Wind power generation method and system based on intelligent variable pitch control

Abstract

The application relates to the technical field of wind power generation, and relates to a wind power generation method and system based on intelligent variable-pitch control, which comprises the following steps: confirming a wind turbine and a wind force regulating mechanism, obtaining multiple sets of historical data, extracting multiple historical wind speeds and multiple historical wind directions from the multiple sets of historical data, calculating wind speed stability according to the multiple historical wind speeds, confirming wind direction concentration based on the multiple historical wind directions, confirming wind energy conversion efficiency based on a wind blade, historical wind speed, historical main shaft rotating speed and historical power generation, obtaining a current wind speed by using a wind speed sensor, obtaining a current pitch angle, a current rotating speed and power generation, confirming a force influence index based on the wind blade and a force sensor, confirming a temperature influence index based on a temperature sensor and the main shaft, obtaining a target pitch angle, and completing intelligent variable-pitch control based on the target pitch angle and a variable-pitch device. The application can improve the intelligent degree of variable-pitch of the wind turbine, and further improve the power generation efficiency of the wind turbine.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, and in particular to a wind power generation method and system based on intelligent pitch control. Background Technology

[0002] With the development of the energy industry, wind turbines, as the main equipment for wind power generation, rely heavily on the ability of wind turbine blades to absorb and convert wind energy. To achieve efficient utilization of wind energy, wind turbines are typically equipped with pitch control devices to adjust the pitch angle of the blades according to changes in wind speed, thereby maintaining optimal aerodynamic performance.

[0003] Currently, most common pitch control methods are based on fixed models or preset rules, and usually only consider single variables such as current wind speed or spindle speed.

[0004] While the above methods can achieve pitch control of wind turbines, in actual operation, wind conditions are often highly uncertain and unstable. Traditional pitch control methods are difficult to achieve precise adjustment of the pitch angle in dynamic environments. They ignore the impact of wind speed fluctuations, wind direction changes, and equipment operating conditions (such as blade stress and main shaft temperature) on system operation, resulting in reduced wind energy utilization. Key components such as blades and main shafts are subjected to non-uniform loads, which accelerates equipment fatigue damage and affects the stable operation of the system. Therefore, how to improve the intelligence of wind turbine pitch control and thus improve the power generation efficiency of wind turbines has become an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a wind power generation method based on intelligent pitch control and a computer-readable storage medium. Its main purpose is to improve the intelligence level of wind turbine pitch control, thereby improving the power generation efficiency of wind turbines.

[0006] To achieve the above objectives, the present invention provides a wind power generation method based on intelligent pitch control, comprising: The wind turbine and wind control mechanism were identified. The wind control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. Acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical spindle speed, and historical power generation. Multiple historical wind speeds and multiple historical wind directions were extracted from multiple sets of historical data; Wind speed stability is calculated based on multiple historical wind speeds, and wind direction concentration is confirmed based on multiple historical wind directions. The wind energy conversion efficiency was determined based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The current wind speed, current paddle pitch angle, current rotation speed, and power generation are obtained using a wind speed sensor. The real-time wind energy conversion efficiency is determined based on the wind turbine blades, current wind speed, current rotation speed, and power generation. The force influence index was determined based on the wind turbine blades and force sensors, and the temperature influence index was determined based on the temperature sensors and the main shaft. By inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into the pre-built intelligent pitch model, the target pitch angle can be obtained. Intelligent pitch control is achieved based on the target pitch angle and the pitch control device.

[0007] Optionally, the formula for calculating wind speed stability is as follows:

[0008] in, Indicates wind speed stability. The number of historical data points in multiple sets of historical data. This indicates the first of multiple historical wind speeds. A historical wind speed.

[0009] Optionally, the determination of wind direction concentration based on multiple historical wind directions includes: Perform the following operation for each of the multiple historical wind directions: The historical wind direction is converted into radian value to obtain the wind direction radian value; Summarize the wind direction radian values ​​to obtain multiple wind direction radian values; Calculate wind direction concentration based on multiple wind direction radian values.

[0010] Optionally, the step of determining wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation includes: To confirm the blade radius of the wind turbine, perform the following operation for each set of historical data from multiple sets of data: The tip speed ratio is calculated based on historical wind speed, historical spindle speed, and blade radius from historical data. The power coefficient is calculated based on historical power generation, historical wind speed, blade radius, and tip speed ratio from historical data. The tip speed ratios are summarized to obtain multiple tip speed ratios. Based on these multiple tip speed ratios, the average tip speed ratio is determined. The average tip speed ratio is the average of the multiple tip speed ratios. The power coefficients are summarized to obtain multiple power coefficients. The average power coefficient is determined based on the multiple power coefficients. The average power coefficient is the average of the multiple power coefficients. Wind energy conversion efficiency is calculated based on the average tip speed ratio and average power coefficient.

[0011] Optionally, the determination of the force influence index based on the wind turbine blades and force sensors includes: Obtain multiple historical stress data points for wind turbine blades, including historical axial stress, historical radial stress, and historical bending moment. Multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments were extracted from multiple historical stress data. The weights of axial stress, radial stress, and bending moment are determined based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments. The force influence index is determined based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight.

[0012] Optionally, the step of determining the axial stress weight, radial stress weight, and bending moment weight based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments includes: The standard deviation of axial stress is calculated based on multiple historical axial stresses. The standard deviation of radial stress was determined based on multiple historical radial stresses, and the standard deviation of bending moment was determined based on multiple historical bending moments. The axial stress weight, radial stress weight, and bending moment weight are calculated based on the standard deviation of axial stress, radial stress, and bending moment.

