Wind turbine generator wind speed reconstruction method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a wind turbine generator wind speed reconstruction method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring wind speeds of a plurality of wind turbine generators in a wind power plant; determining a to-be-reconstructed wind turbine generator and a normal wind turbine generator according to the wind speeds, the average wind speed and the wind speed standard deviation of the plurality of wind turbine generators; according to the distance between the to-be-reconstructed wind turbine generator set and each normal wind turbine generator set, determining the distance weight of each normal wind turbine generator set; and obtaining the reconstructed wind speed of the to-be-reconstructed wind turbine generator according to the wind speed and the distance weight of each normal wind turbine generator. According to the embodiment of the invention, whether the wind speed measured by the wind meter of the wind turbine generator fails or not can be judged, wind speed reconstruction is carried out through the wind speed measurement signals of other wind turbine generators in the wind power plant, the wind turbine generators can still generate power to operate under the condition that the wind speed signals fail, and the power generation loss is reduced.

Description

Technical Field

[0001] The embodiments of the present disclosure belong to the technical field of wind turbine wind speed reconstruction, and specifically relate to a wind turbine wind speed reconstruction method, system, electronic device, and storage medium. Background Art

[0002] Wind speed is a crucial measurement signal for wind turbine operation, used for startup and shutdown, and power generation performance monitoring. Anemometers are typically installed atop the nacelle to measure wind speed. These include mechanical rotary anemometers, ultrasonic anemometers, and lidar anemometers. Mechanical rotary anemometers are widely used in wind turbines due to their simple structure, low cost, and easy installation and use.

[0003] However, due to environmental factors such as freezing, rain, snow, wind and sand, the anemometer may malfunction and be unable to effectively measure the wind speed. The wind turbine will be in a faulty state due to the lack of wind speed signal and cannot continue to generate electricity. The unit must be shut down and wait for maintenance to be completed before it can generate electricity normally, which will lead to loss of power generation. Summary of the Invention

[0004] The embodiments of the present disclosure aim to solve at least one of the technical problems existing in the prior art, and provide a wind turbine wind speed reconstruction method, system, electronic device and storage medium.

[0005] One aspect of the present disclosure provides a wind speed reconstruction method for a wind turbine generator set.

[0006] The law includes:

[0007] Obtain wind speeds for multiple wind turbines in a wind farm;

[0008] Determining the wind turbines to be reconstructed and the normal wind turbines according to the wind speeds, average wind speeds and wind speed standard deviations of the plurality of wind turbines;

[0009] Determining the distance weight of each normal wind turbine group according to the distance between the wind turbine group to be reconstructed and each normal wind turbine group;

[0010] The reconstructed wind speed of the wind turbine to be reconstructed is obtained according to the wind speed and distance weight of each normal wind turbine.

[0011] Furthermore, the determining of the wind turbine to be reconstructed and the normal wind turbine according to the wind speed, average wind speed and wind speed standard deviation of the plurality of wind turbines includes:

[0012] The wind turbines that meet the following equation are determined to be wind turbines to be reconstructed:

[0013] (v n -v m )>βv σ,n=1,2,3…

[0014] Where, v n Indicates the current wind speed of the wind turbine, v m represents the average wind speed of multiple wind turbines, β represents the deviation coefficient, v σ Represents the standard deviation of wind speeds for multiple wind turbines;

[0015] The remaining wind turbines are judged as normal wind turbines.

[0016] Furthermore, determining the distance weight of each normal wind turbine generator set according to the distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set includes:

[0017] The distance weight of each normal wind turbine generator set is calculated according to the following formula:

[0018]

[0019] Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight exponent.

[0020] Furthermore, obtaining the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine includes:

[0021] The reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula:

[0022] v e,i =∑w i,j v j ,j=1,2,3,…,j≠i

[0023] Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the normal wind speed of the wind turbine.

[0024] Another aspect of the present disclosure provides a wind turbine wind speed reconstruction system, the system comprising:

[0025] An acquisition module is used to obtain the wind speed of multiple wind turbines in the wind farm;

[0026] a determination module, configured to determine, based on the wind speeds, average wind speeds, and wind speed standard deviations of the plurality of wind turbines, whether the wind turbines are to be reconstructed or are normal;

[0027] A weight module, configured to determine a distance weight of each normal wind turbine generator set according to a distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set;

[0028] The reconstruction module is used to obtain the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine.

[0029] Furthermore, the determination module is specifically configured to:

[0030] The wind turbines that meet the following formula are determined to be wind turbines to be reconstructed:

[0031] (v n -v m )>βv σ ,n=1,2,3…

[0032] Where, v n Indicates the current wind speed of the wind turbine, v m represents the average wind speed of multiple wind turbines, β represents the deviation coefficient, v σ Represents the standard deviation of wind speeds for multiple wind turbines;

[0033] The remaining wind turbines are judged as normal wind turbines.

