Method and system for evaluating and early warning icing risk of fan blade

Abstract

The invention discloses a fan blade icing risk assessment and early warning method and system. The method comprises the following steps: acquiring meteorological parameters of a wind power plant; inputting the meteorological parameters into a blade three-dimensional ice shape model to simulate the icing state of the surface of the fan blade so as to obtain icing forms of different positions of the blade; the aerodynamic characteristics of the iced blade are calculated through the icing forms of the different positions of the blade, aerodynamic characteristic parameters of the two-dimensional icing airfoil profile structures of the different positions are obtained, and the external airflow field change of each two-dimensional section is obtained; according to the airflow field change, the wind energy utilization rate is calculated; and based on the icing forms of different positions and the wind energy utilization rate, evaluating the icing disaster-causing risk level and performing early warning. According to the method, three-dimensional icing simulation and pneumatic calculation of the fan blade are combined, the relation about the influence of icing on the pneumatic performance and the power characteristic of the wind driven generator is obtained, intelligent risk assessment of the icing disaster of the wind power plant is achieved, and therefore safe operation of the wind driven generator in the severe environment of the icing area is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment detection, and in particular to a method and system for assessing and warning the risk of icing on wind turbine blades. Background Art

[0002] Wind energy is a new energy source with huge potential. In recent years, the prominent terrain in inland areas such as Hunan, Chongqing, Sichuan, Chongqing, Yunnan, and Guizhou in central and southwestern China has led to strong wind flow pressure, providing abundant resources for wind power generation. Due to the prominent climate and terrain characteristics in these areas, the environment is humid and cold in winter, and the overall temperature is below freezing, which provides favorable environmental conditions for icing. Therefore, the problem of wind turbine blade icing has gradually emerged, resulting in a loss of up to 28.4% of power generation each year.

[0003] Wind turbines in southern wind farms are covered with ice many times a year, and the number of ice and freezing days in wind farms is between 30 and 60 days a year. The icing time is relatively long, which seriously restricts the power output and grid connection of wind turbines in winter. Artificial icing tests consume a lot of material and financial resources, while natural icing tests are very difficult to implement. Wind farms have limited observation data on icing and its meteorological parameters, and lack the collection of important icing meteorological parameters, such as ambient temperature, air humidity and ice thickness. The means of collecting the icing status of iced wind turbines are limited, and are currently limited to long-distance photography when weather permits. There is a lack of icing prediction and early warning mechanism for wind turbines. Currently, the shutdown is guided only by combining wind turbine power changes with weather conditions. This has become one of the core issues restricting the safe and stable operation of wind turbines, and it also highlights the importance and urgency of exploring the operation plan of wind turbines under icing conditions through scientific and technological means. At the same time, current research on wind turbine power characteristics under different icing types and degrees at home and abroad is still relatively limited. Large-scale field tests on wind turbines under natural icing conditions are obviously insufficient. Research on natural icing tests is very rare and lacks the support of actual data and images. As a result, there are great limitations in studying the influence of power characteristics under iced wind turbine blades. Research on the power characteristics of medium and large wind turbines has not yet been explored in depth. The blades of large wind turbines are huge, and the air visibility is low in an icing environment. It is difficult to obtain the icing status of wind turbine blades in real time by ordinary means. In addition, different icing states have different degrees of influence on the power output characteristics of wind turbines, which leads to the current means of risk assessment and early warning of wind turbine blade icing are still imperfect. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method and system for assessing and warning of the risk of icing on wind turbine blades to solve the problem that the current shutdown is guided only by combining the power changes of wind turbines and weather conditions, and the few actual parameters obtained make it impossible to accurately obtain the influencing law of the power characteristics of iced wind turbine blades, it is difficult to obtain the icing status of wind turbine blades in real time, and different icing statuses have different degrees of influence on the power output characteristics of the wind turbine, and the means of assessing and warning of the risk of icing on wind turbine blades are still imperfect.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a wind turbine blade icing risk assessment and early warning method, comprising:

[0008] Obtain meteorological parameters of wind farms;