[0013] Optionally, the determination of the force influence index based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight includes: Obtain the allowable stress data of wind turbine blades, which includes: allowable axial stress, allowable radial stress and allowable bending moment; Force sensors are used to monitor the stress on wind turbine blades and obtain stress data, which includes: current axial stress, current radial stress and current bending moment; The stress influence index is calculated based on allowable axial stress, allowable radial stress, allowable bending moment, current axial stress, current radial stress, current bending moment, axial stress weight, radial stress weight, and bending moment weight.

[0014] Optionally, the determination of the temperature influence index based on the temperature sensor and the spindle includes: The spindle temperature is obtained by using a temperature sensor to monitor the spindle temperature. Calculate the temperature effect index based on the spindle temperature.

[0015] Optionally, the intelligent pitch model is as follows:

[0016] in, This represents the intelligent pitch model. Indicates the effect of temperature. Indicates wind energy conversion efficiency. Indicates wind direction concentration. Indicates the current pitch angle. Indicates real-time wind energy conversion efficiency. Indicates the force influence index. Compared to the preset maximum pitch angle, Indicates the effect of temperature. It is the hyperbolic tangent function.

[0017] To achieve the above objectives, the present invention also provides a wind power generation system based on intelligent pitch control, comprising: The basic equipment acquisition module is used to identify the wind turbine and wind power control mechanism. The wind power control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. The historical data analysis module is used to acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical main shaft speed, and historical power generation. It extracts multiple historical wind speeds and multiple historical wind directions from multiple sets of historical data, calculates wind speed stability based on multiple historical wind speeds, confirms wind direction concentration based on multiple historical wind directions, and confirms wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The real-time data monitoring module is used to obtain the current wind speed, current blade pitch angle, current rotation speed and power generation using a wind speed sensor. Based on the wind turbine blades, current wind speed, current rotation speed and power generation, it determines the real-time wind energy conversion efficiency; based on the wind turbine blades and force sensor, it determines the force influence index; and based on the temperature sensor and main shaft, it determines the temperature influence index. The intelligent pitch control module is used to input wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index and temperature influence index into a pre-built intelligent pitch model to obtain the target pitch angle, and complete intelligent pitch control based on the target pitch angle and the pitch control device.

[0018] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; and The processor executes the instructions stored in the memory to implement the wind power generation method based on intelligent pitch control described above.

[0019] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the wind power generation method based on intelligent pitch control described above.

[0020] To address the problems described in the background art, this invention identifies a wind turbine and a wind power control mechanism. The wind power control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. This invention, by pre-identifying a wind power control mechanism integrating wind speed, force, and temperature sensors, facilitates the subsequent acquisition of wind speed, wind turbine blade force data, and temperature. Pre-identifying a wind turbine integrating wind turbine blades, a pitch control device, and a main shaft facilitates subsequent monitoring of wind turbine blade force data and main shaft temperature using a wind power monitoring mechanism. It also facilitates real-time adjustment of the pitch angle using the pitch control device, improving the intelligence of the wind turbine pitch control and enabling the acquisition of multiple sets of historical data. The data includes historical wind speed, historical wind direction, historical main shaft speed, and historical power generation. It is evident that this embodiment of the invention obtains historical wind speed, historical wind direction, historical main shaft speed, and historical power generation. This historical data reflects relevant data from the wind turbine's historical operation. Analyzing this historical data can effectively assess historical operating conditions, thereby calculating wind speed stability, wind direction concentration, and wind energy conversion efficiency. Multiple historical wind speeds and directions are extracted from multiple sets of historical data. Wind speed stability is calculated based on these multiple historical wind speeds, and wind direction concentration is confirmed based on these multiple historical wind directions. Therefore, this embodiment of the invention extracts multiple historical wind speeds and directions from multiple sets of historical data. Since multiple historical wind speeds and directions can reflect... The system reflects the overall wind level in the area where the wind turbine is installed, and calculates wind speed stability and wind direction concentration based on multiple historical wind speeds and directions. This facilitates the subsequent calculation of the target blade pitch angle. The wind energy conversion efficiency is determined based on the wind turbine blades, historical wind speed, historical shaft speed, and historical power generation. Therefore, this embodiment calculates the average wind energy conversion efficiency of the wind turbine over its historical operation, facilitating a comparison between the real-time wind energy conversion efficiency and the actual wind energy conversion efficiency. This allows for precise adjustment of the blade pitch angle based on the difference between the real-time and actual wind energy conversion efficiency. The system uses a wind speed sensor to obtain the current wind speed, current blade pitch angle, current shaft speed, and power generation. Thus, this embodiment obtains the current wind speed, current blade pitch angle, and current wind direction by implementing the acquisition of these parameters. The power generation capacity facilitates subsequent calculations of wind energy conversion efficiency and target blade pitch angle. Based on the wind turbine blades, current wind speed, current rotational speed, and power generation capacity, the real-time wind energy conversion efficiency is determined. This embodiment of the invention calculates the real-time wind energy conversion efficiency and compares it with the average wind turbine operating state, thereby improving the intelligence of the wind turbine pitch control. Based on the wind turbine blades and force sensors, the force influence index is determined; based on temperature sensors and the main shaft, the temperature influence index is determined. This embodiment of the invention utilizes force sensors to obtain real-time force data on the wind turbine blades and then determines the force influence index; and uses temperature sensors to obtain real-time surface temperature of the main shaft and then calculates the temperature influence index.To facilitate subsequent calculation of the pitch angle, wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index are input into a pre-constructed intelligent pitch model to obtain the target pitch angle. It is evident that this embodiment of the invention improves the intelligence level of wind turbine pitch control by calculating the target pitch angle through a pre-constructed intelligent pitch model. Intelligent pitch control is completed based on the target pitch angle and the pitch device. Furthermore, the intelligent pitch model described in this embodiment intelligently calculates the target pitch angle by fitting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index. Based on the precise pitch angle calculated by the model, accurate intelligent pitch control is achieved. This invention improves the intelligence level of wind turbine pitch control, thereby increasing wind turbine power generation efficiency. Therefore, this invention can improve the intelligence level of wind turbine pitch control, thus improving wind turbine power generation efficiency. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a wind power generation method based on intelligent pitch control, provided in an embodiment of the present invention. Figure 2 A functional block diagram of a wind power generation system based on intelligent pitch control provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the wind power generation method based on intelligent pitch control, according to an embodiment of the present invention.

