A method and system for measuring axial projection wind speed of a wind turbine unit

Abstract

The application discloses an axial projection wind speed measurement method and system of a wind turbine unit, relates to the field of laser radars, and alleviates the problems of insufficient data continuity, incapability of providing stable wind speed data, easy interference of blade false signal and inaccurate measurement of the existing axial projection wind speed measurement technology.A kind of axial projection wind speed measurement method obtains multiple sets of measurement data, for each distance gate number, traverses each kind of beam number, obtains effective radial wind speed value and radial wind speed state bit, and then obtains axial projection wind speed.The method disclosed by the application is suitable for the field of wind turbine unit control, and the axial projection wind speed measurement system of the wind turbine unit disclosed by the application is suitable for being embedded in existing wind turbine unit control equipment.

Description

Technical Field

[0001] This invention relates to the field of lidar, specifically to the field of lidar wind measurement. Background Technology

[0002] LiDAR, as the core sensor for feedforward control of wind turbine generators, measures the radial wind speed (RWS) in front of the turbine using a multi-beam non-contact method. This RWS is then converted into the effective wind speed (RAWS) along the turbine's main axis via an axial projection algorithm. This provides 0.2-1 seconds of advance wind condition input for pitch and speed control strategies, potentially improving generator efficiency by 3%-5% and reducing mechanical losses by over 10%. It is a key technology for overcoming the "control delay" defect of traditional nacelle anemometers. Currently, there are two main methods for measuring axial projection wind speed:

[0003] The first type is the real-time measurement method, such as the traditional axial projection algorithm. This type of method relies solely on real-time single-frame radial wind speed data, without historical data redundancy, and directly calculates the axial projected wind speed. However, this method lacks anti-interference capabilities and the data is discontinuous. In the actual operation of wind turbine generators, lidar measurements face various interferences, such as: 1. Blade shading effect, which refers to the periodic blocking of the laser beam during the rotation of the wind turbine blades, resulting in invalid measurement data; 2. Signal attenuation and noise, which refers to the degradation of signal quality caused by changes in atmospheric conditions, rain, snow, and other weather conditions, affecting the accuracy of measurement results; 3. Transient hardware failure, which refers to sensor malfunctions that generate invalid status codes or NaN values, resulting in the inability to obtain measurement results.

[0004] When the above situation occurs, existing real-time measurement methods directly output invalid values, resulting in intermittent gaps in valid wind speed data. This discontinuous wind speed data cannot provide a stable and reliable feedforward input for the wind turbine control system, directly affecting the control strategy.

[0005] The second method is the sliding window measurement method, such as the sliding window averaging algorithm. This method constructs a time window, averages all valid radial wind speed data within the window, and then projects the average before calculation. However, due to high-frequency interference from blade artifacts, this method suffers from measurement inaccuracies.

[0006] "Blade artifact signal" refers to the spurious velocity signal formed by the detection beam emitted by the lidar, after specular reflection from the smooth surface of the blade and electromagnetic diffraction from the blade edges, superimposed on the real airflow echo signal. Essentially, this signal is a misreading of the blade's mechanical motion in lidar Doppler frequency shift measurements, a structural interference unique to wind turbine lidar measurement scenarios. The interference mechanism caused by this "blade artifact signal" involves the introduction of periodic spurious signals into the measurement data due to effects such as blade surface reflection and edge diffraction; the spectral characteristics are that the blade artifact signal manifests as an additional high-frequency component in the wind speed power spectrum; and the control effect is that it causes the wind speed turbulence spectrum to deviate from the Kolmogorov -5 / 3 slope characteristic of natural turbulence. Therefore, the blade artifact signal causes the wind speed turbulence spectrum to deviate from natural turbulence, causing the wind turbine control strategy to respond based on distorted wind speed information, resulting in an "overcompensation" phenomenon. This not only increases the mechanical losses of the unit but also leads to a loss of power generation efficiency.

