Method and system for calculating aerothermic de-icing power of fan blade

Abstract

The application discloses a kind of air-heating deicing power calculation methods of fan blade, including obtaining the data information of target fan;Critical ice-melting basic power and linear velocity of target fan blade are calculated;Centrifugal stress correction coefficient and variable pitch pitch correction coefficient of target fan blade are calculated;The correction coefficient obtained is optimized;Real-time ice-melting power of target fan blade is calculated;The real-time ice-melting power obtained is combined with the current real-time speed of target fan blade, and the calculation of the air-heating deicing power of fan blade is completed.The application also discloses a kind of system for realizing the air-heating deicing power calculation method of fan blade.The application not only can realize the calculation of the air-heating deicing power of fan blade, but also has higher reliability, better accuracy, and lower energy consumption in ice-melting process.

Description

Technical Field

[0001] This invention belongs to the field of electrical automation, and specifically relates to a method and system for calculating the air-heat de-icing power of wind turbine blades. Background Technology

[0002] With economic and technological development and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and daily life, bringing endless convenience. Therefore, ensuring a stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] Currently, an increasing number of wind power systems are being integrated into the power grid and generating electricity. Therefore, ensuring the normal operation of wind turbine generators has become one of the important tasks of the power system.

[0004] In wind farms located in high-altitude and cold mountainous areas, wind turbine blades are prone to icing from cold water droplets in winter, severely impacting the safe and stable operation of the turbines. The current mainstream de-icing solution is an air-heated internal cavity heating system. However, this system does not consider the operating conditions of the wind turbine; instead, it uses a constant heating power value. While simple and convenient, this method has high overall energy consumption and poor accuracy and reliability. Summary of the Invention

[0005] One of the objectives of this invention is to provide a method for calculating the air-thermal de-icing power of wind turbine blades that is highly reliable, accurate, and energy-efficient.

[0006] The second objective of this invention is to provide a system for calculating the power of air-heat de-icing of the wind turbine blades.

[0007] The method for calculating the air-thermal de-icing power of wind turbine blades provided by this invention includes the following steps:

[0008] S1. Obtain data information of the target wind turbine;

[0009] S2. Based on the data obtained in step S1, calculate the critical de-icing power and linear velocity of the target wind turbine blades;

[0010] S3. Based on the data obtained in step S2, calculate the centrifugal stress correction coefficient and pitch correction coefficient of the target wind turbine blade;

[0011] S4. Optimize the correction coefficients obtained in step S3;

[0012] S5. Calculate the real-time de-icing power of the target wind turbine blades based on the optimized correction coefficients obtained in step S4.

[0013] S6. Using the real-time de-icing power obtained in step S5, and combining it with the current real-time rotational speed of the target wind turbine blades, calculate the gas-thermal de-icing power of the wind turbine blades.

[0014] Step S1, which involves obtaining data information about the target wind turbine, specifically includes the following steps:

[0015] The acquired data includes the real-time rotational speed of the target wind turbine blades, blade pitch angle, blade size data, continuous duct heat exchange parameters, and standard winter icing thickness.

[0016] Step S2, which involves calculating the critical de-icing power and linear velocity of the target wind turbine blades based on the data obtained in step S1, specifically includes the following steps:

[0017] Based on the data obtained in step S1, and using the numerical model of thermo-mechanical coupling of the blade ice layer, the critical de-icing power corresponding to the initial cracking of the ice layer at the root, middle section, and tip of the target wind turbine blade under static conditions is calculated. , and ;

[0018] Based on the spanwise radius of the target wind turbine blade, the linear velocities of the blade root, mid-section, and tip are calculated using the following formula:

[0019] In the formula For the corresponding part, This represents the linear velocity of the leaf root. This indicates the linear velocity of the middle section of the blade. This indicates the linear velocity of the blade tip. The real-time rotational speed of the target wind turbine blades; To calibrate the spanwise radius, Indicates the calibrated spanwise radius of the leaf root. Indicates the rated spanwise radius of the middle section of the blade. This indicates the calibrated spanwise radius of the blade tip.