[0022] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0023] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] This application provides a wind power generation method based on intelligent pitch control. The executing entity of the wind power generation method based on intelligent pitch control includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the wind power generation method based on intelligent pitch control can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0026] Reference Figure 1 The diagram shown is a flowchart illustrating a wind power generation method based on intelligent pitch control according to an embodiment of the present invention. In this embodiment, the wind power generation method based on intelligent pitch control includes: S1. Identify the wind turbine and wind control mechanism, wherein the wind control mechanism includes: wind speed sensor, force sensor and temperature sensor, and the wind turbine includes: wind turbine blades, pitch control device and main shaft.

[0027] It should be explained that a wind turbine is a type of wind power generator. The wind control mechanism is a device that integrates a wind speed sensor, a force sensor, and a temperature sensor to obtain real-time information on wind speed, the stress state of the wind turbine blades, and the temperature of the main shaft. The wind speed sensor is an ultrasonic wind speed and direction sensor used to detect changes in external wind speed in real time and provide wind speed information. The wind speed sensor is pre-installed on the wind turbine hub. Optionally, the Fengtu FT-WQX2 ultrasonic wind speed and direction meter can be used as the wind speed sensor. A force sensor is a multi-component sensor, bolted between the flange at the root of the wind turbine blade and the wind turbine hub. It monitors three components of wind force: 1. The component of stress along the length of the blade (i.e., the blade axis direction), i.e., tensile or compressive stress; 2. The component of stress on the blade cross-section, i.e., radial stress; 3. The component of stress at the blade root, causing bending at the blade root cross-section, i.e., bending moment. Optionally, an HBM MCS10 force sensor can be used. A temperature sensor measures the surface temperature of the main shaft and is pre-installed on the wind turbine's main shaft. A wind turbine blade is a blade used in wind turbine generators. A pitch control device adjusts the angle between the wind turbine blade and the wind direction. The main shaft is the core component in a wind turbine generator that transmits torque.

[0028] S2. Acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical spindle speed, and historical power generation.

[0029] It should be explained that historical data refers to data recorded during the operation of the wind turbine over a historical period, and includes: historical wind speed, historical wind direction, historical shaft speed, and historical power generation. Historical wind speed refers to the wind speed monitored and recorded by the wind speed sensor during the operation of the wind turbine over a past period. Historical wind direction refers to the wind direction monitored and recorded by the wind speed sensor during the operation of the wind turbine over a past period. Historical power generation refers to the power generated by the wind turbine during its operation over a past period. Optionally, the past period is the past 10 days. The historical wind speed, historical wind direction, historical shaft speed, and historical power generation are all obtained from the wind turbine's operation logs.

[0030] Understandably, historical wind direction is collected by anemometers pre-installed on the wind turbine hub and recorded in the wind turbine's operating log. The wind direction angle collected by the anemometers is recorded based on a pre-constructed polar coordinate system. This polar coordinate system has the wind turbine's center of gravity as its pole, with the direction from due south to due north as the positive polar axis, and the polar angle is measured counterclockwise from the polar axis. For example, if the collected wind is due west, then the wind direction is 90°.

[0031] S3. Extract multiple historical wind speeds and multiple historical wind directions from multiple sets of historical data, calculate wind speed stability based on multiple historical wind speeds, and confirm wind direction concentration based on multiple historical wind directions.

[0032] For example, if multiple sets of historical data are: the first set (15m / s, 60°, 15rpm, 1.5MW), the second set (20m / s, 30°, 18rpm, 1.3MW), the third set (25m / s, 90°, 16rpm, 1.2MW), and the fourth set (30m / s, 110°, 20rpm, 1.5MW), then after extracting multiple historical wind speeds and multiple historical wind directions from multiple sets of historical data, multiple historical wind speeds (15m / s, 20m / s, 25m / s, 30m / s) and multiple historical wind directions (60°, 30°, 90°, 110°) are obtained.

[0033] In detail, the formula for calculating wind speed stability is as follows:

[0034] in, Indicates wind speed stability. The number of historical data points in multiple sets of historical data. This indicates the first of multiple historical wind speeds. A historical wind speed.

[0035] It should be explained that wind speed stability reflects the degree of wind speed fluctuation; the greater the wind speed stability, the smaller the degree of wind speed fluctuation.

[0036] Specifically, the determination of wind direction concentration based on multiple historical wind directions includes: Perform the following operation for each of the multiple historical wind directions: The historical wind direction is converted into radian value to obtain the wind direction radian value; Summarize the wind direction radian values ​​to obtain multiple wind direction radian values; The wind direction concentration is calculated based on multiple wind direction radian values, using the following formula:

[0037] in, Indicates wind direction concentration. Represents the first of multiple wind direction radian values. One wind direction arc value, Represents the cosine function. This represents the sine function.