[0009] The ice-covered state of the wind turbine blade surface is simulated based on the meteorological parameters input into the blade three-dimensional ice shape model to obtain the ice-covered shapes at different positions of the blade;

[0010] The aerodynamic characteristics of the blade after ice coating are calculated by the ice coating forms at different positions of the blade, the aerodynamic characteristic parameters of the two-dimensional ice-coated airfoil structure at different positions are obtained, and the changes of the external airflow field of each two-dimensional cross section are obtained;

[0011] According to the change of the airflow field, the wind energy utilization rate is calculated;

[0012] Based on the ice cover forms and wind energy utilization rate at the different locations, the risk level of icing disasters is evaluated and a warning is issued.

[0013] As a preferred solution of the wind turbine blade icing risk assessment and early warning method of the present invention, the icing state of the wind turbine blade surface is simulated to obtain the icing form of different positions of the blade, including:

[0014] The thickness values ​​at various locations on the outer surface of the blade are obtained through simulation;

[0015] Based on the thickness values ​​at different positions, they are spliced ​​together to obtain the overall ice cover shape.

[0016] As a preferred scheme of the wind turbine blade icing risk assessment and early warning method described in the present invention, the key blade icing thickness in the blade three-dimensional ice shape model is the ratio of the product value of the water droplet collision coefficient, the freezing coefficient and the wind speed of the wind farm at the calculated position on the blade surface, the area of ​​the calculated position of the wind turbine blade icing, the liquid water content in the air, and the icing duration to the icing density value.

[0017] As a preferred solution of the wind turbine blade icing risk assessment and early warning method of the present invention, the aerodynamic characteristic parameters of the two-dimensional icing airfoil structure at different positions are obtained, including:

[0018] Different positions were obtained by sectioning;

[0019] The different positions include: positions at 0.1R, 0.3R, 0.5R, 0.7R and 0.9R from the blade root, and R is the blade chord length.

[0020] As a preferred solution of the wind turbine blade icing risk assessment and early warning method of the present invention, the wind energy utilization rate is calculated according to the change of the airflow field, including:

[0021] Calculate the lift-to-drag ratio of the wind turbine blades. The wind energy utilization rate is calculated based on the lift-to-drag ratio of the wind turbine blades combined with the tip speed ratio. It is specifically expressed as:

[0022]

[0023] Among them, C P-i is the wind energy utilization rate at the i-th position; e is the lift-to-drag ratio of the wind turbine blade; λ r is the tip speed ratio.

[0024] As a preferred solution of the wind turbine blade icing risk assessment and early warning method of the present invention, wherein: the icing disaster risk level is assessed based on the icing forms at different positions and the wind energy utilization rate, including:

[0025] According to the ice thickness and wind energy utilization rate of wind turbine blades at different positions, the overall weighted ice thickness and overall wind energy utilization rate of wind turbine blades are solved, which can be expressed as follows:

[0026]

[0027] Among them, h i represents the ice thickness at the i-th position; β i and k i They represent weighting coefficients respectively; n represents the total number of positions.

[0028] As a preferred solution of the wind turbine blade icing risk assessment and early warning method of the present invention, wherein: the icing disaster risk level is assessed based on the icing forms at different positions and the wind energy utilization rate, and further includes:

[0029] The risk level range of the overall weighted ice thickness and the overall wind energy utilization rate is set and divided into multiple levels, and each level corresponds to a corresponding overall weighted ice thickness threshold range and an overall wind energy utilization rate threshold range;

[0030] If the two parameters determine different risk levels, the higher risk level of the parameter will be the final judgment result.

[0031] In a second aspect, the present invention provides a wind turbine blade icing risk assessment and early warning system, comprising:

[0032] An acquisition module is used to obtain meteorological parameters of the wind farm;

[0033] A simulation module, for simulating the ice-covered state of the wind turbine blade surface based on the meteorological parameters input into the blade three-dimensional ice shape model, so as to obtain the ice-covered morphology at different positions of the blade;

[0034] A first calculation module is used to calculate the aerodynamic characteristics of the ice-covered blade according to the ice-covered forms at different positions of the blade, obtain the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions, and obtain the changes of the external airflow field of each two-dimensional cross-section;

[0035] A second calculation module is used to calculate the wind energy utilization rate according to the change of the airflow field;

[0036] An assessment module is used to assess the risk level of icing disasters and issue warnings based on the icing forms and wind energy utilization rates at different locations.

