CN117803521B - Anti-icing method and system for fan blade, electronic equipment and storage medium - Google Patents

Abstract

The present application discloses a method, system, electronic device and storage medium for preventing icing of wind turbine blades. The method comprises: obtaining environmental variable data in real time, obtaining a threshold value of icing quality of wind turbine blades and a set value of wind turbine state variables, determining a danger range according to the threshold value of icing quality of wind turbine blades and the set value of wind turbine state variables, comparing the environmental variable data with the determined danger range, judging whether the environmental variable data falls into the danger range, and if the environmental variable data falls into the danger range, using the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, using the first preset value as the target blade pitch angle reference value, and then adjusting the blades of the wind turbine according to the determined target blade pitch angle reference value. Actively adjusting the pitch angle of the wind turbine blades according to environmental information improves the anti-icing effect of the wind turbine blades. The embodiments of the present invention can be widely applied to the field of anti-icing processing technology.

Description

A method, system, electronic device and storage medium for preventing ice accumulation on fan blades

Technical Field

The present invention relates to the technical field of anti-icing treatment, and in particular to a method, system, electronic equipment and storage medium for anti-icing of fan blades.

Background technique

Wind power generation has developed rapidly and has gradually become a research hotspot in the field of new energy. Wind power generation generates electricity by driving the blades of wind turbines to rotate. Due to the location of wind resources, ice will appear on the surface of the blades of wind turbines, which will have a great impact on the operation of wind turbines. In severe cases, it will cause large-scale continuous tripping of wind turbines, resulting in large-scale power shortages and large-scale power outages in local areas.

The existing technology mainly involves adding coatings to fan blades or changing the blade structure. This method requires redesigning the blades or designing the coating materials, which is costly to implement and has a poor anti-icing effect. Alternatively, de-icing is performed by ultrasonically vibrating the fan blades, heating the fan blades, etc. This method may require modification of the fan blades, which is costly to implement and has a poor anti-icing effect.

Summary of the invention

In view of this, the main purpose of the embodiments of the present application is to propose a low-cost anti-icing method, system, electronic device and storage medium for wind turbine blades, which does not require any modification, has low cost and improves the anti-icing effect of wind turbine blades.

To achieve the above-mentioned purpose, one aspect of an embodiment of the present application provides a method for preventing icing of wind turbine blades, the method comprising:

Acquire environmental variable data in real time, and acquire blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture content data and supercooled water droplet average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value;

Determining a danger range according to the blade icing mass threshold and the wind turbine state variable setting value;

Determine a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold;

The environmental variable data is compared with the danger range. If the environmental variable data falls within the danger range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value; if the environmental variable data does not fall within the danger range, the first preset value is used as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold value, and the first preset value represents the blade pitch angle when the ice coating mass of the wind turbine blade is the minimum;

The wind turbine blades are adjusted according to the target blade pitch angle reference value.

In some embodiments, determining the danger range according to the blade icing mass threshold and the wind turbine state variable setting value specifically includes:

Substituting the blade icing mass threshold and the fan state variable setting value into a pre-established multivariate function relationship model, and keeping the fan blade pitch angle unchanged, to obtain several sets of environmental variable ranges; wherein the environmental variables include wind speed, temperature, average effective diameter of supercooled water droplets, and air moisture content;

The hazard range is determined based on several groups of environmental parameter ranges.

In some embodiments, determining the minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold specifically includes:

Obtain fan speed variables in real time;

Substituting the environmental variable data and the wind turbine speed variable into a pre-established multivariate function relationship model to obtain a relationship expression; wherein the relationship expression represents the relationship between the blade ice mass and the wind turbine blade pitch angle;

The blade icing mass threshold is substituted into the relational expression to calculate a minimum blade pitch angle reference value.

In some embodiments, adjusting the wind turbine blades according to the target blade pitch angle reference value specifically includes:

Obtain the current blade pitch angle of the wind turbine blades in real time;

An adjustment value is calculated according to the current blade pitch angle and the target blade pitch angle reference value, and the current blade pitch angle of the wind turbine blade is adjusted according to the adjustment value until a difference between the current blade pitch angle and the target blade pitch angle reference value meets a preset condition.

