Wind turbine generator multi-parameter cooperative control method considering air density change

Abstract

The invention provides a wind turbine generator multi-parameter cooperative control method considering air density change. According to the method, boundaries of an upper threshold value and a lower threshold value of the air density are found out through simulation calculation in a design stage, a combined control method for variable pitch, yaw, rotating speed, torque and the like of a wind turbine generator within the upper threshold value of the air density and a control method for control parameters such as a minimum pitch angle, variable pitch, rotating speed, torque and the like of the lower threshold value of the air density are obtained. By means of the method, the probability of accidents such as blade tower sweeping and tower falling of the wind turbine generator under high air density such as cold waves can be reduced, and meanwhile the power generation efficiency of the wind turbine generator is improved as much as possible when the air density is low in summer.

Description

Technical Field

[0001] This invention relates to the field of wind turbine optimization technology, and in particular to a multi-parameter collaborative control method for wind turbines that takes into account changes in air density. Background Technology

[0002] Wind turbines, as core power generation equipment in renewable energy systems, are widely used in onshore and offshore wind farms. Their operational performance directly impacts the economic benefits and equipment safety of wind farms. Related technologies typically rely on the International Electrotechnical Commission (IEC) standards 61400-1 and 61400-3, using a fixed annual average air density as the benchmark for wind turbine load calculation and control strategy design. Specifically, this technical system covers the entire process from wind energy capture and aerodynamic load analysis to electrical control, including key aspects such as pitch control, yaw regulation, and generator torque optimization. Air density, as a crucial environmental parameter affecting the aerodynamic performance of the wind turbine and structural loads, poses a significant challenge to the unit's operational stability and power generation efficiency due to its dynamic changes.

[0003] However, existing wind turbine control methods generally employ fixed air density or estimation models based on simple temperature and air pressure, failing to fully consider the significant impact of humidity on air density, and lacking multi-parameter collaborative control strategies covering extreme air density conditions. Specifically, when air density is significantly higher than the design value, blade thrust increases sharply, easily leading to tower sweeping, tower resonance, or even tower collapse. Conversely, when air density is lower than the annual average, rotor capture efficiency decreases, and the turbine cannot reach its nominal power output above rated wind speed, impacting power generation revenue. Based on this, while existing technologies have explored power regulation, such as GE patents US20180106279A1 and CN116950837A, their control methods are simplistic and struggle to achieve an effective balance between safety and power generation efficiency. Especially under combined extreme weather conditions, system stability and responsiveness are significantly insufficient. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the first objective of this invention is to propose a multi-parameter collaborative control method for wind turbines that takes into account changes in air density.

[0006] The second objective of this invention is to propose a multi-parameter collaborative control device for wind turbines that takes into account changes in air density.

[0007] The third objective of this invention is to provide an electronic device.

[0008] The fourth objective of this invention is to provide a computer-readable storage medium.

[0009] The fifth objective of this invention is to provide a computer program product.

[0010] To achieve the above objectives, a first aspect of the present invention proposes a multi-parameter coordinated control method for wind turbine generators that considers changes in air density, comprising: S1, based on the wind turbine load calculation software, with the goal of minimizing the calculated load of the wind turbine and the minimum blade clearance to the design value and achieving optimal power generation efficiency, simulates and calculates the combination of control parameters under different air densities. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle; S2, acquire temperature, air pressure and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in S1. S3, when the real-time air density is higher than the annual average air density, the following control strategies are executed in sequence: first, adjust the optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI parameters; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow. S4. When the real-time air density is lower than the annual average air density, the rated speed of the wind turbine is increased to V1. The maximum increase ratio is determined by ensuring that the overall load and the minimum clearance of the blades meet the design requirements after the speed is increased.

[0011] Optionally, the software for calculating the overall load of the wind turbine, aiming to minimize the calculated load and blade clearance of the wind turbine to the design value and achieve optimal power generation efficiency, further includes the simulation calculation of control parameter combinations under different air densities: The upper and lower boundaries of the air density are set according to the extreme low and high temperature conditions that may occur during the design life of the wind turbine, wherein the calculation step of the air density is 0.02~0.05 kg / m³. The process of determining the combination of control parameters includes multi-parameter collaborative optimization of pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw wind angle, gust adjustment PI parameters, turbulence adjustment PI parameters, torque optimal gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle, in order to achieve the comprehensive optimization of aerodynamic load, structural safety, and power generation efficiency.