[0037] In a third aspect, the present invention provides a computing device, comprising:

[0038] Memory and processor;

[0039] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the wind turbine blade icing risk assessment and early warning method are implemented.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, can implement the steps of the wind turbine blade icing risk assessment and early warning method.

[0041] Compared with the prior art, the present invention has the following beneficial effects: the present invention combines three-dimensional icing simulation and aerodynamic calculation of wind turbine blades, inputs the meteorological parameters of the actual wind field into the theoretical model, and compares and verifies the theoretical model with experimental data to obtain a comprehensive analysis of the impact of icing on the aerodynamic performance and power characteristics of wind turbines, thereby realizing intelligent risk assessment of icing disasters in wind farms, thereby ensuring the safe operation of wind turbines in harsh environments such as icing areas and high altitudes. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0043] Figure 1 This is an overall flow chart of a wind turbine blade icing risk assessment and early warning method according to an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a two-dimensional cross-section of a wind blade in a wind blade icing risk assessment and early warning method according to an embodiment of the present invention;

[0045] Figure 3 It is a schematic diagram of the change of the external airflow field after the cross-section of a wind blade is covered with ice in the wind blade icing risk assessment and early warning method described in one embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0047] Example 1

[0048] Reference Figure 1-Figure 3 , which is an embodiment of the present invention, provides a wind turbine blade icing risk assessment and early warning method, comprising:

[0049] S100: Obtaining meteorological parameters of the wind farm;

[0050] S200: simulating the ice-covered state of the surface of the wind turbine blade based on the meteorological parameters input into the blade three-dimensional ice shape model to obtain the ice-covered shapes at different positions of the blade;

[0051] S300: calculating the aerodynamic characteristics of the iced blade according to the ice-covered shapes at different positions of the blade, obtaining the aerodynamic characteristic parameters of the two-dimensional iced airfoil structure at different positions, and obtaining the changes of the external airflow field of each two-dimensional cross section;

[0052] S400: Calculate the wind energy utilization rate according to the change of the airflow field;

[0053] S500: Assess the risk level of icing disasters and issue warnings based on the icing patterns and wind energy utilization rates at different locations.

[0054] It should be noted that currently, the shutdown is guided only by combining the power change of wind turbines with the weather conditions. The lack of wind turbine icing prediction and warning mechanism has become a core problem restricting the safe and stable operation of wind turbines. By using the theory in the above steps to predict the changes in aerodynamic performance after icing, and combining the theoretical model with experimental data for comparative verification, the accuracy and reliability of the model can be further improved; the laws and influencing factors of the impact of icing on the aerodynamic performance and power characteristics of wind turbines can be obtained, effectively improving the reliability and stability of wind power generation systems.

[0055] In the embodiment of the present application, the meteorological parameters of the wind farm obtained in step S100 include: wind speed V (m / s), temperature T (°C), liquid water content w (kg / m 3 ) and meteorological parameters such as median volume diameter of water droplets MVD (μm).

[0056] In the embodiment of the present application, the ice coating state on the surface of the wind turbine blade is simulated in step S200 to obtain the ice coating forms at different positions of the blade, including the following steps A1-A2:

[0057] A1: The thickness values ​​at various locations on the outer surface of the blade are obtained through simulation;

[0058] A2: Based on the thickness values ​​at different positions, the ice is spliced ​​to obtain the overall ice shape.

[0059] In another embodiment, the ice coating state on the surface of the wind turbine blade is simulated in step S200 to obtain the ice coating morphology at different positions of the blade. CFD (computational fluid dynamics) technology can also be used in combination with the principles of heat transfer to simulate the air flow and heat exchange process, thereby predicting the ice coating state on the blade surface.

[0060] In another embodiment, step S200 may also utilize machine learning or deep learning technology to train a model to identify ice morphology.

