Special programmable controller for wind speed measurement of wind power generator

Abstract

The application relates to the field of controllers, and particularly discloses a special programmable controller for wind speed measurement of a wind generator, which comprises an input interface, a memory, a central processing unit and an output interface; the input interface is used for receiving wind speed values at multiple predetermined time points in a predetermined time period from multiple anemometers arranged at the tail of the offshore wind generator; the memory is used for storing a wind speed value reference matrix and multiple wind speed query characteristic vectors, wherein the wind speed value reference matrix and the wind speed query characteristic vectors are obtained based on the wind speed values at the multiple predetermined time points in the predetermined time period; the central processing unit is used for obtaining multiple weight values based on the wind speed value reference matrix and the multiple wind speed query characteristic vectors, obtaining multiple wind speed global average values based on the multiple wind speed query characteristic vectors, and obtaining a wind speed measurement value based on the multiple weight values and the multiple wind speed global average values; and the output interface is used for outputting the wind speed measurement value. According to the special programmable controller, the accuracy of wind speed measurement of the wind generator can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of controllers, in particular to a special programmable controller for wind speed measurement of a wind generator. BACKGROUND

[0002] With the gradual expansion of the scale of wind turbine generators and the increasing perfection of unit safety protection, the operation of wind turbine generators, i.e. the power generation performance, has been paid more and more attention, that is, to improve the power generation and availability of wind generators. How to fully utilize wind energy and obtain maximum energy and economic benefits has become a problem that the main control system of a wind turbine generator must face.

[0003] At present, the starting control mode of a wind generator is generally that if the wind speed value detected by the wind speed sensor of the wind generator is greater than the starting wind speed for 2-5 minutes, the wind generator is started if it is in standby state. This method can prevent unnecessary starting of the wind generator when the wind speed value is small due to the addition of a delay judgment.

[0004] However, when the wind generator starts in a small wind, the wind speed is small and the hub rotation speed is slow, which will cause the blade (for example, when the blade is located in the vertical upward position) to block the anemometer for a long time. Since the starting condition of the wind generator is to detect that the wind speed value is greater than the starting wind speed (generally 3 meters / second) for a period of time (generally 3 minutes), the wind speed measurement value may be low, which will cause the unit to fail to start.

[0005] At present, the wind speed sensor of the wind generator is installed at the tail of the wind generator cabin. When the wind generator is directly facing the wind direction, the blade of the wind generator will block the anemometer. A current solution is to raise the altitude of the anemometer. However, since the length of the blade is relatively long (generally greater than 40 meters), the anemometer is still blocked by the blade, resulting in a low wind speed measurement value. Especially in a small wind, the anemometer is seriously affected by the blade blocking, resulting in inaccurate wind speed measurement by the anemometer, which affects the wind energy utilization rate and power generation of the wind generator.

[0006] Therefore, there is an urgent need for a wind speed measurement technology for a wind generator with high wind speed measurement accuracy. SUMMARY

[0007] The present application aims to at least solve one of the technical problems in the related art. To this end, the present application provides a special programmable controller for wind speed measurement of a wind generator, mainly aiming to improve the accuracy of wind speed measurement of a wind generator.

[0008] According to an embodiment of a first aspect of the present application, a dedicated programmable controller for wind speed measurement of a wind turbine is provided, comprising an input interface, a memory, a central processing unit and an output interface;

[0009] The input interface is configured to receive wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at a tail of the wind turbine;

[0010] The memory is configured to store a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein the wind speed value reference matrix and the plurality of wind speed query feature vectors are based on the wind speed values at the plurality of predetermined time points within the predetermined time period;

[0011] The central processing unit is configured to obtain a plurality of weight values based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, obtain a plurality of wind speed global mean values based on the plurality of wind speed query feature vectors, and obtain a wind speed measurement value based on the plurality of weight values and the plurality of wind speed global mean values;

[0012] The output interface is configured to output the wind speed measurement value.

[0013] In an embodiment of the present application, the central processing unit comprises a calculation unit, and the calculation unit is specifically configured to: multiply the plurality of wind speed query feature vectors with the wind speed value reference matrix respectively to obtain a plurality of global query feature vectors; input the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold respectively to obtain a plurality of global state query vectors; and obtain the plurality of weight values based on the plurality of global state query vectors.

[0014] In an embodiment of the present application, the obtaining of the plurality of weight values based on the plurality of global state query vectors comprises: calculating a Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix; multiplying each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors; and calculating a mean value of eigenvalues of all positions of each global mapping weight vector to obtain the plurality of weight values.

[0015] In an embodiment of the present application, the obtaining of the plurality of wind speed global mean values based on the plurality of wind speed query feature vectors comprises: calculating a mean value of eigenvalues of all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors to obtain the plurality of wind speed global mean values.

[0016] In an embodiment of the present application, the central processing unit comprises an operation unit, and the operation unit is specifically configured to: calculate a weighted sum of the plurality of wind speed global mean values with the plurality of weight values as weights to obtain the wind speed measurement value.

[0017] In one embodiment of the present application, in the plurality of parallel switches, the predetermined threshold of each of the switches is obtained by the same control threshold and / or different control threshold.

[0018] In one embodiment of the present application, the computing unit comprises: a Hamming distance computing subunit configured to input each two of the plurality of global state query vectors into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values; and an arrangement subunit configured to arrange the plurality of Hamming distance values in two dimensions to obtain the global state mapping matrix.

[0019] In one embodiment of the present application, the computing unit comprises: a first adder subunit configured to pass the feature values of all positions of each of the global mapping weight vectors through an adder to obtain a first sum value; a first counting subunit configured to pass each of the global mapping weight vectors through a counter to obtain a first count value; and a first divider subunit configured to pass the first sum value and the first count value through a divider to obtain the weight value.

[0020] In one embodiment of the present application, the computing unit comprises: a second adder subunit configured to pass the feature values of all positions of each of the wind speed query feature vectors through an adder to obtain a second sum value; a second counting subunit configured to pass each of the global mapping weight vectors through a counter to obtain a second count value; and a second divider subunit configured to pass the second sum value and the second count value through a divider to obtain the wind speed global mean value.

