A wind power generation efficiency optimization control method and system and a storage medium

Abstract

The present application relates to the field of wind power generation technology, and more particularly to a wind power generation efficiency optimization control method, system and storage medium, which realizes passive self-adaptive adjustment of a guide vane through a hierarchical adjustment module, so that the guide vane is automatically stabilized at a preset optimal opening and closing angle; wind speed, blade section angle of attack, blade load and state parameters of the hierarchical adjustment module are collected in real time; working condition recognition and state monitoring are performed based on the collected operating parameters; performance adaptation is judged according to the working condition recognition result, and the pain points of airflow separation and laminar separation under the low Reynolds number condition are designed, so that the passive aerodynamic optimization of the guide vane is realized with the hierarchical adjustment module as the core, instead of speed regulation or electric energy conversion process, and the blade size and operating characteristics of the 100kW small fan are completely matched, so that the present application can be directly applied without complex adaptation, fills the gap of the special aerodynamic optimization scheme for the low Reynolds number condition, and solves the technical problem that the megawatt scheme cannot be migrated and applied.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, specifically to a wind power generation efficiency optimization control method, system, and storage medium. Background Technology

[0002] With the deepening of the global energy transition, distributed wind power, as an important component of clean and renewable energy, is facing increasingly urgent development needs in low-wind-speed areas. For 100kW-class small wind turbines, due to the relatively small blade size, the operating Reynolds number is typically around 3×10⁻⁶. 5 -8×10 5 The low Reynolds number range. Under low Reynolds number conditions, airflow is prone to complex flow phenomena such as laminar separation and boundary layer transition, which leads to core technical pain points for wind turbine blades, such as insufficient lift, difficulty in starting at low wind speeds, high risk of stall, and low wind energy capture efficiency, which seriously restrict the large-scale development of distributed wind power in low wind speed areas.

[0003] To improve the aerodynamic performance of blades under low Reynolds number conditions, existing technologies mainly explore blade shape optimization and the addition of passive flow control devices. For example, optimizing the blade airfoil curvature can increase lift, but fixed airfoils cannot adapt to the aerodynamic requirements across the entire wind speed range and are still prone to stalling during sudden wind speed changes. Some solutions add fixed leading-edge slats or vortex generators, which can delay stalling under specific conditions, but are prone to generating additional drag and other problems, and cannot be dynamically adjusted according to real-time wind conditions, making it difficult to simultaneously meet the dual requirements of increasing lift at low wind speeds and controlling loads at high wind speeds.

[0004] Among existing related technologies, the efficiency optimization schemes for megawatt-class large wind turbines focus on speed regulation and power conversion processes. These schemes are suitable for high-power units operating under high Reynolds number conditions, but do not include dedicated aerodynamic optimization strategies for airflow separation under low Reynolds number conditions. Therefore, they cannot be directly applied to 100kW-class small wind turbines. Summary of the Invention

[0005] The purpose of this invention is to address the deficiencies and shortcomings of the prior art by providing a wind power generation efficiency optimization control method, system, and storage medium that can solve at least one of the aforementioned technical problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a wind power generation efficiency optimization control system comprising: a graded adjustment module, the graded adjustment module including a return spring and graded limiting slides installed between the guide vane and the blade body, used to utilize the mechanical balance between airflow pressure and spring force to passively and adaptively stabilize the guide vane at a preset optimal opening angle under different wind speeds; a multi-dimensional parameter acquisition module, used to collect wind speed, angle of attack of each blade section, blade load, and state parameters of the graded adjustment module in real time; a condition identification and status monitoring module, used to receive signals from the multi-dimensional parameter acquisition module, identify the wind turbine operating condition according to a preset judgment standard, and simultaneously evaluate the operating status of the graded adjustment module; a pitch angle auxiliary control module, used to output adjustment commands to adjust the wind turbine pitch angle after receiving a warning signal; and a main controller, connected to the multi-dimensional parameter acquisition module, the condition identification and status monitoring module, and the pitch angle auxiliary control module, used to coordinate data acquisition, processing, condition judgment, and trigger corresponding warning and control commands.

[0008] Furthermore, the graded adjustment module is specifically configured as follows: the stiffness coefficient of the return spring is 3.5 N / mm, and the preload F0 is 70 N; both the guide vane and the blade body are provided with placement slots for placing the return spring, and the two ends of the return spring are respectively fixed in the placement slots of the guide vane and the blade body.

[0009] The graded limiting slide includes a guide rail and a slide. The slide is mounted on the guide vane and is clearance-fitted with the guide rail. The travel of the guide rail is L=35mm, corresponding to the opening and closing angle range of the guide vane from 0° to 15°.

[0010] Furthermore, the multi-dimensional parameter acquisition module includes: an ultrasonic anemometer installed on the top of the nacelle for acquiring wind speed, with a measurement range of 0-40 m / s; a pressure sensor array arranged along the blade spanwise for acquiring the pressure distribution on the blade surface to calculate the angle of attack of each section; strain gauge sensors attached to the blade root and key sections of the main beam for acquiring blade load; and displacement and vibration sensors installed on the slide (6) for acquiring the real-time travel, travel change rate, and vibration amplitude of the slide (6).

[0011] Furthermore, the pressure sensor array is set up at 3m, 7m and 11m from the blade root, with each set including 3 pressure sensors on the leading edge, upper surface and lower surface;

[0012] The displacement sensor is a linear potentiometer type displacement sensor with a measurement range of 0-35mm.

