A method and device for determining an optimal torque coefficient of a wind turbine

Abstract

The present application relates to the technical field of wind driven generators, and discloses a kind of wind driven generator optimal torque coefficient determination method and device, according to the wind wheel torque and torque influence data of wind driven generator at different time to construct data processing set;Optimization analysis is carried out to data processing set, and the optimal data processing set is obtained;Extract the optimal wind wheel torque and optimal torque influence data in optimal data processing set, determine the wind wheel speed when wind driven generator is at optimal wind wheel torque;According to optimal wind wheel torque and wind wheel speed, the torque coefficient of wind driven generator is calculated;According to the environmental data of wind driven generator at different time, the torque coefficient correction factor is determined, and the torque coefficient is corrected according to the torque coefficient correction factor, and the optimal torque coefficient is obtained, the present application realizes the accurate determination of the optimal torque coefficient of wind driven generator, and then improves the wind energy utilization rate and power generation efficiency, and has important significance for improving the operating performance of wind driven generator and optimizing blade design.

Description

Technical Field

[0001] This invention relates to the field of wind turbine technology, and in particular to a method and apparatus for determining the optimal torque coefficient of a wind turbine. Background Technology

[0002] A wind turbine is an electrical device that converts wind energy into mechanical work, which drives a rotor to rotate and ultimately outputs alternating current (AC). A wind turbine typically consists of a rotor, generator, deflector, tower, speed-limiting safety mechanism, and energy storage device. The advantages of wind power generation lie in its cleanliness, environmental friendliness, sustainability, low investment cost, and mature technology. Wind power can replace traditional energy sources, reducing pollution and damage to the environment. A higher torque coefficient in a wind turbine indicates better adaptability to changes in wind speed, thus improving power generation efficiency. Therefore, determining the torque coefficient of a wind turbine is of great significance.

[0003] The torque coefficient of a wind turbine is influenced by a variety of factors, including blade shape and size, as well as wind speed, all of which require precise measurement and complex calculations. Secondly, the performance of a wind turbine is affected by environmental conditions such as temperature and humidity. Therefore, determining the torque coefficient requires a comprehensive evaluation of various environmental conditions. Consequently, determining the torque coefficient based on existing technical solutions carries a significant risk of error, making it impossible to guarantee the accuracy of the wind turbine's torque coefficient.

[0004] Therefore, how to provide a method and device for accurately determining the optimal torque coefficient of a wind turbine is a technical problem that needs to be solved. Summary of the Invention

[0005] This invention provides a method and apparatus for determining the optimal torque coefficient of a wind turbine, which solves the technical problem in the prior art that the torque coefficient of a wind turbine cannot be accurately determined, thus failing to guarantee that the wind turbine is at its optimal torque coefficient.

[0006] To achieve the above objectives, the present invention provides a method for determining the optimal torque coefficient of a wind turbine generator, the method comprising:

[0007] Collect the rotor torque of wind turbines at different times and obtain the torque impact data corresponding to each rotor torque. Construct a data processing set based on each rotor torque and the corresponding torque impact data.

[0008] Optimization analysis is performed on all data processing sets to obtain the optimal data processing set;

[0009] Extract the optimal wind turbine torque and optimal torque influence data from the optimal data processing set, and determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque.

[0010] The torque coefficient of the wind turbine is calculated based on the optimal rotor torque and rotor speed of the wind turbine.

[0011] Environmental data of the wind turbine at different times is collected, a torque coefficient correction factor is determined based on the environmental data of the wind turbine, and the torque coefficient of the wind turbine is corrected based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

[0012] In one embodiment, the data processing set is constructed based on the torque of each wind turbine and the corresponding torque impact data, including:

[0013] Curve fitting was performed on the torque of each wind turbine and the corresponding torque influence data to obtain the wind turbine torque-torque influence data curve;

[0014] A preset first reference wind turbine torque and a second reference wind turbine torque are obtained, and data removal processing is performed on the wind turbine torque-torque influence data curve based on the first reference wind turbine torque and the second reference wind turbine torque.