[0020] Step S3 calculates the centrifugal stress correction factor for the target wind turbine blades, specifically including the following steps:

[0021] The centrifugal stress correction factor of the target wind turbine blade is calculated using the following formula. :

[0022] In the formula The centrifugal attenuation coefficient is... This represents the offline attenuation coefficient of the leaf root portion. This represents the centrifugal attenuation coefficient of the middle section of the blade. This represents the centrifugal attenuation coefficient of the blade tip. ; The initial critical linear velocity, This represents the initial critical linear velocity of the leaf root region. This represents the initial critical linear velocity of the middle section of the blade. This represents the initial critical linear velocity at the blade tip. This refers to the maximum linear velocity of the fan under rated operating conditions. This indicates the maximum linear velocity of the fan at the blade root under rated operating conditions. This indicates the maximum linear velocity of the middle section of the blades under rated operating conditions. This indicates the maximum linear velocity of the fan tip under rated operating conditions.

[0023] Step S3 calculates the pitch correction coefficient for the target wind turbine blades, specifically including the following steps:

[0024] The pitch correction factor for the target wind turbine blades is calculated using the following formula:

[0025] In the formula The pitch correction factor for the target wind turbine blades; To correct the slope for small angles; The blade pitch angle of the target wind turbine blade; The target wind turbine blade's conventional power generation operating angle; This is the lower limit value of the set pitch correction factor; This is the attenuation coefficient at large angles.

[0026] Step S4, which involves optimizing the correction coefficients obtained in step S3, specifically includes the following steps:

[0027] The particle swarm optimization algorithm is used to correct the centrifugal stress coefficient. Variables in the calculation formula The variables in the formula for calculating pitch correction factor and Optimize;

[0028] During optimization, the following formula is used as the fitness function:

[0029] In the formula This is the first weight value set. This represents the total power output for ice melting; This is the maximum set total power for ice melting; This is the set second weight value; This represents the deviation value of the residual ice thickness. This is the set third weight value; This represents the temperature imbalance in the three regions of the leaf during the melting process; the smaller the fitness function value, the better the individual's fitness.

[0030] During optimization, set variable constraint ranges:

[0031] In the formula This is the minimum value of the set centrifugal stress correction factor; This is the maximum value of the set centrifugal stress correction factor; This is the minimum value of the pitch correction factor set; This is the maximum value of the pitch correction factor set for pitch control. This is the set minimum ice-melting power. This represents the minimum ice-melting power at the leaf root. This represents the minimum ice-melting power in the middle section of the blade. This represents the minimum ice-melting power at the blade tip. This is the maximum set ice-melting power. This indicates the maximum ice-melting power at the leaf root. This indicates the maximum ice-melting power in the middle section of the blade. This indicates the maximum ice-melting power at the blade tip. This is the ice-melting power value. This represents the ice-melting power value of the leaf root section. This indicates the de-icing power value of the middle section of the blade. This indicates the ice-melting power value of the blade tip.

[0032] Step S5, which calculates the real-time de-icing power of the target wind turbine blades based on the optimized correction coefficients obtained in step S4, specifically includes the following steps:

[0033] The real-time de-icing power of the target wind turbine blades was calculated. for .

[0034] Step S6 involves using the real-time de-icing power obtained in step S5, combined with the current real-time rotational speed of the target wind turbine blades, to calculate the air-thermal de-icing power of the wind turbine blades. This specifically includes the following steps:

[0035] If the real-time rotational speed of the target fan blades If the value is greater than or equal to the first set value, the calculated real-time de-icing power will be reduced by a set ratio; at this time, the de-icing will be assisted by the centrifugal force of the target fan blades.

[0036] If the real-time rotational speed of the target fan blades If the value is less than or equal to the second set value, the calculated real-time ice melting power will be increased by a set ratio; at this time, the increased power is used to compensate for the centrifugal force of the target wind turbine blades.

[0037] If the target wind turbine blades perform pitch control, the real-time de-icing power of the target wind turbine blades will be measured at a pre-set time before the pitch control action. Update.

[0038] This invention also provides a system for calculating the gas-thermal de-icing power of the wind turbine blades, comprising a data acquisition module, an initial calculation module, a correction calculation module, a coefficient optimization module, an ice-melting calculation module, and a power calculation module; the data acquisition module, initial calculation module, correction calculation module, coefficient optimization module, ice-melting calculation module, and power calculation module are connected in series; the data acquisition module is used to acquire data information of the target wind turbine and upload the data information to the initial calculation module; the initial calculation module is used to calculate the critical ice-melting basic power and linear velocity of the target wind turbine blades based on the received data information and the acquired data information, and upload the data information to the correction calculation module; the correction calculation module is used to calculate the critical ice-melting basic power and linear velocity of the target wind turbine blades based on the received data information and the acquired data information, and upload the data information to the correction calculation module; the correction calculation module is used to calculate the critical ice-melting basic power and linear velocity of the target wind turbine blades based on the received data information and the acquired data information. The system receives data and calculates the centrifugal stress correction coefficient and pitch correction coefficient of the target wind turbine blades. This data is then uploaded to the coefficient optimization module. The coefficient optimization module optimizes the received correction coefficients and uploads them to the de-icing calculation module. The de-icing calculation module calculates the real-time de-icing power of the target wind turbine blades based on the optimized correction coefficients and uploads this data to the power calculation module. Finally, the power calculation module calculates the air-thermal de-icing power of the wind turbine blades based on the received data, the real-time de-icing power, and the current real-time rotational speed of the target wind turbine blades.