[0021] In one embodiment of the present application, the computing unit comprises: a second adder subunit configured to pass the feature values of all positions of each of the wind speed query feature vectors through an adder to obtain a second sum value; a second counting subunit configured to pass each of the global mapping weight vectors through a counter to obtain a second count value; and a second divider subunit configured to pass the second sum value and the second count value through a divider to obtain the wind speed global mean value.

[0022] According to the second aspect of the embodiments of the present application, a method for running a special-purpose programmable controller for wind speed measurement of a wind turbine is also provided, comprising:

[0023] receiving wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of the offshore wind turbine;

[0024] obtaining a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein the wind speed value reference matrix and the wind speed query feature vectors are obtained based on the wind speed values at the plurality of predetermined time points within the predetermined time period;

[0025] Based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, a plurality of weight values is obtained, a plurality of wind speed global mean values is obtained based on the plurality of wind speed query feature vectors, and a wind speed measurement value is obtained based on the plurality of weight values and the plurality of wind speed global mean values.

[0026] In an embodiment of the present application, the obtaining of the plurality of weight values based on the wind speed value reference matrix and the plurality of wind speed query feature vectors comprises: performing matrix multiplication of the plurality of wind speed query feature vectors and the wind speed value reference matrix respectively to obtain a plurality of global query feature vectors; inputting the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold respectively to obtain a plurality of global state query vectors; and obtaining the plurality of weight values based on the plurality of global state query vectors.

[0027] In an embodiment of the present application, the obtaining of the plurality of weight values based on the plurality of global state query vectors comprises: calculating a Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix; multiplying each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors; and calculating a mean value of eigenvalues of all positions of each global mapping weight vector to obtain the plurality of weight values.

[0028] In an embodiment of the present application, the obtaining of the plurality of wind speed global mean values based on the plurality of wind speed query feature vectors comprises: calculating a mean value of eigenvalues of all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors to obtain the plurality of wind speed global mean values.

[0029] In an embodiment of the present application, the obtaining of the wind speed measurement value based on the plurality of weight values and the plurality of wind speed global mean values comprises: calculating a weighted sum of the plurality of wind speed global mean values with the plurality of weight values as weights to obtain the wind speed measurement value.

[0030] In an embodiment of the present application, in the plurality of parallel switches, the predetermined threshold of each switch is obtained by the same control threshold and / or different control thresholds.

[0031] In an embodiment of the present application, the calculation of the Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain the global state mapping matrix comprises: inputting each two global state query vectors in the plurality of global state query vectors into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values; and performing two-dimensional arrangement on the plurality of Hamming distance values to obtain the global state mapping matrix.

[0032] In one embodiment of the present application, the calculating the average of the eigenvalues of all positions of each global mapping weight vector to obtain a plurality of weight values comprises: passing the eigenvalues of all positions of each global mapping weight vector through an adder to obtain a first sum value; passing each global mapping weight vector through a counter to obtain a first count value; and passing the first sum value and the first count value through a divider to obtain the weight value.

[0033] In one embodiment of the present application, the calculating the average of the eigenvalues of all positions of each global mapping weight vector to obtain a plurality of weight values comprises: passing the eigenvalues of all positions of each global mapping weight vector through an adder to obtain a first sum value; passing each global mapping weight vector through a counter to obtain a first count value; and passing the first sum value and the first count value through a divider to obtain the weight value.

[0034] In one embodiment of the present application, the calculating the average of the eigenvalues of all positions of each global mapping weight vector to obtain a plurality of weight values comprises: passing the eigenvalues of all positions of each global mapping weight vector through an adder to obtain a first sum value; passing each global mapping weight vector through a counter to obtain a first count value; and passing the first sum value and the first count value through a divider to obtain the weight value.

[0035] In one or more embodiments of the present application, the special programmable controller comprises an input interface, a memory, a central processing unit and an output interface; the input interface is configured to receive wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of an offshore wind turbine; the memory is configured to store a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein the wind speed value reference matrix and the wind speed query feature vectors are obtained based on the wind speed values at the plurality of predetermined time points within the predetermined time period; the central processing unit is configured to obtain a plurality of weight values based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, obtain a plurality of wind speed global averages based on the plurality of wind speed query feature vectors, and obtain a wind speed measurement value based on the plurality of weight values and the plurality of wind speed global averages; and the output interface is configured to output the wind speed measurement value. According to the special programmable controller of the present application, the accuracy of wind speed measurement of the wind turbine can be improved. In this case, the special programmable logic controller comprises an input interface, an output interface, a memory, a central processing unit, etc., and obtains a wind speed value reference matrix and a wind speed query feature vector based on wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of an offshore wind turbine, obtains a wind speed measurement value based on the wind speed value reference matrix and the wind speed query feature vector, fully considers the correlation between the wind speed values measured by each anemometer at each predetermined time point, and improves the accuracy of wind speed measurement of the wind turbine.

[0036] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the attendant drawings or can be learned by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0037] The foregoing and other objects, features and advantages of the application will be apparent to those skilled in the art in view of the following detailed description of the application, from the drawings, and from the claims.

[0038] Figure 1 Application scenario diagram of the special programmable controller for wind speed measurement of wind turbine according to the embodiment of the present application;

[0039] Figure 2 Structure diagram of the special programmable controller for wind speed measurement of wind turbine according to the embodiment of the present application;

[0040] Figure 3 Architecture operation schematic diagram of the special programmable controller for wind speed measurement of wind turbine according to the embodiment of the present application;

[0041] Figure 4 Block diagram of the central processing unit of the special programmable controller for wind speed measurement of wind turbine according to the embodiment of the present application;

[0042] Figure 5 Flow chart of the operation method of the special programmable controller for wind speed measurement of wind turbine according to the embodiment of the present application. DETAILED DESCRIPTION

[0043] The exemplary embodiments will be described in detail herein below with reference to the drawings. The following description is merely exemplary in nature and is not intended to limit the present application, application, or the application in any way. Although specific embodiments of the application will be described herein for illustrative purposes, various changes in form and detail can be made without departing from the spirit and scope of the application.