[0015] The data removal process includes removing all wind turbine torques on the wind turbine torque-torque influence data curve that are greater than the first reference wind turbine torque, and removing all wind turbine torques on the wind turbine torque-torque influence data curve that are less than the second reference wind turbine torque;

[0016] A data processing set is constructed based on the remaining wind turbine torque and the corresponding torque impact data.

[0017] In one embodiment, when performing optimization analysis on all data processing sets to obtain the optimal data processing set, the process includes:

[0018] The historical power generation data of the wind turbine is obtained, and an intelligent prediction model is established based on the historical power generation data;

[0019] The amount of wind power generation data corresponding to the torque of each wind turbine is calculated based on the intelligent prediction model.

[0020] All wind power generation data are sorted by numerical value, and a set to be processed is established based on the sorting result. The first data in the set to be processed is the largest wind power generation data, and the last data in the set to be processed is the smallest wind power generation data.

[0021] Extract the first four wind power generation data from the set to be processed, and obtain the corresponding wind turbine torque, which are respectively labeled as the first wind turbine torque, the second wind turbine torque, the third wind turbine torque, and the fourth wind turbine torque;

[0022] The optimal data processing set is obtained based on the torque of the first wind turbine, the torque of the second wind turbine, the torque of the third wind turbine, and the torque of the fourth wind turbine.

[0023] In one embodiment, obtaining the optimal data processing set based on the first wind turbine torque, the second wind turbine torque, the third wind turbine torque, and the fourth wind turbine torque includes:

[0024] First torque influence data corresponding to the first wind turbine torque, second torque influence data corresponding to the second wind turbine torque, third torque influence data corresponding to the third wind turbine torque, and fourth torque influence data corresponding to the fourth wind turbine torque are obtained respectively.

[0025] Calculate the fuzzy weights corresponding to the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data respectively;

[0026] The importance of the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data are evaluated respectively, and corresponding evaluation values ​​are obtained.

[0027] The optimal wind turbine torque is determined based on the calculated fuzzy weights and evaluation values, and the optimal data processing set is obtained based on the optimal wind turbine torque and the corresponding optimal torque influence data.

[0028] In one embodiment, before determining the torque coefficient correction factor based on the environmental data of the wind turbine, and before correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, the method further includes:

[0029] All wind speed data are extracted from the environmental data, and a wind speed average value-optimal torque coefficient mapping table is obtained from the historical database of the wind turbine.

[0030] Calculate the average wind speed of all wind speed data, and determine the optimal torque coefficient corresponding to the average wind speed based on the relationship between the average wind speed and the average wind speed-optimal torque coefficient mapping table;

[0031] Based on the relationship between the torque coefficient of the wind turbine and the optimal torque coefficient, it is determined whether the torque coefficient of the wind turbine needs to be corrected.

[0032] If the torque coefficient is greater than the optimal torque dilution, then it is determined that there is no need to correct the torque coefficient of the wind turbine.

[0033] If the torque coefficient is less than or equal to the optimal torque dilution, it is determined that the torque coefficient of the wind turbine needs to be corrected, and the torque coefficient correction factor is determined based on the environmental data of the wind turbine.

[0034] In one embodiment, determining a torque coefficient correction factor based on environmental data of the wind turbine, and correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, includes:

[0035] The environmental impact factor of the wind turbine is calculated based on the environmental data of the wind turbine; wherein...

[0036] The environmental impact factor of the wind turbine is calculated according to the following formula:

[0037]

[0038] Where W is the environmental impact factor of the wind turbine, n is the number of environmental data, Pi is the average value of the i-th environmental data, and ai is the weight of the i-th environmental data.