[0039] The method and system for calculating the air-thermal de-icing power of wind turbine blades provided by this invention, by acquiring, analyzing and considering the real-time data of the target wind turbine blades and taking into account the centrifugal force generated by the rotation of the wind turbine blades, can not only calculate the air-thermal de-icing power of wind turbine blades, but also has higher reliability, better accuracy and lower energy consumption in the de-icing process. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0041] Figure 2 This is a schematic diagram of the functional modules of the system of the present invention. Detailed Implementation

[0042] like Figure 1 The diagram shown is a flowchart of the method of the present invention: The method for calculating the air-thermal de-icing power of wind turbine blades disclosed in this invention includes the following steps:

[0043] S1. Obtain data information of the target wind turbine; specifically including the following steps:

[0044] The acquired data includes the real-time rotational speed of the target wind turbine blades, blade pitch angle, blade size data, continuous duct heat exchange parameters, and standard winter icing thickness.

[0045] S2. Based on the data obtained in step S1, calculate the critical de-icing power and linear velocity of the target wind turbine blades; specifically including the following steps:

[0046] Based on the data obtained in step S1, and using the numerical model of thermo-mechanical coupling of the blade ice layer, the critical de-icing power corresponding to the initial cracking of the ice layer at the root, middle section, and tip of the target wind turbine blade under static conditions is calculated. , and In specific implementation, the scheme in the paper "Enhancing the Air-Heat De-icing Performance of Wind Turbine Blades Based on Numerical Simulation of Multiple Heat Transfer Models" published by Liu Zhongde et al. can be adopted to calculate the critical melting base power.

[0047] Based on the spanwise radius of the target wind turbine blade, the linear velocities of the blade root, mid-section, and tip are calculated using the following formula:

[0048] In the formula For the corresponding part, This represents the linear velocity of the leaf root. This indicates the linear velocity of the middle section of the blade. This indicates the linear velocity of the blade tip. The real-time rotational speed of the target wind turbine blades; To calibrate the spanwise radius, Indicates the calibrated spanwise radius of the leaf root. Indicates the rated spanwise radius of the middle section of the blade. Indicates the calibrated spanwise radius of the blade tip;

[0049] Based on the structural characteristics of the wind turbine blades Therefore, at the same rotational speed, there exists This provides the basic operating conditions for the differentiated correction of the zones;

[0050] S3. Based on the data obtained in step S2, calculate the centrifugal stress correction factor and pitch correction factor for the target wind turbine blades; specifically, this includes the following steps:

[0051] The centrifugal force generated by the blade rotation produces peeling stress within the ice layer. The higher the linear velocity, the greater the centrifugal peeling stress, and the lower the thermal power required for the critical melting of the ice layer. The correction coefficient is a monotonically decreasing factor that increases with the linear velocity of the partition, and its value range is strictly limited to [value range missing]. An exponential decay correction model is adopted, and a partitioned decay coefficient is introduced to match the stress characteristics at different spanwise locations.

[0052] Therefore, the centrifugal stress correction factor of the target wind turbine blade is calculated using the following formula. :

[0053] In the formula The centrifugal attenuation coefficient is... This represents the offline attenuation coefficient of the leaf root portion (preferably ranging from 0.1 to 0.3). This represents the centrifugal attenuation coefficient of the middle section of the blade (preferably ranging from 0.4 to 0.6). This represents the centrifugal attenuation coefficient of the blade tip (preferably ranging from 0.8 to 1.0). ; The initial critical linear velocity, This represents the initial critical linear velocity of the leaf root region. This represents the initial critical linear velocity of the middle section of the blade. This represents the initial critical linear velocity of the blade tip under static conditions. ; This refers to the maximum linear velocity of the fan under rated operating conditions. This indicates the maximum linear velocity of the fan at the blade root under rated operating conditions. This indicates the maximum linear velocity of the middle section of the blades under rated operating conditions. This indicates the maximum linear velocity of the fan tip under rated operating conditions.