[0012] Optionally, acquiring temperature, air pressure, and humidity data at the wheel hub height, and calculating real-time air density based on the data, further includes: The air density under humid conditions is calculated using formula (1), where formula (1) is:

[0013] In the formula This indicates the air density under humid conditions. Atmospheric pressure at wheel hub height; This represents the gas constant of dry air; This indicates the actual absolute temperature at the wheel hub height. ; This indicates the actual measured temperature at the wheel hub height. This represents the actual water vapor pressure. ; This represents the saturated water vapor pressure based on the Tertens formula; Indicates relative humidity; When humidity data is missing, air density is calculated using formula (2), where formula (2) is:

[0014] In the formula This indicates the air density at the height of the wheel hub.

[0015] Optionally, when the real-time air density is higher than the annual average air density, the following control strategy is executed sequentially, further including: Based on the measured temperature, air pressure, and humidity at the wheel hub height, the real-time air density at the wheel hub height is calculated. ,when At the same time, referring to the relationship between air density and control parameters in S1, the optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI and generator torque PI parameters are adjusted in real time. For wind turbines in normal power generation, when the real-time air density continues to increase and the simulated wind turbine load and blade minimum clearance do not meet the design requirements after adjusting the pitch PI, torque PI, transmission chain resistance PI and generator torque PI parameters, pitch can be adjusted in advance by increasing the blade minimum pitch angle. The increase in the minimum pitch angle is determined by the simulation result being less than or equal to the design value. For wind turbines in normal power generation, when the real-time air density continues to increase and the simulated wind turbine load and minimum blade clearance are still greater than the design value after adjusting the pitch PI, torque PI, transmission chain resistance PI and generator torque PI parameters, the wind turbine load and minimum blade clearance are yawed to other angles to reduce the wind speed of the wind turbine inflow. For wind turbines in normal power generation, when the real-time air density continues to increase, the turbine is yawed to other angles to reduce the wind speed of the incoming wind turbine. The yaw angle value is determined by the wind turbine load and the minimum clearance of the blades meeting the design requirements.

[0016] For wind turbines operating in high wind conditions after reaching their rated power, the rated power should be reduced. The preferred method is to reduce the rated speed, and the second best method is to reduce the rated torque.

[0017] Optional, also includes: When the wind turbine does not have weather forecasting or feedforward wind measurement functions, the control parameters are automatically updated at fixed time intervals to adapt to the slow changing trend of air density. When wind turbines have weather forecasting or feedforward wind measurement functions, control parameters are updated in advance based on the predicted air density change trend.

[0018] To achieve the above objectives, a second aspect of the present invention provides a multi-parameter coordinated control device for wind turbine generators that considers changes in air density, comprising: The control parameter simulation module is used to simulate and calculate the combination of control parameters under different air densities based on the wind turbine load calculation software, with the goal of minimizing the calculated load of the wind turbine and the minimum blade clearance to the design value and achieving optimal power generation efficiency. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle. The air density calculation module is used to acquire temperature, air pressure and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in the control parameter simulation module. The high-density control strategy module is used to execute the following control strategies in sequence when the real-time air density is higher than the annual average air density: First, adjust the parameters of optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow. The low-density control strategy module is used to increase the rated speed of the wind turbine to V1 when the real-time air density is lower than the annual average air density. The maximum increase ratio is determined by the fact that the overall load and the minimum blade clearance meet the design requirements after the speed is increased.

[0019] To achieve the above objectives, a third aspect of the present invention provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0020] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of the first aspects.

[0021] To achieve the above objectives, a fifth aspect of the present invention provides a computer program product that, when executed by a processor, implements the method described in any one of the first aspects.

[0022] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0023] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a multi-parameter coordinated control method for wind turbines that considers changes in air density, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the reduction of the rated power of a wind turbine generator under high wind conditions after it has reached its rated power, as provided in this embodiment of the invention. Figure 3 This is a schematic diagram illustrating the improvement of wind turbine speed with low air density provided in an embodiment of the present invention; Figure 4 A comparison diagram of blade tip clearance under different air densities and control methods under a certain gust of wind, provided in an embodiment of the present invention; Figure 5 This is a comparison chart of wind turbine speeds under different air densities and control methods under a certain gust of wind, provided in an embodiment of the present invention. Detailed Implementation

[0024] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0025] Figure 1 This is a flowchart illustrating a multi-parameter coordinated control method for wind turbines that considers changes in air density, provided in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps: S1, based on the wind turbine load calculation software, aims to achieve the calculated load of the wind turbine and the minimum blade clearance less than the design value, and the optimal power generation efficiency. It simulates and calculates the combination of control parameters under different air densities. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle.