[0039] Obtain the pre-defined maximum and minimum extreme values ​​of environmental impact factors;

[0040] The torque coefficient correction factor is determined based on the relationship between the environmental impact factor of the wind turbine, the maximum extreme value of the environmental impact factor, and the minimum extreme value of the environmental impact factor.

[0041] When the environmental impact factor is less than the minimum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ1;

[0042] When the environmental impact factor is greater than or equal to the minimum extreme value of the environmental impact factor, and the environmental impact factor is less than the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ2.

[0043] When the environmental impact factor is greater than or equal to the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ3.

[0044] In one embodiment, after correcting the torque coefficient of the wind turbine according to the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine, the method further includes:

[0045] Obtain the real-time wind power generation of the wind turbine when it is at the optimal torque coefficient;

[0046] Whether to issue an early warning is determined based on the relationship between the real-time wind power generation and the preset wind power generation.

[0047] If the real-time wind power generation is less than the preset wind power generation, an early warning will be issued.

[0048] When the real-time wind power generation is greater than or equal to the preset wind power generation, it is determined that no warning is needed, and the real-time wind power generation of the wind turbine is monitored in real time.

[0049] In one embodiment, real-time detection of the wind power generation of the wind turbine includes:

[0050] The first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation of the wind turbine are obtained within a preset time.

[0051] The detection time interval of the wind turbine is calculated based on the first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation.

[0052] The detection time interval of the wind turbine is calculated according to the following formula:

[0053]

[0054] Where T is the detection time interval of the wind turbine, k1 is the first real-time wind power generation, k2 is the second real-time wind power generation, k3 is the third real-time wind power generation, kj is the preset wind power generation, and L is the loss index in the process of calculating the detection time interval.

[0055] To achieve the above objectives, the present invention provides an apparatus for determining the optimal torque coefficient of a wind turbine generator, the apparatus comprising:

[0056] The module is used to collect the rotor torque of wind turbines at different times and obtain the torque impact data corresponding to each rotor torque. Based on each rotor torque and the corresponding torque impact data, a data processing set is constructed.

[0057] The analysis module is used to perform optimization analysis on all data processing sets to obtain the optimal data processing set.

[0058] The determination module is used to extract the optimal wind turbine torque and the optimal torque influence data from the optimal data processing set, and to determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque.

[0059] The calculation module is used to calculate the torque coefficient of the wind turbine based on the optimal rotor torque and rotor speed of the wind turbine.

[0060] The correction module is used to collect environmental data of the wind turbine at different times, determine the torque coefficient correction factor based on the environmental data of the wind turbine, and correct the torque coefficient of the wind turbine based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

[0061] This invention provides a method and apparatus for determining the optimal torque coefficient of a wind turbine generator, which has the following advantages compared to the prior art:

[0062] This invention discloses a method and apparatus for determining the optimal torque coefficient of a wind turbine. The method involves constructing a data processing set based on the wind turbine's rotor torque and torque influence data at different times; performing optimization analysis on the data processing set to obtain the optimal data processing set; extracting the optimal rotor torque and optimal torque influence data from the optimal data processing set to determine the rotor speed when the wind turbine is at the optimal rotor torque; calculating the torque coefficient of the wind turbine based on the optimal rotor torque and rotor speed; determining a torque coefficient correction factor based on the wind turbine's environmental data at different times; and correcting the torque coefficient based on the torque coefficient correction factor to obtain the optimal torque coefficient. This invention achieves accurate determination of the optimal torque coefficient of a wind turbine, thereby improving wind energy utilization and power generation efficiency, and is of great significance for improving the operating performance of wind turbines and optimizing blade design. Attached Figure Description

[0063] Figure 1 A flowchart illustrating a method for determining the optimal torque coefficient of a wind turbine generator according to an embodiment of the present invention is shown.

