Determining optimal turbine operating temperature based on creep rate data and predicted revenue data

1. A method of operating a turbine, the method comprising the steps of:

gathering thermal profile data for a blade while the turbine operates at different operating temperatures;

gathering measured creep data for the blade while the turbine operates at the different operating temperatures;

gathering operating conditions data for the turbine while the turbine operates at the different operating temperatures, including at least a rotational speed of the turbine;

based on the rotational speed of the turbine at the different operating temperatures, determining the mechanical stress applied to the blade;

given the thermal profile data for the blade and the mechanical stress applied to the blade, calculating predicted creep rate data for the blade while the turbine operates at the different operating temperatures;

calibrating the calculation of the predicted creep rate data with the measured creep data for the different operating temperatures;

calculating calibrated creep rate data for the blade at the different operating temperatures;

wherein the different operating temperatures include at least a first operating temperature and a second operating temperature; and

given the calibrated creep rate data for the blade while the turbine operated at the first operating temperature and the calibrated creep rate data for the blade while the turbine operated at the second operating temperature, determining, using a computer, whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient;

wherein:

predicted revenue data comprises data concerning revenue that the turbine earns while operating at the different operating temperatures; and

the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of calculating the predicted revenue data for the turbine at the first operating temperature and the second operating temperature.

2. The method according to claim 1 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the steps of:

calculating predicted blade part life data for the different operating temperatures given the calibrated creep rate data and a maximum creep limit of the blade; and

given the predicted blade part life data, calculating predicted blade part cost data for the different operating temperatures.

3. The method according to claim 2 , wherein the predicted blade part cost data approximately comprises the rate at which increments of the useful life of the blade are expended for the different operating temperatures multiplied by a cost to replace the blade.

4. The method according to claim 2 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of comparing a ratio of the predicted blade part cost data to the predicted revenue data for the different operating temperatures.

5. The method according to claim 2 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of comparing a first comparison of the predicted blade part cost data and the predicted revenue data at the first operating temperature to a second comparison of the predicted blade part cost data and the predicted revenue data for the second operating temperature.

6. The method according to claim 1 , wherein the gathering of the measured creep data includes the following steps:

taking an initial measurement of the blade with one or more proximity sensors disposed around the circumference of a stage of blades;

after the initial measurement, taking a second measurement of the blade with the one or more proximity sensors; and

making a determination of one of the radial creep and axial creep of the blade by comparing the initial measurement to the second measurement.

7. The method according to claim 6 , wherein the initial measurement and second measurement each indicate the distance from a tip of the blade to the one or more proximity sensors.

8. A method of operating a turbine, the method comprising the steps of:

a) gathering thermal profile data for a blade while the turbine operates at a first operating temperature;

b) gathering operating conditions data for the turbine while the turbine operates at the first operating temperature, including at least a rotational speed of the turbine while the turbine operates at the first operating temperature;

c) based on the rotational speed of the turbine, determining the mechanical stress applied to the blade;

d) given the thermal profile data for the blade and the mechanical stress applied to the blade, calculating predicted creep rate data for the blade while the turbine operates at the first operating temperature;

e) repeating steps “a” through “d” while the turbine operates at a second operating temperature; and

f) given the predicted creep rate data for the blade while the turbine operated at the first operating temperature and the predicted creep rate data for the blade while the turbine operated at the second operating temperature, determining, using a computer, whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient;

wherein:

predicted revenue data comprises data concerning revenue that the turbine earns while operating at the different operating temperatures; and

the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of calculating the predicted revenue data for the turbine at the first operating temperature and the second operating temperature.

9. The method according to claim 8 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the steps of:

calculating predicted blade part life data for the different operating temperatures given the predicted creep rate data and a maximum creep limit of the blade; and

given the predicted blade part life data, calculating predicted blade part cost data for the different operating temperatures.

10. The method according to claim 9 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of comparing a ratio of the predicted blade part cost data to the predicted revenue data for the different operating temperatures.

11. The method according to claim 8 , wherein the gathering thermal profile data for the blade includes measuring the thermal profile of the blade with at least one infrared pyrometer.

12. A method of operating a turbine, the method comprising the steps of:

gathering measured creep data for a blade while the turbine operates at different operating temperatures, the measured creep data comprising at least a measured creep rate for the blade;

wherein the different operating temperatures include at least a first operating temperature and a second operating temperature; and

given the measured creep data for the blade while the turbine operated at the first operating temperature and the measured creep data for the blade while the turbine operated at the second operating temperature, determining, using a computer, whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient

wherein:

predicted revenue data comprises data concerning revenue that the turbine earns while operating at the different operating temperatures; and

the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of calculating the predicted revenue data for the turbine at the first operating temperature and the second operating temperature.

13. The method according to claim 12 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the steps of:

calculating predicted blade part life data for the different operating temperatures given the measured creep data and a maximum creep limit of the blade; and

given the predicted blade part life data, calculating predicted blade part cost data for the different operating temperatures.

14. The method according to claim 13 , wherein the step of determining whether operating the turbine at the first operating temperature or the second operating temperature is more economically efficient includes the step of comparing a ratio of the predicted blade part cost data to the predicted revenue data for the different operating temperatures.

15. The method according to claim 12 , wherein the gathering of the measured creep data includes the following steps:

taking an initial measurement of the blade with one or more proximity sensors disposed around the circumference of a stage of blades;

after the initial measurement, taking a second measurement of the blade with the one or more proximity sensors; and

making a determination of one of the radial creep and axial creep of the blade by comparing the initial measurement to the second measurement.

16. The method according to claim 15 , wherein the initial measurement and second measurement each indicate the distance from a tip of the blade to the one or more proximity sensors.