A method and system for real-time evaluation of fatigue damage for a wind farm

Abstract

The application discloses a kind of real-time evaluation method and system for fatigue damage of wind farm, method includes: obtaining the load data of current time, wherein the load data includes load value, load extreme value, the starting position of sliding window and original cumulative fatigue damage value;According to the load data, update load extreme value, and judge whether the termination position of sliding window changes;If change, then the load data in sliding window is processed by rain flow counting method, extract load amplitude, mean and cycle number;The load amplitude is corrected, and the maximum cycle load number is determined, combined with the original cumulative fatigue damage value, to obtain the cumulative fatigue damage of current time.The application combines dynamic sliding window method with rain flow counting method, solves the problem that traditional rain flow counting method cannot be calculated in real time, and can realize the rapid real-time calculation of fan cumulative fatigue damage on the basis of ensuring accuracy.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wind farm optimization, and particularly relates to a fatigue damage real-time evaluation method and system for a wind farm. BACKGROUND

[0002] The wind power industry is in a rapid development stage, large wind turbines and large-scale wind farms are constantly put into operation, and wind power technology is becoming increasingly mature. However, the wake effect becomes an important factor affecting the efficiency of the wind farm. When the incoming flow wind passes through the upstream wind turbine, part of the kinetic energy is absorbed and converted, resulting in a decrease in the inflow wind speed of the downstream wind turbine, and thus affecting its output power. At the same time, the wind turbine wake makes the wind speed fluctuation of the incoming flow wind more severe, the turbulence intensity increases, and the fatigue damage of the load borne by the wind turbine also increases. In order to improve the overall output power of the wind farm and reduce the average fatigue damage, the power of the wind turbine can be actively controlled in operation.

[0003] In the existing active and fatigue optimization model of the wind farm, there are mainly two methods for calculating the cumulative fatigue damage. The first method is an approximate method. Since the traditional rainflow counting method cannot realize real-time calculation, the existing technology usually directly uses the load (such as the shaft torque) as an index of the fatigue size, or assumes that the fatigue is proportional to the output of the wind turbine, and defines a fatigue coefficient as a fatigue index. However, the calculation accuracy of these approximate methods is obviously insufficient. The second method is a machine learning method, which uses the fatigue data calculated by the rainflow counting method as a training set, and realizes real-time operation optimization by training a neural network offline. Although this method has certain advantages in theory, it has high requirements for the data set and is highly dependent, and the method itself is too complex, which has many limitations in actual application. SUMMARY

[0004] To solve the above technical problems, the present application provides a fatigue damage real-time evaluation method and system for a wind farm to solve the problems existing in the prior art.

[0005] To achieve the above purpose, in a first aspect, the present application provides a fatigue damage real-time evaluation method for a wind farm, comprising:

[0006] obtaining load data at the current time, wherein the load data includes load value, load extreme value, starting position of the sliding window and original cumulative fatigue damage value;

[0007] updating the load extreme value according to the load data, and determining whether the termination position of the sliding window changes;

[0008] if the change occurs, performing rainflow counting method processing on the load data in the sliding window, and extracting the load amplitude, mean value and cycle number;

[0009] The load amplitude is corrected, and the maximum cyclic load number is determined to obtain the cumulative fatigue damage at the current time in combination with the original cumulative fatigue damage value.

[0010] Preferably, the formula for updating the load extreme value is:

[0011]

[0012] In the formula, x t represents the load at time t, x max and x min represent the load extreme value, and respectively represent the start and end positions of the jth sliding window, l win represents the maximum length of the window.

[0013] Preferably, the rainflow counting method processing of the load data in the sliding window comprises:

[0014] The load data in the sliding window is preprocessed to obtain preprocessed load data;

[0015] The preprocessed load data is sheared and reconstructed to obtain a load time sequence;

[0016] According to the load time sequence, a three-point window is selected;

[0017] According to the three-point window, it is judged whether there is a rainflow closed cycle in the window;

[0018] If there is a rainflow closed cycle, the amplitude, mean value and cycle number of each rainflow cycle are extracted.