[0061] In an embodiment of the present application, the key blade ice thickness in the blade three-dimensional ice shape model in step S200 is the ratio of the product of the water droplet collision coefficient, the freezing coefficient and the wind speed of the wind farm at the calculated position on the blade surface, the area of ​​the calculated position of the wind turbine blade ice coverage, the liquid water content in the air, and the ice coverage duration to the ice coverage density value.

[0062] Specifically, environmental parameters such as V, T, w and MVD are used as input, and the blade ice thickness and shape are obtained according to the three-dimensional structure of the wind turbine blade and the ice duration dt. The calculation of the key blade ice thickness can be expressed as:

[0063]

[0064] Among them, α1 and α3 are the water drop collision coefficient and freezing coefficient of the blade surface calculation position respectively. The calculation methods of the two coefficients can refer to the Makkonen model; ds is the area of ​​the wind turbine blade ice calculation position, m 2 ρ i is the ice density, kg / m 3 ; dt is the duration of icing.

[0065] In the embodiments of the present application, Figure 2 As shown, the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions are obtained in step S300, including the following steps:

[0066] Different positions were obtained by sectioning;

[0067] Preferably, the different positions include: positions at 0.1R, 0.3R, 0.5R, 0.7R and 0.9R from the blade root, where R is the blade chord length.

[0068] It should be noted that the sectioning method simplifies a three-dimensional problem into a two-dimensional problem, reducing the computational complexity and amount. By sectioning at a specific position, a two-dimensional airfoil structure can be directly obtained, thereby simplifying the subsequent calculation of aerodynamic characteristics; it does not require complex mathematical models or advanced algorithms and is applicable to various engineering software; at the same time, this method selects any position for sectioning, which has high flexibility. According to actual needs, the above-mentioned key positions can be selected for detailed analysis, such as the blade root, blade tip or other important parts, which helps to fully understand the aerodynamic performance of the blade at different positions. The results obtained can be directly compared with experimental data to verify the accuracy of the calculation.

[0069] In another embodiment, the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions are obtained in step S300, and a proxy model (such as a response surface model, a Kriging model, etc.) can be constructed for the airfoil that has completed the preliminary simulation to quickly predict the aerodynamic performance of the unsimulated points.

[0070] In another embodiment, the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions are obtained in step S300, and the aerodynamic characteristics of the new ice-covered airfoil can be predicted by training a machine learning model (such as a neural network, a support vector machine, etc.).

[0071] In the embodiments of the present application, Figure 3 As shown, in step S300, the finite element method can be used to solve the Navier-Stokes equations on the outside of the ice-covered airfoil to obtain the changes in the external airflow field of each two-dimensional cross section of the blade.

[0072] In another embodiment, in step S300 , a finite difference method (FDM) or a boundary element method (BEM) may be used to solve the changes in the external airflow field of each two-dimensional cross section of the blade.

[0073] In the embodiment of the present application, the wind energy utilization rate is calculated according to the change of the airflow field in step S400, including the following steps:

[0074] Calculate the lift-to-drag ratio of the wind turbine blades. The wind energy utilization rate is calculated based on the lift-to-drag ratio of the wind turbine blades combined with the tip speed ratio. It is specifically expressed as:

[0075]

[0076] Among them, C P-i is the wind energy utilization rate at the i-th position; e is the lift-to-drag ratio of the wind turbine blade; λ r is the tip speed ratio.

[0077] In the embodiment of the present application, the step S500 evaluates the icing disaster risk level based on the icing forms and wind energy utilization rate at different locations, including:

[0078] According to the ice thickness and wind energy utilization rate of wind turbine blades at different positions, the overall weighted ice thickness and overall wind energy utilization rate of wind turbine blades are solved, which can be expressed as follows:

[0079]

[0080] Among them, h i represents the ice thickness at the i-th position; β i and k i They represent weighting coefficients respectively; n represents the total number of positions.

