Performance evaluation method of wind turbine generator variable pitch controller based on parameter identification

Abstract

The invention discloses a performance evaluation method for a variable pitch controller of a wind turbine generator based on parameter identification, and relates to the technical field of electric digital data processing. The parameter identification-based performance evaluation method for the variable pitch controller of the wind turbine generator comprises the following steps of: evaluating signal delay of the wind turbine generator; wind speed and rotating speed influence evaluation; adjusting parameter identification accuracy; and performance evaluation. Whether wind speed influence evaluation and rotating speed influence evaluation are carried out or not is judged through the obtained wind turbine generator signal delay evaluation coefficient, the wind speed influence evaluation coefficient and the rotating speed influence evaluation coefficient are obtained, whether parameter identification accuracy adjustment is carried out or not is judged, and finally performance evaluation of the variable pitch controller is carried out. The effect of improving the accuracy of the performance evaluation data of the wind turbine generator variable pitch controller based on the parameter identification is achieved, and the problem that the accuracy of the performance evaluation data of the wind turbine generator variable pitch controller based on the parameter identification is low in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and particularly to a performance evaluation method for a pitch controller of a wind turbine based on parameter identification. Background Art

[0002] The pitch controller of a wind turbine is one of the core components of a wind power generation system, responsible for adjusting the angle of the wind turbine blades to capture more wind energy and maintain the stable operation of the wind turbine. The performance of the pitch controller directly affects the power generation efficiency and operation stability of the wind turbine, so it is crucial to evaluate its performance. Parameter identification technology is a method of artificially determining parameters such as electrical quantities through the prediction and analysis of experimental measurement results. In a wind power generation system, motor parameter identification is of great significance, especially in high-performance applications such as vector control systems. The key to vector control technology lies in field orientation, and an important factor affecting field orientation is the motor parameters. Therefore, accurate motor parameter identification is crucial for improving the control performance of a wind power generation system.

[0003] The existing performance evaluation methods for pitch controllers mainly collect data on the actual wind speed, actual generator speed, target generator speed, and pitch command of a wind turbine online for performance evaluation.

[0004] For example, a parameter identification method and medium for an electromechanical transient frequency modulation model of a wind turbine disclosed in a patent application with a publication number of CN117556764A includes: applying a grid frequency disturbance excitation signal to a normally operating wind turbine, and collecting input and output variable data of the frequency modulation control system when the excitation signal is applied; using a niche particle swarm algorithm to optimize and solve the established electromechanical transient model of the wind turbine frequency modulation based on the input and output data, and the optimization result is the identification result of the frequency modulation control parameters.

[0005] For example, a method and system for selecting a braking resistor for a wind power generation pitch system based on load calculation disclosed in a patent application with a publication number of CN114647996A includes: obtaining the blade root load sequence of a wind turbine under various working conditions at a time interval of t through simulation; calculating the power of the pitch system under all working conditions according to the load sequence, counting the situations where the pitch motor is in the power generation mode under all working conditions, and finding the maximum number of consecutive power generation periods k of the pitch motor; calculating the sequence of consecutive power generation power values for 1 - k periods under each working condition; calculating the sequence of power values of the bus capacitor absorbing energy of the pitch system for 1 - k periods; calculating the sequence of power values of the braking resistor of the pitch system for 1 - k periods, and drawing the power curve of the braking resistor; selecting the braking resistor according to the sequence of power values of the braking resistor and the resistance value of the braking resistor determined in the design of the pitch controller.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it is found that the above technology has at least the following technical problems:

[0007] In the prior art, since wind turbine generators are usually installed in places with complex environments, such as offshore or mountainous areas, the monitoring equipment in these places may be affected by various factors such as weather, humidity, and corrosion, and the quality of the collected data is unstable, resulting in low timeliness of the performance evaluation data of the pitch controller of the wind turbine generator, and leading to the problem of low accuracy of the performance evaluation data of the pitch controller of the wind turbine generator based on parameter identification. Summary of the Invention

[0008] The embodiments of the present application provide a method for evaluating the performance of a pitch controller of a wind turbine generator based on parameter identification, which solves the problem of low accuracy of the performance evaluation data of the pitch controller of the wind turbine generator based on parameter identification in the prior art, and realizes the improvement of the accuracy of the performance evaluation data of the pitch controller of the wind turbine generator based on parameter identification.

[0009] The embodiments of the present application provide a method for evaluating the performance of a pitch controller of a wind turbine generator based on parameter identification, including the following steps: S1, obtaining a wind turbine generator signal delay evaluation coefficient based on the obtained wind turbine generator signal transmission data, and determining whether to perform a wind speed influence evaluation and a rotational speed influence evaluation based on the wind turbine generator signal delay evaluation coefficient, where the wind turbine generator signal delay evaluation coefficient is used to evaluate the wind turbine generator signal transmission delay situation; S2, when the wind turbine generator signal delay evaluation coefficient is not lower than a preset wind turbine generator transmission delay threshold, obtaining a wind speed influence evaluation coefficient by combining the obtained wind turbine generator wind speed, and obtaining a rotational speed influence evaluation coefficient by combining the obtained wind turbine generator rotational speed, where the wind speed influence evaluation coefficient is used to evaluate the influence of the wind turbine generator wind speed on the signal transmission delay, and the rotational speed influence evaluation coefficient is used to evaluate the influence of the wind turbine generator rotational speed on the signal transmission delay; S3, determining whether to perform parameter identification accuracy adjustment based on the wind speed influence evaluation coefficient and the rotational speed influence evaluation coefficient; S4, performing performance evaluation of the pitch controller based on the wind turbine generator wind speed-related data, the wind turbine generator wind speed, and the wind turbine generator rotational speed after performing parameter identification accuracy adjustment.

[0010] Furthermore, the wind turbine generator signal transmission data includes the wind wheel radius, the blade rotational angular velocity, the air humidity, the base point distance, and the wind energy utilization coefficient; the base point distance represents the distance between the preset electromagnetic signal sending position point and the preset receiving point; the wind wheel radius is obtained by a laser rangefinder; the blade rotational angular velocity is obtained by an angular velocity sensor; the air humidity is obtained by a humidity sensor; the base point distance is obtained by a GPS locator; the wind energy utilization coefficient is obtained by a power meter and an anemometer.

