Method for operating a wind turbine generator

Abstract

A method for modifying the power output of a wind turbine generator. The power output of a wind turbine generator can be modified based on the rate of fatigue and/or damage calculated for components within the wind turbine generator. Damage and/or fatigue can be calculated based on current or predicted future operating conditions. The turbine operation can be modified if the cost of damage and/or cost of fatigue is less than a value for the electricity produced. In this case, the rate of fatigue is calculated using models of the wind turbine generator or its components, where the model may be based on a metamodel or by an Equivalent Operating Hours approach.

Claims

1. A method for modifying operation of a wind turbine generator supplying electricity to a grid by combining a life model and cost information, comprising: obtaining wind parameters by: predicting incoming wind parameters before the predicted incoming wind parameters are experienced by the wind turbine generator using at least a measurement device mounted away from the wind turbine generator; predicting future operating conditions of the wind turbine generator, wherein the predicted operating conditions are associated with the predicted wind parameters; calculating an amount of fatigue and/or damage predicted to be caused to one or more components of the wind turbine generator during a time of running the wind turbine generator under the predicted operating conditions, wherein the one or more components of the wind turbine generator comprise one or more of a gearbox, bearings, a generator, blades, a drivetrain, couplings, a nacelle baseplate, a tower, foundations, a hub, a blade pitch system, a yaw system, and power electronics, and wherein the calculating of the amount of fatigue and/or damage comprises using the life model; calculating a proportion of total life consumed by the wind turbine generator or the one or more components of the wind turbine generator under the predicted operating conditions from the amount of fatigue and/or damage; calculating a cost per unit time of running a component of the wind turbine generator under the predicted operating conditions from the proportion of total life consumed; comparing the calculated cost per unit time of running the component of the wind turbine generator under the predicted operating conditions with a spot price of electricity, wherein the spot price of electricity is a market value per unit time of electricity generated by the wind turbine generator and supplied to the grid; and after the comparison, increasing future power output of the wind turbine generator when the cost per unit time of running the component of the wind turbine generator under the predicted operating conditions is less than the spot price; reducing the future power output when the cost per unit time of running the component of the wind turbine generator under the predicted operating conditions is greater than the spot price; and maintaining the future power output when the cost per unit time of running the component of the wind turbine generator under the predicted operating conditions is similar to the spot price, wherein operation of the wind turbine generator is improved in that a cost of generating electricity by the wind turbine generator does not exceed a revenue gained from selling the electricity generated by the wind turbine generator.

2. The method according to claim 1, wherein the life model comprises: a nominal model of the wind turbine generator or a component thereof; a model unique to the wind turbine generator or a component thereof including information on one or more manufacturing variations of one or more components of the wind turbine generator; or one or more meta-models, wherein the one or more meta-models are specific for each of the one or more components of the wind turbine generator.

3. The method according to claim 1, wherein the life model comprises an Equivalent Operating Hours (EOH) model.

4. The method according to claim 1, wherein the predicted incoming wind parameters are provided from information comprising one or more of: weather forecasts, seasonal variation, statistics from previous operations, statistics from current operations, and met-mast sensor data.

5. The method according to claim 1, wherein the market value per unit time of electricity generated by the wind turbine generator is a current or forecasted electricity market spot price.

6. The method according to claim 1 wherein the wind parameters include one or more of incoming wind speed, wind turbulence, wind gusts and wind direction.

7. The method according to claim 6 wherein the step of predicting wind parameters is done using LIDAR mounted away from the wind turbine generator, wherein the LIDAR is the measurement device.

8. The method according to claim 1 wherein the step of predicting wind parameters is done using sensors mounted away from the wind turbine generator, wherein the sensors is the measurement device.

9. The method according to claim 1 wherein the predicted operating conditions include one or more of torque, speed, force, moment, displacement, power, voltage, current, strain, vibration, temperature, wind speed, wind turbulence, and wind direction.

