Thomas P. Schmitt

Quantifying Correction Curve Uncertainty Through Empirical Methods

The accuracy of a thermal performance test is typically estimated by performing an uncertainty analysis calculation in accordance with ASME PTC 19.1 or equivalent. The resultant test uncertainty estimate is often used as a key factor in the commercial contract, in that many contracts allow a test tolerance and define the test tolerance to be equal to the test uncertainty. As such, the calculated test uncertainty needs to accurately reflect all of the technical factors that contribute to the uncertainty. The test uncertainty is a measure of the test quality, and, in many circumstances, the test setup must be designed such that the uncertainty remains lower than test code limits and/or commercial tolerances.Traditional uncertainty calculations have included an estimate of the measurement uncertainties and the propagation of those uncertainties to the test result. In addition to addressing measurement uncertainties, ASME PTC 19.1 makes reference to other potential errors of method, such as “the assumptions or constants contained in the calculation routines” and “using an empirically derived correlation”. Experience suggests that these errors of method can in some circumstances dominate the overall test uncertainty. Previous studies (POWER2011-55123 and POWER2012-54609) introduced and quantified a number of operational factors and correction curve factors of this type.To facilitate testing over a range of boundary conditions, the industry norm is for the equipment supplier to provide correction curves, typically created using thermodynamic models of the power plant to predict the response of the system to changes in boundary conditions. As noted in various PTC codes (PTC-22, PTC-46, and PTC-6) it is advisable to run the test at conditions as close to the rated conditions as possible to minimize the influence of the correction curves. Experience suggests that large deviations from rated conditions, and the associated influence of the correction curves, can result in decreased accuracy in the final corrected result. A discussion of these types of situations via case studies is discussed, as well as a means by which to reduce the uncertainty contributions from correction curves considerably.Copyright

Model Based Performance Correction Methodology — A Case Study

Correction curves are of great importance in the performance evaluation of heavy duty gas turbines (HDGT). They provide the means by which to translate performance test results from test conditions to the rated conditions. The correction factors are usually calculated using the original equipment manufacturer (OEM) gas turbine thermal model (a.k.a. cycle deck), varying one parameter at a time throughout a given range of interest. For some parameters bi-variate effects are considered when the associated secondary performance effect of another variable is significant. Although this traditional approach has been widely accepted by the industry, has offered a simple and transparent means of correcting test results, and has provided a reasonably accurate correction methodology for gas turbines with conventional control systems, it neglects the associated interdependence of each correction parameter from the remaining parameters. Also, its inherently static nature is not well suited for today’s modern gas turbine control systems employing integral gas turbine aero-thermal models in the control system that continuously adapt the turbine’s operating parameters to the “as running” aero-thermal component performance characteristics.Accordingly, the most accurate means by which to correct the measured performance from test conditions to the guarantee conditions is by use of Model-Based Performance Corrections, in agreement with the current PTC-22 and ISO 2314, although not commonly used or accepted within the industry.The implementation of Model-based Corrections is presented for the Case Study of a GE 9FA gas turbine upgrade project, with an advanced model-based control system that accommodated a multitude of operating boundaries. Unique plant operating restrictions, coupled with its focus on partial load heat rate, presented a perfect scenario to employ Model-Based Performance Corrections.Copyright

Advances in Direct Measurement of Gas Turbine Exhaust Temperature With Multi-Element Thermocouple Rakes for Diagnosing Performance Issues and Characterizing Turbine Upgrades

Heavy-duty gas turbines are designed to deliver maximum performance within their respective technology class and emissions limits. In order to achieve performance goals consistent with hot section durability constraints, it has become more critical than ever for engineers to have an economical, dependable, and accurate measurement of the average exhaust gas temperature and the associated profiles. Simple thermocouples “rakes” have been used for many years to meet the basic need of measuring planar average temperature. In addition, recent testing experience has shown that the measured radial temperature profile data from these same “rakes” can play a key role in the diagnosis of performance issues and also in the characterization of hardware upgrades. For example, high technology hot section spin-offs from F, G, and H class turbines have been applied as upgrades to older B and E class turbines with dramatic impact on the exhaust temperature pattern. Another example has been the use of pressure/temperature exhaust “rakes” in F class turbines to diagnose changes in the radial temperature profile that result from combustion system upgrades. In both cases, the careful measurement and interpretation of these temperature patterns is crucial to the proper setting of control algorithms that govern performance levels and exhaust emissions. Advances in the design and arrangement of exhaust thermocouple rakes, and in the analysis methods used to interpret the resultant test data, are presented. Several recent cases of using rakes to diagnose performance issues and to characterize the temperature pattern for the purpose of optimizing control settings are discussed.Copyright

Gas Turbine Part Load Performance Testing: Comparison of Test Methodologies

Current trends in usage patterns of gas turbines in combined cycle applications indicate a substantial proportion of part load operation. Commensurate with the change in operating profile, there has been an increase in the propensity for part load performance guarantees. When a project is structured such that gas turbines are procured as equipment-only from the manufacturer, there is occasionally a gas turbine part load performance guarantee that coincides with the net plant combined cycle part load performance guarantee. There are several methods by which to accomplish part load gas turbine performance testing. One of the more common methods is to operate the gas turbine at the specified load value and construct correction curves at constant load. Another common method is to operate the gas turbine at a specified load percentage and construct correction curves at constant percent load. A third method is to operate the gas turbine at a selected load level that corresponds to a predetermined compressor inlet guide vane (IGV) angle. The IGV angle for this third method is the IGV angle that is needed to achieve the guaranteed load at the guaranteed boundary conditions. The third method requires correction curves constructed at constant IGV, just like base load correction curves. Each method of test and correction embodies a particular set of advantages and disadvantages. The results of an exploration into the advantages and disadvantages of the various performance testing and correction methods for part load performance testing of gas turbines are presented. Particular attention is given to estimates of the relative uncertainty for each method.Copyright