[0026] In this embodiment, based on wind turbine load calculation software, the goal is to ensure that the calculated load and minimum blade clearance of the wind turbine are less than the design values, while optimizing power generation efficiency. To this end, the system simulates and calculates combinations of control parameters under different air densities to ensure that the wind turbine performance reaches its optimal level within its design life.

[0027] Specific combinations of control parameters include, but are not limited to: pitch PI parameters, torque PI parameters, drive train resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against wind, gust adjustment PI parameters, turbulence adjustment PI parameters, torque optimal gain Kopt, power limiting control parameters, speed, power, minimum pitch angle, etc.

[0028] This embodiment is designed based on international standards such as IEC61400-1, IEC61400-3, and GL. By adhering to these standards, the wind turbine's control system can ensure that its load and headroom results are less than design values, thereby improving its power generation efficiency. The calculation results also consider variations under different air density conditions. To accurately simulate wind turbine operation under different climatic conditions, the air density calculation step size in this embodiment is set to 0.02~0.05 kg / m³, to cover extreme low temperatures (leading to maximum air density) and extreme high temperatures (leading to minimum air density) that may occur during the wind turbine's design life.

[0029] Based on the above parameter combinations, the software can calculate the optimal control parameters through simulation under different air densities, thus providing a theoretical basis for the stable operation and optimal power generation efficiency of wind turbines. By adjusting the control parameters, especially the PI controller, wind turbines can operate stably in various environments, minimizing mechanical load and maximizing energy efficiency.

[0030] This embodiment, through rigorous parameter selection and calculation, not only ensures the safety of the wind turbine unit, but also optimizes its power generation efficiency in various environments, providing technical support for the efficient utilization and sustainable development of wind energy.

[0031] S2: Obtain temperature, air pressure, and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in S1.

[0032] In this embodiment of the invention, the wind turbine adjusts the input signal based on the control parameters of dynamic air density changes: temperature, air pressure, and humidity at the hub height.

[0033] The preferred formula for calculating air density is based on actual air humidity, where formula (1) is:

[0034] In the formula This indicates the density of air under humid conditions, expressed in kg / m³. Atmospheric pressure at wheel hub height, Pa; This represents the gas constant for dry air, 287.1. ; This indicates the actual absolute temperature at the wheel hub height. K; This indicates the actual measured temperature at the wheel hub height. ; This represents the actual water vapor pressure. ; This represents the saturated water vapor pressure, expressed in Pa, based on the Tertens formula. Represents relative humidity, dimensionless.

[0035] When humidity data is missing, air density is calculated using formula (2), where formula (2) is:

[0036] In the formula This indicates the air density at the height of the wheel hub.

[0037] S3, when the real-time air density is higher than the annual average air density, the following control strategies are executed in sequence: first, adjust the optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI parameters; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow.

[0038] In this embodiment, when the real-time air density is higher than the annual average air density, the system will sequentially execute a series of control strategies to ensure that the wind turbine can still meet the design load, minimum clearance requirements, and optimize power generation efficiency under different environmental conditions. The specific control strategies are as follows: First, this embodiment of the invention will calculate the real-time air density at the wheel hub height based on the measured temperature, air pressure, and humidity. ,when At that time, referring to the relationship between air density and control parameters in S1, the optimal speed gain Kopt, pitch PI, torque PI, transmission chain resistance PI and generator torque PI parameters are adjusted in real time.

[0039] Under normal power generation conditions, when the real-time air density continues to increase, and after adjusting parameters such as pitch PI, torque PI, drivetrain resistance PI, and generator torque PI, the simulated load and minimum blade clearance of the wind turbine still cannot meet the design requirements, the system will increase the minimum blade pitch angle to achieve earlier pitch adjustment. This adjusted minimum pitch angle value will be compared with the design value through simulation results to ensure that the adjusted pitch angle does not exceed the design requirements.