[0007] In summary, existing axial projection wind speed measurement technologies suffer from insufficient data continuity, inability to provide stable wind speed data, susceptibility to blade artifact interference, and inaccurate measurements. Summary of the Invention

[0008] This invention alleviates the problems of insufficient data continuity, inability to provide stable wind speed data, susceptibility to blade artifact interference, and measurement inaccuracies in existing axial projection wind speed measurement techniques. This invention provides the following solution:

[0009] Option 1: A method for measuring wind speed in a wind turbine, comprising the following steps:

[0010] Step S01: Obtain multiple sets of measurement data, including radial wind speed values. Radial wind speed status Distance gate number Beam number and timestamp ;

[0011] Step S02: For each distance gate number, iterate through each beam number and perform the following processing for each beam number:

[0012] According to the timestamp In chronological order, each timestamp The corresponding radial wind speed values ​​and radial wind speed status bits are stored sequentially in parallel into the time buffer groups, resulting in a total of N time buffer groups, where N is the timestamp. The number of;

[0013] Step S03: For each distance gate number, iterate through each beam number and perform the following processing for each beam number:

[0014] If, in the time buffer group, the first element satisfying the condition that the radial wind speed state bit is 1 can be found in reverse chronological order, and the radial wind speed value... If the radial wind speed threshold is within the specified range, then the current radial wind speed value will be... As an effective radial wind speed;

[0015] Otherwise, As the effective radial wind speed, and the corresponding radial wind speed state bit is 0;

[0016] Step S04: For each distance gate, the number of beams and their corresponding effective radial wind speed values ​​and radial wind speed status are processed as follows to obtain the corresponding axial projected wind speed. ;

[0017] If the distance gate has a total of The radial wind speed status bit corresponding to each of the aforementioned beam numbers is 1, wherein... ≥beam threshold Based on the above The effective radial wind speed value corresponding to each of the beam numbers is used to obtain the axial projected wind speed. ;

[0018] Otherwise, As axial projection wind speed .

[0019] Furthermore, in one embodiment of the present invention, the step S02 described The range is any integer from 2 to 10.

[0020] Furthermore, in one embodiment of the present invention, the radial wind speed threshold range in step S03 is between 0 and 50. .

[0021] Furthermore, in one embodiment of the present invention, the beam threshold mentioned in step S04... The value range is from 0 to 2.

[0022] Furthermore, in one embodiment of the present invention, in step S04, by...

[0023]

[0024] Obtain the axial projected wind speed, where... This is the projection correction factor.

[0025] Option 2: A wind speed measurement system for a wind turbine unit, comprising the following modules:

[0026] Module 1 is used to obtain multiple sets of measurement data, including radial wind speed values. Radial wind speed status Distance gate number Beam number and timestamp ;

[0027] Module 2 is used to iterate through each beam number for each distance gate number, and perform the following processing for each beam number:

[0028] According to the timestamp In chronological order, each timestamp The corresponding radial wind speed values ​​and radial wind speed status bits are stored sequentially in parallel into the time buffer groups, resulting in a total of N time buffer groups, where N is the timestamp. The number of;

[0029] Module 3 is used to iterate through each beam number for each distance gate number, and perform the following processing for each beam number:

[0030] If, in the time buffer group, the first element satisfying the condition that the radial wind speed state bit is 1 can be found in reverse chronological order, and the radial wind speed value... If the radial wind speed threshold is within the range, then the current radial wind speed value will be... As an effective radial wind speed;

[0031] Otherwise, As the effective radial wind speed, and the corresponding radial wind speed state bit is 0;

[0032] Module four is used to process the numbered beams under each distance gate, along with their corresponding effective radial wind speed values ​​and radial wind speed status, to obtain the corresponding axial projected wind speed.

[0033] If the distance gate has a total of The radial wind speed status bit corresponding to each of the aforementioned beam numbers is 1, wherein... ≥beam threshold Based on the above The effective radial wind speed value corresponding to each of the beam numbers is used to obtain the axial projected wind speed. ;

[0034] Otherwise, As axial projection wind speed .

[0035] Option 3: An electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0036] Memory, used to store computer programs;

[0037] When a processor executes a program stored in memory, it implements the method described in Scheme 1.

[0038] Option 4: A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method described in Option 2.

[0039] The axial projection wind speed measurement method and system for wind turbines described in this invention utilizes lidar wind measurement, effectively alleviating the problems of insufficient data continuity, inability to provide stable wind speed data, susceptibility to blade artifact interference, and inaccurate measurement in existing axial projection wind speed measurement technologies. Specific beneficial effects include:

[0040] 1. The axial projection wind speed measurement method of the wind turbine described in this invention, through the whole process logic of "caching window construction - priority repair of the most recent valid value - multi-beam fusion calculation of axial wind speed", can provide stable and accurate wind speed data that eliminates blade artifact signal interference in the axial wind speed spectrum while ensuring data continuity, which helps to reduce the mechanical loss of the unit and improve the power generation efficiency.