10. The method according to claim 1 wherein the components include one or more of gearbox, bearings, generator, blades, drivetrain, couplings, nacelle baseplate, tower, foundations, hub, blade pitch system, yaw system, and power electronics.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

(1) The invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

(2) FIG. 1 is a flow chart for modifying the operation of a wind turbine generator based on fatigue and/or damage caused by current or future operating parameters; and

(3) FIGS. 2 and 3 are flow charts for modifying the operation of a wind turbine generator based on the measurement of incoming gusts and/or wind conditions before they actually hit the turbine.

DETAILED DESCRIPTION OF THE INVENTION

(4) Methods of operating a wind turbine generator are disclosed. The term wind turbine generator is understood to include a wind farm comprising wind turbine generators.

(5) An exemplary embodiment of the present invention will now be described with reference to FIG. 1, which shows an approach for modifying the operation of a wind turbine generator based on fatigue and/or damage caused by current or future operating parameters.

(6) In a first step, operating parameters for a wind turbine generator are determined. The operating parameters can be current or future (predicted) operating conditions, and can be, for example one or more of torque, speed, force, moment, displacement, power, voltage, current, strain, vibration, temperature, wind speed, wind turbulence, and wind direction. This data can be measured directly or calculated indirectly from other measurements or provided from a SCADA system.

(7) In a second step, the amount of fatigue and/or damage caused to wind turbine generator components under operating conditions is calculated. The operating conditions can be current or future (predicted) operating conditions. The wind turbine generator components can be, for example, one or more of gearbox, bearings, generator, blades, drivetrain, couplings, nacelle baseplate, tower, foundations, hub, blade pitch system, yaw system, and power electronics.

(8) In a third step, the proportion of total life consumed for a component under the operating conditions is calculated.

(9) In a fourth step, the equivalent cost per unit time of running a component under the operating conditions is calculated.

(10) In a fifth step, the cost per unit time of running a component under the operating conditions is compared with a value per unit time of electricity generated by the wind turbine. This may be, for example, the current or forecast electricity market spot price. The forecast spot price can be obtained, for example, by the method of Diongue et al.

(11) In a sixth step, operation of the wind turbine generator is modified.

(12) A second exemplary embodiment will now be described with reference to FIG. 2, which shows an approach for modifying the operation of a wind turbine generator in which incoming gusts and/or wind conditions are measured before they hit the turbine.

(13) In a first step, incoming wind parameters are measured before they are experienced by a wind turbine. This step includes, for example, measuring incoming wind speed, wind turbulence or wind direction. This can be done using LIDAR which could be mounted on the wind turbine generator or away from the wind turbine. This can be done using sensors mounted away from the wind turbine. The information could also be provided from one or more of weather forecasts, seasonal variation, statistics from previous operations, statistics from current operations, or met-mast sensor data.

(14) In a second step, future operation conditions for the wind turbine generator are predicted. The conditions include, for example, one or more of torque, speed, force, moment, displacement, power, voltage, current, strain, vibration, temperature, wind speed, wind turbulence, and wind direction. This data can measured directly or calculated indirectly from other measurements or provided from a SCADA system.

(15) In a third step, the amount of fatigue and/or damage caused to wind turbine generator components under predicted future operating conditions is calculated. Components include, for example, one or more of gearbox, bearings, generator, blades, drivetrain, couplings, nacelle baseplate, tower, foundations, hub, blade pitch system, yaw system, and power electronics.

(16) In a fourth step, the proportion of total life consumed for a component under current or predicted future operating conditions is calculated.

(17) In a fifth step, the equivalent cost per unit time of running a component under current or predicted future operating conditions is calculated.

(18) In a sixth step, the cost per unit time of running a component under current or predicted future operating conditions is compared with the value per unit time of electricity generated by the wind turbine. This can be, for example, the current or forecast electricity market spot price.

(19) In a seventh step the current or future operation of the wind turbine generator is modified.