[0013] The vibration sensor is a piezoelectric vibration sensor with a measurement range of 0-5g.

[0014] Furthermore, the main controller is a PLC controller with an operation cycle of ≤10ms, a built-in fault diagnosis algorithm, and records the long-term operating status data of the graded adjustment module.

[0015] Secondly, the present invention provides a wind power generation efficiency optimization control method, which is implemented using any of the above-mentioned systems and includes the following steps:

[0016] S1: The passive adaptive adjustment of the guide vane is achieved through the graded adjustment module, so that the guide vane automatically stabilizes at the preset optimal opening and closing angle corresponding to the current wind speed condition under the mechanical balance of airflow pressure and spring force.

[0017] S2: The multi-dimensional parameter acquisition module collects wind speed, angle of attack of each blade section, blade load, and status parameters of the graded adjustment module in real time.

[0018] S3: Based on the operating parameters collected in step S2, perform operating condition identification and status monitoring; the operating condition identification includes determining whether the fan is in a low wind speed condition, medium wind speed condition, high wind speed condition, or a transitional stage; the status monitoring includes determining whether the stroke position and vibration amplitude of the graded adjustment module exceed the preset threshold.

[0019] S4: Based on the identification and monitoring results of step S3, a performance adaptation judgment is made. If the blade angle of attack is ≥13.6° and the rate of change of angle of attack is >0.5° / s, or the state of the graded adjustment module is abnormal, an early warning is triggered and the pitch angle auxiliary adjustment is executed.

[0020] Furthermore, the passive adaptive adjustment of the graded adjustment module in step S1 is specifically as follows: under low wind speed conditions, the airflow pressure overcomes the spring preload and part of the stiffness force, and the opening and closing angle of the guide vane is stable at 14°-15°; under medium wind speed conditions, the opening and closing angle of the guide vane decreases linearly with the increase of wind speed and is stable in the range of 8°-12°; under high wind speed conditions, the spring is compressed to the end of its stroke, and the guide vane returns to the opening and closing angle of <2° and remains stable.

[0021] Furthermore, the specific criteria for determining the operating condition in step S3 are as follows: Low wind speed condition: real-time wind speed V < 5 m / s, average blade angle of attack < 10.2°, and maximum blade load < 0.5F. n Medium wind speed conditions: 5 m / s ≤ V ≤ 10 m / s, and 10.2° ≤ average blade angle of attack ≤ 15.3°, and 0.5F n Maximum blade load ≤ 0.9F n High wind speed conditions: V > 10 m / s, average blade angle of attack ≥ 15.3°, and maximum blade load > 0.9F. n; Transitional operating condition stage: The real-time wind speed fluctuates within the boundary of the adjacent operating condition by an amplitude of ≥ ±0.5 m / s and lasts for ≥ 3 s, or the blade angle of attack fluctuates within an amplitude of ≥ ±1° and lasts for ≥ 2 s.

[0022] Furthermore, the specific logic of the warning and pitch angle auxiliary adjustment in step S4 is as follows: when the average angle of attack of the blade is detected to be ≥13.6° and the rate of change of angle of attack is >0.5° / s, a stall warning is triggered, and the pitch angle is increased by 1°-3°; when the slide travel is detected to exceed the preset range of 0°-15°, the rate of change of travel is >5mm / s, or the vibration amplitude of the mechanism is >0.5g, a mechanism fault warning is triggered, and the pitch angle is increased by 3°-5°; when the blade load fluctuation amplitude is detected to be >15% during the transition of operating conditions, the pitch angle is finely adjusted by 0.5°-1° to buffer the load impact.

[0023] Thirdly, the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor to execute the wind power generation efficiency optimization control method as described in any of the above embodiments.

[0024] Fourthly, embodiments of this application provide a computer device, the computer device including a processor and a memory, the memory storing a computer program, the processor executing the wind power generation efficiency optimization control method as described in any of the above embodiments by calling the computer program stored in the memory.

[0025] Fifthly, embodiments of this application provide a computer program product, including computer instructions, which, when executed by a processor, implement the wind power generation efficiency optimization control method as described in any of the above embodiments.

[0026] After adopting the above technical solution, the beneficial effects of the present invention are as follows:

[0027] 1. The core of this invention is designed around the pain points of airflow separation and laminar flow separation under low Reynolds number conditions. It uses a graded adjustment module as the core to achieve passive aerodynamic optimization of the guide vane, rather than targeting speed regulation or power conversion process. It is perfectly matched to the blade size and operating characteristics of 100kW-class small wind turbines and can be directly applied without complicated adaptation. It fills the gap in aerodynamic optimization solutions for low Reynolds number conditions and solves the technical problem that megawatt-level solutions cannot be migrated and applied.

[0028] 2. By using the reset spring and graded limit slide of the graded adjustment module, the guide vane opens at low wind speed to improve effective curvature, linearly adjusts at medium wind speed to maintain the optimal lift-to-drag ratio, and reliably closes at high wind speed to avoid overload. It actively suppresses laminar flow separation and airflow separation from an aerodynamic perspective. Combined with the pressure sensor array to monitor the angle of attack in real time, it forms a synergistic mechanism of passive aerodynamic optimization and active state perception. The laminar flow separation suppression effect is improved by more than 60% compared with single pitch angle control, and the wind energy capture efficiency at low wind speed is improved by ≥15%.

[0029] 3. Through condition monitoring and multi-parameter acquisition, problems such as slide block jamming, spring fatigue, and sensor failure can be identified in real time, triggering early warning and executing auxiliary pitch angle adjustment, improving the mean time between failures and enhancing the reliability of the system.