[0041] 2. The axial projection wind speed measurement method for wind turbines described in this invention stores historical valid data in a time-dimensional buffer pool, solving the problem of missing current data due to blade obstruction and effectively improving data efficiency. For radial wind speed data, a "nearest first" repair logic is used to accurately remove blade artifact signal interference from the axial wind speed spectrum, while ensuring data real-time performance and avoiding the loss of high-frequency characteristics of the wind speed spectrum due to excessive smoothing by the buffer sliding window averaging. Finally, the axial projection wind speed is output to meet the requirements of wind turbine control. Therefore, this invention achieves accurate removal of high-frequency component interference in the axial projection wind speed power spectrum introduced by blade artifact signals, making the processed wind speed turbulence spectrum conform to natural turbulence characteristics and improving the effectiveness of axial wind speed data used for wind turbine control.

[0042] The axial projection wind speed measurement method for wind turbines described in this invention is applicable to the field of wind turbine control. The axial projection wind speed measurement system for wind turbines described in this invention is suitable for embedding in existing wind turbine control equipment. Attached Figure Description

[0043] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 This is a schematic diagram of the laser wind measurement radar beam geometry as described in Implementation Method 5;

[0045] Figure 2These are wind speed power spectrum comparison diagrams generated using different methods at a distance of 100 meters without blade obstruction, as described in Implementation Method 7.

[0046] Figure 3 The wind speed power spectrum comparison diagrams were generated at a distance of 100 meters with blade obstruction as described in Implementation Method 7, using different methods.

[0047] Figure label:

[0048] Wind-measuring lidar Lidar 1; beam 2; axial projection wind speed 3. Detailed Implementation

[0049] Various embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. The embodiments described with reference to the drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0050] Implementation Method 1: The axial projection wind speed measurement method for a wind turbine unit described in this implementation method includes the following steps:

[0051] Step S01: Obtain multiple sets of measurement data, including radial wind speed values. Radial wind speed status Distance gate number Beam number and timestamp ;

[0052] Step S02: For each distance gate number, iterate through each beam number and perform the following processing for each beam number:

[0053] According to the timestamp In chronological order, each timestamp The corresponding radial wind speed values ​​and radial wind speed status bits are stored sequentially in parallel into the time buffer groups, resulting in a total of N time buffer groups, where N is the timestamp. The number of;

[0054] Step S03: For each distance gate number, iterate through each beam number and perform the following processing for each beam number:

[0055] If, in the time buffer group, the first element satisfying the condition that the radial wind speed state bit is 1 can be found in reverse chronological order, and the radial wind speed value... If the radial wind speed threshold is within the range, then the current radial wind speed value will be... As an effective radial wind speed;

[0056] Otherwise, As the effective radial wind speed, and the corresponding radial wind speed state bit is 0;

[0057] Step S04: For each distance gate, the number of beams and their corresponding effective radial wind speed values ​​and radial wind speed status are processed as follows to obtain the corresponding axial projected wind speed. :

[0058] If the distance gate has a total of The radial wind speed status bit corresponding to each of the aforementioned beam numbers is 1, wherein... ≥beam threshold Based on the above The effective radial wind speed value corresponding to each of the beam numbers is used to obtain the axial projected wind speed. ;

[0059] Otherwise, As axial projection wind speed .

[0060] In this embodiment, step S01 preferably organizes the multiple sets of measurement data into a radial wind speed value matrix. and radial wind speed state position matrix This structured approach facilitates data indexing and makes data processing simple and efficient.

[0061] In this embodiment, the radial wind speed status bit is 1 to indicate validity and 0 to indicate invalidity.

[0062] In this embodiment, the steps described in step S03 are as follows: As a marker, it means there is no effective radial wind speed.

[0063] In this embodiment, the distance gates in the distance gate number correspond to different radial positions of the fan.

[0064] In this embodiment, N time cache groups are obtained in step S02 for data storage operations. In this application, the time cache groups are implemented using a "first-in, first-out" (FIFO) strategy. This storage method can ensure that the cached data is always the latest N slices. During data processing, when new data enters, the earliest data stored in the time cache group is removed.

[0065] In this embodiment, the multiple beams of the lidar are preferably symmetrical about the main axis of the wind turbine.