In some embodiments, the multivariate functional relationship model is established by:

Discretely sampling the first parameter variable to obtain sampling data; wherein the first parameter variable includes ambient wind speed, temperature, average effective diameter of supercooled water droplets, air moisture content, and blade pitch angle;

Performing simulation according to the sampled data to obtain a simulated blade ice mass data set; wherein the simulated blade ice mass data set includes blade ice mass data corresponding to one or more parameter combinations in the first parameter variable;

System identification is performed based on the simulated blade ice mass data set to obtain a multivariate functional relationship model.

In some embodiments, performing system identification according to the simulated blade ice mass data set to obtain a multivariate functional relationship model specifically includes:

The simulated blade ice mass data set is input into the data analysis software, and under the premise of fixing other variable parameters, polynomial fitting is performed on each parameter to obtain a relationship model between each parameter and the blade ice mass;

The least squares method is used to calculate the relationship model between each parameter and the ice mass of the blade to obtain a multivariate function relationship model.

In some embodiments, the calculating the adjustment value according to the current blade pitch angle and the reference value includes:

According to the current blade pitch angle and the reference value, the adjustment value is calculated using the first formula, which is:

in, is the adjustment value, τ is the time constant, k _ref is the reference value of the pitch angle in the ideal state, and k is the real pitch angle in the actual state.

To achieve the above object, another aspect of the embodiment of the present application provides a wind turbine blade anti-icing system, the system comprising:

The first module is used to obtain environmental variable data in real time, obtain blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture content data and supercooled water droplet average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value;

The second module is used to determine the danger range according to the blade ice mass threshold and the wind turbine state variable setting value;

A third module is used to determine a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold;

The fourth module is used to compare the environmental variable data with the danger range, and if the environmental variable data falls into the danger range, use the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, use the first preset value as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold, and the first preset value represents the blade pitch angle with the minimum ice coating mass of the wind turbine blade;

The fifth module is used to adjust the wind turbine blades according to the target blade pitch angle reference value.

To achieve the above objective, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above-mentioned method when executing the computer program.

To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

Implementation of the embodiments of the present invention includes the following beneficial effects: The present application provides a method, system, electronic device and storage medium for preventing wind turbine blades from icing. The scheme acquires environmental variable data in real time, and acquires a wind turbine blade icing quality threshold and a wind turbine state variable setting value. The danger range is determined according to the acquired wind turbine blade icing quality threshold and the wind turbine state variable setting value. The environmental variable data acquired in real time is compared with the determined danger range to determine whether the environmental variable data falls within the danger range. If the environmental variable data falls within the danger range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value. If the environmental variable data does not fall within the danger range, the first preset value is used as the target blade pitch angle reference value, and then the pitch angle of the blades of the wind turbine set is adjusted according to the determined target blade pitch angle reference value. The danger range is determined according to the blade icing mass threshold and the set value of the fan state variable, and the current environmental variable data of the fan is monitored according to the danger range. When the current environmental variable data of the fan falls into the danger range, it is determined that the ice mass of the fan blades will exceed the blade icing mass threshold under the current environment. The minimum blade pitch angle reference value is determined according to the current speed of the fan, the environmental variable data and the current environmental variable data of the fan. The pitch angle of the fan blades is actively adjusted according to the minimum blade pitch angle reference value to reduce the risk of icing on the fan blades and improve the anti-icing effect of the fan blades.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic flow chart of the steps of a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

FIG2 is a schematic flow chart of the steps of determining a danger range in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

3 is a schematic flow chart of the steps of establishing a multivariate function relationship model in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

FIG4 is a schematic flow chart of system identification steps in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

5 is a schematic flow chart of the steps of calculating a minimum blade pitch angle reference value in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

6 is a schematic diagram of the relationship between ice mass and pitch angle at different wind speeds in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

7 is a schematic flow chart of the steps of adjusting the blade pitch angle in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

8 is a control block diagram of a variable pitch system in a method for preventing icing of wind turbine blades provided by an embodiment of the present invention;

FIG9 is a schematic diagram of a step flow chart of a specific embodiment provided by an embodiment of the present invention;

10 is a structural block diagram of a fan blade anti-icing system provided in an embodiment of the present invention;

FIG. 11 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention.