[0019] Preferably, obtaining the cumulative fatigue damage at the current time comprises:

[0020] The load amplitude is corrected based on the Goodman curve, the maximum cyclic load number is determined by using the S-N curve, the fatigue damage value at the current time t is calculated and corrected based on the Palmgren-Miner linear cumulative damage theory, and the original cumulative fatigue damage value is superimposed to obtain the cumulative fatigue damage at the current time.

[0021] Preferably, the correction of the load amplitude based on the Goodman curve comprises:

[0022] When the average load is not 0, the Goodman curve is used for correction, and the correction expression is:

[0023]

[0024] In the formula, S ai is the cycle amplitude; S iS is the load amplitude when the equivalent mean value is 0; S mi σ is the cycle mean value; σ b S is the maximum load value of the material at the time of tensile fracture.

[0025] Preferably, the formula for determining the maximum cycle load number using the S-N curve is:

[0026] S m ×N=C

[0027] In the formula, S is the load amplitude; N is the maximum cycle load number under the load amplitude; m is the Wohler index, and C is a constant.

[0028] Preferably, the Palmgren-Miner linear cumulative damage theory is:

[0029]

[0030] In the formula, n i is the cycle number under the load amplitude S i , and D is the cumulative fatigue damage degree.

[0031] D t =k×D+D t-1

[0032] In the formula, D t is the cumulative fatigue damage at time t, D t-1 is the cumulative fatigue damage at the previous time, and k is a damage correction coefficient, which is the same as l win .

[0033] In a second aspect, the application further provides a fatigue damage real-time evaluation system for a wind farm, comprising:

[0034] A data acquisition module is configured to acquire load data at a current time, wherein the load data comprises a load value, a load extreme value, a starting position of a sliding window, and an original cumulative fatigue damage value.

[0035] An extreme value updating module is configured to update the load extreme value according to the load data and determine whether the ending position of the sliding window changes.

[0036] A rainflow counting module is configured to perform rainflow counting method processing on the load data in the sliding window, extract a load amplitude, a mean value, and a cycle number.

[0037] A fatigue damage calculation module is configured to correct the load amplitude, determine a maximum cycle load number, and combine the original cumulative fatigue damage value to obtain a cumulative fatigue damage at the current time.

[0038] In a third aspect, the present application also discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method in the first aspect.

[0039] In a fourth aspect, the present application also discloses a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the method in the first aspect.

[0040] Compared with the prior art, the present application has the following advantages and technical effects:

[0041] The present application provides a real-time fatigue damage evaluation method for a wind farm, comprising: firstly, obtaining load data at a current time, wherein the load data comprises a load value, a load extreme value, a starting position of a sliding window and an original cumulative fatigue damage value; secondly, updating the load extreme value according to the load data, and determining whether the ending position of the sliding window changes; if the ending position changes, performing rainflow counting method processing on the load data in the sliding window, extracting a load amplitude, a mean value and a cycle number; finally, correcting the load amplitude, determining a maximum cycle load number, and combining the original cumulative fatigue damage value to obtain a cumulative fatigue damage at the current time.

[0042] The present application combines the dynamic sliding window method with the rainflow counting method, solves the problem that the traditional rainflow counting method cannot be calculated in real time, and realizes fast and real-time calculation of the cumulative fatigue damage of the wind turbine on the basis of ensuring accuracy. The method of the present application can be used for fatigue quantification in wind farm optimization, has high calculation accuracy and good optimization effect. BRIEF DESCRIPTION OF DRAWINGS

[0043] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The embodiments of this application and their explanations are used to explain this application, and do not constitute an improper limitation on this application. In the drawings:

[0044] Figure 1 The method flowchart of the embodiments of the present application;

[0045] Figure 2 The parameter calculation diagram of the embodiments of the present application;

[0046] Figure 3 The calculation result diagram of the embodiments of the present application;

[0047] Figure 4 The part of the wind turbine fatigue growth diagram of the embodiments of the present application. DETAILED DESCRIPTION

[0048] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0049] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0050] Embodiment one

[0051] The data set used in this embodiment is a certain wind farm group data set, including 100 wind turbines of two wind farms, 2000 seconds of rotating shaft torque data. The data of wind farm 1 is used to calculate the window length l win and the correction coefficient k.