[0066] The axial projection wind speed measurement method described in this embodiment obtains the axial wind speed through step S02 time buffering, step S03 recent valid value priority repair, and step S04 multi-beam fusion. While ensuring data continuity, it can provide stable and accurate wind speed data that eliminates blade artifact signal interference in the axial wind speed spectrum, which helps to reduce unit mechanical losses and improve power generation efficiency.

[0067] The aforementioned recent valid value priority repair ensures the real-time nature and validity of the repaired data by executing a "prioritize current, reverse search" repair logic. Radial wind speed data repair is performed by judging current data and searching historical data, and invalid data processing is provided to improve the accuracy and efficiency of the repair.

[0068] The multi-beam fusion method fuses radial wind speed data from multiple beams within a single distance gate. By filtering out effective beams and eliminating invalid data, it improves fusion efficiency and accuracy.

[0069] Implementation Method Two: This implementation method further defines the axial projection wind speed measurement method described in Implementation Method One. In this implementation method, the step S02 described... The range is any integer from 2 to 10.

[0070] In this embodiment, the The judgment is made based on the sampling frequency. For example, when the sampling frequency is 4Hz, the window time span is 4s and the buffer group size is 4.

[0071] This embodiment further defines step S02, providing an example of the size of the time buffer group. The size N of the time buffer group balances data efficiency and real-time performance. If N is too small (e.g., 1), there is insufficient historical data to repair invalid values ​​caused by occlusion, degenerating into a real-time measurement method that cannot solve the problem of missing current data due to blade occlusion. If N is too large (>10), the timeliness of historical data is poor, and using it for repair will lead to distortion of wind speed information. Therefore, the size N of the time buffer group is 2~10 based on typical sampling frequency and feedforward control requirements, ensuring both data efficiency and the timeliness of data repair.

[0072] Implementation Method 3: This implementation method further defines the axial projection wind speed measurement method described in Implementation Method 1. In this implementation method, the radial wind speed threshold range in step S03 is 0 to 50. .

[0073] This implementation further defines step S03, providing an example of the radial wind speed threshold range. The radial wind speed threshold is used to eliminate physically impossible outliers. If the upper limit is too high, it cannot filter out extreme spikes caused by system hardware failures or strong interference, thus contaminating the radial wind speed; if the lower limit is too small, it may mistakenly eliminate valid data under real extreme operating conditions or complex wind conditions. The range of 0~50m / s in this implementation covers the operating and survival conditions of various wind turbines in the IEC standard, effectively eliminating outliers while ensuring data availability under extreme conditions.

[0074] Implementation Method Four: This implementation method further defines the axial projection wind speed measurement method described in Implementation Method One. In this implementation method, the beam threshold mentioned in step S04... The value range is from 0 to 2.

[0075] In this embodiment, the beam threshold The preferred value is 2.

[0076] This embodiment further defines step S04, specifically the beam threshold. An example was provided to illustrate that the beam threshold M determines the threshold for multi-beam fusion calculation of axial wind speed: if M is too small (e.g., 1), the measurement deviation of a single beam is large, which cannot represent the axial wind speed of the wind turbine surface and results in insufficient accuracy; if M is too large (e.g., 3 or 4), it is sensitive to instantaneous blade shading, resulting in low data efficiency and inability to provide continuous wind speed input. M is preferably 2, which achieves the best balance between data accuracy (spatial averaging of multiple beams) and data efficiency (tolerance for partial beam failure).

[0077] Implementation Method 5: This implementation method further defines the axial projection wind speed measurement method described in Implementation Method 1. In this implementation method, step S04 involves...

[0078]

[0079] Obtain the axial projected wind speed, where... This is the projection correction factor.

[0080] This embodiment further defines step S04 and provides an example of how to obtain the axial projection wind speed, such as... Figure 1 Taking the geometric schematic diagram of a four-beam laser wind radar as an example, the axial projection wind speed is obtained by transforming and fusing the effective beams.

[0081] like Figure 1 As shown, the multiple laser radar beams are symmetrical about the main axis of the wind turbine; beams 1 and 4 are symmetrical, and beams 2 and 3 are symmetrical. In this embodiment, the axial wind speed of the beams is projected to calculate the axial projected wind speed. Different laser radar beams can be calculated by analogy using this principle. It is not required that the angle between each beam and the main axis be consistent. In this case, each beam corresponds to an independent theta angle, and symmetry is preferred.