[0040] If, after the above adjustments, the wind turbine load and blade clearance still fail to meet design requirements, the system will perform a yaw operation to change the rotor angle, thereby reducing the incoming wind speed and further optimizing the turbine's operating status. The yaw angle adjustment will be determined based on whether the wind turbine load and minimum blade clearance meet design requirements.

[0041] In addition, such as Figure 2 As shown, for wind turbine units operating under high wind conditions, when the unit reaches its rated power, the system will take measures to reduce the rated power of the unit to avoid overload operation. In this process, the preferred method is to first reduce the rated speed, followed by reducing the rated torque. The power reduction method can be set to linear reduction, stepped reduction, or other non-linear methods according to actual conditions to ensure that the unit can still operate safely and stably in high wind environments.

[0042] In addition, when the wind turbine is in idling or shutdown condition, and the air density exceeds the average air density, the yaw angle of the wind turbine should be determined based on the specific operating conditions. When the grid loses power, the unit should also have a backup power supply to maintain the yaw state.

[0043] S4. When the real-time air density is lower than the annual average air density, the rated speed of the wind turbine is increased to V1. The maximum increase ratio is determined by ensuring that the overall load and the minimum clearance of the blades meet the design requirements after the speed is increased.

[0044] In the embodiments of this application, such as Figure 3As shown, when the real-time air density is lower than the annual average air density, the system will increase the rated speed of the wind turbine to V1. Specifically, the speed increase will be adjusted based on the actual air density and the turbine's operating conditions. The maximum increase ratio is determined by two factors: first, whether the overall load can be maintained within the design range after increasing the speed; and second, whether the minimum clearance of the blades meets the design requirements.

[0045] The system adjusts the rated speed of the wind turbine by monitoring changes in air density in real time. As the speed increases, the system continues to simulate and calculate the load and clearance of the wind turbine to ensure that, under the new operating conditions, the overall load and minimum blade clearance of the wind turbine do not exceed the design values. If the increase in speed causes the load and clearance to exceed the design range, the system will adjust the increase in speed appropriately based on the simulation results to ensure that the unit operates within a safe and efficient range.

[0046] This adjustment mechanism can effectively address the issue of improving power generation efficiency under low air density conditions. By reasonably increasing the rotational speed, it can further enhance the power generation capacity of wind turbines while avoiding mechanical load problems or insufficient clearance caused by excessively high rotational speeds, thereby achieving the optimal performance of wind turbines under different air density conditions.

[0047] Furthermore, in this embodiment, the control system will adopt different strategies to adjust the control parameters for different wind turbine configurations in order to adapt to changes in air density and thus optimize the operation of the turbine.

[0048] When the wind turbine lacks weather forecasting or feedforward wind measurement capabilities, the system automatically updates its control parameters at fixed time intervals. In this way, the system can adapt to slow changes in air density. For example, air density gradually changes with seasonal variations or long-term fluctuations in climate conditions. By periodically updating control parameters such as pitch PI, torque PI, and drivetrain resistance PI, the system ensures that the wind turbine maintains efficient and stable operation even under climate change conditions.

[0049] On the other hand, when wind turbines are equipped with weather forecasting or feedforward wind measurement capabilities, the system will update control parameters in advance based on predicted air density change trends. With the help of weather forecasting or feedforward wind measurement technology, the system can anticipate changes in air density over a future period, thus adjusting control parameters in time before these changes occur. This proactive adjustment can significantly improve the adaptability and power generation efficiency of wind turbines, especially in responding to sudden weather changes or seasonal variations, allowing for advance preparation and avoiding potential risks or energy efficiency losses caused by unforeseen weather events.

[0050] In summary, by adaptively updating control parameters under different functional conditions, it is possible to ensure that wind turbines are always in optimal operating condition, whether through regular updates to cope with slow changes or through predictive updates to anticipate weather changes, thereby maximizing power generation efficiency and ensuring the long-term stable operation of the units.

[0051] The following uses the changes in minimum tip clearance and rotational speed of a 2MW turbine as an example to illustrate the content of this invention. The turbine blade length is 56m, hub height is 100m, rated rotational speed is 14rpm, and minimum pitch angle is -1deg. The changes in rotational speed and minimum tip clearance of the turbine under a certain gust of wind are calculated and compared when the air density is 1.12kg / m³ (minimum air density), 1.225kg / m³ (annual average air density), and 1.35kg / m³ (maximum air density). The comparison of minimum tip clearance is shown in [link to relevant documentation]. Figure 4 As shown in Table 1, the wind turbine speeds are compared. Figure 5 As shown in Table 2.

