CN116522051A - Full-field cabin transfer function correction method - Google Patents
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Abstract
The invention relates to a full-field cabin transfer function correction method, which comprises the steps of establishing a full-field sector division model according to wind directions, carrying out flow field prediction on fan positions under the influence of different wind directions according to a three-dimensional wake model, judging whether the fan positions are in wake influence sectors, further carrying out inflow equivalent wind speed calculation by combining the established inflow equivalent model and laser radar measurement wind speed, and simultaneously establishing cabin transfer functions of inflow equivalent wind speed, cabin wind speed and rotating speed according to fan rotating speed characteristics in a partition mode, thereby realizing customized correction application of the full-field fan transfer function, effectively improving free inflow wind speed calculation precision and effectively improving transfer function fitting precision.
Description
Technical Field
The invention relates to the technical field of wind power generation, in particular to a full-field cabin transfer function correction method.
Background
The anemometer is used for collecting wind speed data, and is mainly used for power curve calculation, cut-in and cut-out control, storm control, yaw control and the like of the wind turbine generator. At present, the wind turbine generator system anemometer is mainly of a rear mechanical anemometer or an ultrasonic anemometer in installation and use type, and because the anemometer is installed at the tail of a cabin, the wind turbine generator system anemometer is influenced by factors such as rotation disturbance of an impeller of the wind turbine generator system, incoming wind condition characteristics, blade root narrow tube effects and the like, the wind speed measured by the wind turbine generator system anemometer has deviation from the actual wind speed, the wind speed output is directly influenced, the operation control of a fan is further influenced, and risks such as stall, vibration, load and galloping are easily increased.
At present, a wind turbine generator host manufacturer usually introduces a cabin transfer function (corresponding function relation between a cabin anemometer wind speed and a free incoming flow wind speed) according to an IEC 61400 12-2 standard to correct the wind speed measured by the cabin anemometer, and the calculation method proposed by the IEC is a single-value linear relation between the wind tower wind speed and the cabin anemometer wind speed, but for the actual running of the wind turbine generator, the wind speed measured by the anemometer is influenced by multiple factors such as impeller rotation speed, incoming flow wind characteristics and the like, and only the cabin anemometer and the wind tower data are considered, so that the transfer function relation cannot be accurately calculated. Based on this, some papers and patents also propose a transfer function calculation method considering multi-parameter influence, for example, chinese patent application CN113283035a discloses a nacelle transfer function calculation method considering the double-parameter influence of nacelle wind speed and fan power, but the existing techniques only consider the influence factors from the wind turbine generator side, neglect the influence of factors such as turbulence and wind shear on the incoming wind characteristics of the fan, and from the perspective of anemometer wind measurement, the rotation speed of the impeller has a more important influence on the accuracy of the anemometer than the fan power, and the existing transfer function calculation method at present uses the single-point wind speed measured by the anemometer tower or the laser radar as the free incoming wind speed, and does not consider the equivalent wind speed calculation of the whole impeller plane. Meanwhile, the transfer function calculation of each host manufacturer is theoretical environment calculation before delivery, and full-field transfer function customized correction calculation is not performed from the angle of the actual layout of the full-field fan. Therefore, improvements and innovations are necessary.
In order to make up for the defects of the technology, the invention provides a full-field cabin transfer function customizing correction method by taking into consideration factors such as the characteristics of the inflow wind, the rotating speed of a fan, the layout of a unit and the like.
Disclosure of Invention
Aiming at the situation, the invention aims to overcome the defects of the prior art and provide a full-field cabin transfer function correction method taking into consideration the characteristics of inflow wind, the rotating speed of a fan, the layout of a unit and other factors.