[0054] blade pitch angle The larger the blade, the greater the angle of inclination of the windward side, which reduces the stability of ice adhesion, decreases the windward heat exchange area, and lowers the required ice melting thermal power; (Setting) The correction factor is a monotonically decreasing factor that increases with pitch angle, and its value range is [missing information]. A piecewise linear fitting model is used to distinguish between standby small-angle pitch and working large-angle pitch dual operating conditions.

[0055] The pitch correction factor for the target wind turbine blades is calculated using the following formula:

[0056] In the formula The pitch correction factor for the target wind turbine blades; For small-angle correction slope, a value range of 0.02~0.03 is preferred to ensure smooth and fine-tuned power within the working angle; The blade pitch angle of the target wind turbine blade; For the target wind turbine blade's conventional power generation operating angle, the preferred value is [value missing]. ; This corresponds to the wind turbine's normal power generation operating state. This corresponds to the wind turbine's standby, shutdown, and pitch control states. The lower limit of the pitch correction factor is preferably set to 0.4 to prevent the power from being too low at extremely large pitch angles, which could lead to de-icing failure. The preferred value range for the large-angle attenuation coefficient is 0.05~0.08, which is suitable for the rapid load reduction characteristics of large-angle pitch control.

[0057] S4. Optimize the correction coefficients obtained in step S3; specifically, this includes the following steps:

[0058] The particle swarm optimization algorithm is used to correct the centrifugal stress coefficient. Variables in the calculation formula The variables in the formula for calculating pitch correction factor and Optimize the parameters to achieve adaptive iterative optimization based on operating conditions;

[0059] During optimization, the objectives are to minimize ice-melting energy consumption, eliminate ice residue, and prevent localized overheating. The following formula is used as the fitness function:

[0060] In the formula This is the first weight value set. This represents the total power output for ice melting; This is the maximum set total power for ice melting; This is the set second weight value; This represents the deviation value of the residual ice thickness. This is the set third weight value; This represents the temperature imbalance in the three regions of the leaf during the melting process; the smaller the fitness function value, the better the individual's fitness.

[0061] During optimization, set variable constraint ranges:

[0062] In the formula The minimum value of the centrifugal stress correction factor is preferably set to 0.2; The maximum value of the centrifugal stress correction factor is set, preferably 1; The minimum value of the pitch correction factor is set, preferably 0.4; The maximum value of the pitch correction factor is set, preferably 1; The minimum set ice-melting power (preferably taken as a value) ), This represents the minimum ice-melting power at the leaf root. This represents the minimum ice-melting power in the middle section of the blade. This represents the minimum ice-melting power at the blade tip. The maximum set ice-melting power (preferably taken as [value]) ), This indicates the maximum ice-melting power at the leaf root. This indicates the maximum ice-melting power in the middle section of the blade. This indicates the maximum ice-melting power at the blade tip. This is the ice-melting power value. This represents the ice-melting power value of the leaf root section. This indicates the de-icing power value of the middle section of the blade. This indicates the ice-melting power value at the blade tip;

[0063] S5. Based on the optimized correction coefficients obtained in step S4, calculate the real-time de-icing power of the target wind turbine blades; specifically including the following steps:

[0064] The real-time de-icing power of the target wind turbine blades was calculated. for ;

[0065] This method quantifies the real-time rotational speed of the impeller. Blade pitch angle The coupled influence of the de-icing heating power in the three zones of leaf root, leaf middle section and leaf tip is used to achieve differentiated and dynamic heat load distribution in the three zones;

[0066] S6. Using the real-time de-icing power obtained in step S5, and combining it with the current real-time rotational speed of the target wind turbine blades, calculate the air-thermal de-icing power of the wind turbine blades; specifically including the following steps:

[0067] If the real-time rotational speed of the target fan blades Greater than or equal to the first set value (preferred value) If the calculated real-time de-icing power is reduced by a set ratio, then the de-icing is assisted by the centrifugal force of the target fan blades.

[0068] If the real-time rotational speed of the target fan blades Less than or equal to the second set value (preferred value) If the calculated real-time ice-melting power is increased by a set ratio, the increased power will be used to compensate for the centrifugal force of the target wind turbine blades.