[0034] Furthermore, the weight module is specifically used to:

[0035] The distance weight of each normal wind turbine generator set is calculated according to the following formula:

[0036]

[0037] Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight exponent.

[0038] Furthermore, the reconstruction module is specifically used to:

[0039] The reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula:

[0040] v e,i =∑w i,j v j ,j=1,2,3,…,j≠i

[0041] Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the normal wind speed of the wind turbine.

[0042] Another aspect of the present disclosure provides an electronic device, comprising:

[0043] at least one processor; and,

[0044] The memory communicatively connected to the at least one processor is used to store one or more programs, which, when executed by the at least one processor, enable the at least one processor to implement the wind turbine wind speed reconstruction method described above.

[0045] Another aspect of the present disclosure provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the wind turbine wind speed reconstruction method described above.

[0046] A wind turbine wind speed reconstruction method, system, electronic device and storage medium of the embodiments of the present disclosure can determine whether the wind speed measured by the wind turbine anemometer is invalid, and reconstruct the wind speed through the wind speed measurement signals of other wind turbines in the wind farm. In the event of a wind speed signal failure, the wind turbine can still generate electricity and reduce power generation losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a wind speed reconstruction method for a wind turbine generator system according to an embodiment of the present disclosure;

[0048] Figure 2 This is a structural schematic diagram of a wind speed reconstruction system for a wind turbine generator set according to another embodiment of the present disclosure;

[0049] Figure 3 This is a schematic structural diagram of an electronic device according to another embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] The following will be combined with the accompanying drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the embodiments described are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present disclosure.

[0051] In addition, the described features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail to avoid blurring various aspects of the present disclosure.

[0052] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0053] It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Thus, the first component discussed below can be referred to as the second component without departing from the teachings of the concepts of this disclosure. As used in this disclosure, the term "and / or" includes any one of the associated listed items and all combinations of one or more of them.

[0054] Those skilled in the art will understand that the drawings are merely schematic diagrams of example embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing the present disclosure, and therefore cannot be used to limit the scope of protection of the present disclosure.

[0055] like Figure 1 As shown, an embodiment of the present disclosure provides a wind speed reconstruction method for a wind turbine generator set, the method comprising:

[0056] Step S1: Obtain wind speeds of multiple wind turbines in a wind farm.

[0057] Specifically, in wind farms in flat terrain areas, the wind conditions between each wind turbine are relatively small. When the wind speed signal of one or several wind turbines is missing, the reconstructed wind speed obtained by calculating the wind speed measurement values ​​of other normally operating turbines through the wind speed reconstruction model can be used to replace the wind speed measured by the wind meter of the turbine itself when the signal is missing.

[0058] Usually, each wind turbine in a wind farm transmits the wind speed measured by the wind speed meter to the station control platform through network communication. Therefore, each wind turbine has a channel for transmitting wind speed signals to the outside. Adding the function of wind turbines collecting wind speed signals from other wind turbines from the station control platform allows wind turbines to transmit their own measured wind speed to other wind turbines while also collecting wind speeds measured by other wind turbines in the wind farm. Suppose the wind speed of the nth wind turbine is v n , collect and obtain the wind speed measurement values ​​of all wind turbines in the wind farm to form a wind speed data set V.

[0059] Step S2: determining the wind turbine to be reconstructed and the normal wind turbine according to the wind speed, average wind speed and wind speed standard deviation of the plurality of wind turbines.

[0060] Specifically, calculate the average wind speed v of all wind speeds in the data set V mAnd the standard deviation of wind speed v σ . Calculate the wind speed v of the nth wind turbine in sequence n Are the following conditions met?

[0061] (v n -v m )>βv σ ,n=1,2,3…

[0062] Where β represents the deviation coefficient. When the wind speed v that satisfies the above formula appears n When , the wind speed is considered invalid data, and the data is filtered out from the data set V to form a new data set V, and the average wind speed v of the new data set V is recalculated. m and wind speed standard deviation v σ , substitute into the above formula to calculate the wind speed v of the next wind turbine n Is it satisfied? Similarly, the wind speeds of all wind turbines are traversed until all invalid data in the data set are filtered out. The wind turbines corresponding to the remaining wind speed values ​​in the data set can be judged as normal wind turbines; and for the wind turbines corresponding to the screened wind speed measurement values, it is determined that the wind speed measured by its anemometer is abnormal, and it is necessary to reconstruct the abnormal unit through the wind speed measurement values ​​of the remaining normal wind turbines, that is, the wind speed at the location of the wind turbine to be reconstructed. In order to facilitate the distinction between the wind turbine to be reconstructed and the normal wind turbine in subsequent calculations, the wind speed valid mark η of the wind turbine to be reconstructed is defined as 0, and the wind speed valid mark η of the normal wind turbine is defined as 1.

