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gas turbine performance data and regression

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The attached data set is derived from actual performance of an engine that is very well maintained, as is the instrumentation. Sadly, this is not often the case in the power industry, making this an extraordinary data set. In the spreadsheet you will find the ambient conditions, operational controls, fuel data, reported performance, and regressions. These regressions (for generator output and heat input) are curve fits you can use for various analyses and can be scaled to match your specific engine. EOH is equivalent operating hours, which is the literal running time plus adjustments for start up, shut down, and cleaning. Your regression should be based on absolute humidity, not relative humidity (Google "psychrometrics" for details). Controls include grid frequency (generator rotational speed), anti-icing, and inlet guide vane angle (think: accelerator pedal position on a car). Fitting power is straight-forward. You always want to perform a regression on heat input rather than heat rate, as the former is a single entity and the latter is the ratio of two (see ASME PTC-22 and PTC-46 for discussion). The scatter is remarkably tight for power and heat input due to the exceptional maintenance. The scatter for heat rate is significantly more because it's a quotient. The multi-variate regression is easily obtained by copying cells B4:M7329 to the clipboard, launching CURVEFIT, selecting Y(X1,X2,...), and pressing "Fit Curve". The result, ready for Excel, is copied to the clipboard by pressing "Copy Fit to Clipboard". Switch to Excel, press Alt-F11, and paste. It's that simple. You can download CURVEFIT anytime for free.





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