[0052] The torque of 100 wind turbines of wind farm 1 is used as the load, and the traditional rainflow counting method is used to calculate the fatigue damage as the reference data. The real-time calculation is performed according to the time sequence input load, and the time t is from 1 to 2000s.

[0053] As Figure 1 shown, the present embodiment provides a real-time fatigue damage evaluation method for wind farms, comprising:

[0054] Step 1: input the load x t , the load extreme value x max and x min , the starting position of the sliding window and the original cumulative fatigue damage value D t-1 ;

[0055] Step 2: update the load extreme value according to the input load data, and judge whether the termination position of the sliding window changes; if it does not change, the cumulative fatigue damage is equal to the cumulative damage value of the last time, and the calculation is ended; if it changes, go to step 3;

[0056] As an innovative implementation, the window update formula is as follows:

[0057]

[0058] In the formula, is the termination position of the jth sliding window, and if the determination condition is met, go to step 3 to calculate the data in the window. l win represents the maximum length of the window, l win takes a value of 5 to 200 steps (discrete integers of 5); according to the fitting degree of the calculation result and the reference data, select the appropriate window length.

[0059] Step 3: perform rainflow counting method processing on the load data in the sliding window, extract the load amplitude, mean value and cycle number;

[0060] Further, the "three-point" rainflow counting method is adopted to calculate to the load data in the window. The specific steps are as follows:

[0061] Step 301, load data preprocessing;

[0062] The load time series in the sliding window is converted into a series of peak-valley points (i.e. local extreme values), denoted as sequence where M≤N. y i is a local extreme value, and the judgment condition formula is:

[0063]

[0064] Step 302, load time history reconstruction;

[0065] For the load time series, the maximum value is cut and rearranged, so that the maximum value point is located at the beginning, and the following formula is the load sequence before and after cutting and reconstruction:

[0066]

[0067] Step 303, three-point window selection;

[0068] According to the cut and reconstructed load sequence, three consecutive extreme value points y j , y j+1 , y j+2 are selected in turn to construct a three-point window (y j , y j+1 , y j+2 ).

[0069] Step 304, judgment of rainflow closure condition;

[0070] According to the following rules to determine whether there is an effective rainflow closure cycle in the window, first define two load amplitude Δy1=|y j+1 -y j | and Δy2=|y j+2 -y j+1 |, if Δy1≤Δy2, it is considered that an effective cycle is formed in the window, and the closed cycle amplitude is:

[0071] Δy=Δy1

[0072] Step 305, counting and updating;

[0073] If the closure condition in step 304 is met, a complete cycle is recorded, denoted as Δy, and the mean value is:

[0074]

[0075] The closed point (y j ,y j+1 ) is removed from the sequence, and the remaining data continues to iterate through steps 303-305.

[0076] If the closure condition is not met, the point y j is retained, and the next set of three points (y j+1 ,y j+2 ,y j+3 ) is processed.

[0077] Step 306, non-closed loop processing;

[0078] After traversing all the data, if there are still unclosed points in the sequence, it is assumed that the remaining points form a half-cycle, and their amplitude and mean value are recorded.

[0079] Step 306, output results;

[0080] Output the amplitude Δy k , mean y k and cycle number n k of each rainflow cycle, which is used for subsequent fatigue damage calculation.

[0081] Step 4: Based on the Goodman curve, the load amplitude is corrected, the maximum cycle load number is determined using the S-N curve, the fatigue damage value at the current time t is calculated and corrected according to the Palmgren-Miner linear cumulative damage theory, and the original cumulative damage value is superimposed to obtain the cumulative fatigue damage at the current time. The specific formula is as follows:

[0082] (1) Goodman curve correction: The basic S-N curve is when the average load is 0. When the average load is not 0, the Goodman curve is used for correction, and the correction expression is:

[0083]

[0084] In the formula, S ai is the cycle amplitude calculated in step three; S i is the load amplitude when the equivalent mean value is 0; S mi is the cycle mean value calculated in step three; σ b is the maximum load value of the material at the time of tensile fracture.