[0011] Further, the specific process for obtaining the wind turbine signal delay evaluation coefficient is as follows: Calculate the tip speed compliance by combining the rotor radius, the blade rotational angular velocity, and the preset tip speed obtained from the database; Calculate the air humidity interference degree value by taking the ratio of the difference between the preset maximum air humidity and the air humidity and the preset maximum air humidity obtained from the database; Calculate the signal propagation delay duration by taking the ratio of the base point distance and the speed of light obtained from the database; Calculate the propagation delay interference degree value by taking the ratio of the difference between the preset maximum propagation delay and the signal propagation delay duration and the preset maximum propagation delay obtained from the database; Calculate the wind energy utilization compliance by taking the ratio of the sum of the wind energy utilization coefficient and the preset maximum wind energy utilization coefficient obtained from the database and twice the preset maximum wind energy utilization coefficient; Calculate the tip speed influence degree by multiplying the tip speed compliance and the reference first delay evaluation weight obtained from the database; Calculate the air humidity influence degree by multiplying the air humidity interference degree value and the reference second delay evaluation weight obtained from the database; Calculate the propagation delay influence degree by multiplying the propagation delay interference degree value and the reference third delay evaluation weight obtained from the database; Calculate the wind energy utilization influence degree by multiplying the wind energy utilization compliance and the reference fourth delay evaluation weight obtained from the database; Combine the tip speed influence degree, the air humidity influence degree, the propagation delay influence degree, and the wind energy utilization influence degree to obtain the wind turbine signal delay evaluation coefficient.

[0012] Further, the specific process for determining whether to perform the wind speed influence evaluation and the rotational speed influence evaluation based on the wind turbine signal delay evaluation coefficient is as follows: Determine whether the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold obtained from the database; When the wind turbine signal delay evaluation coefficient is lower than the preset wind turbine transmission delay threshold, do not perform the wind speed influence evaluation and the rotational speed influence evaluation; When the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, perform the wind speed influence evaluation and the rotational speed influence evaluation.

[0013] Further, the limiting expression of the wind turbine signal delay evaluation coefficient is as follows:

[0014]

[0015] In the formula, XHYC represents the wind turbine signal delay evaluation coefficient of the wind turbine, S ( t ) represents the tip speed influence degree of the wind turbine at time t, t ∈ [ t 0 , t 1] , SDG ( t ) represents the air humidity influence degree of the wind turbine at time t, t0 Indicates the start time point of monitoring, t 1 Indicates the end time point of monitoring. CYG represents the propagation delay influence degree of the wind turbine generator set, and FL ( t ) Represents the wind energy utilization influence degree of the wind turbine generator set at time t. e represents the natural constant.

[0016] Furthermore, the specific acquisition process of the wind speed influence evaluation coefficient is as follows: Obtain the wind speed influence degree value through the ratio operation of the difference between the preset maximum wind speed obtained from the database and the wind speed of the wind turbine generator set to the preset maximum wind speed; Combine the wind speed influence degree value and the wind turbine generator set signal delay evaluation coefficient not lower than the preset wind turbine generator set transmission delay threshold for operation to obtain the wind speed influence evaluation coefficient.

[0017] Furthermore, the specific acquisition process of the rotational speed influence evaluation coefficient is as follows: Obtain the rotational speed influence degree value through the ratio operation of the difference between the rotational speed of the wind turbine generator set and the preset minimum rated rotational speed of the wind turbine generator set obtained from the database to the preset minimum rated rotational speed of the wind turbine generator set; Combine the rotational speed influence degree value and the wind turbine generator set signal delay evaluation coefficient not lower than the preset wind turbine generator set transmission delay threshold for operation to obtain the rotational speed influence evaluation coefficient.

[0018] Furthermore, the specific process of judging whether to adjust the parameter identification accuracy based on the wind speed influence evaluation coefficient and the rotational speed influence evaluation coefficient is as follows: Judge whether the wind speed influence degree value and the rotational speed influence degree value meet the parameter identification conditions; When the wind speed influence degree value and the rotational speed influence degree value meet the parameter identification conditions, no transmission influence adjustment is performed, otherwise transmission influence adjustment is performed; The specific process of performing transmission influence adjustment is as follows: Step 1, send a prompt to the preset personnel to increase the control signal redundancy. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise execute Step 2; Step 2, perform wind speed and rotational speed prediction. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise execute Step 3; Step 3, perform data smoothing. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise send an alarm prompt to the preset personnel; The parameter identification conditions indicate that the wind speed influence degree value is not higher than the preset average wind speed influence obtained from the database, and at the same time whether the rotational speed influence degree value is not higher than the preset average rotational speed influence obtained from the database.

[0019] Further, the specific process of performing the performance evaluation of the pitch controller is as follows: Obtain the wind turbine signal transmission data, wind turbine wind speed, and wind turbine rotational speed corresponding to the wind speed influence degree value and rotational speed influence degree value after the parameter identification accuracy is adjusted; Identify the pitch controller of the wind turbine to obtain the first-order approximation model parameters, where the first-order approximation model parameters include gain, pure delay, and first-order lag time constant; Obtain the actual performance of the pitch controller, where the actual performance of the pitch controller is represented by the integral of the absolute value of the deviation between the preset wind turbine rotational speed target value and the wind turbine rotational speed with respect to time; Obtain the expected performance of the pitch controller, where the expected performance of the pitch controller is obtained from the first-order approximation model parameters; Perform the performance evaluation of the pitch controller of the wind turbine, where the performance evaluation of the pitch controller of the wind turbine represents the ratio operation of the expected performance of the pitch controller and the actual performance of the pitch controller.