[0038] It should be explained that converting historical wind direction to radians means converting the wind direction value, which is expressed in degrees (°), into a value expressed in radians (rad). The wind direction radian value refers to the historical wind direction expressed in radians (rad). The wind direction concentration reflects the consistency of multiple historical wind directions. The greater the wind direction concentration, the higher the consistency of multiple historical wind directions.

[0039] For example, if the historical wind direction is 30°, then the wind direction in radians obtained after converting the historical wind direction to radians is [value missing]. .

[0040] S4. Based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation, the wind energy conversion efficiency is determined.

[0041] Specifically, the determination of wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation includes: To confirm the blade radius of the wind turbine, perform the following operation for each set of historical data from multiple sets of data: The tip speed ratio is calculated based on historical wind speed, historical spindle speed, and blade radius from historical data. The calculation formula is shown below:

[0042] in, Indicates the tip speed ratio. Indicates the historical spindle speed. Indicates the blade radius. Indicates historical wind speed; The power coefficient is calculated based on historical power generation, historical wind speed, blade radius, and tip speed ratio from historical data. The calculation formula is shown below:

[0043] in, Indicates power coefficient, Indicates historical power generation. The preset air density; The tip speed ratios are summarized to obtain multiple tip speed ratios. Based on these multiple tip speed ratios, the average tip speed ratio is determined. The average tip speed ratio is the average of the multiple tip speed ratios. The power coefficients are summarized to obtain multiple power coefficients. The average power coefficient is determined based on the multiple power coefficients. The average power coefficient is the average of the multiple power coefficients. The wind energy conversion efficiency is calculated based on the average tip speed ratio and average power coefficient, using the following formula:

[0044] in, Indicates wind energy conversion efficiency. Indicates average power. This indicates the average tip speed ratio.

[0045] It should be explained that blade radius refers to the radius of the wind turbine blade, and tip speed ratio refers to the ratio of the linear velocity of the blade tip to the wind speed blowing towards the blade. Wind energy conversion efficiency reflects the ability of a wind turbine to effectively convert wind energy into electrical energy; the higher the wind energy conversion efficiency, the greater the ability of the wind turbine to effectively convert wind energy into electrical energy.

[0046] Understandably, this embodiment of the invention calculates wind energy conversion efficiency using the average tip speed ratio and average power coefficient, thereby normalizing the wind turbine output capacity under different historical operating conditions and effectively evaluating the aerodynamic design level, operational control performance, and power response capability of the wind turbine unit. Air density is... .

[0047] S5. Use a wind speed sensor to obtain the current wind speed, current paddle pitch angle, current rotation speed, and power generation.

[0048] It should be explained that obtaining the current wind speed using a wind speed sensor refers to monitoring the wind speed at the wind turbine hub using a wind speed sensor pre-installed on the hub. This technology is existing and will not be elaborated upon here. The current blade pitch angle refers to the rotation angle of the wind turbine blades relative to the wind direction during current operation. The current rotational speed refers to the rotational speed of the main shaft during current operation. The power generation refers to the actual electrical power output by the wind turbine during current operation. All of these parameters are read from the wind turbine's control system.

[0049] S6. Based on the wind turbine blades, current wind speed, current rotation speed, and power generation, the real-time wind energy conversion efficiency is determined; based on the wind turbine blades and force sensors, the force influence index is determined; and based on the temperature sensors and main shaft, the temperature influence index is determined.

[0050] It should be understood that the method for determining real-time wind energy conversion efficiency based on wind turbine blades, current wind speed, current rotation speed, and power generation is the same as the method for determining wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft rotation speed, and historical power generation, and will not be repeated here.

[0051] Specifically, the determination of the force influence index based on wind turbine blades and force sensors includes: Obtain multiple historical stress data points for wind turbine blades, including historical axial stress, historical radial stress, and historical bending moment. Multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments were extracted from multiple historical stress data. The weights of axial stress, radial stress, and bending moment are determined based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments. The force influence index is determined based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight.

[0052] It should be explained that historical stress data refers to the stress conditions recorded during the historical operation of the wind turbine, and includes historical axial stress, historical radial stress, and historical bending moment. Historical axial stress refers to the tensile or compressive stress generated when wind force acts on the wind turbine blades during historical operation. It is mainly generated by the thrust of the wind transmitted along the blades and reflects the longitudinal stress state of the blades. Historical radial stress refers to the radial stress generated when wind force acts on the wind turbine blades during historical operation. It is mainly caused by centrifugal force and crosswind load generated during rotation and is used to assess the lateral stress and rotational stability of the blades. Historical bending moment refers to the bending moment generated when wind force acts on the wind turbine blades during historical operation. It reflects the lever arm effect caused by uneven distribution of wind pressure along the blade length and is an important parameter for judging blade fatigue damage and structural stability. The historical axial stress, historical radial stress, and historical bending moment are all monitored, recorded, and stored by force sensors pre-installed between the root flange and the hub of the wind turbine blades. Since all wind loads (thrust, shear force, bending moment, etc.) experienced by wind turbine blades during operation are transmitted along the blade structure to the root flange, and then through the hub to the main shaft, the connection area between the root flange of the wind turbine blade and the hub is the concentrated area of ​​stress on the entire wind turbine. Therefore, force sensors are installed in the connection area between the root flange of the wind turbine blade and the hub to monitor and record the stress condition of the wind turbine blade.

[0053] For example, if multiple sets of historical stress data are: the first set (2 MPa, 3 MPa, 4 N·m), the second set (5 MPa, 5 MPa, 7 N·m), the third set (1 MPa, 3 MPa, 4 N·m), and the fourth set (2 MPa, 7 MPa, 9 N·m), then after extracting multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments from multiple sets of historical stress data, multiple historical axial stresses are obtained as (2 MPa, 5 MPa, 1 MPa, 2 MPa), multiple historical radial stresses are obtained as (3 MPa, 5 MPa, 3 MPa, 7 MPa), and multiple historical bending moments are obtained as (4 N·m, 7 N·m, 4 N·m, 9 N·m).