[0044] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. The illustrative description of the above terms in the present application does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples. In addition, different embodiments or examples described in the present application and the features of different embodiments or examples can be combined and combined by those skilled in the art without contradiction.

[0045] In addition, the terms "first", "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise specifically limited. It should also be understood that the term "and / or" used in the present application means and includes any or all possible combinations of one or more associated listed items.

[0046] The embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0047] The current wind speed meter of the wind turbine is installed at the tail of the wind turbine cabin. When the wind turbine is directly facing the wind direction, the blades of the wind turbine will block the wind speed meter. A current solution is to raise the altitude of the wind speed meter. However, due to the relatively long length of the blades (generally greater than 40 meters), the wind speed meter is still blocked by the blades, resulting in a low wind speed measurement value. Especially in small wind, the wind speed meter is seriously affected by the blade blocking, resulting in inaccurate wind speed measurement by the wind speed meter, affecting the wind energy utilization rate and power generation of the wind turbine. Therefore, there is an urgent need for a wind speed measurement technology for wind turbines with high wind speed measurement accuracy. Considering the complex and harsh working conditions of offshore wind turbines, it is expected that offshore wind turbines have relatively high control and monitoring robustness. Therefore, in offshore wind turbines, a programmable logic controller (PLC) is used to measure the wind speed, so as to build a special edge side control chip suitable for offshore wind turbine wind speed measurement through the programmable logic controller. However, most of the foreign general PLC devices are used, and most of the inventions are concentrated on the wiring control system of the PLC module and the field device, which cannot realize the controllability based on the data, algorithm and control process inside the PLC module, and the optimization of the algorithm and control process based thereon.

[0048] Therefore, in view of the above technical problems, the present application provides a special programmable controller for wind turbine wind speed measurement and a running method thereof, mainly aiming to improve the accuracy of wind turbine wind speed measurement. In particular, in the application scenario, when the wind turbine is directly facing the wind direction, the blades of the wind turbine will block the wind speed meter, and even if the altitude of the wind speed meter is raised, the wind speed meter will still be blocked by the blades, resulting in a low wind speed measurement value, that is, the wind speed meter cannot be completely unblocked at the hardware end. However, considering that when multiple wind speed meters are installed at the tail of the offshore wind turbine, there is a correlation between the wind speed values measured by each wind speed meter at each predetermined time point, the present application fully excavates and utilizes the implicit correlation between the wind speed data measured by multiple wind speed meters to improve the accuracy of wind speed measurement.

[0049] In the first embodiment, Figure 1 The application scenario diagram of the special programmable controller for wind turbine wind speed measurement according to the embodiment of the present application. In this application scenario, as Figure 1As shown, in the application scenario of the special programmable controller for wind speed measurement of wind turbines, first, from the multiple anemometers deployed at the tail of the offshore wind turbine G (i.e., offshore wind turbine), the number of anemometers is n, specifically including the first anemometer Se1, the second anemometer Se2, the third anemometer Se3, …, and the n-th anemometer Sen, the wind speed values at multiple predetermined time points within a predetermined time period are received from the multiple anemometers, and then the wind speed values at multiple predetermined time points within a predetermined time period are input into the special programmable controller PLC for wind speed measurement of wind turbines through the input interface In, wherein the special programmable controller for wind speed measurement of wind turbines can process the wind speed values at multiple predetermined time points within a predetermined time period to obtain a wind speed measurement value, wherein the wind speed measurement value is output through the output interface Out.

[0050] In this embodiment, the special programmable controller for wind speed measurement of wind turbines includes an input interface, a memory, a central processing unit, and an output interface; the input interface is used to receive wind speed values at multiple predetermined time points within a predetermined time period from multiple anemometers deployed at the tail of the offshore wind turbine; the memory is used to store a wind speed value reference matrix and multiple wind speed query feature vectors, wherein the wind speed value reference matrix and the multiple wind speed query feature vectors are obtained based on the wind speed values at multiple predetermined time points within a predetermined time period; the central processing unit is used to obtain multiple weight values based on the wind speed value reference matrix and the multiple wind speed query feature vectors, obtain multiple wind speed global mean values based on the multiple wind speed query feature vectors, and obtain a wind speed measurement value based on the multiple weight values and the multiple wind speed global mean values; and the output interface is used to output the wind speed measurement value.

[0051] In this embodiment, the wind speed values at multiple predetermined time points within a predetermined time period collected by the multiple anemometers deployed at the tail of the offshore wind turbine can be received by the input interface and / or the communication interface of the special programmable controller.

[0052] In this embodiment, the memory can store the wind speed values at multiple predetermined time points for subsequent retrieval and operation. Specifically, in some embodiments, the wind speed values at multiple predetermined time points within a predetermined time period obtained by each anemometer are arranged as multiple wind speed query feature vectors according to the time dimension, and the wind speed values at multiple predetermined time points within a predetermined time period obtained by each anemometer are arranged as a wind speed value reference matrix according to the time dimension and the anemometer sample dimension, and the wind speed query feature vectors and the wind speed value reference matrix are stored in the registers of the memory of the special programmable controller.

[0053] In the embodiment, the central processor comprises a computing unit, and the computing unit is specifically configured to: perform matrix multiplication on the plurality of wind speed query feature vectors and the wind speed value reference matrix respectively to obtain a plurality of global query feature vectors. In this case, a global mapping distribution subset of a time series numerical distribution corresponding to the wind speed of a single anemograph in the global numerical distribution of all anemographs is represented by calculating the vector query result of each of the plurality of wind speed query feature vectors in the wind speed value reference matrix as a common data background, so as to facilitate the calculation of the correspondence relationship between the distribution subsets.