Detailed ways

The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only provided for the convenience of explanation and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present invention described herein can be implemented in an order other than that illustrated or described herein.

Unless otherwise defined, all technical and scientific terms used in the embodiments of the present invention have the same meanings as those commonly understood by those skilled in the art of the present invention. The terms used in the embodiments of the present invention are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

Wind power generation is an important source in the new energy system. Wind turbines use wind power to drive the blades to rotate, which in turn drives the generator to generate electricity. Therefore, wind turbines are usually installed in areas with abundant wind resources. In areas with abundant wind resources, weather conditions change frequently, and the blades of wind turbines are very sensitive to changes in weather conditions. For example, when wind turbines operate in an environment with supercooled air, the collision between the wind turbine blades and water droplets caused by the supercooled air can easily lead to ice on the surface of the wind turbine blades. After ice appears on the surface of the wind turbine blades, the roughness of the blade surface increases, resulting in lower aerodynamic performance of the blades, and the operating power of the wind turbine also decreases. When the mass of ice on the blade surface exceeds a certain threshold, the torque of the blade is zero, causing the output power of the wind turbine to also be zero, or even causing damage to the wind turbine.

In view of this, an embodiment of the present application provides a method, system, electronic device and storage medium for preventing icing on wind turbine blades. The scheme obtains environmental variable data of the wind turbine in real time, obtains a blade icing quality threshold and a fan state variable setting value, determines a danger range according to the blade icing quality threshold and the fan state variable setting value, and determines whether the icing quality of the wind turbine blades exceeds the tolerable threshold through the danger range, and whether it is necessary to adjust the blade pitch angle of the wind turbine blades; compares the environmental variable data obtained in real time with the danger range, and if the environmental variable data falls into the danger range, adjusts the wind turbine blade pitch angle by taking the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, adjusts the wind turbine blade pitch angle by taking the first preset value as the target blade pitch angle reference value; by adjusting the size of the pitch angle of the wind turbine blades, the windward angle of the wind turbine blades is changed, and the risk of icing on the wind turbine blades is reduced, thereby improving the anti-icing effect of the wind turbine blades.

FIG1 is an optional flow chart of a method for preventing icing of wind turbine blades provided in an embodiment of the present application. The method in FIG1 may include but is not limited to steps S101 to S105.

Step S101, real-time acquisition of environmental variable data, blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture data and supercooled water droplet average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value;

Step S102, determining a danger range according to a blade icing mass threshold and a set value of a wind turbine state variable;

Step S103, determining a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold;

Step S104, comparing the environmental variable data with the danger range, if the environmental variable data falls into the danger range, taking the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, taking the first preset value as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold value, and the first preset value represents the blade pitch angle when the ice coating mass of the wind turbine blade is the minimum;

Step S105, adjusting the wind turbine blades according to the target blade pitch angle reference value.

In steps S101 to S105 shown in the embodiment of the present application, some sensors arranged on the wind turbine generator set collect the current environmental variable data of the environment in which the wind turbine generator set is located in real time, including the environmental wind speed, temperature, air moisture content, average effective diameter of supercooled water droplets and other data. Based on the environmental variable data acquired in real time, it can be analyzed that under the current environment, the possibility of ice covering the wind turbine blades can be obtained; then, the blade ice covering mass threshold value and the fan state variable setting value of the wind turbine generator set are obtained. The blade ice covering mass threshold value is set according to the carrying capacity of the fan blades. When the ice covering mass on the fan blades exceeds the threshold value, the fan blades will be damaged. The fan state variable setting value includes the fan blade pitch angle and the fan speed. The fan state variable setting value indicates the maximum value of the blade pitch angle that can be set for the fan blades and the fan operation speed. The allowable speed is determined according to the blade icing mass threshold and the set value of the fan state variable. When the environmental variable falls into the danger range, if the fan state variable remains unchanged, the icing mass of the fan blades may exceed the blade icing threshold. At this time, it is necessary to set the minimum blade pitch angle reference value as the target blade pitch angle reference value to adjust the fan blade pitch angle. If the environmental variable does not fall into the danger range, it means that the fan state variable remains unchanged, and the icing mass of the fan blades is still within the allowable range. At this time, the first preset value is set to the target blade pitch angle reference value. Under the condition that the icing mass of the fan blades is within the allowable range, the output power of the wind turbine is maintained. By way of example, the first preset value can be set to 60 degrees, and the icing mass of the fan blades is minimum when maintaining the output power of the wind turbine.