[0085] (2) S-N curve:

[0086] S m ×N=C

[0087] Wherein, S is the load amplitude; N is the maximum cyclic load times under the load amplitude; m is the Wohler index, taking 10; C is a constant, taking 9.77*1070.

[0088] (3) Palmgren-Miner linear cumulative damage theory:

[0089]

[0090] Wherein, n i is the cyclic times under the load amplitude S i , when the cumulative fatigue damage degree D reaches 1, the material fails.

[0091] (4) Cumulative fatigue damage:

[0092] D t = k*D+D t-1

[0093] Wherein, D t and D t-1 are the cumulative fatigue damage at t time and the last time, k is the damage correction coefficient, from 0.1 to 10, the step is 0.1 discrete data, in each window length l win , select the calculation result and the maximum correlation coefficient corresponding value of the reference data.

[0094] Through the method of the embodiment, the calculation result is obtained, as shown in Figure 2 The determination coefficient under different window lengths represents the calculation accuracy of the method of the application, the window length is selected as 20, the determination coefficient is more than 0.8, and the corresponding correction coefficient is 0.9.

[0095] In the embodiment, the data of the wind farm 2 is used to verify the effect of the method of the embodiment. The torque of 100 wind turbines of the wind farm 2 is taken as the load, first, the traditional rain flow counting method is used to calculate the fatigue damage as the reference data. The real-time calculation is carried out by using the method of the embodiment, the specific steps are the same as above, the window length is fixed as 20, and the correction coefficient is fixed as 0.9.

[0096] In the embodiment, the test formula of the determination coefficient is as follows:

[0097]

[0098] Wherein, R 2 is the determination coefficient, the closer to 1, the better the data fitting effect is; is the calculation result of the method of the embodiment, is the average value; d i is the calculation result of the traditional rain flow counting method.

[0099] Table 1 is a comparison of the calculation time of the method of the embodiment and the traditional method. The calculation platform is MATLAB2024a, the CPU is Intel i5-12400F, the memory is 16GB DDR4, and the operating system is Windows10. It can be seen that the calculation time is much less than the traditional rainflow counting method.

[0100] Table 1

[0101]

[0102] Figure 3 The fatigue damage of 100 wind turbines and the reference data fitting degree are calculated, and the determination coefficient of each wind turbine calculation result is above 0.96. The method of the embodiment can accurately and real-timely calculate the fatigue damage.

[0103] Figure 4 The cumulative fatigue damage growth chart of part of the wind turbine can be seen, which is similar to the original data growth trend.

[0104] Embodiment two

[0105] Based on the same inventive concept, the embodiment also provides a fatigue damage real-time evaluation system for a wind farm, comprising:

[0106] A data acquisition module is configured to acquire load data at a current time, wherein the load data comprises a load value, a load extreme value, a starting position of a sliding window, and an original cumulative fatigue damage value.

[0107] An extreme value updating module is configured to update the load extreme value according to the load data, and determine whether the ending position of the sliding window changes.

[0108] A rainflow counting module is configured to perform rainflow counting on the load data in the sliding window, and extract a load amplitude, a mean value, and a cycle number.

[0109] A fatigue damage calculation module is configured to correct the load amplitude, determine a maximum cycle load number, and combine the original cumulative fatigue damage value to obtain a cumulative fatigue damage at the current time.

[0110] The fatigue damage real-time evaluation system for a wind farm provided by the embodiment has all the advantages of the fatigue damage real-time evaluation method for a wind farm provided by the embodiment one.

[0111] Embodiment three

[0112] The embodiment also discloses a computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method of the embodiment are implemented.

[0113] Embodiment four

[0114] The embodiment also discloses a computer program product comprising a computer program which, when executed by a processor, implements the steps of the method according to the first embodiment.