[0052] Table 1. Comparison of Minimum Tip Clearance under Different Air Densities and Control Methods under a Certain Gust Wind Condition

[0053] As shown in Table 1, with the increase of air density, specifically from an annual average air density of 1.225-1.35 kg / m³ to 1.35 kg / m³, the minimum blade tip clearance under this gust wind condition decreases from 5.338 m to 4.78 m, a reduction of 0.558 m, significantly increasing the risk of blade sweeping to the tower. By adjusting the pitch ratio (PI) parameter (increasing the pitch proportional coefficient Kp from 1.56 to 1.76), the minimum blade tip clearance at an air density of 1.35 kg / m³ increases from 4.780 m to 4.803 m, showing a slight increase. Further increasing the minimum pitch angle corresponding to an air density of 1.35 kg / m³ from -1 degree to 1 degree increases the minimum blade tip clearance to 6.345 m, an increase of 1.542 m, or 32.1%, greatly reducing the risk of tower sweeping.

[0054] Table 2. Maximum wind turbine speed under different air densities and control methods under a certain gust wind condition.

[0055] Table 2 shows that as air density increases, the thrust on the wind turbine increases. Under a certain gust of wind, the maximum speed of the wind turbine increases from 14.46 rpm to 14.56 rpm, an increase of about 0.1 rpm. After adjusting the pitch PI parameter (the pitch proportional coefficient Kp is increased from 1.56 to 1.76), the maximum speed of the wind turbine decreases to 14.51 rpm. After further adjusting the pitch angle, the maximum speed of the wind turbine decreases to 14.09 rpm. The reduction in the maximum speed of the wind turbine has a positive effect on the overspeed control of the unit, aeroelastic stability, blade clearance, and unit load.

[0056] To achieve the above embodiments, the present invention also proposes a multi-parameter coordinated control device for wind turbines that considers changes in air density. This device includes: The control parameter simulation module is used to simulate and calculate the combination of control parameters under different air densities based on the wind turbine load calculation software, with the goal of minimizing the calculated load of the wind turbine and the minimum blade clearance to the design value and achieving optimal power generation efficiency. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle. The air density calculation module is used to acquire temperature, air pressure and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in the control parameter simulation module. The high-density control strategy module is used to execute the following control strategies in sequence when the real-time air density is higher than the annual average air density: First, adjust the parameters of optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow. The low-density control strategy module is used to increase the rated speed of the wind turbine to V1 when the real-time air density is lower than the annual average air density. The maximum increase ratio is determined by the fact that the overall load and the minimum blade clearance meet the design requirements after the speed is increased.

[0057] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0058] To implement the above embodiments, the present invention also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0059] To implement the above embodiments, the present invention also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0060] To implement the above embodiments, the present invention also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0061] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this invention all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0062] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0063] This invention is intended to provide implementation schemes for users to selectively prevent the use or access to personal information data. That is, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0064] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0065] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0066] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0067] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0068] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0069] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0070] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0071] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0072] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0073] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A multi-parameter coordinated control method for wind turbine generators considering changes in air density, characterized in that, include: S1, based on the wind turbine load calculation software, with the goal of minimizing the calculated load of the wind turbine and the minimum blade clearance to the design value and achieving optimal power generation efficiency, simulates and calculates the combination of control parameters under different air densities. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle; S2, acquire temperature, air pressure and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in S1. S3, when the real-time air density is higher than the annual average air density, the following control strategies are executed in sequence: first, adjust the optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI parameters; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow. S4. When the real-time air density is lower than the annual average air density, the rated speed of the wind turbine is increased to V1. The maximum increase ratio is determined by ensuring that the overall load and the minimum clearance of the blades meet the design requirements after the speed is increased.

2. The method as described in claim 1, characterized in that, The wind turbine load calculation software, with the goal of minimizing the calculated load and blade clearance of the wind turbine to the design value and achieving optimal power generation efficiency, simulates and calculates control parameter combinations under different air densities, and also includes: The upper and lower boundaries of the air density are set according to the extreme low and high temperature conditions that may occur during the design life of the wind turbine, wherein the calculation step of the air density is 0.02~0.05 kg / m³. The process of determining the combination of control parameters includes multi-parameter collaborative optimization of pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw wind angle, gust adjustment PI parameters, turbulence adjustment PI parameters, torque optimal gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle, in order to achieve the comprehensive optimization of aerodynamic load, structural safety, and power generation efficiency.