[0054] Specifically, the determination of axial stress weights, radial stress weights, and bending moment weights based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments includes: The standard deviation of axial stress is calculated based on multiple historical axial stresses, using the following formula:

[0055] in, Indicates the standard deviation of axial stress. This refers to the number of historical force data points within a set of historical force data. This indicates the first of multiple historical force data. One axial stress; The standard deviation of radial stress was determined based on multiple historical radial stresses, and the standard deviation of bending moment was determined based on multiple historical bending moments. The axial stress weight, radial stress weight, and bending moment weight are calculated based on the standard deviation of axial stress, radial stress, and bending moment.

[0056] In detail, the formula for calculating the axial stress weight is as follows:

[0057] in, Indicates the axial stress weight. Indicates the standard deviation of radial stress. Indicates the standard deviation of bending moment; In detail, the formula for calculating the radial stress weight is as follows:

[0058] in, Indicates radial stress weight; In detail, the formula for calculating the bending moment weight is as follows:

[0059] in, This represents the bending moment weight.

[0060] It should be explained that the standard deviation of axial stress reflects the degree of dispersion of multiple historical axial stress values. The larger the standard deviation of axial stress, the greater the dispersion of multiple historical axial stress values. The standard deviation of radial stress reflects the dispersion of multiple historical radial stress values; a larger standard deviation of radial stress indicates greater dispersion. The standard deviation of bending moment reflects the dispersion of multiple historical bending moment values; a larger standard deviation of bending moment indicates greater dispersion. Axial stress weight refers to the proportion of axial stress fluctuation in the total axial stress, radial stress, and bending moment; radial stress weight refers to the proportion of radial stress fluctuation in the total axial stress, radial stress, and bending moment; and bending moment weight refers to the proportion of bending moment fluctuation in the total axial stress, radial stress, and bending moment.

[0061] It should be understood that the method for determining the standard deviation of radial stress based on multiple historical radial stresses and the method for determining the standard deviation of bending moment based on multiple historical bending moments are the same as the method for calculating the standard deviation of axial stress based on multiple historical axial stresses, and will not be described again here.

[0062] Specifically, the determination of the force influence index based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight includes: Obtain the allowable stress data of wind turbine blades, which includes: allowable axial stress, allowable radial stress and allowable bending moment; Force sensors are used to monitor the stress on wind turbine blades and obtain stress data, which includes: current axial stress, current radial stress and current bending moment; The stress influence index is calculated based on allowable axial stress, allowable radial stress, allowable bending moment, current axial stress, current radial stress, current bending moment, axial stress weight, radial stress weight, and bending moment weight. The calculation formula is shown below:

[0063] in, Indicates the force influence index. Indicates the allowable axial stress. Indicates the current axial stress. Indicates the allowable radial stress. Indicates the current radial stress. Indicates the allowable bending moment. This indicates the current bending moment.

[0064] It should be explained that obtaining the allowable stress data for wind turbine blades refers to obtaining the allowable stress data from the technical manuals provided by the wind turbine blade manufacturers. This allowable stress data includes: allowable axial stress, allowable radial stress, and allowable bending moment. Allowable axial stress refers to the maximum safe stress that the wind turbine blade can withstand along its length (main axis direction). Exceeding this value may cause material yielding, fracture, or structural instability. Allowable radial stress refers to the upper limit of the stress distributed radially from the root to the tip of the wind turbine blade, mainly used to assess the blade's resistance to fracture under centrifugal force or lateral wind pressure. Allowable bending moment is the maximum safe bending moment that the wind turbine blade can withstand under the action of external forces such as wind and gravity. Exceeding this value may lead to permanent deformation or fracture.

[0065] It is understood that the use of force sensors to monitor the stress on wind turbine blades refers to using force sensors to monitor the stress at the root flange of the wind turbine blade. The stress data is the stress data at the root flange of the wind turbine blade, and the stress data includes: current axial stress, current radial stress, and current bending moment.

[0066] Current axial stress refers to the tensile or compressive stress generated on the wind turbine blades during current operation, primarily caused by the thrust of the wind transmitted along the blades, and reflects the longitudinal stress state of the blades. Current radial stress refers to the radial stress generated on the wind turbine blades during current operation, primarily caused by centrifugal force and crosswind loads generated during rotation, and is used to assess the lateral stress and rotational stability of the blades. Current bending moment refers to the bending moment generated on the wind turbine blades during current operation, reflecting the lever arm effect caused by uneven wind pressure distribution along the blade length, and is an important parameter for judging blade fatigue damage and structural stability. The stress influence index reflects the safety of the wind turbine blades under wind load; the larger the stress influence index, the lower the safety of the operating state under wind load.

[0067] Specifically, the determination of the temperature influence index based on the temperature sensor and the spindle includes: The spindle temperature is obtained by using a temperature sensor to monitor the spindle temperature. The temperature influence index is calculated based on the spindle temperature, using the following formula:

[0068] in, Indicates the effect of temperature. Represents spindle temperature. This is the preset safe temperature.

[0069] It should be explained that monitoring the spindle temperature using a temperature sensor means monitoring the temperature of the spindle surface using a temperature sensor, and the spindle temperature is the same as the temperature of the spindle surface. The temperature influence index is a control indicator used to describe whether the spindle temperature is within the safe operating range. A value of 1 indicates "temperature is safe, normal operation is allowed", and a value of 0 indicates "temperature is too high, operation must be stopped".