In step S101 of some embodiments, environmental variable data of the current environment of the wind turbine generator set can be obtained in real time through sensors installed in the wind turbine generator set, or meteorological data information can be obtained through networking and analyzed to obtain environmental variable data of the current environment of the wind turbine generator set, but the present invention is not limited thereto.

Please refer to FIG. 2 . In some embodiments, step S102 may include but is not limited to steps S201 to S202:

Step S201, substituting the blade ice mass threshold and the fan state variable setting value into a pre-established multivariate function relationship model, and keeping the fan blade pitch angle unchanged, to obtain several sets of environmental variable ranges; wherein the environmental variables include wind speed, temperature, average effective diameter of supercooled water droplets, and air moisture content;

Step S202, determining a danger range according to several groups of environmental parameter ranges.

In step S201 of some embodiments, before determining the danger range, a multivariate functional relationship model is pre-established with environmental variables and wind turbine state variables as independent variables and blade icing mass as dependent variable, the acquired blade icing mass threshold is substituted into the multivariate functional relationship model, the blade pitch angle is set as a constant and also substituted into the multivariate functional relationship model, the multivariate functional relationship model after the data is substituted is reversed to obtain the range of different parameters in the environmental variable data, and this range is the environmental variable parameter corresponding to when the icing mass on the wind turbine blades reaches the blade icing mass threshold.

In step S202 of some embodiments, after inverting the multivariate functional relationship model in step S201, a set of ranges of environmental variable parameters are obtained, and these ranges of environmental variable parameters are integrated to obtain the dangerous range of the environmental variables of the wind turbine group, so as to subsequently determine whether the wind turbine blades need to be adjusted.

Please refer to FIG. 3 . In some embodiments, through steps S301 to S303 shown in FIG. 3 , a multivariate functional relationship model is established;

Step S301, discretely sampling the first parameter variable to obtain sampling data; wherein the first parameter variable includes ambient wind speed, temperature, average effective diameter of supercooled water droplets, air moisture content, and blade pitch angle;

Step S302, performing simulation according to the sampled data to obtain a simulated blade icing mass data set; wherein the simulated blade icing mass data set includes blade icing mass data corresponding to one or more parameter combinations in the first parameter variable;

Step S303: performing system identification based on the simulated blade ice mass data set to obtain a multivariate functional relationship model.

In step S301 of some embodiments, in order to establish a multivariate functional relationship model between different environmental parameters and the ice mass of wind turbine blades, first, data is collected within a preset parameter range to obtain data on the ice mass of blades under different environmental parameters. For example, the collection range of the ambient wind speed is 2 meters per second to 10 meters per second, and the data collection device discretely samples the ice mass data of blades under different wind speeds at intervals of 1 meter per second.

In step S302 of some embodiments, sampling data of blade icing mass under different environmental parameters are obtained through step S301, and the obtained sampling data are input into CFD simulation model software for simulation, and different environmental variable parameters are combined accordingly, and discrete sampling data are integrated to obtain the blade icing mass under the joint influence of different environmental parameters; because different environmental parameters do not all interact positively with each other, therefore, the blade icing mass under the joint influence of different environmental parameters is not the superposition of the blade icing mass corresponding to different environmental parameters; by performing CFD simulation on the sampling data, a simulated blade icing mass data set is obtained, which includes blade icing mass data corresponding to different environmental parameters and blade icing mass data under the joint influence of different environmental parameters; so as to improve the accuracy and reliability of the subsequent dangerous range or minimum blade pitch angle reference value determined based on the multivariate functional relationship model, thereby improving the blade anti-icing effect.