[0030] 4. By configuring a reset spring and a graded limit slide, the guide vane can be passively and adaptively adjusted under different wind speed conditions by utilizing the mechanical balance between airflow pressure and spring force, without the need for active electronic control command intervention. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the wind power generation efficiency optimization control method of the present invention;

[0033] Figure 2 This is a schematic diagram of the assembly structure of the guide vane and the graded limiting slide in this invention;

[0034] Figure 3 This is a schematic diagram of the opening and closing states of the guide vanes under different wind speeds in this invention;

[0035] Figure 4 This is a schematic diagram of the module connections of the wind power generation efficiency optimization control system in this invention;

[0036] Figure 5 This is a schematic diagram of the wind power generation efficiency optimization control device in this invention.

[0037] Explanation of reference numerals in the attached drawings: 1. Guide vane; 2. Blade body; 3. Return spring; 4. Placement groove; 5. Guide rail; 6. Slide. Detailed Implementation

[0038] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. Example 1

[0039] like Figures 2 to 4 As shown, this embodiment provides a wind power generation efficiency optimization control system, which is used in conjunction with the control method of Embodiment 1 and is adapted to 100kW-class distributed wind turbines. The hardware configuration, connection method, and functional implementation details of each module are as follows:

[0040] 1. Graded adjustment module

[0041] As a core passive adjustment component, used to achieve passive adaptive angle adjustment of the guide vanes, it includes a return spring and a graded limit slide:

[0042] Return spring: A cylindrical helical spring is selected, with a wire diameter of 6.5 mm, a spring mean diameter of 32 mm, 10 effective turns, a stiffness coefficient k=3.5 N / mm, and a preload F0=70 N. The spring material is 60Si2Mn, which has good fatigue strength. Placement slots for the spring are provided at the positions of the guide vane near the blade body and the blade body near the guide vane. The two ends of the spring are fixed in the placement slots of the guide vane and the blade body, respectively. This arrangement ensures that when the guide vane is fully in contact with the blade body, the spring can be completely retracted into the placement slot, minimizing the impact on the gap between the guide vane and the blade body.

[0043] The graded limiting slide includes a guide rail and a slide mounted on the guide vane. The slide and guide rail are clearance-fitted. The guide rail is bolted to the blade body and located on the front and rear sides of the guide vane. The slide is positioned at both ends of the guide vane. The slide guide rail travel L = 35mm, corresponding to the guide vane's opening angle range of 0°-15°. The clearance between the slide and guide rail is 0.05-0.1mm, and grease lubrication can be used to reduce sliding resistance. (For the guide rail and slide structure, multiple guide rails can also be installed between the guide vane and the blade body. In this case, the guide vane is divided into multiple small components, all of which are connected to the slide and blade body via guide rails.)

[0044] 2. Multi-dimensional parameter acquisition module

[0045] Used to synchronously collect wind speed, blade angle of attack, blade load, and mechanism status parameters, providing data support for operating condition identification and condition monitoring:

[0046] The installation locations and connection methods of each sensor are as follows:

[0047] Wind speed sensor: Installed on the windward side of the top of the nacelle, fixed by a bracket, with a cable passing through the inside of the nacelle and connected to the analog input module of the main controller; an ultrasonic anemometer (model: RS485 output) is selected, installed on the windward side of the top of the nacelle, and communicates with the main controller via RS485 bus, with a baud rate of 9600bps and a data update frequency of 10Hz.

[0048] Pressure sensor array: The sensors are installed flush with the blade surface and waterproofed. The cables run along the inside of the blade to the nacelle, connect to the signal conditioning module, and then to the main controller. Miniature piezoelectric pressure sensors (model: MSP-300) are selected, with a range of 0-1MPa and an accuracy of ±0.01kPa. The six sensors are arranged in three groups along the blade span and connected to the signal conditioning module (model: AD8233) via waterproof cables. The pressure signal is converted into a 0-5V analog signal and transmitted to the main controller.

[0049] Strain gauge sensors: After being pasted onto the blade root transition section and the main beam, they are insulated and waterproofed, and connected to the strain gauge via wires. The strain gauge communicates with the main controller via Ethernet. Metal foil strain gauges (model: BF120-3AA) are selected, with 6 measuring points pasted onto the blade root transition section (2 points), the blade 1 / 3 spanwise main beam (2 points), and the blade 2 / 3 spanwise main beam (2 points). They are connected to the strain gauge (model: DH3816N) via a half-bridge circuit, outputting a 4-20mA current signal.

[0050] Displacement sensor: Mounted on the side of the slide block via a bracket, with the measuring rod parallel to the guide rail, and the output wire connected to the analog input module of the main controller; a linear potentiometer-type displacement sensor (model: WDD35D4) is selected, installed between the slide block and the guide rail, with a measurement range of 0-35mm, an accuracy of ±0.1mm, and an output of 0-5V analog signal to acquire the slide block travel in real time.

[0051] Vibration sensor: Fixed to the slide by a magnetic base, outputting a 4-20mA current signal to the main controller; a piezoelectric vibration sensor (model: CA-YD-105) is selected, installed on the slide, with a measurement range of 0-5g, an accuracy of ±0.01g, and an output of a 4-20mA current signal to monitor the vibration status of the mechanism.

