The ultimate proof of the soundness and viability of a novel technology is a full-scale demonstration test in which actual components are run successfully over the entire operating envelope. Consequently, collection of accurate and meaningful test data is of utmost importance to the success of the test. Analysis of such data will validate the original design concepts and lead to paths of further improvement for the next generations thereof. Statistical fundamentals to determine accuracy and precision of measured data are amply documented and readily available in well-established standards. The yardstick that should be used for the “meaningfulness” of measured test data is the satisfaction of the fundamental laws of conservation. While it is known that the “true” values of the sensor data when inserted into the governing equations for the tested component will result in perfect balances, “actual” measured values will always result in “imbalances”. Therefore, reconciliation of the individual measurements with the governing conservation equations is a must prior to actual analysis of the data. Reconciliation in this context is estimation of the “true” values of the sensor data from “actual” sensor data by using statistical concepts. This paper describes the development of a data reconciliation concept that is universally applicable to any process or power plant system where sensor data is used. The usefulness and power of the technique is demonstrated by its application to a single-shaft combined cycle with both gas turbine and steam turbine driving a common generator. In the absence of a reliable and accurate measuring system to individually determine gas and steam turbine shaft outputs, data reconciliation is vital to the accurate analysis of data.

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