[0081] In the embodiment of the present application, the step S500 of evaluating the icing disaster risk level based on the icing forms and wind energy utilization rate at different locations also includes:

[0082] The risk level range of the overall weighted ice thickness and the overall wind energy utilization rate is set and divided into multiple levels, and each level corresponds to a corresponding overall weighted ice thickness threshold range and an overall wind energy utilization rate threshold range;

[0083] If the two parameters determine different risk levels, the higher risk level of the parameter will be the final judgment result.

[0084] Exemplarily, the risk level of wind turbine blade icing disaster is divided into four levels, namely, slight icing (level I), moderate icing (level II), severe icing (level III) and heavy icing (level IV), as shown in Table 1. The risk level of wind turbine blade icing disaster is determined according to two parameters, namely, ice thickness and weighted wind energy utilization rate. If the risk levels determined by the two parameters are different, the higher risk level shall prevail.

[0085] Table 1 Risk level of wind turbine blade icing disaster

[0086]

[0087] In another embodiment, the evaluation of the icing disaster risk level based on the icing forms and wind energy utilization rate at different locations in step S500 can also be performed by a comprehensive scoring method, that is, weights are set for the icing thickness and wind energy utilization rate at different locations, and a comprehensive score is calculated by weighted average. The risk level is divided according to the comprehensive score; or, based on expert experience and knowledge, a rule base is established to evaluate the risk level by rule matching.

[0088] It should be noted that this solution can more accurately understand the operating environment of wind turbines through real-time or predicted meteorological parameters. At the same time, the three-dimensional ice shape model based on meteorological parameters can accurately simulate the icing state of the blade surface and improve the accuracy of icing prediction. By calculating the aerodynamic characteristic parameters of the ice-covered airfoil structure at different positions and the wind energy utilization rate through changes in the airflow field, the impact of icing on blade performance can be more accurately evaluated. Through icing prediction and risk assessment, a more reasonable maintenance plan can be formulated to reduce unnecessary downtime, improve the availability of wind turbines, reduce the loss of power generation caused by icing, extend the service life of wind turbines, reduce maintenance and replacement costs, and improve the economic benefits of wind turbines.

[0089] The above is a schematic scheme of a wind turbine blade icing risk assessment and early warning method of this embodiment. It should be noted that the technical scheme of the wind turbine blade icing risk assessment and early warning system and the technical scheme of the wind turbine blade icing risk assessment and early warning method described above belong to the same concept. For details not described in detail in the technical scheme of the wind turbine blade icing risk assessment and early warning system in this embodiment, please refer to the description of the technical scheme of the wind turbine blade icing risk assessment and early warning method described above.

[0090] This embodiment also provides a system for wind turbine blade icing risk assessment and early warning method, including:

[0091] An acquisition module is used to obtain meteorological parameters of the wind farm;

[0092] A simulation module is used to simulate the ice-covered state of the wind turbine blade surface based on the meteorological parameters input into the blade three-dimensional ice shape model to obtain the ice-covered morphology at different positions of the blade;

[0093] The first calculation module is used to calculate the aerodynamic characteristics of the blade after ice coating according to the ice coating forms at different positions of the blade, obtain the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions, and obtain the changes of the external airflow field of each two-dimensional cross section;

[0094] The second calculation module is used to calculate the wind energy utilization rate according to the change of the airflow field;

[0095] The assessment module is used to assess the risk level of icing disasters and issue warnings based on the icing patterns and wind energy utilization rates at different locations.

[0096] This embodiment also provides a computing device suitable for wind blade icing risk assessment and early warning, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the wind blade icing risk assessment and early warning method proposed in the above embodiment.

[0097] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for evaluating and warning the risk of icing on wind turbine blades as proposed in the above embodiment is implemented.

[0098] The storage medium proposed in this embodiment and the method for implementing wind turbine blade icing risk assessment and early warning proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0099] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0100] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A wind turbine blade icing risk assessment and early warning method, characterized in that: include: Obtain meteorological parameters of wind farms; Based on the meteorological parameters input into the blade three-dimensional ice shape model, the ice covering state on the surface of the wind turbine blade is simulated to obtain the ice covering shape at different positions of the blade; The aerodynamic characteristics of the blade after ice coating are calculated by the ice coating forms at different positions of the blade, the aerodynamic characteristic parameters of the two-dimensional ice-coated airfoil structure at different positions are obtained, and the changes of the external airflow field of each two-dimensional cross section are obtained; According to the change of the airflow field, the wind energy utilization rate is calculated; Based on the ice cover forms and wind energy utilization rate at the different locations, the risk level of icing disasters is evaluated and a warning is issued.