[0052] 3. Operating Condition Identification and Status Monitoring Module

[0053] Integrated into the main controller, it processes the collected multi-dimensional parameters through a preset algorithm:

[0054] Data preprocessing: A moving average filtering algorithm is used to average five consecutive sets of collected data to remove random noise and improve data accuracy;

[0055] Operating condition identification: Based on the preset operating condition judgment criteria, perform logical judgment on the pre-processed wind speed, angle of attack, and load data, and output the operating condition identifier (low / medium / high wind speed / transition stage).

[0056] Condition assessment: Set threshold variables for stroke and vibration amplitude, determine whether the threshold is exceeded by comparison command, check the integrity of sensor signals, and identify mechanism failure or sensor failure.

[0057] Warning Trigger: When stall conditions, mechanism failure, or sensor failure are met, a corresponding warning signal is output to the main controller.

[0058] 4. Pitch Angle Auxiliary Control Module

[0059] Used to receive adjustment commands from the main controller, enabling precise adjustment of the pitch angle, and assisting in stall suppression and load mitigation, including:

[0060] Pitch angle driver: Installed with the stepper motor inside the nacelle at the pitch angle adjustment mechanism, the driver receives adjustment commands from the main controller via pulse signals, controls the motor rotation angle, and thus adjusts the pitch angle; a servo motor driver (model: MSD043A1XX) is selected, which works in conjunction with a stepper motor (model: 57HS22) to drive the pitch angle adjustment. The adjustment range is 0°-30°, the adjustment accuracy is ±0.1°, and the output torque is ≥20N·m;

[0061] Position feedback unit: The encoder collects the actual rotation angle of the motor and feeds it back to the main controller to form a closed-loop control. It is integrated into the stepper motor and collects the actual position of the pitch angle in real time and feeds it back to the main controller to form a closed-loop control, ensuring the adjustment accuracy is ±0.1°.

[0062] 5. Main Controller

[0063] Using a Siemens S7-1200 CPU 1214C, equipped with an SM1231 analog input module (8 channels) and an SM1222 digital output module (16 channels), the following functions are implemented through programming:

[0064] Communication functions: Supports Modbus RTU and Profinet communication protocols for data exchange with wind speed sensors, displacement sensors, etc.; Configures Profinet protocol for communication with strain gauges and pitch angle actuators.

[0065] Data processing function: Write an interrupt program to collect data from each sensor every 10ms and perform filtering and calculation processing;

[0066] Fault diagnosis and storage functions: Write a data storage program to store daily operating data to an SD card; write a fault diagnosis program to generate fault codes based on monitoring results and record information such as the time of fault occurrence and operating conditions;

[0067] Emergency control function: Write an emergency control program that, when a serious fault is triggered, immediately outputs a command to adjust the pitch angle to 30° and control the wind turbine speed to reduce to a standstill.

[0068] Blade basic parameters and dimensions

[0069] (I) Core performance parameters

[0070]

[0071] (ii) Geometric Dimensions

[0072]

[0073] (III) Material selection and layup

[0074]

[0075] (iv) Adaptive airfoil design:

[0076] Example 2

[0077] like Figure 1 As shown, this embodiment provides a wind power generation efficiency optimization control method based on graded regulation. This method can be executed by a wind turbine generator; alternatively, it can be executed by a computer device, such as a terminal 200 or a server. For ease of explanation, this embodiment uses a 100kW distributed wind turbine generator with a blade length of 15m, a rated speed of 180r / min, a stall angle of attack of 17°, and a rated load F. n Taking 50kN as an example, it should be noted that the embodiments of this application do not impose restrictions on the generator's power, blade length, rated speed, stall angle of attack, and rated load, etc., which will not be listed here.

[0078] This application provides a wind power generation efficiency optimization control method based on hierarchical regulation, which is applied to a wind power generation efficiency optimization control system proposed in this application. The method is implemented by steps S1 to S4, as detailed below:

[0079] Step S1: Passive adaptive adjustment of the graded adjustment module

[0080] By utilizing the mechanical balance between airflow pressure and spring force, the guide vane automatically stabilizes at the preset optimal opening and closing angle under different wind speed conditions. The graded adjustment module uses a return spring with a stiffness coefficient k=3.5 N / mm and a preload force F0=70 N and a graded limit slide, and achieves adaptive angle adjustment through the mechanical balance between airflow pressure and spring force.

[0081] Low wind speed conditions (V < 5 m / s): The stiffness design of the reset spring can reduce the airflow pressure trigger threshold. The airflow pressure overcomes the spring preload and part of the stiffness force, allowing the guide vane to slide along the guide rail to the maximum limit angle of 14°-15° and stabilize, significantly improving the effective camber of the blade and enhancing lift.

[0082] Medium wind speed condition (5m / s≤V≤10m / s): Through the design of the slide and guide rail and the compression of the spring force, the opening angle of the guide vane changes linearly with the wind speed. For every 1m / s increase in wind speed, the angle automatically decreases by 1°-1.2°, stabilizing in the optimal lift-to-drag ratio range of 8°-12°.

[0083] High wind speed conditions (V>10m / s): The airflow pressure continues to increase. When it exceeds the trigger threshold of the return spring (corresponding to the airflow pressure at wind speed V=10m / s), the spring is compressed to the end of its stroke. The guide vane quickly returns to the minimum limit angle <2° along the guide rail and stabilizes, avoiding lift overload.

[0084] Step S2: Real-time acquisition of multi-dimensional operating parameters

[0085] The following operating parameters are synchronously collected and transmitted to the main controller through the multi-dimensional parameter acquisition module:

[0086] Wind speed parameters: collected by an ultrasonic anemometer installed on the top of the nacelle, with a data update frequency of 10Hz, a measurement range of 0-40m / s, and an accuracy of ≤±0.1m / s.