[0020] Further, after performing the performance evaluation of the pitch controller of the wind turbine, it further includes performance level classification: Perform the ratio operation of the expected performance of the pitch controller and the actual performance of the pitch controller to obtain the performance ratio result; When the performance ratio result meets Condition 1, mark the corresponding performance ratio result as performance qualified; When the performance ratio result meets Condition 2, mark the corresponding performance ratio result as performance unqualified.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. By obtaining the wind turbine signal delay evaluation coefficient to determine whether to perform the wind speed influence evaluation and rotational speed influence evaluation, obtaining the wind speed influence evaluation coefficient and rotational speed influence evaluation coefficient when the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold and determining whether to perform parameter identification accuracy adjustment, and finally performing the performance evaluation of the pitch controller, the timeliness of the performance evaluation data of the pitch controller of the wind turbine is improved, and further the accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification is improved, effectively solving the problem of low accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification in the prior art.

[0023] 2. By determining whether the wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, when the wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, no transmission influence adjustment is performed, otherwise transmission influence adjustment is performed, thereby realizing the dynamic adjustment of the performance evaluation of the pitch controller of the wind turbine, and further realizing the improvement of the reliability of the performance evaluation of the pitch controller of the wind turbine.

[0024] 3. The wind turbine signal delay evaluation coefficient is obtained by combining the tip speed influence degree, air humidity influence degree, propagation delay influence degree, and wind energy utilization influence degree. Then, the wind speed influence evaluation coefficient is obtained by performing an operation on the wind speed influence degree value and the wind turbine signal delay evaluation coefficient that is not lower than the preset wind turbine transmission delay threshold. Finally, the rotational speed influence evaluation coefficient is obtained by performing an operation on the rotational speed influence degree value and the wind turbine signal delay evaluation coefficient that is not lower than the preset wind turbine transmission delay threshold. Thus, the accuracy of the data related to the performance evaluation of the pitch controller of the wind turbine is improved, and the precise quantification of the performance evaluation of the pitch controller of the wind turbine is realized. Description of the Drawings

[0025] Figure 1 It is a flowchart of a method for evaluating the performance of a pitch controller of a wind turbine based on parameter identification provided by an embodiment of the present application;

[0026] Figure 2 It is the overall flowchart provided by an embodiment of the present application;

[0027] Figure 3 It is a statistical chart of the change of the wind speed - wind speed influence degree value of the wind turbine provided by an embodiment of the present application. Detailed Embodiments

[0028] An embodiment of the present application provides a method for evaluating the performance of a pitch controller of a wind turbine based on parameter identification, which solves the problem of low accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification in the prior art. The wind turbine signal delay evaluation coefficient is obtained from the obtained wind turbine signal transmission data. Whether to perform wind speed influence evaluation and rotational speed influence evaluation is judged based on the wind turbine signal delay evaluation coefficient. Then, when the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, the wind speed influence evaluation coefficient is obtained by combining the obtained wind speed of the wind turbine, and the rotational speed influence evaluation coefficient is obtained by combining the obtained rotational speed of the wind turbine. Then, whether to adjust the accuracy of parameter identification is judged based on the wind speed influence evaluation coefficient and the rotational speed influence evaluation coefficient. Finally, the performance of the pitch controller is evaluated based on the wind turbine wind speed - related data, the wind speed of the wind turbine, and the rotational speed of the wind turbine after adjusting the accuracy of parameter identification, realizing the improvement of the accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification.

[0029] The technical solution in the embodiment of the present application is to solve the problem of low accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification, and the overall idea is as follows:

[0030] Based on the obtained wind turbine signal delay evaluation coefficient, it is determined whether to conduct wind speed influence evaluation and rotational speed influence evaluation. When the obtained wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, the wind speed influence evaluation coefficient and rotational speed influence evaluation coefficient are obtained and it is determined whether to adjust the parameter identification accuracy. Finally, the performance evaluation of the pitch controller is carried out, achieving the effect of improving the accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification.

[0031] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0032] As Figure 1 shown, it is a flowchart of a performance evaluation method for a wind turbine pitch controller based on parameter identification provided by an embodiment of the present application. The method includes the following steps: S1, wind turbine signal delay evaluation: Based on the obtained wind turbine signal transmission data, a wind turbine signal delay evaluation coefficient is obtained. Based on the wind turbine signal delay evaluation coefficient, it is determined whether to conduct wind speed influence evaluation and rotational speed influence evaluation. The wind turbine signal delay evaluation coefficient is used to evaluate the wind turbine signal transmission delay situation; S2, wind speed and rotational speed influence evaluation: When the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, in combination with the obtained wind turbine wind speed, a wind speed influence evaluation coefficient is obtained, and in combination with the obtained wind turbine rotational speed, a rotational speed influence evaluation coefficient is obtained. The wind speed influence evaluation coefficient is used to evaluate the influence of the wind turbine wind speed on the signal transmission delay, and the rotational speed influence evaluation coefficient is used to evaluate the influence of the wind turbine rotational speed on the signal transmission delay; S3, parameter identification accuracy adjustment: Based on the wind speed influence evaluation coefficient and rotational speed influence evaluation coefficient, it is determined whether to adjust the parameter identification accuracy. The parameter identification accuracy adjustment is used to reduce the influence degree of the wind turbine wind speed and rotational speed on the signal transmission delay; S4, performance evaluation: Based on the wind turbine wind speed-related data, wind turbine wind speed, and wind turbine rotational speed after the parameter identification accuracy adjustment, the performance evaluation of the pitch controller is carried out. The performance evaluation of the pitch controller indicates whether the performance of the pitch controller meets the preset target by means of system identification method.

[0033] It should be added that the wind turbine signal transmission data includes the wind wheel radius, blade rotational angular velocity, air humidity, base point distance, and wind energy utilization coefficient; the base point distance represents the distance between the preset electromagnetic signal sending position point and the preset receiving point; the wind wheel radius is obtained by a laser rangefinder; the blade rotational angular velocity is obtained by an angular velocity sensor; the air humidity is obtained by a humidity sensor; the base point distance is obtained by a GPS locator (Global Positioning System); the wind energy utilization coefficient is obtained by a power meter and an anemometer.