In step S303 of some embodiments, after obtaining the simulated blade icing mass data set in step S302, the multivariate functional relationship model is regarded as a black box system, different environmental parameters and combinations of different environmental parameters are regarded as inputs of the black box system, and the simulated blade icing mass data set is regarded as outputs of the black box system. System identification is performed through the relationship between input and output, the black box system is described, and the multivariate functional relationship model is obtained.

Please refer to FIG. 4 . In some embodiments, step S303 may include but is not limited to steps S401 to S402:

Step S401, inputting the simulated blade ice mass data set into the data analysis software, and performing polynomial fitting on each parameter under the premise of fixing other variable parameters, to obtain a relationship model between each parameter and the blade ice mass;

Step S402: performing least squares calculation on the relationship model between each parameter and the blade ice mass to obtain a multivariate function relationship model.

In step S401 of some embodiments, it can be known from step S303 that a multivariate functional relationship model is used to describe the black box model, and according to the simulated blade ice mass data set, it can be known that this black box system is a multi-input and multi-output system, so the simulated blade ice mass data set is input into the data analysis software, and each parameter is separated out for mathematical modeling, that is, other parameters are kept unchanged, and a functional relationship model between each environmental parameter and the blade ice mass is obtained by polynomial fitting.

In step S402 of some embodiments, since the black box system is a multi-input and multi-output system, it means that there is influence between different parameters, and the functional relationship models between different parameters and blade ice coverage mass obtained by polynomial fitting in step S401 are independent of each other, then the independent functional relationship models are integrated by least squares method to obtain a mathematical model describing the black box system, and the mathematical model describing the black box system is used as a multivariate functional relationship model.

Please refer to FIG. 5 . In some embodiments, through steps S501 to S503 shown in FIG. 5 , the minimum blade pitch angle reference value in step S103 is obtained;

Step S501, obtaining the fan speed variable in real time;

Step S502, substituting the environmental variable data and the wind turbine speed variable into a pre-established multivariate function relationship model to obtain a relationship expression; wherein the relationship expression represents the relationship between the blade ice mass and the wind turbine blade pitch angle;

Step S503: Substitute the blade ice mass threshold into the relational expression to calculate the minimum blade pitch angle reference value.

In step S501 of some embodiments, in step S103, when the environmental variable data acquired in real time falls into a dangerous range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value, and the blade pitch angle of the wind turbine blade is adjusted. The minimum blade pitch angle reference value indicates the minimum blade pitch angle that makes the blade icing mass of the wind turbine blade not exceed the blade icing mass threshold under the current environmental variable data; in order to obtain the minimum blade pitch angle reference value, it is necessary to first derive the relationship expression between the blade icing mass of the wind turbine blade and the blade pitch angle of the wind turbine blade.

In step S502 of some embodiments, the current environmental variable data and wind speed variable data acquired in real time are substituted into a pre-established multivariate functional relationship model for derivation, and the relationship expression between the blade ice coverage mass of the wind blade and the blade pitch angle of the wind blade is analyzed and extracted from the multivariate functional relationship model.

In step S503 of some embodiments, after obtaining the relationship expression between the blade icing mass of the wind turbine blade and the blade pitch angle of the wind turbine blade in step S502, the blade icing mass threshold is substituted into the relationship expression, so as to obtain the minimum blade pitch angle reference value at which the blade icing mass of the wind turbine blade does not exceed the blade icing mass threshold; illustratively, the wind turbine adopts NACA0012 airfoil blades, and the relationship expression is obtained by deriving and calculating the multivariate function relationship model, and a relationship diagram as shown in FIG6 is obtained, which includes the relationship expression of the blade under different ambient wind speeds. It can be seen from the figure that after the blade pitch angle is greater than 18°, the overall trend is that the larger the blade pitch angle, the lower the blade icing mass, and the blade icing mass decreases significantly around 60°, while the blade icing mass decreases insignificantly after it is greater than 60°. Therefore, 60° can be set as the minimum blade pitch angle reference value of the blade.

Please refer to FIG. 7 . In some embodiments, step S104 may include but is not limited to steps S601 to S602:

Step S601, obtaining the current blade pitch angle of the wind turbine blade in real time;

Step S602, calculating an adjustment value according to the current blade pitch angle and the target blade pitch angle reference value, and adjusting the current blade pitch angle of the wind turbine blade according to the adjustment value until the difference between the current blade pitch angle and the target blade pitch angle reference value meets a preset condition.