[0063] Step S3: determining the distance weight of each normal wind turbine generator set according to the distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set.

[0064] Specifically, let the number of the wind turbine to be reconstructed be i, the numbers of the normal wind turbines be j = 1, 2, 3, ..., and the straight-line distance between the wind turbine to be reconstructed and the normal wind turbines be L i,j The distance weight of each normal wind turbine generator set is calculated according to the following formula:

[0065]

[0066] Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight index. Since the valid markers for the wind turbine to be reconstructed and the normal wind turbines have been determined separately in the previous step S2, the distance weights of all remaining wind turbines can actually be calculated during the calculation process. The distance weights of abnormal wind turbines other than the current wind turbine to be reconstructed will be automatically determined to be 0, thereby simplifying the calculation steps in the program.

[0067] Step S4: obtaining the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine.

[0068] Specifically, the reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula:

[0069] v e,i =∑w i,j v j ,j=1,2,3,…,j≠i

[0070] Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the wind speed of a normal wind turbine. During calculation, other abnormal wind turbines with a distance weight of 0 will be automatically ignored, thus simplifying the calculation steps in the program.

[0071] For wind turbine i when the anemometer fails and the wind speed signal is missing, the reconstructed wind speed v obtained by the above wind speed reconstruction calculation can be used. e,i As the wind speed input signal of the control system, it maintains the normal power generation operation of the unit.

[0072] A wind turbine wind speed reconstruction method according to an embodiment of the present disclosure can determine whether the wind speed measured by the wind turbine anemometer is invalid, and reconstruct the wind speed through the wind speed measurement signals of other wind turbines in the wind farm. In this way, the wind turbine can still generate electricity even when the wind speed signal fails, thereby reducing power generation losses.

[0073] like Figure 2 As shown, another embodiment of the present disclosure provides a wind speed reconstruction system for a wind turbine generator set, the system comprising:

[0074] An acquisition module 210 is used to acquire wind speeds of multiple wind turbines in a wind farm;

[0075] A determination module 220 is configured to determine whether a wind turbine to be reconstructed is a normal wind turbine according to the wind speed, average wind speed and wind speed standard deviation of the plurality of wind turbines;

[0076] A weighting module 230 is configured to determine a distance weight of each normal wind turbine generator set according to a distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set;

[0077] The reconstruction module 240 is configured to obtain the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine.

[0078] Exemplarily, the determination module is specifically configured to:

[0079] The wind turbines that meet the following formula are determined to be wind turbines to be reconstructed:

[0080] (v n -v m )>βv σ ,n=1,2,3…

[0081] Where, v n Indicates the current wind speed of the wind turbine, v m represents the average wind speed of multiple wind turbines, β represents the deviation coefficient, v σ Represents the wind speed standard deviation of multiple wind turbines; the remaining wind turbines are judged as normal wind turbines.

[0082] Exemplarily, the weight module is specifically used to:

[0083] The distance weight of each normal wind turbine generator set is calculated according to the following formula:

[0084]

[0085] Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight exponent.

[0086] Exemplarily, the reconstruction module is specifically used to:

[0087] The reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula:

[0088] v e,i =∑w i,j v j ,j=1,2,3,…,j≠i

[0089] Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the normal wind speed of the wind turbine.

[0090] Specifically, a wind turbine wind speed reconstruction system in an embodiment of the present disclosure is used to implement the wind turbine wind speed reconstruction method described in the above embodiments. The specific implementation process has been described in detail in the above embodiments and will not be repeated here.

[0091] A wind turbine wind speed reconstruction system according to an embodiment of the present disclosure can determine whether the wind speed measured by the wind turbine anemometer is invalid, and reconstruct the wind speed through the wind speed measurement signals of other wind turbines in the wind farm. In this way, the wind turbine can still generate electricity even when the wind speed signal fails, thereby reducing power generation losses.

[0092] like Figure 3 As shown, another embodiment of the present disclosure provides an electronic device, including:

[0093] At least one processor 301; and a memory 302 in communication with the at least one processor 301, for storing one or more programs, which, when executed by the at least one processor 301, enable the at least one processor 301 to implement the wind turbine wind speed reconstruction method described above.