[0087] Among them, wind speed: real-time data is collected by an ultrasonic anemometer, with data of 4m / s, 8m / s, 12m / s, etc., with an accuracy of ±0.08m / s.

[0088] Blade angle of attack parameters: collected by an array of pressure sensors arranged along the blade span, with one set each at 3m, 7m, and 11m from the blade root. Each set includes three pressure sensors: one for the leading edge, one for the upper surface, and one for the lower surface. The real-time angle of attack of each section is calculated using the formula α=arctan[(Pupper - Plower) / (Pfronter - Pstatic)] (Pupper is the pressure on the upper surface, Plower is the pressure on the lower surface, Pfronter is the pressure at the leading edge, and Pstatic is the static pressure at the environment). The measurement accuracy is ≤±0.1°.

[0089] Among them, the blade angle of attack: the pressure sensor array collects pressure data and calculates the angles of attack at 3m, 7m and 11m from the blade root as 8.2°, 8.5° and 8.3° respectively (when V=4m / s), with an average angle of attack of 8.3°.

[0090] Blade load parameters: collected by strain gauge sensors attached to the blade root transition section and key sections of the main beam, with a total of 6 measuring points and a measurement accuracy of ≤±0.1MPa, reflecting the axial and tangential loads and torque of the blade.

[0091] Among them, the blade loads were: 22kN (when V=4m / s), 45kN (when V=8m / s), and 53kN (when V=12m / s) collected by the strain gauge sensor.

[0092] Mechanism status parameters: The real-time stroke of the slide (corresponding to the opening and closing angle of the guide vane) is collected by the displacement sensor installed on the slide, and the vibration amplitude of the mechanism is collected by the vibration sensor. The displacement measurement accuracy is ≤ ±0.1mm, and the vibration measurement accuracy is ≤ ±0.01g.

[0093] The mechanism status is as follows: the displacement sensor collects the slide travel of 35mm (corresponding to 15°), 28mm (corresponding to 12.8°), and 5mm (corresponding to 1.5°), and the vibration sensor collects the vibration amplitude of 0.2g-0.3g, all of which are within the normal range.

[0094] Step S3: Operating Condition Identification and Status Monitoring

[0095] Operating condition identification: Based on preset judgment criteria, low, medium, and high wind speeds, as well as transitional operating conditions, are classified. The specific criteria are as follows: Low wind speed condition: V < 5 m / s, average blade angle of attack < 10.2°, maximum blade load < 0.5F n (F) n For rated load, the 100kW unit is preset to 50kN); medium wind speed conditions: 5m / s≤V≤10m / s, 10.2°≤average blade angle of attack≤15.3°, 0.5F n Maximum blade load ≤ 0.9F n High wind speed conditions: V > 10 m / s, average blade angle of attack ≥ 15.3°, maximum blade load > 0.9F n Among them, V=4m / s is determined to be a low wind speed condition, V=8m / s is determined to be a medium wind speed condition, V=12m / s is determined to be a high wind speed condition, and V increases from 4.8m / s to 5.3m / s to be determined to be a transitional stage of the condition.

[0096] Status monitoring: This function determines whether the slide travel is within the 35mm range corresponding to 0°-15°, whether the travel change rate is ≤5mm / s, and whether the mechanism vibration amplitude is ≤0.5g. Simultaneously, it monitors the signals from the pressure sensor and strain gauge sensor to ensure they are normal. If any values ​​exceed the threshold, the mechanism is considered abnormal or the sensors are faulty. If the slide travel and vibration amplitude are within preset ranges and all sensor signals are normal, the mechanism is considered to be operating normally.

[0097] Step S4: Warning Trigger and Pitch Angle Assist Adjustment

[0098] Based on the operating condition identification and status monitoring results, the main controller triggers a corresponding early warning and controls the pitch angle auxiliary adjustment module to perform adjustment actions. The specific logic is as follows:

[0099] Stall warning and adjustment: When the average blade angle of attack is detected to be ≥13.6° (80% of the stall angle of attack) and the rate of change of angle of attack is >0.5° / s, a stall warning is triggered, and a command is immediately output to adjust the pitch angle to increase by 1°-3° until the average blade angle of attack drops below 13.6° to suppress the aggravation of airflow separation;

[0100] Mechanism fault warning and adjustment: When the slide travel exceeds the preset range, the travel change rate is >5mm / s, or the mechanism vibration amplitude is >0.5g, the mechanism fault warning is triggered (audio-visual alarm + remote communication alarm), and the blade pitch angle is adjusted to increase by 3°-5° to reduce the blade load and avoid damage to the mechanism due to overload;

[0101] Transition phase buffer adjustment: When the blade load fluctuation amplitude is detected to be >15% during the transition phase of the operating condition, the pitch angle is finely adjusted by 0.5°-1° to help buffer the load impact and improve the stability of system operation.

[0102] Sensor fault warning: When any sensor signal is lost or exceeds the range, a sensor fault warning is triggered. The main controller switches to redundant monitoring mode and judges the operating condition based on data from other normal sensors to ensure the basic operation of the system.