[0034] In this embodiment, the wind turbine signal delay evaluation coefficient, the wind speed influence evaluation coefficient, and the rotational speed influence evaluation coefficient are interrelated. The wind turbine signal delay evaluation coefficient is mainly used to evaluate the delay of wind turbine signal transmission and is an important basis for subsequent judgment on whether to conduct wind speed and rotational speed influence evaluations. The severity of signal delay directly determines whether it is necessary to further analyze the affected conditions of wind speed and rotational speed. By comprehensively considering the influences of the wind turbine signal delay evaluation coefficient, the wind speed influence evaluation coefficient, and the rotational speed influence evaluation coefficient, the operating state and performance of the wind turbine can be judged more accurately, and the accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification is improved.

[0035] It should be understood that the wind wheel radius of the wind turbine is measured by a laser rangefinder, an angular velocity sensor is deployed at a preset position point of the blade of the wind turbine to measure the rotational angular velocity of the blade, a humidity sensor is deployed at a preset position point of the wind farm to measure the air humidity, the distance between the preset electromagnetic signal transmission position point and the preset receiving point is measured by a GPS (Global Positioning System) locator to obtain the base point distance, the output power at a preset position point of the output shaft of the wind turbine is measured by a power meter, the wind turbine wind speed at a preset position point of the output shaft of the wind turbine is measured by an anemometer, and the wind energy utilization coefficient is obtained by combining the acquired output power and the wind turbine wind speed.

[0036] Further, the specific process of obtaining the wind turbine signal delay evaluation coefficient is as follows: Calculate the tip speed compliance by combining the rotor radius, the blade rotational angular velocity, and the preset tip speed obtained from the database; the tip speed compliance is used to reflect the wind turbine rotor vibration condition; Calculate the air humidity interference degree value by taking the ratio of the difference between the preset maximum air humidity and the air humidity obtained from the database to the preset maximum air humidity; the air humidity interference degree value is used to reflect the interference degree of air humidity on signal transmission; Calculate the signal propagation delay duration by taking the ratio of the base point distance to the speed of light obtained from the database; Calculate the propagation delay interference degree value by taking the ratio of the difference between the preset maximum propagation delay and the signal propagation delay duration obtained from the database to the preset maximum propagation delay; the propagation delay interference degree value is used to reflect the interference degree of signal propagation delay on signal transmission; Calculate the wind energy utilization compliance by taking the ratio of the sum of the wind energy utilization coefficient and the preset maximum wind energy utilization coefficient obtained from the database to twice the preset maximum wind energy utilization coefficient; the wind energy utilization compliance is used to reflect the compliance of the wind turbine in utilizing wind energy; Obtain the tip speed influence degree (i.e., S(t) in the limit expression of the wind turbine signal delay evaluation coefficient) through the product operation of the tip speed compliance and the reference first delay evaluation weight obtained from the database; Obtain the air humidity influence degree (i.e., SDG(t) in the limit expression of the wind turbine signal delay evaluation coefficient) through the product operation of the air humidity interference degree value and the reference second delay evaluation weight obtained from the database; Obtain the propagation delay influence degree (i.e., CYG in the limit expression of the wind turbine signal delay evaluation coefficient) through the product operation of the propagation delay interference degree value and the reference third delay evaluation weight obtained from the database; Obtain the wind energy utilization influence degree (i.e., FL(t) in the limit expression of the wind turbine signal delay evaluation coefficient) through the product operation of the wind energy utilization compliance and the reference fourth delay evaluation weight obtained from the database; The reference first delay evaluation weight is used to evaluate the influence degree of the rotor area on the wind turbine signal delay evaluation coefficient; The reference second delay evaluation weight is used to evaluate the influence degree of air humidity on the wind turbine signal delay evaluation coefficient; The reference third delay evaluation weight is used to evaluate the influence degree of propagation delay on the wind turbine signal delay evaluation coefficient; The reference fourth delay evaluation weight is used to evaluate the influence degree of wind energy utilization on the wind turbine signal delay evaluation coefficient; Combine the tip speed influence degree, the air humidity influence degree, the propagation delay influence degree, and the wind energy utilization influence degree to obtain the wind turbine signal delay evaluation coefficient.

[0037] Among them, the limit expression of the wind turbine signal delay evaluation coefficient is as follows:

[0038]

[0039] In the formula, XHYC represents the wind turbine signal delay evaluation coefficient of the wind turbine, and S ( t ) represents the influence degree of the tip speed of the wind turbine at time t, where t ∈ [ t 0 , t 1] , SDG ( t ) represents the influence degree of the air humidity of the wind turbine at time t, and t 0 represents the start time point of monitoring, and t 1 represents the end time point of monitoring, CYG represents the propagation delay influence degree of the wind turbine, and FL ( t ) represents the influence degree of the wind energy utilization of the wind turbine at time t, and WR ( t ) represents the angular velocity of the blade rotation of the wind turbine at time t, FR represents the wind wheel radius of the wind turbine, and SD ( t ) represents the air humidity of the wind turbine at time t, JL represents the base point distance of the wind turbine, and LY ( t ) represents the wind energy utilization coefficient of the wind turbine at time t, c represents the speed of light, and S 0 represents the preset tip speed, and SD 0 represents the maximum value of the preset air humidity, and SY 0 represents the maximum value of the preset propagation delay, and FL 0 represents the maximum value of the preset wind energy utilization coefficient, and γ 1 represents the reference first delay evaluation weight, and γ 2 represents the reference second delay evaluation weight, and γ 3 represents the reference third delay evaluation weight, and γ 4 represents the reference fourth delay evaluation weight, and e represents the natural constant.

[0040] It should be added that the specific process of judging whether to conduct wind speed influence evaluation and rotational speed influence evaluation based on the wind turbine signal delay evaluation coefficient is as follows: Judge whether the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold obtained from the database; When the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, it indicates that the influence degree of the wind turbine signal transmission delay is small, and no wind speed influence evaluation and rotational speed influence evaluation are conducted; When the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, it indicates that the influence degree of the wind turbine signal transmission delay is large, and wind speed influence evaluation and rotational speed influence evaluation are conducted.