In step S601 of some embodiments, after obtaining the target blade pitch angle reference value through step S103, the blade pitch angle of the wind turbine is adjusted according to the target blade pitch angle reference value, specifically by driving the pitch servo mechanism to control the rotation of the wind turbine blades, and the pitch servo mechanism is controlled and driven by a closed-loop controlled variable pitch system. The structure of the variable pitch system is shown in Figure 8, and the variable pitch system is controlled by real-time acquisition of the current blade pitch angle of the wind turbine blades.

In step S602 of some embodiments, the pitch system uses the target blade pitch angle reference value obtained in step S103 as the target output of the pitch system, and inputs the real-time collected blade pitch angle into the pitch system as the control quantity. The output of the pitch system drives the pitch servo mechanism to rotate the fan blade. Since the pitch system is a closed-loop control, the real-time collected blade pitch angle is adjusted to the target blade pitch angle reference value before being adjusted until the difference between the current blade pitch angle of the fan and the target blade pitch angle reference value meets the stop condition. For example, the target blade pitch angle is set to 45 degrees, and the current blade pitch angle of the fan is obtained by collecting data to be 55 degrees. The adjustment value is 10 degrees by calculation. The pitch system adjusts the current blade pitch angle of the fan according to the adjustment value. When the difference between the current blade pitch angle of the fan and the target blade pitch angle is within 1 degree, it is determined that the pitch angle system has completed the adjustment of the fan blade pitch angle, thereby reducing the risk of blade icing. Therefore, it has the ability to suppress interference and improve the anti-icing effect of blades.

The following is a detailed description and explanation of the solution of the embodiment of the present invention in conjunction with a specific application example:

Referring to Figure 9, Figure 9 shows a schematic diagram of the application of a method for preventing wind turbine blade icing provided in an embodiment of the present application. In the embodiment of the present application, the blade icing quality threshold set by the wind turbine is obtained, and the fan state variable setting value of the wind turbine is read. Then, the obtained blade icing quality threshold and the fan state variable setting value are substituted into a pre-established multivariate function relationship model for calculation to obtain a dangerous range of environmental variables; then, the current environmental variable data of the wind turbine is obtained in real time, and the current environmental variable data is compared with the determined dangerous range of environmental variables to determine whether it falls into the dangerous range of environmental variables. If the current environmental variable data falls into the dangerous range, the blade icing quality threshold, the current environmental variable input and the current state variable of the wind turbine are input into the multivariate function relationship model to calculate the minimum The blade pitch angle reference value is 60 degrees; if the current environmental variable data does not fall into the danger range, the current blade pitch angle of the wind turbine is maintained, and the current environmental variable data of the wind turbine continues to be obtained; then the obtained minimum blade pitch angle reference value is used as the target blade pitch angle reference value, and the target blade pitch angle reference value is input into the variable pitch system, and the current blade pitch angle of the wind turbine is collected in real time and input into the variable pitch system. The variable pitch system drives the pitch servo mechanism according to the input current blade pitch angle and the target blade pitch angle reference value, and adjusts the blade pitch angle of the wind turbine until the current blade pitch angle is equal to the target blade pitch angle reference value of 60 degrees, thereby achieving the blade anti-icing effect.

The implementation of the embodiments of the present invention includes the following beneficial effects: the present application provides a method, system, electronic device and storage medium for preventing icing of wind turbine blades. The scheme acquires environmental variable data in real time, and acquires the icing quality threshold of wind turbine blades and the setting value of wind turbine state variables. The danger range is determined according to the acquired icing quality threshold of wind turbine blades and the setting value of wind turbine state variables. The environmental variable data acquired in real time is compared with the determined danger range to determine whether the environmental variable data falls into the danger range. If the environmental variable data falls into the danger range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, the first preset value is used as the target blade pitch angle reference value, and then the blades of the wind turbine set are adjusted according to the determined target blade pitch angle reference value. The pitch angle of the wind turbine blades is actively adjusted according to the environmental information to reduce the risk of icing of the wind turbine blades and improve the anti-icing effect of the wind turbine blades; the pitch angle of the wind turbine blades is adjusted by the variable pitch system controlled by the closed loop, which has strong anti-interference ability and high reliability of anti-icing effect.