[0064] Figure 2 A schematic diagram of a system for determining the optimal torque coefficient of a wind turbine generator is shown in an embodiment of the present invention. Detailed Implementation

[0065] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0066] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0067] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0068] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0069] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0070] like Figure 1 As shown, an embodiment of the present invention discloses a method for determining the optimal torque coefficient of a wind turbine generator, the method comprising:

[0071] S110: Collect the wind turbine rotor torque at different times, obtain the torque influence data corresponding to each wind turbine rotor torque, and construct a data processing set based on each wind turbine rotor torque and the corresponding torque influence data;

[0072] In some embodiments of this application, the data processing set is constructed based on the torque of each wind turbine and the corresponding torque influence data, including:

[0073] Curve fitting was performed on the torque of each wind turbine and the corresponding torque influence data to obtain the wind turbine torque-torque influence data curve;

[0074] A preset first reference wind turbine torque and a second reference wind turbine torque are obtained, and data removal processing is performed on the wind turbine torque-torque influence data curve based on the first reference wind turbine torque and the second reference wind turbine torque.

[0075] The data removal process includes removing all wind turbine torques on the wind turbine torque-torque influence data curve that are greater than the first reference wind turbine torque, and removing all wind turbine torques on the wind turbine torque-torque influence data curve that are less than the second reference wind turbine torque;

[0076] A data processing set is constructed based on the remaining wind turbine torque and the corresponding torque impact data.

[0077] In this embodiment, a Cartesian coordinate system including the XY axis can be used to perform curve fitting on the torque of each wind turbine and the corresponding torque influence data.

[0078] In this embodiment, the first reference wind turbine torque is greater than the second reference wind turbine torque. The first reference wind turbine torque and the second reference wind turbine torque can be used to eliminate wind turbine torques that do not meet the requirements or are obviously wrong.

[0079] The beneficial effects of the above technical solution are: by eliminating wind turbine torques that do not meet the requirements or are obviously wrong, the present invention can lay the foundation for determining the optimal torque coefficient of wind turbine generators.

[0080] S120: Perform optimization analysis on all data processing sets to obtain the optimal data processing set;

[0081] In some embodiments of this application, when performing optimization analysis on all data processing sets to obtain the optimal data processing set, the following steps are included:

[0082] The historical power generation data of the wind turbine is obtained, and an intelligent prediction model is established based on the historical power generation data;

[0083] The amount of wind power generation data corresponding to the torque of each wind turbine is calculated based on the intelligent prediction model.

[0084] All wind power generation data are sorted by numerical value, and a set to be processed is established based on the sorting result. The first data in the set to be processed is the largest wind power generation data, and the last data in the set to be processed is the smallest wind power generation data.

[0085] Extract the first four wind power generation data from the set to be processed, and obtain the corresponding wind turbine torque, which are respectively labeled as the first wind turbine torque, the second wind turbine torque, the third wind turbine torque, and the fourth wind turbine torque;

[0086] The optimal data processing set is obtained based on the torque of the first wind turbine, the torque of the second wind turbine, the torque of the third wind turbine, and the torque of the fourth wind turbine.

[0087] In this embodiment, the intelligent prediction model can be used to predict the wind power generation of wind turbines.

[0088] The beneficial effects of the above technical solution are: the present invention extracts the first four wind power generation data from the set to be processed, which can provide reliable data support for obtaining the optimal data processing set and ensure the accuracy of the determination of the wind turbine torque coefficient.

[0089] In some embodiments of this application, when obtaining the optimal data processing set based on the first wind turbine torque, the second wind turbine torque, the third wind turbine torque, and the fourth wind turbine torque, the following is included:

[0090] First torque influence data corresponding to the first wind turbine torque, second torque influence data corresponding to the second wind turbine torque, third torque influence data corresponding to the third wind turbine torque, and fourth torque influence data corresponding to the fourth wind turbine torque are obtained respectively.

[0091] Calculate the fuzzy weights corresponding to the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data respectively;

[0092] The importance of the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data are evaluated respectively, and corresponding evaluation values ​​are obtained.