[0069] If the target wind turbine blades undergo pitch control, the real-time de-icing power of the target wind turbine blades is measured at a pre-set time (preferably 0.5s) before the pitch control action. Update.

[0070] This invention introduces impeller speed and pitch angle as feedforward correction parameters, upgrading the existing de-icing heating scheme to a synergistic de-icing process of "thermal de-icing + centrifugal stripping". Under the same icing conditions, the energy consumption of this invention is significantly reduced. Moreover, this invention corrects the critical de-icing power of the three zones based on the blade spanwise linear velocity gradient, solving the problem of uneven heating caused by the large centrifugal force at the blade tip and the small centrifugal force at the blade root of long blades, avoiding local overheating or substandard de-icing, and thus achieving higher reliability and better accuracy.

[0071] The present invention will be further described below with reference to an embodiment:

[0072] The embodiment uses a 95m single-chamber fan blade, which is divided into three heating zones along the blade span: blade root, mid-section, and blade tip. The rated spanwise radii of the three zones are as follows: (Leaf roots) (Middle section) and (Blade tip); Rated blade speed of the fan Conventional generator pitch angle range large angle range of standby and shutdown ;

[0073] Based on a three-dimensional simulation model of blade thermo-mechanical coupling, and inputting parameters such as continuous duct heat transfer parameters, blade wall thickness, and standard winter icing thickness of 20 mm, the critical base power for ice layer cracking in the three internal zones of the blade under static conditions is calculated. , and ;

[0074] After the wind turbine blades become icy, the impeller speed and pitch angle are read in real time. Combined with the spanwise radius of the 95m blade in three zones, the outer edge linear velocity of each zone is calculated.

[0075] Rated high speed operating conditions: Calculations yielded , , ;

[0076] Low-speed standby mode: Calculations yielded , , ;

[0077] Zone attenuation coefficient values: , , ; Static reference Rated maximum linear velocity , , ;

[0078] Calculations were performed at the rated high speed: , , ;

[0079] Set segment threshold , , , ;

[0080] Calculation of conventional power generation attitude (Corresponding to the small angle range): ;

[0081] Calculate the standby state (Corresponding to the large angle range): ;

[0082] Set weight values: , , ;

[0083] Define the constraint interval: , , ;

[0084] Parameter optimization is performed using the particle swarm optimization algorithm;

[0085] The power of each partition is calculated as follows:

[0086] Operating Condition 1: High-Speed ​​Power Generation Condition ( , ), calculated , , Total heating capacity The overall high-speed output power is further reduced by 15% to 30%, with a 22% reduction for this specific operating condition, resulting in the final actual total output power. At this point, compared to the traditional solution, the total reference power of the three zones is maintained at a constant throughout the entire process. Therefore, the power was reduced. The energy saving rate is 56.21%;

[0087] Operating Condition 2: Low-speed standby condition ( , After optimization and calibration, the coefficients are: , , , The corrected power for the three zones was calculated as follows: , , The basic total power is Layered scheduling and low-speed compensation improve performance by 30%, ultimately resulting in higher actual total output power. At this point, compared to the traditional solution, the total reference power of the three zones is maintained at a constant throughout the entire process. Therefore, the power was reduced. The energy saving rate is 32.43%.

[0088] As can be seen from the above embodiments, the solution of the present invention can indeed reduce the energy consumption of the ice melting process.

[0089] like Figure 2The diagram shows the functional modules of the system of the present invention: The system for calculating the air-thermal de-icing power of the wind turbine blades disclosed in this invention includes a data acquisition module, an initial calculation module, a correction calculation module, a coefficient optimization module, an ice-melting calculation module, and a power calculation module; the data acquisition module, initial calculation module, correction calculation module, coefficient optimization module, ice-melting calculation module, and power calculation module are connected in series; the data acquisition module is used to acquire data information of the target wind turbine and upload the data information to the initial calculation module; the initial calculation module is used to calculate the critical ice-melting basic power and linear velocity of the target wind turbine blades based on the received data information and the acquired data information, and upload the data information to the correction calculation module; the correction calculation... The first module calculates the centrifugal stress correction coefficient and pitch correction coefficient of the target wind turbine blade based on the received data, and uploads the data to the coefficient optimization module. The second module optimizes the correction coefficients based on the received data and uploads the data to the de-icing calculation module. The third module calculates the real-time de-icing power of the target wind turbine blade based on the received data and the optimized correction coefficients, and uploads the data to the power calculation module. The fourth module calculates the air-thermal de-icing power of the wind turbine blade based on the received data, the real-time de-icing power, and the current real-time rotational speed of the target wind turbine blade.