[0070] S7. Input the wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index and temperature influence index into the pre-constructed intelligent pitch model to obtain the target pitch angle, and complete the intelligent pitch control based on the target pitch angle and the pitch device.

[0071] In detail, the intelligent pitch model is shown below:

[0072] in, This represents the intelligent pitch model. Indicates the effect of temperature. Indicates wind energy conversion efficiency. Indicates wind direction concentration. Indicates the current pitch angle. Indicates real-time wind energy conversion efficiency. Indicates the force influence index. Compared to the preset maximum pitch angle, Indicates the effect of temperature. It is the hyperbolic tangent function.

[0073] It should be explained that the target pitch angle is the value calculated by inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into the intelligent pitch model. Once the target pitch angle is calculated in the intelligent pitch model, the pitch control device can adjust the pitch angle of the wind turbine blades according to the target pitch angle, thereby completing intelligent pitch control. The maximum pitch angle refers to the maximum angle that the wind turbine blades can adjust during operation, obtained from the technical manual provided by the wind turbine manufacturer.

[0074] Understandably, the adjustment principle of the intelligent pitch model is as follows: Since the current pitch angle corresponds to the wind energy conversion efficiency, when the real-time wind energy conversion efficiency is less than or equal to the wind energy conversion efficiency, the pitch angle should be appropriately reduced to improve the utilization rate of wind energy and balance the loss of wind energy conversion efficiency. At the same time, the greater the wind speed stability and the greater the wind direction concentration, the higher the consistency of the wind. The more concentrated the wind direction, the more conducive it is to large-angle wind. Therefore, the pitch angle needs to be reduced by more to make full use of wind power. When the force influence index is large, it indicates that the wind turbine is more sensitive to changes in force. At this time, the adjustment of the pitch angle should be appropriately reduced to prevent excessive adjustment from damaging the equipment.

[0075] For example, when the spindle temperature is higher than the safe temperature, the temperature influence index is 0, indicating that the temperature is too high and the wind turbine needs to be stopped. Therefore, the target pitch angle calculated by the model at this time is the maximum pitch angle to stop the wind turbine. When the spindle temperature is lower than the safe temperature, it means the temperature is safe and normal operation is allowed. In this case, the pitch angle is adjusted based on the current pitch angle. If the real-time wind energy conversion efficiency is less than or equal to the wind energy conversion efficiency, in order to balance the loss of wind energy conversion efficiency, the pitch angle calculated by the model is a reduction from the current pitch angle to improve the utilization rate of wind energy.

[0076] To address the problems described in the background art, this invention identifies a wind turbine and a wind power control mechanism. The wind power control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. This invention, by identifying a wind power control mechanism integrating wind speed, force, and temperature sensors beforehand, facilitates the subsequent acquisition of wind speed, wind turbine blade force data, and temperature. The identification of a wind turbine integrating wind turbine blades, a pitch control device, and a main shaft facilitates subsequent monitoring of wind turbine blade force data and main shaft temperature using a wind power monitoring mechanism. It also facilitates real-time adjustment of the pitch angle using the pitch control device, improving the intelligence of the wind turbine pitch control and enabling the acquisition of multiple sets of historical data. The historical data includes historical wind speed, historical wind direction, historical main shaft speed, and historical power generation. This embodiment of the invention obtains historical wind speed, historical wind direction, historical main shaft speed, and historical power generation. Since this historical data reflects relevant data from the wind turbine's historical operation, analyzing the historical data can effectively assess the historical operating conditions, thereby calculating wind speed stability, wind direction concentration, and wind energy conversion efficiency. Multiple historical wind speeds and directions are extracted from multiple sets of historical data. Wind speed stability is calculated based on these multiple historical wind speeds, and wind direction concentration is confirmed based on these multiple historical wind directions. Therefore, this embodiment of the invention extracts multiple historical wind speeds and directions from multiple sets of historical data. Wind speed and multiple historical wind directions can reflect the overall wind force level of the wind turbine installation area. Based on these historical wind speeds and directions, wind speed stability and wind direction concentration can be calculated, facilitating subsequent calculation of the target blade pitch angle. The wind energy conversion efficiency is confirmed based on the wind turbine blades, historical wind speed, historical shaft speed, and historical power generation. Therefore, this embodiment of the invention calculates the average wind energy conversion efficiency of the wind turbine over its historical operation, facilitating subsequent comparison of the real-time wind energy conversion efficiency with the actual wind energy conversion efficiency. Furthermore, the current wind speed, blade pitch angle, current shaft speed, and power generation are obtained using a wind speed sensor. This embodiment of the invention facilitates subsequent calculations of the actual wind energy conversion efficiency by acquiring the current wind speed, blade pitch angle, and power generation. The wind turbine's pitch angle is determined based on the wind turbine blades, current wind speed, current rotational speed, and power generation. This invention calculates the real-time wind energy conversion efficiency and compares it with the average wind turbine operating state to obtain the difference between the current operating state and the average operating state, thus improving the intelligence of the wind turbine's pitch control. The invention also determines the force influence index based on the wind turbine blades and force sensors, and the temperature influence index based on the temperature sensor and main shaft. This allows for the calculation of the pitch angle by using force sensors to obtain real-time force data on the wind turbine blades and using temperature sensors to obtain the surface temperature of the main shaft in real time.By inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into a pre-constructed intelligent pitch model, the target pitch angle is obtained. It is evident that this embodiment of the invention improves the intelligence level of wind turbine pitch control by calculating the target pitch angle using a pre-constructed intelligent pitch model. Intelligent pitch control is then completed based on the target pitch angle and the pitch control device. Therefore, this embodiment of the invention improves the intelligence level of wind turbine pitch control by calculating the target pitch angle according to the intelligent pitch model, thereby improving the power generation efficiency of the wind turbine. Thus, this invention can improve the intelligence level of wind turbine pitch control, thereby improving the power generation efficiency of the wind turbine.