[0054] In the embodiment, the central processor comprises a computing unit, and the computing unit is specifically configured to: input the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold to obtain a plurality of global state query vectors. Specifically, the plurality of global query feature vectors are input into the plurality of parallel switches based on the predetermined threshold to convert the plurality of global query feature vectors into the plurality of global state query vectors with numerical values in the (0, 1) distribution. In this case, the numerical values in the global query feature vectors are converted into logical values of 0 or 1 by a simple hardware circuit of the central processor, so as to represent the plurality of global state query vectors by a logical value column vector, which facilitates the implementation of complex wind speed measurement by a simple hardware circuit of a dedicated programmable controller.

[0055] In the embodiment, in the plurality of parallel switches, the predetermined threshold of each switch is obtained by the same control threshold and / or different control thresholds. Specifically, in some embodiments, each switch has the same control threshold, so as to maintain the consistency of the global state metric between the wind speed values at a plurality of time points. In other embodiments, each switch has a separate control threshold (for example, different control thresholds), so as to maintain the adaptability of the global state metric of the wind speed values at each time point, that is, to adaptively determine the control threshold based on the wind speed values at different time points. In other embodiments, the threshold of each switch is a separate control threshold multiplied by the same control threshold in order to improve the confidence of the state metric for each time point. In this way, not only the consistency of the global state metric between the wind speed values at a plurality of time points can be effectively maintained, but also the adaptability of the global state metric of the wind speed values at each time point can be taken into account.

[0056] In the embodiment, the central processor comprises a calculation unit, which is specifically configured to: obtain a plurality of weight values based on a plurality of global state query vectors. Wherein, obtaining the plurality of weight values based on the plurality of global state query vectors comprises: calculating a Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix; multiplying each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors; and calculating a mean value of eigenvalues of all positions of each global mapping weight vector to obtain the plurality of weight values. It is easy to understand that the Hamming distance is used to represent the similarity between two binary global state query vectors.

[0057] In the embodiment, the calculation unit comprises a Hamming distance calculation sub-unit, which is configured to input each two global state query vectors in the plurality of global state query vectors into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values; and an arrangement sub-unit, which is configured to arrange the plurality of Hamming distance values in two dimensions to obtain the global state mapping matrix.

[0058] In some embodiments, specifically, each two global state query vectors in the plurality of global state query vectors can be input into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values, and the plurality of Hamming distance values can be arranged in two dimensions to obtain the global state mapping matrix. In this way, by calculating the global state mapping matrix based on the Hamming distance of the switch values of the plurality of global query feature vectors, the global correspondence relationship between the global mapping distribution subsets of each global query feature vector can be obtained by a simple hardware form (switch + counter). In addition, each global state query vector is multiplied by the global state mapping matrix to obtain a global mapping weight vector. In this way, the eigenvalues of the predetermined positions of each anemograph wind speed switch value vector represented by the global query feature vector relative to the overall anemograph are calculated, and then the mean value of the eigenvalues of all positions of the global mapping weight vector is calculated to obtain the weight value.

[0059] In the embodiment, through the operation of the above calculation unit, the global correspondence between each distribution subset of the time sequence numerical distribution of the wind speed of a single anemograph in the global numerical distribution can be obtained, so that the attention confidence of the wind speed measured by each anemograph at each time point is determined based on the similarity relationship of the corresponding correlation between the wind speeds measured by each anemograph, so as to determine the weighted score of the wind speed value measured at each time point relative to the overall wind speed measurement value from the perspective of global measurement, so as to obtain a more accurate wind speed measurement result.

[0060] In the embodiment, the plurality of wind speed global averages are obtained based on the plurality of wind speed query feature vectors, including: calculating the average of the feature values of all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors to obtain the plurality of wind speed global averages, and calculating the weighted sum of the plurality of wind speed global averages with the plurality of weight values as weights to obtain the wind speed measurement value. In this case, based on the attention confidence of the wind speed measured by each anemometer at each time point, a more accurate wind speed measurement result is obtained by calculating the weighted sum.

[0061] In the embodiment, the wind speed measurement value is output using the output interface of the special programmable controller, and the start control strategy of the wind turbine is determined based on the wind speed measurement value to realize the control of the wind turbine.

[0062] In the embodiment, the calculation unit includes: a first adder sub-unit for adding the feature values of all positions of each global mapping weight vector through an adder to obtain a first sum value; a first counting sub-unit for counting each global mapping weight vector through a counter to obtain a first count value; and a first divider sub-unit for dividing the first sum value and the first count value through a divider to obtain the weight value.

[0063] In the embodiment, the calculation unit includes: a second adder sub-unit for adding the feature values of all positions of each wind speed query feature vector through an adder to obtain a second sum value; a second counting sub-unit for counting each global mapping weight vector through a counter to obtain a second count value; and a second divider sub-unit for dividing the second sum value and the second count value through a divider to obtain the wind speed global average.

[0064] In the embodiment, the weighted sum of the plurality of wind speed global averages is calculated with the plurality of weight values as weights to obtain the wind speed measurement value, including: the plurality of weight values and the plurality of wind speed global averages are multiplied through a parallel multiplier and an adder to obtain the wind speed measurement value.

[0065] Figure 2 The structural diagram of a special programmable controller for wind speed measurement of a wind turbine according to an embodiment of the present application. As shown in the figure, the special programmable controller for wind speed measurement of a wind turbine 100 includes an input interface 110, a storage 120, a central processing unit 130 and an output interface 140, wherein: Figure 2

[0066] The input interface 110 is used to receive wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers arranged at the tail of an offshore wind turbine;

[0067] ​a memory 120 comprising registers for storing a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein each wind speed query feature vector is a numerical column vector of wind speed values at a plurality of predetermined time points within a predetermined time period for each anemometer, and the wind speed value reference matrix is a numerical matrix of wind speed values at a plurality of predetermined time points within a predetermined time period for a plurality of anemometers;

[0068] a central processing unit 130 comprising: a calculation unit configured to: perform matrix multiplication of each of the plurality of wind speed query feature vectors with the wind speed value reference matrix to obtain a plurality of global query feature vectors; input each of the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold to convert each of the plurality of global query feature vectors into a plurality of global state query vectors with numerical values distributed in (0, 1); calculate a Hamming distance between each two of the plurality of global state query vectors to obtain a global state mapping matrix; multiply each of the plurality of global state query vectors with the global state mapping matrix to obtain a plurality of global mapping weight vectors; calculate a mean value of eigenvalues at all positions of each of the plurality of global mapping weight vectors to obtain a plurality of weight values; calculate a mean value of eigenvalues at all positions of each of the plurality of wind speed query feature vectors to obtain a plurality of wind speed global mean values; and an arithmetic unit configured to calculate a weighted sum of the plurality of wind speed global mean values with the plurality of weight values as weights to obtain a wind speed measurement value;

[0069] an output interface 140 configured to output the wind speed measurement value.