[0115] The above merely shows the preferred embodiments of the present application, but the protection scope of the present application is not limited thereto, any changes or replacements within the technical scope disclosed by the present application can be easily thought by those skilled in the art, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for real-time assessment of fatigue damage for a wind farm, characterized in that, The method comprises the following steps: obtaining load data at the current time, wherein the load data comprises a load value, a load extreme value, a starting position of a sliding window and an original cumulative fatigue damage value; updating the load extreme value according to the load data and determining whether the ending position of the sliding window changes; if the ending position changes, performing rainflow counting on the load data in the sliding window to obtain a load amplitude, a mean value and a cycle number; the rainflow counting on the load data in the sliding window comprises: preprocessing the load data in the sliding window to obtain preprocessed load data; reconstructing the preprocessed load data to obtain a load time sequence; selecting a three-point window according to the load time sequence; determining whether there is a rainflow closed cycle in the window according to the three-point window; if there is a rainflow closed cycle, extracting an amplitude, a mean value and a cycle number of each rainflow cycle; correcting the load amplitude and determining a maximum cycle load number to obtain a cumulative fatigue damage at the current time in combination with the original cumulative fatigue damage value.

2. The method according to claim 1, wherein the formula for updating the load extreme value is:

3. The method according to claim 1, wherein obtaining the cumulative fatigue damage at the current time comprises: In the formula, x t represents the load at time t, x max and x min represents the load extreme value, and respectively represent the start and end positions of the jth sliding window, l win represents the maximum window length. correcting the load amplitude based on a Goodman curve, determining the maximum cycle load number by using an S-N curve, calculating a fatigue damage value at the current time t by using a Palmgren-Miner linear cumulative damage theory and correcting the fatigue damage value, and obtaining the cumulative fatigue damage at the current time in combination with the original cumulative fatigue damage value.

4. The method according to claim 3, wherein the correction of the load amplitude based on the Goodman curve comprises: when the mean load is not 0, correcting the load amplitude by using the Goodman curve, and the correction expression is:

5. The method according to claim 3, wherein the formula for determining the maximum cycle load number by using the S-N curve is: wherein S is the load amplitude, N is the maximum cycle load number under the load amplitude, m is a Wohler index, and C is a constant.

6. The method according to claim 1, wherein the Palmgren-Miner linear cumulative damage theory comprises: where S ai is the cyclic amplitude; S i is the load amplitude with equivalent mean of 0; S mi is the cyclic mean; σ b is the maximum load value of the material at tensile fracture. a data acquisition module for obtaining load data at the current time, wherein the load data comprises a load value, a load extreme value, a starting position of a sliding window and an original cumulative fatigue damage value; an extreme value updating module for updating the load extreme value according to the load data and determining whether the ending position of the sliding window changes; S m ×N=C a rainflow counting module for performing rainflow counting on the load data in the sliding window to obtain a load amplitude, a mean value and a cycle number; the rainflow counting on the load data in the sliding window comprises: preprocessing the load data in the sliding window to obtain preprocessed load data; where n is the number of cycles at a load amplitude S i D is the accumulated fatigue damage level i where n is the number of cycles at a load amplitude S D t = k x D + D t-1 In the formula, D t is the accumulated fatigue damage at time t, D t-1 is the accumulated fatigue damage at the previous time, and k is a damage correction coefficient, which is the same as l win .

7. A system for real-time assessment of fatigue damage for a wind farm, characterized by, reconstructing the preprocessed load data to obtain a load time sequence; selecting a three-point window according to the load time sequence; determining whether there is a rainflow closed cycle in the window according to the three-point window; ​ ​ ​ ​ ​ ​ If there is a rainflow closed cycle, the amplitude, mean value and cycle number of each rainflow cycle are extracted; The fatigue damage calculation module is used for correcting the load amplitude and determining the maximum cycle load number, and combining the original cumulative fatigue damage value to obtain the cumulative fatigue damage at the current time.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the method of any one of claims 1-6.

9. A computer program product comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the method of any one of claims 1-6.

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