[0094] The memory 302 and processor 301 are connected using a bus. The bus can include any number of interconnected buses and bridges, connecting various circuits of one or more processors 301 and memory 302. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits. These are all well known in the art and are therefore not described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single component or multiple components, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor 301 is transmitted over a wireless medium via an antenna. Furthermore, the antenna receives data and transmits it to the processor 301.

[0095] The processor 301 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. The memory 302 can be used to store data used by the processor 301 when performing operations.

[0096] Yet another embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the wind turbine wind speed reconstruction method described above.

[0097] The computer-readable storage medium may be included in the system or electronic device of the present disclosure, or may exist independently.

[0098] Computer-readable storage media may be any tangible medium that contains or stores a program, which may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, optical fiber, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0099] The computer-readable storage medium may also include a data signal propagated in baseband or as part of a carrier wave, which carries the computer-readable program code. Specific examples include but are not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0100] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present disclosure, and such modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A wind turbine wind speed reconstruction method, characterized in that: The method comprises: Obtain wind speeds for multiple wind turbines in a wind farm; Determining the wind turbines to be reconstructed and the normal wind turbines according to the wind speeds, average wind speeds and wind speed standard deviations of the plurality of wind turbines; Determining the distance weight of each normal wind turbine group according to the distance between the wind turbine group to be reconstructed and each normal wind turbine group; The reconstructed wind speed of the wind turbine to be reconstructed is obtained according to the wind speed and distance weight of each normal wind turbine.

2. The wind turbine wind speed reconstruction method according to claim 1, characterized in that: The determining of the wind turbine to be reconstructed and the normal wind turbine according to the wind speed, average wind speed and wind speed standard deviation of the plurality of wind turbines includes: The wind turbines that meet the following equation are determined to be wind turbines to be reconstructed: (v n -v m )>βv σ ,n=1,2,3… Where, v n Indicates the current wind speed of the wind turbine, v m represents the average wind speed of multiple wind turbines, β represents the deviation coefficient, v σ Represents the standard deviation of wind speeds for multiple wind turbines; The remaining wind turbines are judged as normal wind turbines.

3. The wind turbine wind speed reconstruction method according to claim 1, characterized in that: Determining the distance weight of each normal wind turbine generator set according to the distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set includes: The distance weight of each normal wind turbine generator set is calculated according to the following formula: Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight exponent.

4. The wind turbine wind speed reconstruction method according to claim 3, characterized in that: Obtaining the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine includes: The reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula: in e,i =∑w i,j in j ,j=1,2,3,…,j≠i Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the normal wind speed of the wind turbine.

5. A wind turbine wind speed reconstruction system, characterized in that: The system comprises: An acquisition module is used to obtain the wind speed of multiple wind turbines in the wind farm; a determination module, configured to determine, based on the wind speeds, average wind speeds, and wind speed standard deviations of the plurality of wind turbines, whether the wind turbines are to be reconstructed or are normal; A weight module, configured to determine a distance weight of each normal wind turbine generator set according to a distance between the wind turbine generator set to be reconstructed and each normal wind turbine generator set; The reconstruction module is used to obtain the reconstructed wind speed of the wind turbine to be reconstructed according to the wind speed and distance weight of each normal wind turbine.

6. The wind turbine wind speed reconstruction system according to claim 5, characterized in that: The determination module is specifically used for: The wind turbines that meet the following formula are determined to be wind turbines to be reconstructed: (v n -v m )>βv σ ,n=1,2,3… Where, v n Indicates the current wind speed of the wind turbine, v m represents the average wind speed of multiple wind turbines, β represents the deviation coefficient, v σ Represents the standard deviation of wind speeds for multiple wind turbines; The remaining wind turbines are judged as normal wind turbines.

7. The wind turbine wind speed reconstruction system according to claim 5, characterized in that: The weight module is specifically used for: The distance weight of each normal wind turbine generator set is calculated according to the following formula: Where w i,j represents the distance weight, η j Indicates the effective mark of wind speed, L i,j represents the distance, and α represents the distance weight exponent.

8. The wind turbine wind speed reconstruction system according to claim 7, characterized in that: The reconstruction module is specifically used for: The reconstructed wind speed of the wind turbine to be reconstructed is calculated according to the following formula: in e,i =∑w i,j in j ,j=1,2,3,…,j≠i Where, v e,i represents the reconstructed wind speed, w i,j represents the distance weight, v j Indicates the normal wind speed of the wind turbine.

9. An electronic device, characterized in that: include: at least one processor; as well as, A memory communicatively connected to the at least one processor is used to store one or more programs, which, when executed by the at least one processor, enables the at least one processor to implement the wind turbine wind speed reconstruction method according to any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the wind turbine wind speed reconstruction method according to any one of claims 1 to 4 is implemented.

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