The technical scheme of the invention is as follows:
a full field nacelle transfer function correction method comprising the steps of:
step 1, full field fan sector division
The method comprises the steps of collecting full-field fan machine point coordinate information, elevation information, wind direction information, wind speed information and turbulence intensity in full-field fan sector division, predicting full-field flow field distribution conditions under different wind direction variables by combining a wake superposition model, and further judging that each machine position is fan inflow wind resource information, wherein a full-field fan sector judgment model is as follows:
wherein F is S Judging a model for the sector of the full-field fan; f (theta) is a wind direction model, and different wind direction angles theta are input to convert a coordinate system, wherein x, y and z are position coordinate parameters under a corresponding coordinate system; v (x, y, z) is the three-dimensional inflow wind speed of the fan, and is measured by a laser radar; v (V) w Is a three-dimensional wake model and is used for predicting wake wind speed distribution, wherein k is a wake expansion coefficient, m is an empirical coefficient, and is determined by the actual running condition of a fan, and r 0 For the length of the wind wheel blade r w For wake radius at downwind position x, σ is the standard deviation of gaussian distribution, a is the axial induction factor;
step 2, establishing an inflow equivalent wind speed model
Setting input parameters of an inflow equivalent wind speed model according to the inflow wind condition of the fan judged in the step 1, wherein the impeller plane inflow equivalent wind speed model is shown as the following formula (2), and single-point wind speed measurement is carried out by adopting a laser radar:
wherein V is eq Equivalent wind speed for inflow;the wind speed is the wind speed of the height plane of the fan hub; v (V) w Representing wake parameter effect vectors; v (V) sh Vector representing wind shear phenomenon, v 1 At a height h 1 Wind speed at alpha isThe wind shear index is determined by fitting the wind speed measured by the laser radar up and down light speed; v (V) to The vector is expressed as a tower shadow effect, beta is a wind acceleration parameter, phi is an included angle parameter of a wind wheel assembly blade and the ground in the vertical direction, l is a distance parameter between the wind wheel and a wind turbine tower, and d is a distance parameter between the blade and the hub;
step 3, data acquisition and processing
a) Acquiring wind speed data at the height of a fan hub by adopting a laser radar, simultaneously acquiring cabin anemometer data and rotating speed data, wherein the sampling frequency is 1Hz, and respectively calculating the acquired data to obtain an arithmetic average value of 10 min;
b) And c) carrying out abnormal elimination on the data counted in the step a), wherein the abnormal elimination comprises the condition of damage of test equipment, the data that the average wind speed of 10min is lower than the cut-in wind speed of the fan or higher than the cut-out wind speed and the fan electricity limiting data.
c) Dividing the wind direction angle of 0-360 degrees into 36 intervals by using an interval method, wherein the width of each interval is 10 degrees, and judging whether each unit is in a wake flow area or not by combining the full-field sector division model in the step 1;
d) Substituting the data measured by the laser radar into the inflow equivalent wind speed model in the step 2 to calculate and convert the data into inflow equivalent wind speed according to the judging result of whether the data is in the wake flow area or not;
e) Dividing the wind speed acquired by the laser radar into a plurality of Bin intervals according to intervals, wherein the central value of each Bin interval is an integer multiple of the wind speed interval, and simultaneously dividing the fan rotating speed corresponding to the wind speed measured by the radar and the wind speed of a cabin anemometer according to Bin method intervals; calculating a cabin wind speed average value, an equivalent wind speed average value and a rotating speed average value of each Bin interval by using the following formula (3):
in the formula, v n,i Mean value of cabin wind speed of ith Bin section, v n,i,j The cabin wind speed of the j th group in the i Bin interval; v eq,i Inflow equivalent wind speed level for ith Bin sectionMean, v eq,i,j The wind speed is equivalent to the inflow wind speed of the j-th group in the i-th Bin interval; v r,i The average value v of the fan rotation speed in the ith Bin interval r,i,j The rotation speed of the fan in the j group in the i Bin interval is the rotation speed of the fan in the j group;
step 4, transfer function establishment
Carrying out partition fitting according to the rotating speed characteristics of the unit, regarding the inflow equivalent wind speed as a function of the wind speed of the cabin anemometer and the rotating speed of the unit in the interval from the cut-in rotating speed to the rated rotating speed, and establishing a transfer function of the equivalent inflow wind speed, the cabin wind speed and the rotating speed of the unit through a polynomial surface fitting method; for the interval above the rated rotation speed, the inflow wind speed is regarded as a single-value function of the cabin wind speed as the rotation speed is a fixed value, and polynomial fitting is carried out:
a) Cutting-in speed to rated speed interval
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n Rotational speed v of fan r As an independent variable, a polynomial surface fitting method is adopted, and a calculation formula is shown as follows, wherein c is a undetermined fitting parameter:
b) Interval above rated rotation speed
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n As an independent variable, a polynomial fitting method is adopted, and a calculation formula is shown as follows, wherein b is a pending fitting parameter:
v eq ＝f(v n )＝b 0 +b 1 v n +b 2 v n 2 +b 3 v n 3 +... (5)
after the whole-field cabin transfer function correction method is established, transfer function customization correction can be carried out on the whole-field fan according to wind directions, free flow wind speed recovery precision is effectively improved, and further fan operation control and power performance precision are improved.