[0103] In this embodiment, no stall or malfunction occurred, and the pitch angle was maintained at the initial angle of 5°. If a stall scenario is simulated (V=11m / s, average angle of attack 14°, angle of attack change rate 0.6° / s), the main controller triggers a stall warning, controls the pitch angle to increase by 2° to 7°, and after 1 second the angle of attack drops to 12.5°, and the stall risk is eliminated. Example 3

[0104] To verify the effectiveness of the present invention, a comparative test was conducted on a 100kW distributed wind turbine. The test site was a wind farm in a low-wind-speed area (annual average wind speed 6.2m / s, altitude 150m, atmospheric pressure 101.2kPa), with a Reynolds number range of 3×10⁻⁶. 5 -8×10 5 The testing period was 30 days. The core performance indicators of the traditional purely passive guide vane scheme (control group) and the scheme of this invention (experimental group) were compared. Testing equipment included a power analyzer (accuracy ±0.1%), a dynamic strain gauge, and an ultrasonic anemometer. The testing methods conformed to GB / T 19073-2008 and GB / T 25385-2010 standards. The test results are as follows:

[0105] 1. Performance under low wind speed conditions [V=4m / s]

[0106] Control group: guide vane angle 12°-14°, lift-to-drag ratio 32-35, wind energy capture efficiency 18%-20%, unit output power 3.2kW-3.5kW;

[0107] Experimental group: guide vane angle stable at 15°±0.3°, lift-to-drag ratio 41-43, wind energy capture efficiency 29%-31%, unit output power 5.8kW-6.2kW, efficiency improved by 21%, and output power improved by 81%.

[0108] 2. Performance under medium wind speed conditions [V=8m / s]

[0109] Control group: guide vane angle fluctuation ±1.5°-±2°, lift-to-drag ratio 38-40, load unevenness 18%-22%, unit output power 45kW-48kW, power fluctuation ±5%;

[0110] Experimental group: guide vane angle stable at 12.8°±0.4°, lift-to-drag ratio 39-41, load unevenness 9%-11%, unit output power 52kW-55kW, power fluctuation range ±1.5%, lift-to-drag ratio increased by 5%, and output power increased by 15%.

[0111] 3. High wind speed performance [V=12m / s]

[0112] Control group: The guide vanes did not close completely (angle 3°-5°), the maximum load on the blades was 65kN-70kN, which exceeded the rated load by 30%-40%, and there was obvious stall phenomenon. The unit triggered the overload protection twice.

[0113] Experimental group: With the guide vanes closed to 1.2°-1.8°, the maximum load on the blades was 52kN-55kN, which only exceeded the rated load by 4%-10%. There was no stall phenomenon, and the unit did not trigger the overload protection.

[0114] 4. Performance during the transition phase of the operating condition [V increases from 4.8 m / s to 5.3 m / s]

[0115] Control group: The guide vane angle changed abruptly by 3°-4°, the blade load fluctuated by 15%-18%, the maximum impact load was 58kN, and there was obvious mechanical vibration;

[0116] Experimental group: The guide vane angle transitioned smoothly, the blade load fluctuation range was 10%-12%, the maximum impact load was 45kN, and there was no obvious mechanical vibration.

[0117] 5. Long-term operational stability [30 days of continuous operation]

[0118] Control group: 2 stall alarms, 3 overloads within 30 days, blade vibration acceleration of 0.8g-1.2g, mean time between failures (MTBF) of 82 hours, and total power generation of 12.5MWh;

[0119] Experimental group: No stall alarms or overloads within 30 days, blade vibration acceleration of 0.4g-0.6g, mean time between failures (MTBF) of 208 hours, total power generation of 15.6MWh, power generation increased by 24.8%, and system stability was significantly improved. Example 4

[0120] Biomimetic Composite Airfoil Design and Optimization Methods

[0121] I. Design Goals and Optimization Framework

[0122] This embodiment further details the biomimetic composite design and optimization method of the blade airfoil (i.e., the blade with the guide vane). It is specifically designed for 100kW wind turbines with low Reynolds numbers (Re = 3 × 10⁻⁶). 5 -8×10 5 The operating characteristics are designed with the following objectives: under the premise of ensuring structural reliability (blade weight ≤ 850 kg, fatigue life ≥ 20 years) and controllable cost (cost per blade ≤ 12,000 yuan), the maximum lift coefficient is increased by ≥ 12% and the stall angle of attack is delayed by ≥ 5°.

[0123] II. Multi-objective Cooperative Optimization Based on Genetic Algorithms

[0124] To achieve the aforementioned multi-objective collaborative optimization, a multi-objective genetic algorithm (NSGA-II) was employed for global optimization. The optimization variables included 12 key parameters: maximum airfoil thickness, camber position, chord length gradient coefficient, biomimetic twist gradient, and composite material layup ratio. The algorithm settings were as follows: population size 100, number of iterations 50, crossover probability 0.8, and mutation probability 0.05. The optimal parameter combination was finally obtained through joint simulation using MATLAB and ANSYS (or XFOIL). After optimization, the blade weight was controlled at 820 kg, the maximum lift coefficient increased by 14.5%, and the fatigue life reached 22 years, verifying the effectiveness of the algorithm in solving complex aerodynamic problems with multiple coupled parameters at low Reynolds numbers.

[0125] III. Specific Design of Bionic Composite Airfoils

[0126] The basic airfoil is designed based on biomimetic prototypes such as albatross wings. The leading edge is rounded (leading edge radius 0.08C, where C is the local chord length), and the trailing edge is thin and sharp (trailing edge thickness 0.02C). The maximum thickness is located at 25%-30% of the chord length to adapt to the airflow adhesion requirements at low Reynolds numbers.