[0093] The optimal wind turbine torque is determined based on the calculated fuzzy weights and evaluation values, and the optimal data processing set is obtained based on the optimal wind turbine torque and the corresponding optimal torque influence data.

[0094] In this embodiment, fuzzy weighting is a mathematical method that uses fuzzy set theory to analyze and handle fuzziness. Fuzzy weighting describes the importance of each factor by assigning a number between 0 and 1; this number is called the fuzzy number.

[0095] In this embodiment, the evaluation value is obtained based on the importance of the torque influence data and can be used to measure the importance of the torque influence data.

[0096] The beneficial effects of the above technical solution are: the present invention determines the optimal wind turbine torque based on the calculated fuzzy weights and evaluation values, and obtains the optimal data processing set based on the optimal wind turbine torque and the corresponding optimal torque influence data, which can lay the foundation for subsequent calculation of the optimal torque coefficient of the wind turbine and avoid large errors.

[0097] S130: Extract the optimal wind turbine torque and optimal torque influence data from the optimal data processing set, and determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque.

[0098] S140: Calculate the torque coefficient of the wind turbine based on the optimal rotor torque and rotor speed of the wind turbine;

[0099] In this embodiment, the torque coefficient of the wind turbine can be obtained by calculating the ratio of the optimal wind turbine torque to the wind turbine speed.

[0100] S150: Collect environmental data of the wind turbine at different times, determine the torque coefficient correction factor based on the environmental data of the wind turbine, and correct the torque coefficient of the wind turbine based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

[0101] In some embodiments of this application, before determining the torque coefficient correction factor based on the environmental data of the wind turbine, and before correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, the method further includes:

[0102] All wind speed data are extracted from the environmental data, and a wind speed average value-optimal torque coefficient mapping table is obtained from the historical database of the wind turbine.

[0103] Calculate the average wind speed of all wind speed data, and determine the optimal torque coefficient corresponding to the average wind speed based on the relationship between the average wind speed and the average wind speed-optimal torque coefficient mapping table;

[0104] Based on the relationship between the torque coefficient of the wind turbine and the optimal torque coefficient, it is determined whether the torque coefficient of the wind turbine needs to be corrected.

[0105] If the torque coefficient is greater than the optimal torque dilution, then it is determined that there is no need to correct the torque coefficient of the wind turbine.

[0106] If the torque coefficient is less than or equal to the optimal torque dilution, it is determined that the torque coefficient of the wind turbine needs to be corrected, and the torque coefficient correction factor is determined based on the environmental data of the wind turbine.

[0107] The beneficial effects of the above technical solution are: the present invention determines whether the torque coefficient of the wind turbine needs to be corrected based on the relationship between the torque coefficient of the wind turbine and the optimal torque coefficient, thereby ensuring the best power generation performance of the wind turbine.

[0108] In some embodiments of this application, when determining the torque coefficient correction factor based on the environmental data of the wind turbine, and correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, the process includes:

[0109] The environmental impact factor of the wind turbine is calculated based on the environmental data of the wind turbine; wherein...

[0110] The environmental impact factor of the wind turbine is calculated according to the following formula:

[0111]

[0112] Where W is the environmental impact factor of the wind turbine, n is the number of environmental data, Pi is the average value of the i-th environmental data, and ai is the weight of the i-th environmental data.

[0113] Obtain the pre-defined maximum and minimum extreme values ​​of environmental impact factors;

[0114] The torque coefficient correction factor is determined based on the relationship between the environmental impact factor of the wind turbine, the maximum extreme value of the environmental impact factor, and the minimum extreme value of the environmental impact factor.

[0115] When the environmental impact factor is less than the minimum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ1;

[0116] When the environmental impact factor is greater than or equal to the minimum extreme value of the environmental impact factor, and the environmental impact factor is less than the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ2.

[0117] When the environmental impact factor is greater than or equal to the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ3.