The invention considers the layout characteristics of a full-field fan, establishes a full-field sector division model according to wind directions, predicts the fan positions under the influence of different wind directions according to a three-dimensional wake model, judges whether the fan positions are in wake influence sectors, further calculates inflow equivalent wind speeds by combining the established inflow equivalent model and laser radar measured wind speeds, and simultaneously establishes cabin transfer functions of the inflow equivalent wind speeds, cabin wind speeds and rotating speeds in a partitioning manner according to the rotating speed characteristics of the fan:
1. the method is based on the consideration of the layout among wind field fans, establishes a full field sector division model wind profile model according to wind direction and wake flow model, accurately and effectively predicts the incoming wind condition of a unit, and further realizes the customized correction application of the full field fan transfer function;
2. in the existing cabin transfer function calculation, the inflow wind speed of the fan is represented by measuring single-point wind speed through a wind measuring tower or a laser radar, and the actual inflow wind speed of the fan is comprehensively influenced by unit arrangement, tower shadow effect, wake flow effect, shearing effect and the like, and the inflow equivalent wind speed is needed to be calculated reversely through the single-point measured wind speed. According to the method, an inflow equivalent wind speed model is established by considering the influence of factors such as average wind speed, wind shearing, tower shadow effect and wake effect, and equivalent wind speed is calculated by combining laser radar wind measurement data, so that the calculation accuracy of free inflow wind speed is effectively improved;
3. the rotating speed of the fan has an important influence on the measuring precision of the cabin wind speed behind the impeller. The IEC 61400-12-2 standard adopts a single-value relation between the free incoming wind speed and the cabin wind speed to carry out transfer function linear fitting, and the influence of the rotating speed of the fan on the cabin wind measuring precision is ignored. According to the invention, partition division is performed based on the fan rotating speed characteristic, and a polynomial curve fitting relation is established according to the relation between the fan inflow equivalent wind speed and the cabin wind speed and the fan rotating speed, so that a cabin transfer function calculated value is obtained by deduction, and the fitting precision of the transfer function is effectively improved.
Drawings
FIG. 1 is a schematic diagram of a method for calculating sector division of a full-field fan according to the present invention.
FIG. 2 is a flow chart of a full-field cabin transfer function correction method according to the present invention.
FIG. 3 is a schematic diagram showing the contrast effect of the transfer function application of the present invention.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the drawings.
As shown in fig. 1-3, the invention discloses a full-field cabin transfer function correction method, which comprises the following steps:
step 1, full field fan sector division
In the traditional cabin transfer function calculation process, only a single machine is used for calculation, so that the wind speed influenced by wake sectors in the inflow wind speed is eliminated, however, in the actual wind field layout, a fan in the wind field is mostly influenced by wake superposition, tower shadow effect and the like, so that the inflow wind speed of the fan is intricate and complex, and the undisturbed inflow wind speed and the cabin anemometer wind speed are simply adopted for fitting, so that the calculation accuracy cannot be ensured.