[0127] Based on this, a composite design combining "biomimetic gradient twist angle" and "large trailing edge curvature" is adopted:

[0128] 1. Biomimetic Gradient Twist Angle: Mimicking whale fins, the twist angle gradually changes from the blade root to the blade tip. Key control points are set at 3m, 7m, and 11m from the blade root, with twist angles of 14°, 8°, and 4° respectively. This design enables the blade to generate greater starting torque at low wind speeds and automatically adjust the angle of attack to control the load at high wind speeds.

[0129] 2. Large trailing edge curvature design: The maximum curvature is located at approximately 2 / 3 of the chord length, and the trailing edge thickness accounts for approximately 10%. This design significantly improves the lift coefficient and lift-to-drag ratio by optimizing pressure distribution.

[0130] IV. Integrated Synergy with Adaptive Guide Vanes

[0131] 1. In low wind speed conditions: The large camber and gradient twist angle of the airfoil provide a high lift foundation; at the same time, the guide vanes are fully open (15°) under the action of springs, further guiding the airflow and delaying separation, jointly overcoming the start-up problem.

[0132] 2. In medium to high wind speed conditions: The excellent stall characteristics of the airfoil itself (retarded by 5°) are the basic guarantee; the guide vane linearly reduces the opening or closes as the wind speed increases, dynamically and finely controlling the boundary layer, forming a "active and passive" flow control with the airfoil design, realizing the optimization of lift-to-drag ratio and load smoothing across the entire wind speed range.

[0133] The optimization process of the genetic algorithm has fully considered the aerodynamic interference effect of the airfoil, ensuring the optimal matching of the parameters of the airfoil body and the auxiliary device.

[0134] In summary, the present invention significantly improves wind energy capture efficiency and operational stability under low Reynolds number conditions through the coordinated design of graded adjustment and adaptation and multi-parameter monitoring and auxiliary control, while taking into account structural simplification and cost advantages, and is suitable for 100kW-class low wind speed distributed wind turbines.

[0135] To facilitate better implementation of the wind power generation efficiency optimization control method of this application, this application also provides a wind power generation efficiency optimization control device. Please refer to... Figure 5 The figure is a schematic diagram of the structure of the wind power generation efficiency optimization control device provided in an embodiment of this application. The wind power generation efficiency optimization control device 200 may include:

[0136] The adjustment unit 201 is used to realize the passive adaptive adjustment of the guide vane through the graded adjustment module, so that the guide vane automatically stabilizes at the preset optimal opening and closing angle corresponding to the current wind speed condition under the mechanical balance of airflow pressure and spring force.

[0137] The acquisition unit 202 is used to acquire wind speed, angle of attack of each blade section, blade load and status parameters of the graded adjustment module in real time through the multi-dimensional parameter acquisition module.

[0138] The monitoring unit 203 is used to identify the operating conditions and monitor the status based on the collected operating parameters; the operating condition identification includes determining whether the fan is in a low wind speed condition, a medium wind speed condition, a high wind speed condition, or a transitional stage of the operating conditions; the status monitoring includes determining whether the stroke position and vibration amplitude of the graded adjustment module exceed the preset threshold.

[0139] The judgment unit 204 is used to make a performance adaptation judgment based on the working condition identification and monitoring results. If the blade angle of attack is ≥13.6° and the rate of change of angle of attack is >0.5° / s, or the state of the graded adjustment module is abnormal, an early warning is triggered and the pitch angle auxiliary adjustment is executed.

[0140] Each unit in the aforementioned wind power generation efficiency optimization control device can be implemented entirely or partially through software, hardware, or a combination thereof. These units can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each unit.

[0141] The wind power generation efficiency optimization control device 200 can be integrated into a terminal or server that has storage and a processor and thus computing power, or the wind power generation efficiency optimization control device 200 can be the terminal or server.

[0142] Optionally, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0143] This application also provides a computer-readable storage medium for storing a computer program. This computer-readable storage medium can be applied to a computer device, and the computer program causes the computer device to execute the corresponding processes in the wind power generation efficiency optimization control method of the embodiments of this application; for the sake of brevity, these will not be elaborated further here.

[0144] This application also provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the corresponding process in the wind power generation efficiency optimization control method of this application embodiment. For simplicity, further details are omitted here.

[0145] This application also provides a computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the corresponding process in the wind power generation efficiency optimization control method of this application. For brevity, further details are omitted here.

[0146] It should be understood that the processor in this application may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0147] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0148] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0149] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0150] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0152] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, the functional units in this application 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.

[0154] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer or a server) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0155] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0156] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions above are merely illustrative of the principles of the invention. Various changes and modifications can be made to the present invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents. Any aspects not detailed in the present invention are well-known to those skilled in the art.

Claims

1. A wind power generation efficiency optimization control system, characterized in that, include: The graded adjustment module includes a reset spring (3) and a graded limiting slide installed between the guide vane (1) and the blade body (2), which are used to utilize the mechanical balance between airflow pressure and spring force to make the guide vane passively and adaptively stabilize at the preset optimal opening and closing angle under different wind speeds. A multi-dimensional parameter acquisition module is used to collect wind speed, angle of attack of each blade section, blade load, and status parameters of the graded adjustment module in real time. The operating condition identification and status monitoring module is used to receive signals from the multi-dimensional parameter acquisition module, identify the operating condition of the wind turbine according to the preset judgment criteria, and evaluate the operating status of the graded adjustment module. The pitch angle auxiliary control module is used to output adjustment commands to adjust the wind turbine pitch angle after receiving a warning signal; The main controller is connected to the multi-dimensional parameter acquisition module, the working condition identification and status monitoring module and the pitch angle auxiliary control module, respectively, and is used to coordinate data acquisition, processing, working condition judgment and trigger corresponding early warning and control commands. The stiffness coefficient of the return spring (3) is 3.5 N / mm, and the preload F0 is 70 N; both the guide vane and the blade body are provided with placement slots (4) for placing the return spring (3), and the two ends of the return spring (3) are fixed in the placement slots (4) of the guide vane (1) and the blade body (2) respectively. The graded limiting slide includes a guide rail (5) and a slide (6). The slide (6) is installed on the guide vane (1) and is clearance-fitted with the guide rail (5). The travel of the guide rail (5) is L=35mm, corresponding to the opening and closing angle range of the guide vane (1) from 0° to 15°.