[0077] like Figure 2 The diagram shown is a functional block diagram of a wind power generation system based on intelligent pitch control provided in an embodiment of the present invention.

[0078] The wind power generation system 100 based on intelligent pitch control described in this invention can be installed in an electronic device. Depending on the functions implemented, the wind power generation system 100 based on intelligent pitch control may include a basic equipment acquisition module 101, a historical data analysis module 102, a real-time data monitoring module 103, and an intelligent calculation pitch module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0079] The basic equipment acquisition module 101 is used to identify the wind turbine and wind power control mechanism. The wind power control mechanism includes a wind speed sensor, a force sensor and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device and a main shaft. The historical data analysis module 102 is used to acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical main shaft speed and historical power generation. It extracts multiple historical wind speeds and multiple historical wind directions from the multiple sets of historical data, calculates wind speed stability based on multiple historical wind speeds, confirms wind direction concentration based on multiple historical wind directions, and confirms wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed and historical power generation. The real-time data monitoring module 103 is used to obtain the current wind speed, current blade pitch angle, current rotation speed and power generation using a wind speed sensor; to determine the real-time wind energy conversion efficiency based on the wind turbine blades, current wind speed, current rotation speed and power generation; to determine the force influence index based on the wind turbine blades and force sensor; and to determine the temperature influence index based on the temperature sensor and main shaft. The intelligent pitch control module 104 is used to input wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index and temperature influence index into a pre-constructed intelligent pitch model to obtain the target pitch angle, and complete intelligent pitch control based on the target pitch angle and the pitch control device.

[0080] In detail, the modules in the wind power generation system 100 based on intelligent pitch control described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method uses the same technical means as the wind power generation method based on intelligent pitch control described in the article and can produce the same technical effect, so it will not be repeated here.

[0081] like Figure 3 The diagram shown is a structural schematic of an electronic device for implementing a wind power generation method based on intelligent pitch control, according to an embodiment of the present invention.

[0082] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a wind power generation method program based on intelligent pitch control.

[0083] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for a wind power generation method program based on intelligent pitch control, but also to temporarily store data that has been output or will be output.

[0084] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a wind power generation method program based on intelligent pitch control) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0085] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0086] Figure 3 Only electronic devices with components are shown; those skilled in the art will understand that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0087] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0088] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0089] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0090] The wind power generation method program based on intelligent pitch control stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following: The wind turbine and wind control mechanism were identified. The wind control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. Acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical spindle speed, and historical power generation. Multiple historical wind speeds and multiple historical wind directions were extracted from multiple sets of historical data; Wind speed stability is calculated based on multiple historical wind speeds, and wind direction concentration is confirmed based on multiple historical wind directions. The wind energy conversion efficiency was determined based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The current wind speed, current paddle pitch angle, current rotation speed, and power generation are obtained using a wind speed sensor. The real-time wind energy conversion efficiency is determined based on the wind turbine blades, current wind speed, current rotation speed, and power generation. The force influence index was determined based on the wind turbine blades and force sensors, and the temperature influence index was determined based on the temperature sensors and the main shaft. By inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into the pre-built intelligent pitch model, the target pitch angle can be obtained. Intelligent pitch control is achieved based on the target pitch angle and the pitch control device.

[0091] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0092] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0093] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: The wind turbine and wind control mechanism were identified. The wind control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. Acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical spindle speed, and historical power generation. Multiple historical wind speeds and multiple historical wind directions were extracted from multiple sets of historical data; Wind speed stability is calculated based on multiple historical wind speeds, and wind direction concentration is confirmed based on multiple historical wind directions. The wind energy conversion efficiency was determined based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The current wind speed, current paddle pitch angle, current rotation speed, and power generation are obtained using a wind speed sensor. The real-time wind energy conversion efficiency is determined based on the wind turbine blades, current wind speed, current rotation speed, and power generation. The force influence index was determined based on the wind turbine blades and force sensors, and the temperature influence index was determined based on the temperature sensors and the main shaft. By inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into the pre-built intelligent pitch model, the target pitch angle can be obtained. Intelligent pitch control is achieved based on the target pitch angle and the pitch control device.

[0094] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0095] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0096] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0097] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A wind power generation method based on intelligent pitch control, characterized in that, The method includes: The wind turbine and wind control mechanism were identified. The wind control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. Acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical spindle speed, and historical power generation. Multiple historical wind speeds and multiple historical wind directions were extracted from multiple sets of historical data; Wind speed stability is calculated based on multiple historical wind speeds, using the following formula: in, Indicates wind speed stability. The number of historical data points in multiple sets of historical data. This indicates the first of multiple historical wind speeds. A historical wind speed; Based on multiple historical wind directions, the concentration of wind direction was determined, including performing the following operations for each of the multiple historical wind directions: The historical wind direction is converted into radian value to obtain the wind direction radian value; Summarize the wind direction radian values ​​to obtain multiple wind direction radian values; The wind direction concentration is calculated based on multiple wind direction radian values, using the following formula: in, Indicates wind direction concentration. Represents the first of multiple wind direction radian values. One wind direction arc value, Represents the cosine function. Represents the sine function; The wind energy conversion efficiency was determined based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The current wind speed, current paddle pitch angle, current rotation speed, and power generation are obtained using a wind speed sensor. The real-time wind energy conversion efficiency is determined based on the wind turbine blades, current wind speed, current rotation speed, and power generation. The force influence index was determined based on the wind turbine blades and force sensors, and the temperature influence index was determined based on the temperature sensors and the main shaft. By inputting wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index, and temperature influence index into the pre-built intelligent pitch model, the target pitch angle can be obtained. Intelligent pitch control is achieved based on the target pitch angle and the pitch control device.