The method comprises the steps of collecting full-field fan machine point coordinate information, elevation information, wind direction information, wind speed information and turbulence intensity in full-field fan sector division, predicting full-field flow field distribution conditions under different wind direction variables by combining a wake superposition model, and further judging that each machine position is fan inflow wind resource information, wherein a full-field fan sector judgment model is as follows:
wherein F is S Judging a model for the sector of the full-field fan; f (theta) is a wind direction model, and different wind direction angles theta are input to convert a coordinate system, wherein x, y and z are position coordinate parameters under a corresponding coordinate system; v (x, y, z) is the three-dimensional inflow wind speed of the fan, and is measured by a laser radar; v (V) w Is a three-dimensional wake model for predicting wake windA speed distribution, wherein k is wake expansion coefficient, m is empirical coefficient, and is determined by the actual running condition of the fan, r 0 For the length of the wind wheel blade r w For wake radius at downwind position x, σ is the standard deviation of the gaussian distribution, a is the axial induction factor (by the wind turbine thrust coefficient C T Determining;
the wake expansion coefficient k shown is 0.075; the empirical factor c shown takes a value of 2.58 in combination with gaussian distribution characteristics.
Step 2, establishing an inflow equivalent wind speed model
The defect that single-point wind speed is adopted in the traditional method is overcome in the establishment process of the inflow equivalent wind speed model, the influences of factors such as average wind speed, wind shearing, tower shadow effect, wake effect and the like are comprehensively considered, the input parameters of the inflow equivalent wind speed model are set according to the inflow wind condition of the fan judged in the step 1, the impeller plane inflow equivalent wind speed model is shown as the following formula (2), and the single-point wind speed measurement is carried out by adopting a laser radar:
wherein V is eq Equivalent wind speed for inflow;the wind speed is the wind speed of the height plane of the fan hub; v (V) w Representing wake parameter effect vectors, and calculating by combining fan sectors divided in the step 1; v (V) sh Vector representing wind shear phenomenon, v 1 At a height h 1 The wind speed at the position, alpha is a wind shear index, and is determined by fitting the wind speed measured by the laser radar in the up-down light speed; v (V) to The vector is expressed as a tower shadow effect, beta is a wind acceleration parameter, phi is an included angle parameter of a wind wheel assembly blade and the ground in the vertical direction, l is a distance parameter between the wind wheel and a wind turbine tower, and d is a distance parameter between the blade and the hub;
step 3, data acquisition and processing
a) Acquiring wind speed data at the height of a fan hub by adopting a laser radar, simultaneously acquiring cabin anemometer data and rotating speed data, wherein the sampling frequency is 1Hz, and respectively calculating the acquired data to obtain an arithmetic average value of 10 min;
b) And c) carrying out abnormal elimination on the data counted in the step a), wherein the abnormal elimination comprises the condition of damage of test equipment, the data that the average wind speed of 10min is lower than the cut-in wind speed of the fan or higher than the cut-out wind speed and the fan electricity limiting data.
c) Dividing the wind direction angle of 0-360 degrees into 36 intervals by using an interval method, wherein the width of each interval is 10 degrees, and judging whether each unit is in a wake flow area or not by combining the full-field sector division model in the step 1;
d) Substituting the data measured by the laser radar into the inflow equivalent wind speed model in the step 2 to calculate and convert the data into inflow equivalent wind speed according to the judging result of whether the data is in the wake flow area or not;
e) Dividing the wind speed acquired by the laser radar into a plurality of Bin intervals according to intervals, wherein the central value of each Bin interval is an integer multiple of the wind speed interval, and simultaneously dividing the fan rotating speed corresponding to the wind speed measured by the radar and the wind speed of a cabin anemometer according to Bin method intervals; calculating a cabin wind speed average value, an equivalent wind speed average value and a rotating speed average value of each Bin interval by using the following formula (3), wherein the preferable wind speed interval is 0.5m/s in consideration of the efficiency of model calculation:
in the formula, v n,i Mean value of cabin wind speed of ith Bin section, v n,i,j The cabin wind speed of the j th group in the i Bin interval; v eq,i For the inflow equivalent wind speed average value of the ith Bin section, v eq,i,j The wind speed is equivalent to the inflow wind speed of the j-th group in the i-th Bin interval; v r,i The average value v of the fan rotation speed in the ith Bin interval r,i,j The rotation speed of the fan in the j group in the i Bin interval is the rotation speed of the fan in the j group;
step 4, transfer function establishment