Referring to FIG. 10 , the embodiment of the present application further provides a fan blade anti-icing system, which can implement the above-mentioned fan blade anti-icing method, and the system includes:

The first module is used to obtain environmental variable data in real time, obtain blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture content data and supercooled water drop average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value;

The second module is used to determine the danger range according to the blade ice mass threshold and the set value of the wind turbine state variable;

The third module is used to determine a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold;

The fourth module is used to compare the environmental variable data with the danger range. If the environmental variable data falls into the danger range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, the first preset value is used as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold value, and the first preset value represents the blade pitch angle with the minimum ice coating mass of the wind turbine blade;

The fifth module is used to adjust the wind turbine blades according to the target blade pitch angle reference value.

It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned wind turbine blade anti-icing method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

Please refer to FIG. 11 , which schematically shows the hardware structure of an electronic device according to another embodiment. The electronic device includes:

The processor 1101 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

The memory 1102 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1102 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1102, and the processor 1101 calls and executes the wind turbine blade anti-icing method of the embodiment of this application;

Input/output interface 1103, used to implement information input and output;

The communication interface 1104 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

A bus 1105 that transmits information between various components of the device (e.g., the processor 1101, the memory 1102, the input/output interface 1103, and the communication interface 1104);

The processor 1101 , the memory 1102 , the input/output interface 1103 and the communication interface 1104 are connected to each other in communication within the device via the bus 1105 .

In addition, the embodiment of the present application also discloses a computer program product or a computer program, and the computer program product or the computer program is stored in a computer-readable storage medium. The processor of the computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the above method. Similarly, the contents in the above method embodiment are all applicable to the storage medium embodiment, and the functions specifically implemented by the storage medium embodiment are the same as those in the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method embodiment.

An embodiment of the present invention further provides a computer-readable storage medium, which stores a program executable by a processor. The program executable by the processor is used to implement the above method when executed by the processor.

It is understood that all or some steps and systems in the disclosed method above can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

The embodiments of the present application provide a method for preventing icing on fan blades, a system for preventing icing on fan blades, an electronic device and a storage medium, which obtain the current environmental variable data of the fan in real time, obtain the blade icing quality threshold of the fan and the setting value of the fan state variable, determine the dangerous range of the fan environmental variable according to the blade icing quality threshold and the setting value of the fan state variable, compare the current environmental variable data obtained in real time with the dangerous range of the fan environmental variable, and if the obtained environmental variable data falls within the dangerous range, use the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the obtained environmental variable data does not fall .... When it falls within the danger range, the first preset value is used as the target blade pitch angle reference value; after determining the target blade pitch angle reference value, the pitch angle of the wind turbine blades is adjusted according to the target blade pitch angle reference value; the pitch angle of the wind turbine blades is adjusted according to the current real-time environmental variable data of the wind turbine and the determined danger range, without the need to modify the existing wind turbine, and the anti-icing cost is low; the current real-time environmental variable data of the wind turbine is compared with the determined danger range, and when the real-time environmental variable data falls into the danger range, the pitch angle of the wind turbine blades is actively adjusted to reduce the risk of blade icing and improve the effect of blade anti-icing.

The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims (10)