(20) A third exemplary embodiment will now be described with reference to FIG. 3, which shows an approach for modifying the operation of a wind turbine generator by measuring incoming gusts and/or wind conditions before the hit the wind turbine.

(21) In a first step, incoming wind parameters are measured before they are experienced by a wind turbine. This can include, for example, measuring incoming wind speed, wind turbulence or wind direction. This can be done using LIDAR which could be mounted on the wind turbine generator or away from the wind turbine. This can be done using sensors mounted away from the wind turbine. The information could also be provided from one or more of weather forecasts, seasonal variation, statistics from pervious operations, statistics from current operations, or met-mast sensor data.

(22) In a second step, future operation conditions for the wind turbine generator are predicted. The operating conditions can include, for example, one or more of torque, speed, force, moment, displacement, power, voltage, current, strain, vibration, temperature, wind speed, wind turbulence, and wind direction. This data can measured directly or calculated indirectly from other measurements or provided from a SCADA system.

(23) In a third step, the amount of fatigue and/or damage caused to wind turbine generator components under predicted future operating conditions is calculated. The components can include, for example, one or more of gearbox, bearings, generator, blades, drivetrain, couplings, nacelle baseplate, tower, foundations, hub, blade pitch system, yaw system, and power electronics.

(24) In a fourth step, the current or future operation of the wind turbine generator is modified.

(25) Fatigue and/or damage caused to wind turbine generator components can be calculated or determined in a number of ways. In one approach, the step of assessing damage comprises the step of providing information on the wind turbine generator or a component thereof, which includes providing: a nominal model of the gearbox, drive-train and/or generator; a model unique to the specific gearbox, drive-train and/or generator including information on one or more manufacturing variations of one or more components of the gearbox, drive-train and/or generator; a fully coupled finite element model comprising nodes with six degrees of freedom unique to the gearbox, drive-train and/or generator; or one or more meta-models, wherein the one or more meta-models are specific for each of the one or more components.

(26) In another approach a metamodel may be used.

(27) In another approach Equivalent Operating Hours (EOH) defines damage as being equivalent to the damage caused to a wind or water turbine or components thereof by one hour of operation under rated operating conditions. The EOH is equal to a weighting factor related to the operational condition multiplied by a duration (or alternatively, frequency) of that condition. For any operation in which damage caused is the same as that expected to be caused under rated conditions, the EOH of a component after 1 h will be 1 h, and the weighting factor will be 1.0. If an operational event causes greater damage, then the EOH will be reduced accordingly. Thus, an operational event of duration of 0.2 h of duration and having a weighting factor of 0.7, then the EOH after 1 h will be 0.81+0.20.7=0.94.

(28) Operating conditions may relate to previous, current or future operation of the wind turbine generator.

(29) For example, the amount of fatigue and/or damage can be equated to a cost of fatigue for previous, current or future operation. The operation of the wind turbine generator can thus be compared to the spot price of electricity supplied to the grid, and the output of the wind turbine generator could be maintained at the current level or boosted or up-rated under conditions where the fatigue cost is less than the spot price.

(30) Thus if electricity price is low and wind speed is high, the turbine can be de-rated the turbine; conversely, if electricity price is high and wind speed is high, the turbine can be fully rated.

(31) This allows a wind turbine generator installation to be operated to ensure that the cost of generating electricity by the wind turbine installation does not exceed the revenue gained from selling that electricity. These values may vary to reflect an underlying demand and/or to reflect the unreliability of renewable sources of energy. Typically, when demand for electricity is high, the price is also high. Thus when the demand for electricity is high, the output of a wind turbine installation can be increased as described above.

(32) In the foregoing methods, the operating parameter can be a control parameter. Control parameters are used to control the wind turbine operation at any wind condition and protect it while avoiding any mechanical or electrical overload. Different control strategies can be implemented through changing the control parameters and their values. Control parameters are any parameters collected by the control system and used to control the system, and include pitch angle, yaw position, power output, cut-in wind speed and others.