[0070] Figure 3 a schematic diagram of an architecture of a special-purpose programmable controller for wind speed measurement of a wind turbine according to an embodiment of the present application; Figure 4 a block diagram of a central processing unit of a special-purpose programmable controller for wind speed measurement of a wind turbine according to an embodiment of the present application.

[0071] In some embodiments, as Figure 3As shown, the operation process is as follows: first, the wind speed values at multiple predetermined time points in a predetermined time period are received from multiple anemometers arranged at the tail of the offshore wind turbine through the input interface; then, data processing is performed by the central processing unit, including: through the calculation unit: matrix multiplication is performed between the multiple wind speed query feature vectors and the wind speed value reference matrix to obtain multiple global query feature vectors; the multiple global query feature vectors are respectively input into multiple parallel switches based on a predetermined threshold to convert the multiple global query feature vectors into multiple global state query vectors with values distributed in (0, 1); the Hamming distance between each two global state query vectors in the multiple global state query vectors is calculated to obtain a global state mapping matrix; each global state query vector is multiplied by the global state mapping matrix to obtain multiple global mapping weight vectors; the mean value of the eigenvalues of all positions of each global mapping weight vector is calculated to obtain multiple weight values; the mean value of the eigenvalues of all positions of each wind speed query feature vector in the multiple wind speed query feature vectors is calculated to obtain multiple wind speed global mean values; and through the operation unit, the weighted sum of the multiple wind speed global mean values is calculated to obtain the wind speed measurement value with the multiple weight values as the weights, and at the same time, the wind speed value reference matrix and the registers of the multiple wind speed query feature vectors are stored in the memory, wherein the wind speed query feature vector is a numerical column vector of the wind speed values at multiple predetermined time points in a predetermined time period of each anemometer, and the wind speed value reference matrix is a numerical matrix of the wind speed values at multiple predetermined time points in a predetermined time period of multiple anemometers; finally, the wind speed measurement value is output through the output interface.

[0072] In some embodiments, as shown in Figure 2 As shown, the dedicated programmable controller 100 for wind speed measurement of a wind turbine further includes a communication interface 150. The wind speed values at multiple predetermined time points in a predetermined time period collected by multiple anemometers arranged at the tail of the offshore wind turbine can be received by the input interface 110 and / or the communication interface 150 of the dedicated programmable controller.

[0073] In some embodiments, the memory 120 includes registers for storing the wind speed value reference matrix and the multiple wind speed query feature vectors, wherein the wind speed query feature vector is a numerical column vector of the wind speed values at multiple predetermined time points in a predetermined time period of each anemometer, and the wind speed value reference matrix is a numerical matrix of the wind speed values at multiple predetermined time points in a predetermined time period of multiple anemometers. In this case, the wind speed values at multiple predetermined time points are stored in the memory of the dedicated programmable controller for subsequent retrieval and operation.

[0074] In some embodiments, the wind speed values obtained by each anemometer at a plurality of predetermined time points within a predetermined time period are arranged into a plurality of wind speed query feature vectors in the time dimension, and the wind speed values obtained by each anemometer at a plurality of predetermined time points within a predetermined time period are arranged into a wind speed value reference matrix in the time dimension and the anemometer sample dimension, and the wind speed query feature vectors and the wind speed value reference matrix are stored in the registers of the memory of the special programmable controller.

[0075] In some embodiments, as shown in FIG. 1, the central processing unit 130 includes a calculation unit 131 and an operation unit 132. Figure 4

[0076] Specifically, the calculation unit 131 is configured to perform matrix multiplication between each of the plurality of wind speed query feature vectors and the wind speed value reference matrix to obtain a plurality of global query feature vectors. In this case, each of the plurality of global query feature vectors corresponds to a global mapping distribution subset of the time series numerical distribution of the wind speed of a single anemometer in the global numerical distribution of all anemometers, thereby facilitating the calculation of the correspondence relationship between each distribution subset. That is, the vector query result of each of the plurality of wind speed query feature vectors in the wind speed value reference matrix is calculated respectively to represent each global mapping distribution subset of the time series numerical distribution of the wind speed of a single anemometer in the global numerical distribution of all anemometers, thereby facilitating the calculation of the correspondence relationship between each distribution subset.

[0077] Specifically, the calculation unit 131 is configured to input the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold to convert the plurality of global query feature vectors into a plurality of global state query vectors with numerical values in the (0, 1) distribution, respectively. That is, the numerical values in the global query feature vectors are converted into logical values of 0 or 1 by the simple hardware circuit of the central processing unit, so as to represent the plurality of global state query vectors by a logical value column vector, which facilitates the implementation of complex wind speed measurement by the simple hardware circuit of the special programmable controller.

[0078] ​In some embodiments, the predetermined threshold of each switch in the plurality of parallel switches is obtained by the same control threshold and / or different control thresholds. Specifically, in some embodiments, each switch in the plurality of parallel switches has the same control threshold so as to maintain consistency of the global state metric between the wind speed values of the plurality of time points. In some embodiments, each switch in the plurality of parallel switches has a separate control threshold so as to maintain adaptability of the global state metric of the wind speed values of the respective time points, that is, to adaptively determine the control threshold based on the wind speed values of the different time points. In some embodiments, to enhance the confidence of the state metric for each time point, the threshold of each switch in the plurality of parallel switches is the separate control threshold multiplied by the same control threshold, in this way, not only the consistency of the global state metric between the wind speed values of the plurality of time points can be effectively maintained, but also the adaptability of the global state metric of the wind speed values of the respective time points can be taken into account.

