One of the key goals of pipeline hydraulic optimization is the capability to minimize fuel consumption of gas turbine driven centrifugal compressors. This requires an accurate, and computationally efficient method to calculate the fuel consumption of a gas turbine driven centrifugal compressor system.

This feature is available for any current pipeline modeling software. The issue, however, is in accuracy of the currently provided methods of calculations. Authors have found that errors in the leading software exceed 2-3%. More accurate computations would allow pipeline operator to increase system's throughput and also more accurately assess the station and pipeline fuel cost.

A common requirement is to calculate the fuel flow of the gas turbine for a given compressor operating point. In this case, the compressor speed and power consumption (and therefore, the shaft power at the power turbine and the power turbine speed) are known. To accurately calculate the station fuel consumption the user requires the gas turbine performance data for each particular compressor station, considering the station's site conditions which include ambient temperature, humidity, and the site elevation.

This information is often unavailable for the pipeline analyst, so one of the main objectives of this paper was to find universal set of data that would be able to provide most accurate fuel consumption for all compressor stations regardless their different site conditions.

This paper presents the results of a study conducted for a compressor stations where two different methods were used to reduce the accuracy of compressor station fuel calculation down to around 0.25%.

The first method relates to elevation correction and it uses engine data files that contain the fuel consumptions data for the sea level only. The basis for this method is that gas turbine efficiency doesn't change with the change of the site elevation assuming the same percentage of turbine's part load.

The second method is a "Power Turbine Off-Optimum Speed" iteration process where the actual fuel consumption value is found using some iterations between power turbine optimum power and speed until the target value is found. As in the "Elevation Correction" method the only one set of turbine's sea level data is needed and can be used for any site elevation. The methods described avoid shortfalls of previous methods when dealing with Lean-Premix Low Emissions gas turbines, and are simple enough to provide a effective means to properly account for part load and off-optimum gas turbine performance at arbitrary operating conditions.

Both methods can also be used to calculate the fuel consumption at any given ambient temperature by interpolating between two closest sets of ambient temperatures.

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