The IEC 61400-12-2 fits the cabin wind speed and the free incoming flow wind speed by adopting a linear function, the calculation method is simple, but ignores the influence of factors such as rotating speed and the like, has larger error by adopting the linear fitting, has high accuracy and reliability to be further improved, and is used for improving the accuracy and efficiency of the calculation of the cabin transfer function based on the analysis; for the interval above the rated rotation speed, the inflow wind speed is regarded as a single-value function of the cabin wind speed as the rotation speed is a fixed value, and polynomial fitting is carried out:
a) Cutting-in speed to rated speed interval
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n Rotational speed v of fan r As an independent variable, a polynomial surface fitting method is adopted, and a calculation formula is shown as follows, wherein c is a undetermined fitting parameter:
fitting suggestions are five-term formulas;
b) Interval above rated rotation speed
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n As an independent variable, a polynomial fitting method is adopted, and a calculation formula is shown as follows, wherein b is a pending fitting parameter:
v eq ＝f(v n )＝b 0 +b 1 v n +b 2 v n 2 +b 3 v n 3 +... (5)
fitting suggestions are five-term formulas;
after the whole-field cabin transfer function correction method is established, transfer function customization correction can be carried out on the whole-field fan according to wind directions, free flow wind speed recovery precision is effectively improved, and further fan operation control and power performance precision are improved.
In order to verify the accuracy of the established transfer function, the invention combines with the actually measured power curve data of the cabin lidar of a certain plain wind power plant, the actually measured data period is 2022, 3 months, 1 day to 2022, 8 months, 31 days, the SCADA data of the unit of the same period is collected in the verification process, the data such as wind direction, cabin wind speed, unit position and the like are substituted into the cabin transfer function established by the invention to calculate the corrected cabin wind speed, and the cabin wind speed is substituted into a calculation formula adopted by the cabin wind speed IEC to calculate the cabin wind speed, and the wind speed-power curve established by the two methods is respectively compared with the actually measured standard power curve of the cabin radar, as shown in fig. 3, the verification result shows that the transfer function calculation method and the actually measured data provided by the invention have higher coincidence degree, the error rate is +0.997 percent, and the error rate of the method and the actually measured data provided by the IEC is up to-3.945 percent.
Claims (4)
1. A method for correcting a full-field cabin transfer function, comprising the steps of:
step 1, full field fan sector division
The method comprises the steps of collecting full-field fan machine point coordinate information, elevation information, wind direction information, wind speed information and turbulence intensity in full-field fan sector division, predicting full-field flow field distribution conditions under different wind direction variables by combining a wake superposition model, and further judging that each machine position is fan inflow wind resource information, wherein a full-field fan sector judgment model is as follows:
wherein F is S Judging a model for the sector of the full-field fan; f (theta) is a wind direction model, and different wind direction angles theta are input to convert a coordinate system, wherein x, y and z are position coordinate parameters under a corresponding coordinate system; v (x, y, z) is the three-dimensional inflow of the fanWind speed, measured by lidar; v (V) w Is a three-dimensional wake model and is used for predicting wake wind speed distribution, wherein k is a wake expansion coefficient, m is an empirical coefficient, and is determined by the actual running condition of a fan, and r 0 For the length of the wind wheel blade r w For wake radius at downwind position x, σ is the standard deviation of gaussian distribution, a is the axial induction factor;
step 2, establishing an inflow equivalent wind speed model
Setting input parameters of an inflow equivalent wind speed model according to the inflow wind condition of the fan judged in the step 1, wherein the impeller plane inflow equivalent wind speed model is shown as the following formula (2), and single-point wind speed measurement is carried out by adopting a laser radar:
wherein V is eq Equivalent wind speed for inflow;the wind speed is the wind speed of the height plane of the fan hub; v (V) w Representing wake parameter effect vectors; v (V) sh Vector representing wind shear phenomenon, v 1 At a height h 1 The wind speed at the position, alpha is a wind shear index, and is determined by fitting the wind speed measured by the laser radar in the up-down light speed; v (V) to The vector is expressed as a tower shadow effect, beta is a wind acceleration parameter, phi is an included angle parameter of a wind wheel assembly blade and the ground in the vertical direction, l is a distance parameter between the wind wheel and a wind turbine tower, and d is a distance parameter between the blade and the hub;
step 3, data acquisition and processing
a) Acquiring wind speed data at the height of a fan hub by adopting a laser radar, simultaneously acquiring cabin anemometer data and rotating speed data, wherein the sampling frequency is 1Hz, and respectively calculating the acquired data to obtain an arithmetic average value of 10 min;
b) And c) carrying out abnormal elimination on the data counted in the step a), wherein the abnormal elimination comprises the condition of damage of test equipment, the data that the average wind speed of 10min is lower than the cut-in wind speed of the fan or higher than the cut-out wind speed and the fan electricity limiting data.