[0041] In this embodiment, the aforementioned database is a database established before the design of a performance evaluation method for a pitch controller of a wind turbine based on parameter identification provided in the embodiments of the present application, and is used to store various types of set data. The database includes, but is not limited to, wind turbine wind speed, wind turbine rotational speed, air humidity, etc. Various numerical values therein are directly set by technicians. For example, the preset maximum air humidity is represented by the maximum value of air humidity in the historical time period in the database, the preset maximum propagation delay is represented by the maximum value of propagation delay in the historical time period in the database, the preset maximum wind energy utilization coefficient is represented by the maximum value of the wind energy utilization coefficient in the historical time period in the database, the preset tip speed is represented by the average value of the wind turbine blade tip speed in the historical time period in the database, and the preset wind turbine transmission delay threshold is represented by the average value of the wind turbine signal delay evaluation coefficient in the historical time period.

[0042] Among them, in this embodiment, the reference first delay evaluation weight, the reference second delay evaluation weight, the reference third delay evaluation weight, and the reference fourth delay evaluation weight are the weights corresponding to the tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient in the database respectively. The reference first delay evaluation weight, the reference second delay evaluation weight, the reference third delay evaluation weight, and the reference fourth delay evaluation weight respectively describe the numerical values corresponding to the influence degrees of the tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient on the wind turbine signal delay evaluation coefficient, and can be directly obtained from the database during use. Their corresponding relationships are preset. For example, the tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient form a mapping set with the weights corresponding to the preset tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient in the database. Inputting the real-time tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient into the mapping set to obtain the weights corresponding to the tip speed, air humidity, electromagnetic signal propagation delay, and wind energy utilization coefficient. The mapping relationship therein can be a one-to-one or many-to-one relationship, and the value range in this embodiment is 0-1.

[0043] It should be understood that the algorithm in this embodiment combines the signal transmission data of the wind turbine to comprehensively analyze and obtain the wind turbine signal delay evaluation coefficient. The wind turbine signal transmission data in the algorithm of this embodiment does not exist independently and has mutual relevance. The size of the wind wheel radius directly affects the ability of the wind turbine to capture wind energy. The larger the wind wheel radius, the more wind energy can be captured, thereby increasing the wind energy utilization coefficient. However, when the wind energy utilization coefficient is lower, the output power of the wind turbine may be unstable, which may lead to problems such as grid voltage fluctuations and frequency offsets, thus affecting the quality of signal transmission and increasing the wind turbine signal delay evaluation coefficient. At the same wind speed, the larger the wind wheel radius, the more likely it is to cause an increase in the rotational angular velocity of the blade, but the increase in the tip angular velocity may lead to increased mechanical vibration, which will interfere with the communication line, thereby increasing the transmission delay and increasing the wind turbine signal delay evaluation coefficient. In an offshore wind farm, the greater the air humidity, the more likely it is to increase the current impedance and cause a short circuit, and it may also increase the weight and resistance of the blade, resulting in a decrease in the wind energy capture ability, thereby affecting the wind energy utilization coefficient. The longer the base point distance, the more likely it is that the wind turbine cannot respond to changes in wind speed and direction in a timely manner, thus affecting the efficiency of wind energy capture, increasing the delay time of signal transmission, and increasing the wind turbine signal delay evaluation coefficient. The parameters of the algorithm in this embodiment need to jointly consider the impact on the results; the accurate quantification of the wind turbine signal transmission delay situation is realized; and further, the accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification is improved.

[0044] Further, the specific process of obtaining the wind speed influence evaluation coefficient is as follows: The difference between the preset maximum wind speed obtained from the database and the wind speed of the wind turbine is divided by the preset maximum wind speed to obtain the wind speed influence degree value (i.e., SFY in the wind speed influence evaluation coefficient ( t ) ); The wind speed influence degree value is used to reflect the influence degree of the wind turbine wind speed affected by signal transmission delay; The wind speed influence evaluation coefficient is obtained by performing an operation on the basis of combining the wind speed influence degree value and the wind turbine signal delay evaluation coefficient not lower than the preset wind turbine transmission delay threshold.

[0045] Among them, the wind speed influence evaluation coefficient is obtained by the following method:

[0046]

[0047]

[0048] In the formula, FSPG represents the wind speed influence evaluation coefficient of the wind turbine, SFY ( t ) represents the wind speed influence degree value of the wind turbine at time t, t 0 represents the monitoring start time point, t 1Indicates the monitoring end time point, XHYC' represents the wind turbine signal delay evaluation coefficient of the wind turbine not less than the preset wind turbine transmission delay threshold, FV ( t ) Represents the wind turbine wind speed at time t of the wind turbine, SFY 0 Represents the preset maximum wind speed, and e represents the natural constant.

[0049] In this embodiment, the preset maximum wind speed is represented by the maximum value of the wind speed in the historical time period in the database.

[0050] It should be understood that the algorithm of this embodiment comprehensively analyzes the wind turbine wind speed and the wind turbine signal delay evaluation coefficient to obtain the wind speed influence evaluation coefficient. In the algorithm of this embodiment, the wind turbine wind speed and the wind turbine signal delay evaluation coefficient do not exist independently and are interrelated. Signal delay may reduce the real-time performance of wind speed data, resulting in an increase in the wind speed influence evaluation coefficient. The delayed signal may not accurately reflect the current change in wind speed, resulting in the wind turbine being unable to respond to wind speed fluctuations in a timely manner. The higher the wind turbine wind speed, the more complex the operating state of the wind turbine may be, and the higher the requirement for the stability of communication equipment. Specifically, since offshore wind farms are usually located in waters far from land, the base distance may increase, thereby interfering with data transmission, which may cause the wind speed data to not reflect the current wind speed change in real time during the transmission process, thereby reducing the real-time performance of the data, and further resulting in an increase in the wind speed influence evaluation coefficient. The parameters of the algorithm in this embodiment need to jointly consider the impact on the results.

