information about measured entities can be deducted from other measurements through the model, e.g. from mass and heat balances. Uncertainties of the computed results depend on both the uncertainties of the measurement data and the inaccuracy and uncertainty of the data reconciliation model. The TEMPO system has been in daily use in the analysis of thermal performance of the secondary side of the Loviisa NPP turbine cycle for several years [3]. This paper presents an approach where distributions of measurement errors are estimated from observed time series data. Principal Component Analysis (PCA) is used to identify process variability modes observable in several measurements, which are then subtracted from observed data to estimate the distributions of measurement errors. Uncertainty estimates for the reconciled values are then computed using Monte Carlo simulation. The approach described above is applied to a turbine section of a nuclear power plant. The estimated distributions of measurement errors are utilized in both reactor power monitoring and sensor drift detection. The results indicate that the measurement uncertainty in the process examined is not too significant a source of uncertainty affecting the results computed with data reconciliation.

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KW - data reconciliation

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BT - 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies

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Saarela O, Wingstedt E. Reduction of uncertainty of thermal performance calculations in nuclear power plants. In 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies. Curran Associates Inc. 2015. p. 2130-2140