[0079] In some embodiments, the computing unit 131 is configured to calculate the Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix. Specifically, the Hamming distance is used to represent the number of corresponding different characters at the same position of two equal-length strings, which is used to measure the similarity of two binary feature vectors. The Hamming distance between two vectors to be calculated can be obtained by taking the exclusive OR operation, and the smaller the value, the higher the similarity of the two vectors. Here, the Hamming distance is used to represent the similarity between two binary global state query vectors.

[0080] In some embodiments, the computing unit 131 comprises a Hamming distance calculation subunit and an arrangement subunit. The Hamming distance calculation subunit is configured to input each two global state query vectors in the plurality of global state query vectors into a parallel exclusive OR gate and a counter to obtain a plurality of Hamming distance values; and the arrangement subunit is configured to arrange the plurality of Hamming distance values in two dimensions to obtain a global state mapping matrix. In this case, by calculating the global state mapping matrix based on the Hamming distance of the switch values of the plurality of global query feature vectors, the global correspondence relationship between the global mapping distribution subsets of the respective global query feature vectors can be obtained by a simple hardware form (e.g., switch + counter).

[0081] In some embodiments, the computing unit 131 is configured to multiply each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors. In this way, the feature values of the wind speed switch value vectors of the respective anemometers represented by the global query feature vectors are obtained relative to the predetermined positions that need to be focused on by the plurality of anemometers as a whole.

[0082] In some embodiments, the computing unit 131 is configured to calculate the mean of the eigenvalues of all positions of each global mapping weight vector to obtain a plurality of weight values. Through the above operation, the global correspondence between the time series numerical distribution of the wind speed of a single anemometer and each distribution subset of the global numerical distribution can be obtained, so as to determine the attention confidence of the wind speed measured by each anemometer at each time point based on the similarity relationship of the corresponding correlation between the wind speeds measured by each anemometer, so as to determine the weighted score of the wind speed value measured at each time point relative to the overall wind speed measurement value from the perspective of global measurement, so as to obtain a more accurate wind speed measurement result.

[0083] In some embodiments, the computing unit 131 includes a first adder subunit, a first counting subunit, and a first divider subunit, wherein the first adder subunit is configured to add the eigenvalues of all positions of each global mapping weight vector to obtain a first sum value; the first counting subunit is configured to count each global mapping weight vector to obtain a first count value; and the first divider subunit is configured to divide the first sum value and the first count value to obtain a weight value.

[0084] In some embodiments, the computing unit 131 is configured to calculate the mean of the eigenvalues of all positions of each wind speed query feature vector to obtain a plurality of wind speed global means.

[0085] In some embodiments, the computing unit 131 includes a second adder subunit, a second counting subunit, and a second divider subunit, wherein the second adder subunit is configured to add the eigenvalues of all positions of each wind speed query feature vector to obtain a second sum value; the second counting subunit is configured to count each global mapping weight vector to obtain a second count value; and the second divider subunit is configured to divide the second sum value and the second count value to obtain a wind speed global mean.

[0086] In some embodiments, the computing unit 131 is configured to calculate the mean of the eigenvalues of all positions of each wind speed query feature vector to obtain a plurality of wind speed global means.

[0087] In some embodiments, the computing unit 131 includes a second adder subunit, a second counting subunit, and a second divider subunit, wherein the second adder subunit is configured to add the eigenvalues of all positions of each wind speed query feature vector to obtain a second sum value; the second counting subunit is configured to count each global mapping weight vector to obtain a second count value; and the second divider subunit is configured to divide the second sum value and the second count value to obtain a wind speed global mean.

[0088] In some embodiments, the output interface 140 is configured to output the wind speed measurement value. That is, the output interface of the dedicated programmable controller can be used to output the wind speed measurement value, so as to determine the start control strategy of the wind turbine based on the wind speed measurement value.

[0089] In some embodiments, as shown in Figure 2 The power supply 160 is used to provide working voltage for the input interface 110, the storage 120, the central processing unit 130 and the output interface 140.

[0090] In the special-purpose programmable controller for wind speed measurement of a wind turbine according to the embodiments of the present application, the special-purpose programmable controller comprises an input interface, a storage, a central processing unit and an output interface; the input interface is used to receive wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of an offshore wind turbine; the storage is used to store a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein the wind speed value reference matrix and the plurality of wind speed query feature vectors are obtained based on the wind speed values at the plurality of predetermined time points within the predetermined time period; the central processing unit is used to obtain a plurality of weight values based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, obtain a plurality of wind speed global mean values based on the plurality of wind speed query feature vectors, and obtain a wind speed measurement value based on the plurality of weight values and the plurality of wind speed global mean values; and the output interface is used to output the wind speed measurement value. According to the special-purpose programmable controller of the present application, the accuracy of wind speed measurement of a wind turbine can be improved. In this case, the special-purpose programmable logic controller comprises an input interface, an output interface, a storage, a central processing unit, etc., the wind speed value reference matrix and the wind speed query feature vectors are obtained using the wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of an offshore wind turbine, the wind speed measurement value is obtained based on the wind speed value reference matrix and the wind speed query feature vectors, the correlation between the wind speed values measured by each anemometer at each predetermined time point is fully considered, and the accuracy of wind speed measurement of a wind turbine is improved. Compared with the prior art, the special-purpose programmable logic controller of the present application considers that when a plurality of anemometers are installed at the tail of an offshore wind turbine, there is a correlation between the wind speed values measured by each anemometer at each predetermined time point, and the special-purpose programmable logic controller is used to fully exploit and utilize the implicit correlation between the wind speed data measured by the plurality of anemometers to obtain the wind speed measurement value, thereby to a certain extent reducing the influence of blade blocking on wind speed measurement and improving the accuracy of wind speed measurement.

[0091] The following is a method embodiment of the present application, which is based on the above-mentioned special-purpose programmable controller embodiment for wind speed measurement. For details not disclosed in the method embodiment of the present application, please refer to the special-purpose programmable controller embodiment of the present application.