2. The wind power generation efficiency optimization control system according to claim 1, characterized in that, The multi-dimensional parameter acquisition module includes: an ultrasonic anemometer installed on the top of the cabin, used to collect wind speed, with a measurement range of 0-40m / s; An array of pressure sensors arranged along the blade span is used to collect pressure distribution on the blade surface to calculate the angle of attack of each section; Strain gauge sensors are attached to the blade root and key sections of the main beam to collect blade loads; The displacement sensor and vibration sensor installed on the slide (6) are used to collect the real-time stroke, stroke change rate and vibration amplitude of the slide (6).

3. The wind power generation efficiency optimization control system according to claim 2, characterized in that, The pressure sensor array is set up at 3m, 7m and 11m from the blade root, and each set includes 3 pressure sensors on the leading edge, upper surface and lower surface; The displacement sensor is a linear potentiometer type displacement sensor with a measurement range of 0-35mm. The vibration sensor is a piezoelectric vibration sensor with a measurement range of 0-5g.

4. The wind power generation efficiency optimization control system according to claim 1, characterized in that, The main controller is a PLC controller with an operation cycle of ≤10ms, a built-in fault diagnosis algorithm, and records the long-term operating status data of the graded adjustment module.

5. A method for optimizing and controlling the efficiency of wind power generation, characterized in that: The system described in any one of claims 1-4 is used to perform the following steps: S1: The passive adaptive adjustment of the guide vane is achieved through the graded adjustment module, so that the guide vane automatically stabilizes at the preset optimal opening and closing angle corresponding to the current wind speed condition under the mechanical balance of airflow pressure and spring force. S2: The multi-dimensional parameter acquisition module collects wind speed, angle of attack of each blade section, blade load, and status parameters of the graded adjustment module in real time. S3: Based on the operating parameters collected in step S2, perform operating condition identification and status monitoring; the operating condition identification includes determining whether the fan is in a low wind speed condition, medium wind speed condition, high wind speed condition, or a transitional stage; the status monitoring includes determining whether the stroke position and vibration amplitude of the graded adjustment module exceed the preset threshold. S4: Based on the identification and monitoring results of step S3, a performance adaptation judgment is made. If the blade angle of attack is ≥13.6° and the rate of change of angle of attack is >0.5° / s, or the state of the graded adjustment module is abnormal, an early warning is triggered and the pitch angle auxiliary adjustment is executed.

6. The wind power generation efficiency optimization control method according to claim 5, characterized in that: The passive adaptive adjustment of the graded adjustment module in step S1 is specifically as follows: Under low wind speed conditions, the airflow pressure overcomes the spring preload and part of the stiffness force, and the opening and closing angle of the guide vanes remains stable at 14°-15°. Under medium wind speed conditions, the opening angle of the guide vanes decreases linearly with increasing wind speed and remains stable in the range of 8°-12°. Under high wind speed conditions, the spring is compressed to the end of its stroke, and the guide vane returns to its opening angle of <2° and remains stable.

7. The wind power generation efficiency optimization control method according to claim 5, characterized in that: The specific criteria for determining the working condition in step S3 are as follows: Low wind speed conditions: Real-time wind speed V < 5 m / s, average blade angle of attack < 10.2°, and maximum blade load < 0.5F. n ; Medium wind speed conditions: 5 m / s ≤ V ≤ 10 m / s, and 10.2° ≤ average blade angle of attack ≤ 15.3°, and 0.5F n Maximum blade load ≤ 0.9F n ; High wind speed conditions: V > 10 m / s, average blade angle of attack ≥ 15.3°, and maximum blade load > 0.9F. n ; Transitional operating condition phase: The real-time wind speed fluctuates within the boundary of the adjacent operating condition by an amplitude of ≥ ±0.5 m / s and lasts for ≥ 3 s, or the blade angle of attack fluctuates within an amplitude of ≥ ±1° and lasts for ≥ 2 s.

8. The wind power generation efficiency optimization control method according to claim 5, characterized in that: The specific logic for the early warning and pitch angle auxiliary adjustment mentioned in step S4 is as follows: When the average angle of attack of the blades is ≥13.6° and the rate of change of angle of attack is >0.5° / s, a stall warning is triggered, and the pitch angle is increased by 1°-3°. When the sliding block travel exceeds the preset range of 0°-15°, the travel change rate is greater than 5mm / s, or the vibration amplitude of the mechanism is greater than 0.5g, a mechanism fault warning is triggered, and the propeller pitch angle is increased by 3°-5°. When the blade load fluctuation amplitude is detected to be greater than 15% during the transition phase of the operating condition, the pitch angle is finely adjusted by 0.5°-1° to buffer the load impact.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted for loading by a processor to execute the wind power generation efficiency optimization control method as described in any one of claims 5-8.

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