2. The wind power generation method based on intelligent pitch control as described in claim 1, characterized in that, The determination of wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation includes: To confirm the blade radius of the wind turbine, perform the following operation for each set of historical data from multiple sets of data: The tip speed ratio is calculated based on historical wind speed, historical spindle speed, and blade radius from historical data. The power coefficient is calculated based on historical power generation, historical wind speed, blade radius, and tip speed ratio from historical data. The tip speed ratios are summarized to obtain multiple tip speed ratios. Based on these multiple tip speed ratios, the average tip speed ratio is determined. The average tip speed ratio is the average of the multiple tip speed ratios. The power coefficients are summarized to obtain multiple power coefficients. The average power coefficient is determined based on the multiple power coefficients. The average power coefficient is the average of the multiple power coefficients. Wind energy conversion efficiency is calculated based on the average tip speed ratio and average power coefficient.

3. The wind power generation method based on intelligent pitch control as described in claim 2, characterized in that, The force influence index determined based on wind turbine blades and force sensors includes: Obtain multiple historical stress data points for wind turbine blades, including historical axial stress, historical radial stress, and historical bending moment. Multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments were extracted from multiple historical stress data. The weights of axial stress, radial stress, and bending moment are determined based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments. The force influence index is determined based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight.

4. The wind power generation method based on intelligent pitch control as described in claim 3, characterized in that, The determination of axial stress weights, radial stress weights, and bending moment weights based on multiple historical axial stresses, multiple historical radial stresses, and multiple historical bending moments includes: The standard deviation of axial stress was calculated based on multiple historical axial stresses. The standard deviation of radial stress was determined based on multiple historical radial stresses, and the standard deviation of bending moment was determined based on multiple historical bending moments. The axial stress weight, radial stress weight, and bending moment weight are calculated based on the standard deviations of axial stress, radial stress, and bending moment.

5. The wind power generation method based on intelligent pitch control as described in claim 4, characterized in that, The force influence index, determined based on wind turbine blades, force sensors, axial stress weight, radial stress weight, and bending moment weight, includes: Obtain the allowable stress data of wind turbine blades, which includes: allowable axial stress, allowable radial stress and allowable bending moment; Force sensors are used to monitor the stress on wind turbine blades and obtain stress data, which includes: current axial stress, current radial stress and current bending moment; The stress influence index is calculated based on allowable axial stress, allowable radial stress, allowable bending moment, current axial stress, current radial stress, current bending moment, axial stress weight, radial stress weight, and bending moment weight.

6. The wind power generation method based on intelligent pitch control as described in claim 5, characterized in that, The temperature influence index determined based on the temperature sensor and spindle includes: The spindle temperature is obtained by using a temperature sensor to monitor the spindle temperature. Calculate the temperature effect index based on the spindle temperature.

7. The wind power generation method based on intelligent pitch control as described in claim 6, characterized in that, The intelligent pitch model is shown below: in, This represents the intelligent pitch model. Indicates the effect of temperature. Indicates wind energy conversion efficiency. Indicates wind direction concentration. Indicates the current pitch angle. Indicates real-time wind energy conversion efficiency. Indicates the force influence index. Compared to the preset maximum pitch angle, Indicates the effect of temperature. It is the hyperbolic tangent function.

8. A wind power generation system based on intelligent pitch control, characterized in that, The system includes: The basic equipment acquisition module is used to identify the wind turbine and wind power control mechanism. The wind power control mechanism includes a wind speed sensor, a force sensor, and a temperature sensor. The wind turbine includes wind turbine blades, a pitch control device, and a main shaft. The historical data analysis module is used to acquire multiple sets of historical data, including historical wind speed, historical wind direction, historical main shaft rotation speed, and historical power generation. Multiple historical wind speeds and directions are extracted from these sets of historical data using the following calculation formulas: in, Indicates wind speed stability. The number of historical data points in multiple sets of historical data. This indicates the first of multiple historical wind speeds. A historical wind speed; Based on multiple historical wind directions, the concentration of wind direction was determined, including performing the following operations for each of the multiple historical wind directions: The historical wind direction is converted into radian value to obtain the wind direction radian value; Summarize the wind direction radian values ​​to obtain multiple wind direction radian values; The wind direction concentration is calculated based on multiple wind direction radian values, using the following formula: in, Indicates wind direction concentration. Represents the first of multiple wind direction radian values. One wind direction arc value, Represents the cosine function. The sine function is used to determine the wind energy conversion efficiency based on wind turbine blades, historical wind speed, historical main shaft speed, and historical power generation. The real-time data monitoring module is used to obtain the current wind speed, current blade pitch angle, current rotation speed and power generation using a wind speed sensor. Based on the wind turbine blades, current wind speed, current rotation speed and power generation, it determines the real-time wind energy conversion efficiency; based on the wind turbine blades and force sensor, it determines the force influence index; and based on the temperature sensor and main shaft, it determines the temperature influence index. The intelligent pitch control module is used to input wind speed stability, wind direction concentration, wind energy conversion efficiency, real-time wind energy conversion efficiency, current pitch angle, force influence index and temperature influence index into a pre-built intelligent pitch model to obtain the target pitch angle, and complete intelligent pitch control based on the target pitch angle and the pitch control device.

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