[0082] Implementation Method Six: This implementation method is based on the axial projection wind speed measurement method of the wind turbine described in Implementation Method One, combined with the beam threshold of the optimized step S02 in Implementation Method Two, the optimized step S03 in Implementation Method Three, the optimized step S04 in Implementation Method Four, and the optimized axial projection wind speed in Implementation Method Five.

[0083] This implementation method can accurately eliminate high-frequency component interference in the wind speed power spectrum introduced by blade artifact signals, such as Figure 2 The bladeless obstruction shown is Figure 3 The comparison with the blade obstruction shown reveals that the power spectrum curve of this embodiment still fits the Kolmogorov -5 / 3 slope curve in the blade obstruction scenario, and the wind speed turbulence spectrum conforms to the characteristics of natural turbulence. This indicates that the blade artifact signal generated by blade obstruction is accurately eliminated. This embodiment improves the reliability (accuracy + data validity) of wind speed data used for wind turbine control, which helps to reduce unit mechanical losses and improve power generation efficiency.

Claims

1. A method for measuring the axial projection wind speed of a wind turbine, characterized in that, Includes the following steps: Step S01: Obtain multiple sets of measurement data, including radial wind speed values. Radial wind speed status Distance gate number Beam number and timestamp ; Step S02: For each distance gate number, iterate through each beam number and perform the following processing for each beam number: According to the timestamp In chronological order, each timestamp The corresponding radial wind speed values ​​and radial wind speed status bits are stored sequentially in parallel into time buffer groups, resulting in a total of N time buffer groups, where N is the timestamp. The number of; Step S03: For each distance gate number, iterate through each beam number and perform the following processing for each beam number: If, in the time buffer group, the first element satisfying the condition that the radial wind speed state bit is 1 can be found in reverse chronological order, and the radial wind speed value... If the radial wind speed threshold is within the specified range, then the current radial wind speed value will be... As an effective radial wind speed; Otherwise, As the effective radial wind speed, and the corresponding radial wind speed state bit is 0; Step S04: For each distance gate, the number of beams and their corresponding effective radial wind speed values ​​and radial wind speed status are processed as follows to obtain the corresponding axial projected wind speed. ; If the distance gate has a total of The radial wind speed status bit corresponding to each of the aforementioned beam numbers is 1, wherein... ≥beam threshold Based on the above The effective radial wind speed value corresponding to each of the beam numbers is used to obtain the axial projected wind speed. ; Otherwise, As axial projection wind speed .

2. The method for measuring the axial projection wind speed of a wind turbine unit according to claim 1, characterized in that, The steps described in step S02 The range is any integer from 2 to 10.

3. The method for measuring the axial projection wind speed of a wind turbine unit according to claim 1, characterized in that, The radial wind speed threshold range mentioned in step S03 is from 0 to 50. .

4. The method for measuring the axial projection wind speed of a wind turbine unit according to claim 1, characterized in that, The beam threshold mentioned in step S04 The value range is from 0 to 2.

5. An axial projection wind speed measurement system for a wind turbine, characterized in that, Includes the following modules: Module 1 is used to obtain multiple sets of measurement data, including radial wind speed values. Radial wind speed status Distance gate number Beam number and timestamp ; Module 2 is used to iterate through each beam number for each distance gate number, and perform the following processing for each beam number: According to the timestamp In chronological order, each timestamp The corresponding radial wind speed values ​​and radial wind speed status bits are stored sequentially in parallel into time buffer groups, resulting in a total of N time buffer groups, where N is the timestamp. The number of; Module 3 is used to iterate through each beam number for each distance gate number, and perform the following processing on each beam number: If, in the time buffer group, the first element satisfying the condition that the radial wind speed state bit is 1 can be found in reverse chronological order, and the radial wind speed value... If the radial wind speed threshold is within the specified range, then the current radial wind speed value will be... As an effective radial wind speed; Otherwise, As the effective radial wind speed, and the corresponding radial wind speed state bit is 0; Module four is used to process the numbered beams under each distance gate, along with their corresponding effective radial wind speed values ​​and radial wind speed status, to obtain the corresponding axial projected wind speed. If the distance gate has a total of The radial wind speed status bit corresponding to each of the aforementioned beam numbers is 1, wherein... ≥beam threshold Based on the above The effective radial wind speed value corresponding to each of the beam numbers is used to obtain the axial projected wind speed. ; Otherwise, As axial projection wind speed .

6. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1-4.

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