[0118] In this embodiment, the environmental data of the wind turbine mainly includes wind speed, wind direction, temperature, humidity, and air pressure. This data can be monitored and collected in real time using sensors built into the wind turbine.

[0119] In this embodiment, the environmental impact factor of the wind turbine refers to the degree of influence of these data on the wind power generation of the wind turbine.

[0120] In this embodiment, the maximum extreme value of the environmental impact factor is greater than the minimum extreme value of the environmental impact factor. The specific value can be set according to actual needs, and the value set for each wind turbine is different.

[0121] In this embodiment, Δβ1, Δβ2 and Δβ3 are also set according to actual needs, satisfying Δβ1<Δβ2<Δβ3.

[0122] The beneficial effects of the above technical solution are as follows: Based on the relationship between the environmental impact factor, the maximum extreme value of the environmental impact factor and the minimum extreme value of the environmental impact factor of the wind turbine, the present invention determines the torque coefficient correction factor, which can accurately determine the optimal torque coefficient of the wind turbine, ensure the best power generation performance of the wind turbine, improve the wind power generation efficiency, and is of great significance for improving the operating performance of the wind turbine and optimizing the blade design.

[0123] In some embodiments of this application, after correcting the torque coefficient of the wind turbine according to the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine, the method further includes:

[0124] Obtain the real-time wind power generation of the wind turbine when it is at the optimal torque coefficient;

[0125] Whether to issue an early warning is determined based on the relationship between the real-time wind power generation and the preset wind power generation.

[0126] If the real-time wind power generation is less than the preset wind power generation, an early warning will be issued.

[0127] When the real-time wind power generation is greater than or equal to the preset wind power generation, it is determined that no warning is needed, and the real-time wind power generation of the wind turbine is monitored in real time.

[0128] The beneficial effects of the above technical solution are: the present invention determines whether to issue an early warning based on the relationship between real-time wind power generation and preset wind power generation, which can ensure the stable operation of wind turbines and avoid major failures of wind turbines.

[0129] In some embodiments of this application, the real-time detection of the wind power generation of the wind turbine includes:

[0130] The first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation of the wind turbine are obtained within a preset time.

[0131] The detection time interval of the wind turbine is calculated based on the first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation.

[0132] The detection time interval of the wind turbine is calculated according to the following formula:

[0133]

[0134] Where T is the detection time interval of the wind turbine, k1 is the first real-time wind power generation, k2 is the second real-time wind power generation, k3 is the third real-time wind power generation, kj is the preset wind power generation, and L is the loss index in the process of calculating the detection time interval.

[0135] The beneficial effects of the above technical solution are: the present invention calculates the detection time interval of the wind turbine based on the first real-time wind power generation, the second real-time wind power generation and the third real-time wind power generation, and detects the wind turbine based on the detection time interval, which can not only ensure the normal operation of the wind turbine, but also avoid repetitive work by the staff and improve work efficiency.

[0136] To further illustrate the technical concept of this invention, the technical solution of this invention will now be described in conjunction with specific application scenarios.

[0137] Correspondingly, such as Figure 2 As shown, this application also provides a device for determining the optimal torque coefficient of a wind turbine generator, the device comprising:

[0138] The module is used to collect the rotor torque of wind turbines at different times and obtain the torque impact data corresponding to each rotor torque. Based on each rotor torque and the corresponding torque impact data, a data processing set is constructed.

[0139] The analysis module is used to perform optimization analysis on all data processing sets to obtain the optimal data processing set.

[0140] The determination module is used to extract the optimal wind turbine torque and the optimal torque influence data from the optimal data processing set, and to determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque.

[0141] The calculation module is used to calculate the torque coefficient of the wind turbine based on the optimal rotor torque and rotor speed of the wind turbine.