[0092] Figure 5 The flow chart of the operation method of the special-purpose programmable controller for wind speed measurement of a wind turbine according to the embodiments of the present application.

[0093] AsFigure 5 The operation method of the special-purpose programmable controller for wind speed measurement of a wind turbine includes:

[0094] Step S11, receiving wind speed values at multiple predetermined time points within a predetermined time period from multiple anemometers deployed at the tail of the offshore wind turbine.

[0095] In step S11, the wind speed values at multiple predetermined time points within a predetermined time period are received from multiple anemometers deployed at the tail of the offshore wind turbine through an input interface.

[0096] Step S12, obtaining a wind speed value reference matrix and multiple wind speed query feature vectors, wherein the wind speed value reference matrix and the wind speed query feature vectors are based on the wind speed values at multiple predetermined time points within a predetermined time period.

[0097] In step S12, the wind speed value reference matrix and the multiple wind speed query feature vectors are stored in the memory, wherein the wind speed query feature vector is a numerical column vector of the wind speed values at multiple predetermined time points within a predetermined time period for each anemometer, and the wind speed value reference matrix is a numerical matrix of the wind speed values at multiple predetermined time points within a predetermined time period for multiple anemometers.

[0098] Step S13, obtaining multiple weight values based on the wind speed value reference matrix and the multiple wind speed query feature vectors, obtaining multiple global mean wind speeds based on the multiple wind speed query feature vectors, and obtaining a wind speed measurement value based on the multiple weight values and the multiple global mean wind speeds.

[0099] In step S13, the multiple weight values are obtained based on the wind speed value reference matrix and the multiple wind speed query feature vectors, including: performing matrix multiplication of the multiple wind speed query feature vectors with the wind speed value reference matrix to obtain multiple global query feature vectors (step S131); inputting the multiple global query feature vectors into multiple parallel switches based on a predetermined threshold to obtain multiple global state query vectors (step S132); and obtaining the multiple weight values based on the multiple global state query vectors (step S132).

[0100] In step S132, specifically, the multiple global query feature vectors are input into multiple parallel switches based on a predetermined threshold to convert the multiple global query feature vectors into multiple global state query vectors with numerical values distributed as (0, 1).

[0101] In step S132, in the plurality of parallel switches, the predetermined threshold value of each switch is obtained by the same control threshold value and / or different control threshold values. Among them, in some embodiments, in the plurality of parallel switches, each switch has the same control threshold value; in some embodiments, in the plurality of parallel switches, each switch has an independent control threshold value. In some embodiments, in the plurality of parallel switches, the threshold value of each switch is the product of the individual control threshold value and the same control threshold value.

[0102] In step S133, a plurality of weight values are obtained based on the plurality of global state query vectors, including: calculating the Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix; multiplying each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors; calculating the mean value of the eigenvalues of all positions of each global mapping weight vector to obtain the plurality of weight values.

[0103] In step S133, the mean value of the eigenvalues of all positions of each global mapping weight vector is calculated to obtain a plurality of weight values, including: passing the eigenvalues of all positions of each global mapping weight vector through an adder to obtain a first sum value; passing each global mapping weight vector through a counter to obtain a first count value; passing the first sum value and the first count value through a divider to obtain the weight value.

[0104] In step S133, the Hamming distance between each two global state query vectors in the plurality of global state query vectors is calculated to obtain a global state mapping matrix, including: inputting each two global state query vectors in the plurality of global state query vectors into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values; two-dimensionally arranging the plurality of Hamming distance values to obtain the global state mapping matrix.

[0105] In step S13, a plurality of wind speed global mean values are obtained based on the plurality of wind speed query feature vectors, including: calculating the mean value of the eigenvalues of all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors to obtain the plurality of wind speed global mean values.

[0106] In step S13, the mean value of the eigenvalues of all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors is calculated to obtain a plurality of wind speed global mean values, including: passing the eigenvalues of all positions of each wind speed query feature vector through an adder to obtain a second sum value; passing each global mapping weight vector through a counter to obtain a second count value; passing the second sum value and the second count value through a divider to obtain the wind speed global mean value.

[0107] In step S13, the wind speed measurement value is obtained based on the plurality of weight values and the plurality of wind speed global averages, including calculating a weighted sum of the plurality of wind speed global averages with the plurality of weight values as weights to obtain the wind speed measurement value.

[0108] In step S13, the wind speed measurement value is obtained based on the plurality of weight values and the plurality of wind speed global averages, including calculating a weighted sum of the plurality of wind speed global averages with the plurality of weight values as weights to obtain the wind speed measurement value.

[0109] In the embodiment, the operation method of the special programmable controller for wind speed measurement of a wind turbine further includes: outputting the wind speed measurement value through an output interface.

[0110] The above-mentioned embodiment numbers of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0111] In the operation method of the special programmable controller for wind speed measurement of a wind turbine, wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of the offshore wind turbine are received; a wind speed value reference matrix and a plurality of wind speed query feature vectors are obtained, wherein the wind speed value reference matrix and the wind speed query feature vectors are obtained based on the wind speed values at the plurality of predetermined time points within the predetermined time period; a plurality of weight values are obtained based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, a plurality of wind speed global averages are obtained based on the plurality of wind speed query feature vectors, and a wind speed measurement value is obtained based on the plurality of weight values and the plurality of wind speed global averages. In this case, the wind speed value reference matrix and the wind speed query feature vectors are obtained using the wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers deployed at the tail of the offshore wind turbine, and the wind speed measurement value is obtained based on the wind speed value reference matrix and the wind speed query feature vectors, fully considering the correlation between the wind speed values measured by each anemometer at each predetermined time point, thereby improving the accuracy of wind speed measurement of the wind turbine. Compared with the prior art, the operation method of the special programmable logic controller of the present disclosure considers that when a plurality of anemometers are installed at the tail of the offshore wind turbine, there is a correlation between the wind speed values measured by each anemometer at each predetermined time point, and uses the special programmable logic controller to fully exploit and utilize the implicit correlation between the wind speed data measured by the plurality of anemometers to obtain the wind speed measurement value, thereby to a certain extent reducing the influence of blade shielding on wind speed measurement and improving the accuracy of wind speed measurement.