3. The method as described in claim 1, characterized in that, The process of acquiring temperature, air pressure, and humidity data at the wheel hub height, and calculating real-time air density based on the data, further includes: The air density under humid conditions is calculated using formula (1), where formula (1) is: In the formula This indicates the air density under humid conditions. Atmospheric pressure at wheel hub height; This represents the gas constant of dry air; This indicates the actual absolute temperature at the height of the wheel hub. ; This indicates the actual measured temperature at the wheel hub height. This represents the actual water vapor pressure. ; This represents the saturated water vapor pressure based on the Tertens formula; Indicates relative humidity; When humidity data is missing, air density is calculated using formula (2), where formula (2) is: In the formula This indicates the air density at the height of the wheel hub.

4. The method as described in claim 1, characterized in that, When the real-time air density is higher than the annual average air density, the following control strategies are executed sequentially, including: Based on the measured temperature, air pressure, and humidity at the wheel hub height, the real-time air density at the wheel hub height is calculated. ,when At the same time, referring to the relationship between air density and control parameters in S1, the optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI and generator torque PI parameters are adjusted in real time. For wind turbines in normal power generation conditions, when the real-time air density continues to increase and the simulated wind turbine load and blade minimum clearance do not meet the design requirements after adjusting the pitch PI, torque PI, transmission chain resistance PI and generator torque PI parameters, pitch can be adjusted in advance by increasing the blade minimum pitch angle. The increase in the minimum pitch angle is determined by the simulation result being less than or equal to the design value. For wind turbines in normal power generation, when the real-time air density continues to increase and the simulated wind turbine load and minimum blade clearance are still greater than the design value after adjusting the pitch PI, torque PI, transmission chain resistance PI and generator torque PI parameters, the wind turbine can be yawed to other angles by yaw to reduce the wind speed of the incoming wind turbine. For wind turbines in normal power generation, when the real-time air density continues to increase, the turbine is yawed to other angles to reduce the wind speed of the incoming wind turbine. The yaw angle value is determined by the wind turbine load and the minimum clearance of the blades meeting the design requirements. For wind turbines operating in high wind conditions after reaching their rated power, the rated power should be reduced. The preferred method is to reduce the rated speed, and the second best method is to reduce the rated torque.

5. The method as described in claim 1, characterized in that, Also includes: When the wind turbine does not have weather forecasting or feedforward wind measurement functions, the control parameters are automatically updated at fixed time intervals to adapt to the slow changing trend of air density. When wind turbines have weather forecasting or feedforward wind measurement functions, control parameters are updated in advance based on the predicted air density change trend.

6. A multi-parameter coordinated control device for wind turbine generators that considers changes in air density, characterized in that, include: The control parameter simulation module is used to simulate and calculate the combination of control parameters under different air densities based on the wind turbine load calculation software, with the goal of minimizing the calculated load of the wind turbine and the minimum blade clearance to the design value and achieving optimal power generation efficiency. The control parameters include pitch PI parameters, torque PI parameters, transmission chain resistance PI parameters, tower front-to-back and lateral vibration PI parameters, yaw angle against the wind, gust adjustment PI parameters, turbulence adjustment PI parameters, optimal torque gain Kopt, power limiting control parameters, speed, power, and minimum pitch angle. The air density calculation module is used to acquire temperature, air pressure and humidity data at the hub height, calculate real-time air density based on the data, and dynamically adjust the control parameters of the wind turbine according to the mapping relationship between the real-time air density and the control parameter combination established in the control parameter simulation module. The high-density control strategy module is used to execute the following control strategies in sequence when the real-time air density is higher than the annual average air density: First, adjust the parameters of optimal speed gain Kopt, pitch PI, torque PI, drive train resistance PI, and generator torque PI; if the design load and clearance requirements are still not met after adjustment, increase the minimum pitch angle to achieve early pitch control; if the requirements are still not met, adjust the yaw angle to reduce the wind speed of the wind turbine inflow. The low-density control strategy module is used to increase the rated speed of the wind turbine to V1 when the real-time air density is lower than the annual average air density. The maximum increase ratio is determined by the fact that the overall load and the minimum blade clearance meet the design requirements after the speed is increased.

7. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

9. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-6.

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