[0051] Specifically, assume that the wind turbine wind speed FV ( t ) ranges from 10 - 15 (m / s), and the preset maximum wind speed SFY 0 is fixed at 15 (m / s). As Figure 3 shown, it is the change statistical chart of the wind turbine wind speed - wind speed influence degree value provided by the embodiment of the present application. It can be seen from Figure 3 that as the wind turbine wind speed gradually increases, the wind speed influence degree value gradually decreases, which means that the degree of interference of the wind turbine wind speed by signal transmission gradually decreases, realizing the accurate quantification of the influence of signal transmission delay on the wind turbine wind speed, and further realizing the improvement of the accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification.

[0052] Further, the specific acquisition process of the rotational speed influence evaluation coefficient is as follows: The difference between the wind turbine rotational speed and the preset minimum rated rotational speed of the wind turbine obtained from the database is divided by the preset minimum rated rotational speed of the wind turbine to obtain the rotational speed influence degree value (i.e., ZSY in the rotational speed influence evaluation coefficient ( t ));The rotational speed influence degree value is used to reflect the influence degree of the rotational speed of the wind turbine on signal transmission delay; an operation is performed by combining the rotational speed influence degree value and the wind turbine signal delay evaluation coefficient not lower than the preset wind turbine transmission delay threshold to obtain the rotational speed influence evaluation coefficient.

[0053] Among them, the rotational speed influence evaluation coefficient is obtained through the following method:

[0054]

[0055] In the formula, ZSPG represents the rotational speed influence evaluation coefficient of the wind turbine, ZSY ( t ) represents the rotational speed influence degree value of the wind turbine at time t, t 0 represents the monitoring start time point, t 1 represents the monitoring end time point, XHYC' represents the wind turbine signal delay evaluation coefficient of the wind turbine not lower than the preset wind turbine transmission delay threshold, ZS ( t ) represents the rotational speed of the wind turbine at time t, ZSY 0 represents the minimum value of the preset wind turbine rated speed, and e represents the natural constant.

[0056] In this embodiment, the minimum value of the preset wind turbine rated speed is represented by the minimum value of the wind turbine rated speed in the historical time period in the database, and the rotational speed of the wind turbine is obtained by measuring the rotational speed of the wind turbine generator with a tachometer.

[0057] It should be understood that the algorithm of this embodiment comprehensively analyzes the rotational speed of the wind turbine and the wind turbine signal delay evaluation coefficient to obtain the rotational speed influence evaluation coefficient. In the algorithm of this embodiment, the rotational speed of the wind turbine and the wind turbine signal delay evaluation coefficient do not exist independently and are interrelated. Signal delay may cause inaccurate rotational speed control of the wind turbine, resulting in inaccurate control effect. The longer the signal delay time, the greater the rotational speed fluctuation may be, affecting the stable operation of the wind turbine. When the rotational speed of the wind turbine changes, especially when the rotational speed is faster, it may cause delay in signal transmission. This is because the change in rotational speed may affect the physical properties of the signal transmission medium (such as cables, wireless channels, etc.), such as electromagnetic fields, temperature, etc., thus changing the signal transmission speed. The change in rotational speed may also cause a change in the load of the signal processor or controller, thereby affecting its processing speed and resulting in signal delay. In an offshore wind farm, the influence of signal delay on the rotational speed control of the wind turbine is particularly significant. The environmental conditions in an offshore wind farm are complex, and natural factors such as sea waves, salt spray, and lightning may interfere with signal transmission. These interferences will cause a decrease in signal quality, further increasing signal delay, thereby affecting the rotational speed of the wind turbine. The parameters of the algorithm in this embodiment need to jointly consider the influence on the result.

[0058] Specifically, assume that the range of the rotational speed influence degree value ZSY(t) is 0.6 - 1, and the range of the wind turbine signal delay evaluation coefficient XHYC' not lower than the preset wind turbine transmission delay threshold is 1.5 - 2. The time difference between the monitoring start time point and the monitoring end time point is 9 minutes. (The monitoring start time point t 0 is fixed at 10:01, and the monitoring end time point t 1 is fixed at 10:10) As shown in Table 1, it is the change statistical table of the rotational speed influence evaluation coefficient provided by the embodiment of the present application:

[0059] Table 1 Change Statistical Table of Rotational Speed Influence Evaluation Coefficient

[0060]

[0061]

[0062] As can be seen from the above table, as the rotational speed influence degree value gradually increases and the wind turbine signal delay evaluation coefficient not lower than the preset wind turbine transmission delay threshold gradually decreases, the rotational speed influence evaluation coefficient gradually decreases, indicating that the influence degree of the wind turbine rotational speed by the signal transmission delay is reduced; realizing the accurate quantification of the influence of the wind turbine rotational speed by the signal transmission delay, and further improving the accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification.

[0063] Further, the specific process of determining whether to adjust the parameter identification accuracy based on the wind speed influence evaluation coefficient and the rotational speed influence evaluation coefficient is as follows: Determine whether the wind speed influence degree value and the rotational speed influence degree value meet the parameter identification conditions; when the wind speed influence degree value and the rotational speed influence degree value meet the parameter identification conditions, no transmission influence adjustment is performed, otherwise transmission influence adjustment is performed; the specific process of performing transmission influence adjustment is as follows: Step 1, send a prompt to a preset person to increase the control signal redundancy. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise execute Step 2. Increasing the control signal redundancy is used to recover the control command through redundant information; Step 2, perform wind speed and rotational speed prediction. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise execute Step 3. Wind speed and rotational speed prediction means making an early response through the MPC (Model Predictive Control) algorithm to reduce the signal delay error; Step 3, perform data smoothing. When the monitored wind speed influence degree value and rotational speed influence degree value meet the parameter identification conditions, stop performing transmission influence adjustment, otherwise send an alarm prompt to the preset person. Data smoothing means reducing the instability of rotational speed control caused by sensor delay through the Kalman filter algorithm; the parameter identification conditions mean that the wind speed influence degree value is not higher than the preset average wind speed influence obtained from the database, and at the same time whether the rotational speed influence degree value is not higher than the preset rotational speed influence average obtained from the database.

[0064] In this embodiment, the preset average wind speed influence is represented by the average value of the wind speed influence degree values in the historical time period, and the preset average rotational speed influence is represented by the average value of the rotational speed influence degree values in the historical time period.