[0112] It should be noted that the above-mentioned embodiments provide the special programmable controller for wind speed measurement of wind driven generators in the execution of the operation method of the special programmable controller for wind speed measurement of wind driven generators, only the above-mentioned division of each functional module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional modules according to needs, that is, the internal structure of the special programmable controller for wind speed measurement of wind driven generators is divided into different functional modules to complete all or part of the functions described above. In addition, the operation method of the special programmable controller for wind speed measurement of wind driven generators provided by the above-mentioned embodiments and the special programmable controller for wind speed measurement of wind driven generators belong to the same concept, and the implementation process is embodied in the method embodiments, which will not be repeated here.

[0113] It should be understood that the steps can be reordered, added, or deleted using the various forms of flow shown above. For example, each step described in the present application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present application can be achieved, and the present application is not limited herein.

[0114] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0115] The basic principles of the present application are described above in combination with specific embodiments, but it should be noted that the advantages, advantages, effects and the like mentioned in the present application are only examples and not limitations, and these advantages, advantages, effects and the like cannot be considered as necessary for each embodiment of the present application. In addition, the above-mentioned specific details are only for the purpose of example and for the purpose of understanding, and are not limited to the above-mentioned specific details, and the present application must be realized by using the above-mentioned specific details.

[0116] The block diagrams of the devices, apparatuses, equipment, systems involved in the present application are only illustrative examples and are not intended to require or imply that the connection, arrangement, configuration must be as shown in the block diagram. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, mean "include but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0117] It is also important to note that the devices, apparatuses and methods described herein can be capable of further division and / or combination. These divisions and / or combinations should be considered as equivalent to the described embodiments.

[0118] The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0119] The foregoing description has been presented for the purposes of illustration and description. Furthermore, the description is not intended to limit the embodiments of the application to the forms disclosed herein. Although the above discussion has focused on multiple example aspects and embodiments, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations.

Claims

1. A dedicated programmable controller for wind speed measurement of a wind generator, characterized in that, The input interface, the memory, the central processing unit and the output interface are included. The input interface is configured to receive wind speed values at a plurality of predetermined time points within a predetermined time period from a plurality of anemometers arranged at the tail of an offshore wind turbine. The memory is configured to store a wind speed value reference matrix and a plurality of wind speed query feature vectors, wherein the wind speed value reference matrix and the wind speed query feature vectors are based on the wind speed values at the plurality of predetermined time points within the predetermined time period. The central processing unit is configured to obtain a plurality of weight values based on the wind speed value reference matrix and the plurality of wind speed query feature vectors, obtain a plurality of wind speed global mean values based on the plurality of wind speed query feature vectors, and obtain a wind speed measurement value based on the plurality of weight values and the plurality of wind speed global mean values. The output interface is configured to output the wind speed measurement value. The central processing unit includes a calculation unit, and the calculation unit is specifically configured to: perform matrix multiplication on the plurality of wind speed query feature vectors and the wind speed value reference matrix respectively to obtain a plurality of global query feature vectors; input the plurality of global query feature vectors into a plurality of parallel switches based on a predetermined threshold respectively to obtain a plurality of global state query vectors; obtain a plurality of weight values based on the plurality of global state query vectors, including: calculating a Hamming distance between each two global state query vectors in the plurality of global state query vectors to obtain a global state mapping matrix; multiplying each global state query vector by the global state mapping matrix to obtain a plurality of global mapping weight vectors; and calculating a mean value of eigenvalues at all positions of each global mapping weight vector to obtain the plurality of weight values; obtain a plurality of wind speed global mean values based on the plurality of wind speed query feature vectors, including: calculating a mean value of eigenvalues at all positions of each wind speed query feature vector in the plurality of wind speed query feature vectors to obtain the plurality of wind speed global mean values; The central processing unit includes an operation unit, and the operation unit is specifically configured to: calculate a weighted sum of the plurality of wind speed global mean values with the plurality of weight values as weights to obtain a wind speed measurement value.

2. The dedicated programmable controller for wind speed measurement of wind generators as claimed in claim 1 wherein, In the plurality of parallel switches, the predetermined threshold of each switch is obtained by the same control threshold and / or different control thresholds.

3. The dedicated programmable controller for wind speed measurement of wind generators as claimed in claim 1 wherein, The calculation unit includes: a Hamming distance calculation sub-unit configured to input each two global state query vectors in the plurality of global state query vectors into a parallel XOR gate and a counter to obtain a plurality of Hamming distance values; an arrangement sub-unit configured to arrange the plurality of Hamming distance values in two dimensions to obtain the global state mapping matrix.

4. The dedicated programmable controller for wind speed measurement of wind generators as claimed in claim 1 wherein, The calculation unit includes: a first adder sub-unit configured to pass eigenvalues at all positions of each global mapping weight vector through an adder to obtain a first sum value; a first counting sub-unit configured to pass each global mapping weight vector through a counter to obtain a first count value; a first divider sub-unit configured to pass the first sum value and the first count value through a divider to obtain the weight value.

5. The dedicated programmable controller for wind speed measurement of wind generators as claimed in claim 1 wherein, The calculation unit includes: a second adder subunit configured to add all the feature values of all the positions of the respective wind speed query feature vector to obtain a second sum value; a second counter subunit configured to count the number of non-zero elements of the respective global mapping weight vector to obtain a second count value; a second divider subunit configured to divide the second sum value by the second count value to obtain the global mean wind speed.

6. The dedicated programmable controller for wind speed measurement of wind generators as claimed in claim 1 wherein, the calculating a weighted sum of the plurality of global mean wind speeds using the plurality of weight values as weights to obtain a wind speed measurement value, comprises: multiplying the plurality of weight values and the plurality of global mean wind speeds using parallel multipliers and adding the results of the multiplications using parallel adders to obtain the wind speed measurement value.

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