[0142] The correction module is used to collect environmental data of the wind turbine at different times, determine the torque coefficient correction factor based on the environmental data of the wind turbine, and correct the torque coefficient of the wind turbine based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

[0143] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0144] Although the invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, features in the embodiments disclosed herein can be combined with each other in any manner, provided there is no structural conflict. The omission of all such combinations in this specification is merely for brevity and resource conservation. Therefore, the invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

[0145] It will be understood by those skilled in the art that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for determining the optimal torque coefficient of a wind turbine generator, characterized in that, The method includes: Collect the rotor torque of wind turbines at different times and obtain the torque impact data corresponding to each rotor torque. Construct a data processing set based on each rotor torque and the corresponding torque impact data. Optimization analysis is performed on all data processing sets to obtain the optimal data processing set; Extract the optimal wind turbine torque and optimal torque influence data from the optimal data processing set, and determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque. The torque coefficient of the wind turbine is calculated based on the optimal rotor torque and rotor speed of the wind turbine. Environmental data of the wind turbine is collected at different times. A torque coefficient correction factor is determined based on the environmental data of the wind turbine. The torque coefficient of the wind turbine is then corrected based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

2. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 1, characterized in that, When constructing a data processing set based on the torque of each wind turbine and the corresponding torque impact data, the following are included: Curve fitting was performed on the torque of each wind turbine and the corresponding torque influence data to obtain the wind turbine torque-torque influence data curve; A preset first reference wind turbine torque and a second reference wind turbine torque are obtained, and data removal processing is performed on the wind turbine torque-torque influence data curve based on the first reference wind turbine torque and the second reference wind turbine torque. The data removal process includes removing all wind turbine torques on the wind turbine torque-torque influence data curve that are greater than the first reference wind turbine torque, and removing all wind turbine torques on the wind turbine torque-torque influence data curve that are less than the second reference wind turbine torque; A data processing set is constructed based on the remaining wind turbine torque and the corresponding torque impact data.

3. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 1, characterized in that, When performing optimization analysis on all data processing sets to obtain the optimal data processing set, the following are included: The historical power generation data of the wind turbine is obtained, and an intelligent prediction model is established based on the historical power generation data; The amount of wind power generation data corresponding to the torque of each wind turbine is calculated based on the intelligent prediction model. All wind power generation data are sorted by numerical value, and a set to be processed is established based on the sorting result. The first data in the set to be processed is the largest wind power generation data, and the last data in the set to be processed is the smallest wind power generation data. Extract the first four wind power generation data from the set to be processed, and obtain the corresponding wind turbine torque, which are respectively labeled as the first wind turbine torque, the second wind turbine torque, the third wind turbine torque, and the fourth wind turbine torque; The optimal data processing set is obtained based on the torque of the first wind turbine, the torque of the second wind turbine, the torque of the third wind turbine, and the torque of the fourth wind turbine.

4. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 3, characterized in that, When obtaining the optimal data processing set based on the torques of the first, second, third, and fourth wind turbines, the process includes: First torque influence data corresponding to the first wind turbine torque, second torque influence data corresponding to the second wind turbine torque, third torque influence data corresponding to the third wind turbine torque, and fourth torque influence data corresponding to the fourth wind turbine torque are obtained respectively. Calculate the fuzzy weights corresponding to the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data respectively; The importance of the first torque influence data, the second torque influence data, the third torque influence data, and the fourth torque influence data are evaluated respectively, and corresponding evaluation values ​​are obtained. The optimal wind turbine torque is determined based on the calculated fuzzy weights and evaluation values, and the optimal data processing set is obtained based on the optimal wind turbine torque and the corresponding optimal torque influence data.

5. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 1, characterized in that, Before determining the torque coefficient correction factor based on the environmental data of the wind turbine, and before correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, the method further includes: All wind speed data are extracted from the environmental data, and a wind speed average value-optimal torque coefficient mapping table is obtained from the historical database of the wind turbine. Calculate the average wind speed of all wind speed data, and determine the optimal torque coefficient corresponding to the average wind speed based on the relationship between the average wind speed and the average wind speed-optimal torque coefficient mapping table; Based on the relationship between the torque coefficient of the wind turbine and the optimal torque coefficient, it is determined whether the torque coefficient of the wind turbine needs to be corrected. If the torque coefficient is greater than the optimal torque dilution, then it is determined that there is no need to correct the torque coefficient of the wind turbine. If the torque coefficient is less than or equal to the optimal torque dilution, it is determined that the torque coefficient of the wind turbine needs to be corrected, and the torque coefficient correction factor is determined based on the environmental data of the wind turbine.

6. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 1, characterized in that, When determining the torque coefficient correction factor based on the environmental data of the wind turbine, and correcting the torque coefficient of the wind turbine based on the torque coefficient correction factor, the process includes: The environmental impact factor of the wind turbine is calculated based on the environmental data of the wind turbine; wherein... The environmental impact factor of the wind turbine is calculated according to the following formula: Where W is the environmental impact factor of the wind turbine, n is the number of environmental data, Pi is the average value of the i-th environmental data, and ai is the weight of the i-th environmental data. Obtain the pre-defined maximum and minimum extreme values ​​of environmental impact factors; The torque coefficient correction factor is determined based on the relationship between the environmental impact factor of the wind turbine, the maximum extreme value of the environmental impact factor, and the minimum extreme value of the environmental impact factor. When the environmental impact factor is less than the minimum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ1; When the environmental impact factor is greater than or equal to the minimum extreme value of the environmental impact factor, and the environmental impact factor is less than the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ2. When the environmental impact factor is greater than or equal to the maximum extreme value of the environmental impact factor, the torque coefficient correction factor is determined to be Δβ3.

7. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 6, characterized in that, After correcting the torque coefficient of the wind turbine according to the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine, the method further includes: Obtain the real-time wind power generation of the wind turbine when it is at the optimal torque coefficient; Whether to issue an early warning is determined based on the relationship between the real-time wind power generation and the preset wind power generation. If the real-time wind power generation is less than the preset wind power generation, an early warning will be issued. When the real-time wind power generation is greater than or equal to the preset wind power generation, it is determined that no warning is needed, and the real-time wind power generation of the wind turbine is monitored in real time.

8. The method for determining the optimal torque coefficient of a wind turbine generator according to claim 7, characterized in that, Real-time monitoring of the wind power generation of the wind turbine includes: The first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation of the wind turbine are obtained within a preset time. The detection time interval of the wind turbine is calculated based on the first real-time wind power generation, the second real-time wind power generation, and the third real-time wind power generation. The detection time interval of the wind turbine is calculated according to the following formula: Where T is the detection time interval of the wind turbine, k1 is the first real-time wind power generation, k2 is the second real-time wind power generation, k3 is the third real-time wind power generation, kj is the preset wind power generation, and L is the loss index in the process of calculating the detection time interval.

9. A device for determining the optimal torque coefficient of a wind turbine generator, characterized in that, The device includes: The module is used to collect the rotor torque of wind turbines at different times and obtain the torque impact data corresponding to each rotor torque. Based on each rotor torque and the corresponding torque impact data, a data processing set is constructed. The analysis module is used to perform optimization analysis on all data processing sets to obtain the optimal data processing set; The determination module is used to extract the optimal wind turbine torque and the optimal torque influence data from the optimal data processing set, and to determine the wind turbine speed when the wind turbine is at the optimal wind turbine torque. The calculation module is used to calculate the torque coefficient of the wind turbine based on the optimal rotor torque and rotor speed of the wind turbine. The correction module is used to collect environmental data of the wind turbine at different times, determine the torque coefficient correction factor based on the environmental data of the wind turbine, and correct the torque coefficient of the wind turbine based on the torque coefficient correction factor to obtain the optimal torque coefficient of the wind turbine.

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