1. A method for preventing icing of wind turbine blades, comprising the following steps: Acquire environmental variable data in real time, and acquire blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture content data and supercooled water droplet average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value; Determining a danger range according to the blade icing mass threshold and the wind turbine state variable setting value; Determine a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold; The environmental variable data is compared with the danger range. If the environmental variable data falls within the danger range, the minimum blade pitch angle reference value is used as the target blade pitch angle reference value; if the environmental variable data does not fall within the danger range, the first preset value is used as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold value, and the first preset value represents the blade pitch angle when the ice coating mass of the wind turbine blade is the minimum; The wind turbine blades are adjusted according to the target blade pitch angle reference value. 2. The method according to claim 1, characterized in that the step of determining the danger range according to the blade icing mass threshold and the wind turbine state variable setting value specifically comprises: Substituting the blade icing mass threshold and the fan state variable setting value into a pre-established multivariate function relationship model, and keeping the fan blade pitch angle unchanged, to obtain several sets of environmental variable ranges; wherein the environmental variables include wind speed, temperature, average effective diameter of supercooled water droplets, and air moisture content; The risk variables are determined based on several sets of ranges of the environmental variables. 3. The method according to claim 1, characterized in that the step of determining the minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold comprises: Obtain fan speed variables in real time; Substituting the environmental variable data and the wind turbine speed variable into a pre-established multivariate function relationship model to obtain a relationship expression; wherein the relationship expression represents the relationship between the blade ice mass and the wind turbine blade pitch angle; The blade icing mass threshold is substituted into the relational expression to calculate a minimum blade pitch angle reference value. 4. The method according to claim 1, characterized in that the step of adjusting the wind turbine blades according to the target blade pitch angle reference value specifically comprises: Obtain the current blade pitch angle of the wind turbine blades in real time; An adjustment value is calculated according to the current blade pitch angle and the target blade pitch angle reference value, and the current blade pitch angle of the wind turbine blade is adjusted according to the adjustment value until a difference between the current blade pitch angle and the target blade pitch angle reference value meets a preset condition. 5. The method according to claim 2, characterized in that the multivariate functional relationship model is established by: Discretely sampling the first parameter variable to obtain sampling data; wherein the first parameter variable includes ambient wind speed, temperature, average effective diameter of supercooled water droplets, air moisture content, and blade pitch angle; Performing simulation according to the sampled data to obtain a simulated blade ice mass data set; wherein the simulated blade ice mass data set includes blade ice mass data corresponding to one or more parameter combinations in the first parameter variable; System identification is performed based on the simulated blade ice mass data set to obtain a multivariate functional relationship model. 6. The method according to claim 5, characterized in that the system identification is performed according to the simulated blade ice mass data set to obtain a multivariate functional relationship model, specifically comprising: The simulated blade ice mass data set is input into the data analysis software, and under the premise of fixing other variable parameters, each parameter is respectively fitted with a polynomial to obtain a relationship model between each parameter and the blade ice mass; The least squares method is used to calculate the relationship model between each parameter and the ice mass of the blade to obtain a multivariate function relationship model. 7. The method according to claim 4, characterized in that the calculating the adjustment value according to the current blade pitch angle and the target blade pitch angle reference value comprises: According to the current blade pitch angle and the reference value, the adjustment value is calculated using the first formula, which is: Wherein, k is the adjustment value, τ is the time constant, k _ref is the reference value of the pitch angle in the ideal state, and k is the real pitch angle in the actual state. 8. A wind turbine blade anti-icing system, characterized in that the system comprises: The first module is used to obtain environmental variable data in real time, obtain blade ice mass threshold and fan state variable setting value; wherein the environmental variable data includes wind speed data, temperature data, air moisture content data and supercooled water droplet average effective diameter data of the current environment, the blade ice mass threshold represents the maximum ice mass allowed on the fan blade, and the fan state variable setting value includes the fan blade pitch angle setting value and the fan speed setting value; The second module is used to determine the danger range according to the blade ice mass threshold and the wind turbine state variable setting value; A third module is used to determine a minimum blade pitch angle reference value according to the environmental variable data and the blade icing mass threshold; The fourth module is used to compare the environmental variable data with the danger range, and if the environmental variable data falls into the danger range, use the minimum blade pitch angle reference value as the target blade pitch angle reference value; if the environmental variable data does not fall into the danger range, use the first preset value as the target blade pitch angle reference value; wherein the minimum blade pitch angle reference value represents the minimum blade pitch angle when the ice coating mass of the wind turbine blade reaches the blade ice coating mass threshold, and the first preset value represents the blade pitch angle with the minimum ice coating mass of the wind turbine blade; The fifth module is used to adjust the wind turbine blades according to the target blade pitch angle reference value. 9. An electronic device, comprising: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7. 10. A computer-readable storage medium storing a processor-executable program, wherein the processor-executable program is used to execute the method according to any one of claims 1 to 7 when executed by a processor.