2. The wind turbine blade icing risk assessment and early warning method according to claim 1, characterized in that: The ice coating state of the wind turbine blade surface is simulated to obtain the ice coating morphology at different positions of the blade, including: The thickness values ​​at various locations on the outer surface of the blade are obtained through simulation; Based on the thickness values ​​at different positions, they are spliced ​​together to obtain the overall ice cover shape.

3. The wind turbine blade icing risk assessment and early warning method according to claim 1 or 2, characterized in that: The key blade ice thickness in the blade three-dimensional ice shape model is the ratio of the product of the water drop collision coefficient, the freezing coefficient and the wind speed of the wind farm at the calculated position on the blade surface, the area of ​​the calculated position of the wind turbine blade ice, the liquid water content in the air, and the ice duration to the ice density value.

4. The wind turbine blade icing risk assessment and early warning method according to claim 3, characterized in that: The aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions are obtained, including: Different positions are obtained by sectioning; The different positions include: positions at 0.1R, 0.3R, 0.5R, 0.7R and 0.9R from the blade root, and R is the blade chord length.

5. The wind turbine blade icing risk assessment and early warning method according to claim 4, characterized in that: According to the change of the airflow field, the wind energy utilization rate is calculated, including: Calculate the lift-to-drag ratio of the wind turbine blades. The wind energy utilization rate is calculated based on the lift-to-drag ratio of the wind turbine blades combined with the tip speed ratio. It is specifically expressed as: Among them, C P-i is the wind energy utilization rate at the i-th position; e is the lift-to-drag ratio of the wind turbine blade; λ r is the tip speed ratio.

6. The wind turbine blade icing risk assessment and early warning method according to claim 5, characterized in that: The icing disaster risk level is assessed based on the icing forms and wind energy utilization rates at different locations, including: According to the ice thickness and wind energy utilization rate of wind turbine blades at different positions, the overall weighted ice thickness and overall wind energy utilization rate of wind turbine blades are solved, which can be expressed as follows: Among them, h i represents the ice thickness at the i-th position; β i and k i They represent weighting coefficients respectively; n represents the total number of positions.

7. The wind turbine blade icing risk assessment and early warning method according to claim 6, characterized in that: The icing disaster risk level is evaluated based on the icing forms and wind energy utilization rates at the different locations, and also includes: The risk level range of the overall weighted ice thickness and the overall wind energy utilization rate is set and divided into multiple levels, and each level corresponds to a corresponding overall weighted ice thickness threshold range and an overall wind energy utilization rate threshold range; If the two parameters determine different risk levels, the higher risk level of the parameter will be the final judgment result.

8. A system applied to the wind turbine blade icing risk assessment and early warning method according to any one of claims 1 to 7, characterized in that: include: An acquisition module is used to obtain meteorological parameters of the wind farm; A simulation module, for simulating the ice-covered state of the wind turbine blade surface based on the meteorological parameters input into the blade three-dimensional ice shape model, so as to obtain the ice-covered morphology at different positions of the blade; A first calculation module is used to calculate the aerodynamic characteristics of the ice-covered blade according to the ice-covered forms at different positions of the blade, obtain the aerodynamic characteristic parameters of the two-dimensional ice-covered airfoil structure at different positions, and obtain the changes of the external airflow field of each two-dimensional cross-section; A second calculation module is used to calculate the wind energy utilization rate according to the change of the airflow field; An assessment module is used to assess the risk level of icing disasters and issue warnings based on the icing forms and wind energy utilization rates at different locations.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the wind turbine blade icing risk assessment and early warning method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the wind turbine blade icing risk assessment and early warning method as described in any one of claims 1 to 7.

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