[0065] Specifically, when sending a signal to control the wind turbine, the same signal can be repeatedly sent multiple times to increase the probability that the receiving end successfully receives the complete signal. A check code or checksum is added to the control signal to verify the integrity of the signal at the receiving end. Through the MPC algorithm, the prediction of the dynamic changes of the wind speed and rotational speed of the wind turbine can be realized, ensuring timely response in the face of the real-time changes of the wind speed and rotational speed of the wind turbine. The Kalman filter algorithm can process process noise and observation noise, and balance the influence of these two noises on the state estimation by adjusting the corresponding covariance matrix, realizing the improvement of the accuracy of the performance evaluation data of the pitch controller of the wind turbine based on parameter identification.

[0066] Further, the specific process of performing the performance evaluation of the pitch controller is as follows: Obtain the wind turbine signal transmission data, wind turbine wind speed, and wind turbine rotational speed corresponding to the adjusted wind speed influence degree value and rotational speed influence degree value after parameter identification accuracy adjustment; Identify the wind turbine pitch controller through the system identification method (least squares method) to obtain the first-order approximation model parameters, where the first-order approximation model parameters include gain, pure delay, and first-order lag time constant; Obtain the actual performance of the pitch controller, and the actual performance of the pitch controller is represented by the integral of the absolute value of the deviation between the preset wind turbine rotational speed target value and the wind turbine rotational speed over time; Obtain the expected performance of the pitch controller, and the expected performance of the pitch controller is obtained from the first-order approximation model parameters; Perform the performance evaluation of the wind turbine pitch controller, and the performance evaluation of the wind turbine pitch controller means performing a ratio operation on the expected performance and the actual performance of the pitch controller.

[0067] It should be added that after performing the performance evaluation of the wind turbine pitch controller, it also includes performance level classification: Perform a ratio operation on the expected performance and the actual performance of the pitch controller to obtain the performance ratio result; When the performance ratio result meets Condition 1, mark the corresponding performance ratio result as performance qualified; When the performance ratio result meets Condition 2, mark the corresponding performance ratio result as performance unqualified; Condition 1 means that the performance ratio result is within the reference qualified range; Condition 2 means that the performance ratio result is within the reference unqualified range.

[0068] In this embodiment, the obtained first-order approximation model parameters can describe the dynamic characteristics of the pitch controller. The actual performance of the pitch controller is represented by the integral of the absolute value of the deviation between the preset wind turbine rotational speed target value and the wind turbine rotational speed over time. This integral value reflects the ability of the pitch controller to track the rotational speed target value. Use the first-order approximation model parameters to calculate the expected performance of the pitch controller, and calculate the integral of the deviation between the simulated response and the rotational speed target value. Perform a ratio operation on the expected performance and the actual performance of the pitch controller to obtain the performance ratio result. The closer the performance ratio result is to 1, the better the performance. In this embodiment, the reference qualified range is set to the performance ratio result being greater than 0.5 and less than or equal to 1, and the reference unqualified range is set to the performance ratio result being greater than 0 and less than or equal to 0.5. Through the performance evaluation of the wind turbine pitch controller, it is ensured that the wind turbine can adapt to different wind speed and rotational speed conditions and achieve efficient and stable operation; The accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification is improved.

[0069] In summary, in the embodiments of the present application, it is determined whether to perform wind speed influence evaluation and rotational speed influence evaluation by obtaining the wind turbine signal delay evaluation coefficient. When the obtained wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, the wind speed influence evaluation coefficient and the rotational speed influence evaluation coefficient are obtained and it is determined whether to adjust the parameter identification accuracy. Finally, the performance evaluation of the pitch controller is performed, thereby improving the timeliness of the performance evaluation data of the wind turbine pitch controller, and further improving the accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification, effectively solving the problem of low accuracy of the performance evaluation data of the wind turbine pitch controller based on parameter identification in the prior art.

[0070] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce a device for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0072] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for realizing the functions in the processFigure 1 one or more processes and / or blocks Figure 1 steps of the functions specified in one or more blocks

[0074] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0075] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A performance evaluation method for a wind turbine pitch controller based on parameter identification, characterized in that: The following steps are involved: S1, obtaining a wind turbine signal delay evaluation coefficient based on the acquired wind turbine signal transmission data, and judging whether to perform wind speed impact evaluation and rotation speed impact evaluation based on the wind turbine signal delay evaluation coefficient, wherein the wind turbine signal delay evaluation coefficient is used to evaluate the wind turbine signal transmission delay; S2, when the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, the wind speed impact evaluation coefficient is obtained in combination with the obtained wind speed of the wind turbine, and the speed impact evaluation coefficient is obtained in combination with the obtained wind turbine rotation speed, the wind speed impact evaluation coefficient is used to evaluate the influence of the wind speed of the wind turbine on the signal transmission delay, and the speed impact evaluation coefficient is used to evaluate the influence of the signal transmission delay on the speed of the wind turbine; S3, judging whether to adjust the parameter identification accuracy based on the wind speed impact assessment coefficient and the rotation speed impact assessment coefficient; S4, evaluating the performance of the pitch controller based on the wind turbine wind speed related data after the parameter identification accuracy adjustment and the wind turbine wind speed and wind turbine rotation speed.

2. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The wind turbine signal transmission data includes the rotor radius, blade rotation angular velocity, air humidity, base point distance and wind energy utilization coefficient; The base point distance represents the distance between the preset sending position point of the electromagnetic signal and the preset receiving point; The wind wheel radius is obtained by a laser rangefinder; The blade rotation angular velocity is obtained by an angular velocity sensor; The air humidity is obtained by a humidity sensor; The base point distance is obtained by a GPS locator; The wind energy utilization coefficient is obtained through a power meter and an anemometer.

3. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 2, characterized in that: The specific process of obtaining the wind turbine signal delay evaluation coefficient is as follows: The blade tip speed compliance is obtained by combining the wind wheel radius, the blade rotation angular velocity and the preset blade tip speed obtained from the database; The air humidity interference degree value is obtained by performing a ratio operation between the preset air humidity maximum value obtained from the database and the difference between the air humidity and the preset air humidity maximum value; The signal propagation delay time is obtained by performing a ratio operation based on the base point distance and the speed of light obtained from the database; The propagation delay interference degree value is obtained by performing a ratio operation between the difference between the preset maximum propagation delay value obtained from the database and the signal propagation delay time length and the preset maximum propagation delay value; The wind energy utilization compliance is obtained by performing a ratio operation on the sum of the wind energy utilization coefficient and the preset maximum wind energy utilization coefficient value obtained from the database and twice the preset maximum wind energy utilization coefficient value; The influence degree of the blade tip speed is obtained by multiplying the blade tip speed compliance degree and the reference first delay evaluation weight obtained from the database; The air humidity influence degree is obtained by multiplying the air humidity interference degree value and the reference second delay evaluation weight obtained from the database; The propagation delay influence degree is obtained by performing a product operation on the propagation delay interference degree value and the reference third delay evaluation weight obtained from the database; The wind energy utilization impact is obtained by multiplying the wind energy utilization compliance and the reference fourth delay evaluation weight obtained from the database; The wind turbine signal delay evaluation coefficient is obtained by combining the influence of blade tip speed, air humidity, propagation delay and wind energy utilization.

4. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The specific process of judging whether to perform wind speed impact assessment and rotation speed impact assessment based on the wind turbine signal delay assessment coefficient is as follows: Determine whether the wind turbine signal delay evaluation coefficient is not lower than a preset wind turbine transmission delay threshold obtained from a database; When the wind turbine signal delay evaluation coefficient is lower than the preset wind turbine transmission delay threshold, the wind speed impact evaluation and rotation speed impact evaluation are not performed; When the wind turbine signal delay evaluation coefficient is not lower than the preset wind turbine transmission delay threshold, wind speed impact evaluation and rotation speed impact evaluation are performed.

5. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 3, characterized in that: The limiting expression of the wind turbine signal delay evaluation coefficient is as follows: Where XHYC represents the wind turbine signal delay evaluation coefficient of the wind turbine, S ( t ) Represents the influence of the blade tip speed of the wind turbine at time t, t∈ [ t0,t 1] , SDG ( t ) represents the air humidity influence of the wind turbine at time t, t0 represents the monitoring start time point, t1 represents the monitoring end time point, CYG represents the propagation delay influence of the wind turbine, FL ( t ) It represents the influence of wind energy utilization of wind turbine at time t, and e represents the natural constant.

6. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The specific process of obtaining the wind speed impact assessment coefficient is as follows: The wind speed influence degree value is obtained by performing a ratio calculation between the difference between the preset maximum wind speed value obtained from the database and the wind speed of the wind turbine generator set and the preset maximum wind speed value; The wind speed impact assessment coefficient is obtained by combining the wind speed impact degree value and a wind turbine signal delay assessment coefficient that is not less than a preset wind turbine transmission delay threshold.

7. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The specific process of obtaining the speed impact assessment coefficient is as follows: The speed influence degree value is obtained by performing a ratio operation between the difference between the speed of the wind turbine set and the preset minimum value of the rated speed of the wind turbine set obtained from the database and the preset minimum value of the rated speed of the wind turbine set; The speed impact assessment coefficient is obtained by performing calculations based on the speed impact degree value and a wind turbine signal delay assessment coefficient that is not less than a preset wind turbine transmission delay threshold.

8. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The specific process of judging whether to adjust the parameter identification accuracy based on the wind speed impact assessment coefficient and the rotation speed impact assessment coefficient is as follows: Determine whether the wind speed influence degree value and the rotation speed influence degree value meet the parameter identification conditions; When the wind speed influence degree value and the rotation speed influence degree value meet the parameter identification conditions, no transmission influence adjustment is performed, otherwise, transmission influence adjustment is performed; The specific process of adjusting the transmission impact is as follows: Step 1: Send a reminder to the preset personnel to increase the control signal redundancy. When the monitored wind speed influence degree value and rotation speed influence degree value meet the parameter identification conditions, stop the transmission influence adjustment, otherwise execute step 2; Step 2: predict the wind speed and rotation speed. When the monitored wind speed influence degree value and rotation speed influence degree value meet the parameter identification conditions, stop adjusting the transmission influence. Otherwise, execute step 3. Step 3: Perform data smoothing. When the monitored wind speed influence degree value and rotation speed influence degree value meet the parameter identification conditions, stop adjusting the transmission influence. Otherwise, send an alarm prompt to the preset personnel. The parameter identification condition indicates whether the wind speed influence degree value is not higher than the preset wind speed influence average value obtained from the database, and whether the rotation speed influence degree value is not higher than the preset rotation speed influence average value obtained from the database.

9. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 1, characterized in that: The specific process of performing the performance evaluation of the pitch controller is as follows: Obtain wind turbine signal transmission data, wind turbine wind speed, and wind turbine speed corresponding to the wind speed influence degree value and the speed influence degree value after adjusting the parameter identification accuracy; Identify the wind turbine pitch controller to obtain first-order approximate model parameters, wherein the first-order approximate model parameters include gain, pure delay and first-order lag time constant; Acquire actual performance of the pitch controller, where the actual performance of the pitch controller is represented by an integral of an absolute value of a deviation between a preset wind turbine speed target value and the wind turbine speed over time; Obtaining expected performance of a pitch controller, wherein the expected performance of the pitch controller is obtained through first-order approximate model parameters; A performance evaluation of a wind turbine pitch controller is performed, wherein the performance evaluation of the wind turbine pitch controller represents a ratio operation between an expected performance of the pitch controller and an actual performance of the pitch controller.

10. A performance evaluation method for a wind turbine pitch controller based on parameter identification as claimed in claim 9, characterized in that: The wind turbine pitch controller performance evaluation is described, and the performance level classification is also included afterwards: Performing a ratio operation on the expected performance of the pitch controller and the actual performance of the pitch controller to obtain a performance ratio result; When the performance ratio result meets condition 1, the corresponding performance ratio result is marked as qualified performance; When the performance ratio result meets condition 2, the corresponding performance ratio result is marked as unqualified.

Images