c) Dividing the wind direction angle of 0-360 degrees into 36 intervals by using an interval method, wherein the width of each interval is 10 degrees, and judging whether each unit is in a wake flow area or not by combining the full-field sector division model in the step 1;
d) Substituting the data measured by the laser radar into the inflow equivalent wind speed model in the step 2 to calculate and convert the data into inflow equivalent wind speed according to the judging result of whether the data is in the wake flow area or not;
e) Dividing the wind speed acquired by the laser radar into a plurality of Bin intervals according to intervals, wherein the central value of each Bin interval is an integer multiple of the wind speed interval, and simultaneously dividing the fan rotating speed corresponding to the wind speed measured by the radar and the wind speed of a cabin anemometer according to Bin method intervals; calculating a cabin wind speed average value, an equivalent wind speed average value and a rotating speed average value of each Bin interval by using the following formula (3):
in the formula, v n,i Mean value of cabin wind speed of ith Bin section, v n,i,j The cabin wind speed of the j th group in the i Bin interval; v eq,i For the inflow equivalent wind speed average value of the ith Bin section, v eq,i,j The wind speed is equivalent to the inflow wind speed of the j-th group in the i-th Bin interval; v r,i The average value v of the fan rotation speed in the ith Bin interval r,i,j The rotation speed of the fan in the j group in the i Bin interval is the rotation speed of the fan in the j group;
step 4, transfer function establishment
Carrying out partition fitting according to the rotating speed characteristics of the unit, regarding the inflow equivalent wind speed as a function of the wind speed of the cabin anemometer and the rotating speed of the unit in the interval from the cut-in rotating speed to the rated rotating speed, and establishing a transfer function of the equivalent inflow wind speed, the cabin wind speed and the rotating speed of the unit through a polynomial surface fitting method; for the interval above the rated rotation speed, the inflow wind speed is regarded as a single-value function of the cabin wind speed as the rotation speed is a fixed value, and polynomial fitting is carried out:
a) Cutting-in speed to rated speed interval
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n Rotational speed v of fan r As independent variables, a polynomial surface fitting method is adopted, and a calculation formula is shown as follows, wherein c is a fitting parameter to be determined;
b) Interval above rated rotation speed
Equivalent wind velocity v of inflow eq As a dependent variable, the nacelle wind speed v n As an independent variable, a polynomial fitting method is adopted, and a calculation formula is shown as follows, wherein b is a pending fitting parameter:
v eq ＝f(v n )＝b 0 +b 1 v n +b 2 v n 2 +b 3 v n 3 +... (5)
after the whole-field cabin transfer function correction method is established, transfer function customization correction can be carried out on the whole-field fan according to wind directions, free flow wind speed recovery precision is effectively improved, and further fan operation control and power performance precision are improved.
2. The method for correcting the transfer function of the full-field nacelle according to claim 1, wherein in the step one full-field fan sector judgment model, the wake expansion coefficient k is 0.075; and combining the characteristics of Gaussian distribution, wherein the value of the empirical coefficient m is 2.58.
3. The full field nacelle transfer function correction method of claim 1, wherein the wind speed interval in step three e) is 0.5m/s.
4. The full-field nacelle transfer function correction method of claim 1, wherein the step four transfer function establishes a preferably five-term expression.
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