Claims

1. A method for calculating the air-thermal de-icing power of wind turbine blades, comprising the following steps: S1. Obtain data information of the target wind turbine; S2. Based on the data obtained in step S1, calculate the critical de-icing power and linear velocity of the target wind turbine blades; S3. Based on the data obtained in step S2, calculate the centrifugal stress correction coefficient and pitch correction coefficient of the target wind turbine blade; S4. Optimize the correction coefficients obtained in step S3; S5. Calculate the real-time de-icing power of the target wind turbine blades based on the optimized correction coefficients obtained in step S4. S6. Using the real-time de-icing power obtained in step S5, and combining it with the current real-time rotational speed of the target wind turbine blades, the air-thermal de-icing power of the wind turbine blades is calculated.

2. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 1, characterized in that... Step S1, which involves obtaining data information about the target wind turbine, specifically includes the following steps: The acquired data includes the real-time rotational speed of the target wind turbine blades, blade pitch angle, blade size data, continuous duct heat exchange parameters, and standard winter icing thickness.

3. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 2, characterized in that... Step S2, which involves calculating the critical de-icing power and linear velocity of the target wind turbine blade based on the data obtained in step S1, specifically includes the following steps: Based on the data obtained in step S1, and using the numerical model of thermo-mechanical coupling of the blade ice layer, the critical de-icing power corresponding to the initial cracking of the ice layer at the root, middle section, and tip of the target wind turbine blade under static conditions is calculated. , and ; Based on the spanwise radius of the target wind turbine blade, the linear velocities of the root, mid-section, and tip of the blade are calculated using the following formula: In the formula For the corresponding part, This represents the linear velocity of the leaf root. This indicates the linear velocity of the middle section of the blade. This indicates the linear velocity of the blade tip. The real-time rotational speed of the target wind turbine blades; To calibrate the spanwise radius, Indicates the calibrated spanwise radius of the leaf root. Indicates the rated spanwise radius of the middle section of the blade. Indicates the calibrated spanwise radius of the blade tip.

4. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 3, characterized in that... Step S3 calculates the centrifugal stress correction factor for the target wind turbine blades, specifically including the following steps: The centrifugal stress correction factor of the target wind turbine blade is calculated using the following formula. : In the formula The centrifugal attenuation coefficient is... This represents the offline attenuation coefficient of the leaf root portion. This represents the centrifugal attenuation coefficient of the middle section of the blade. This represents the centrifugal attenuation coefficient of the blade tip. ; The initial critical linear velocity, This represents the initial critical linear velocity of the leaf root region. This represents the initial critical linear velocity of the middle section of the blade. This represents the initial critical linear velocity at the blade tip. This refers to the maximum linear velocity of the fan under rated operating conditions. This indicates the maximum linear velocity of the fan at the blade root under rated operating conditions. This indicates the maximum linear velocity of the middle section of the blades under rated operating conditions. This indicates the maximum linear velocity of the fan tip under rated operating conditions.

5. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 4, characterized in that... Step S3 calculates the pitch correction coefficient for the target wind turbine blades, specifically including the following steps: The pitch correction factor for the target wind turbine blades is calculated using the following formula: In the formula The pitch correction factor for the target wind turbine blades; To correct the slope for small angles; The blade pitch angle of the target wind turbine blade; The target wind turbine blade's conventional power generation operating angle; The lower limit value of the set pitch correction factor; This is the attenuation coefficient at large angles.

6. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 5, characterized in that... Step S4, which involves optimizing the correction coefficients obtained in step S3, specifically includes the following steps: The particle swarm optimization algorithm is used to correct the centrifugal stress coefficient. Variables in the calculation formula The variables in the formula for calculating pitch correction factor and Optimize; During optimization, the following formula is used as the fitness function: In the formula This is the first weight value set. This represents the total power output for ice melting; This is the maximum set total power for ice melting; This is the set second weight value; This represents the deviation value of the residual ice thickness. This is the set third weight value; This represents the temperature imbalance in the three regions of the leaf during the melting process; the smaller the fitness function value, the better the individual's fitness. During optimization, set variable constraint ranges: In the formula This is the minimum value of the set centrifugal stress correction factor; This is the maximum value of the set centrifugal stress correction factor; This is the minimum value of the pitch correction factor set; This is the maximum value of the pitch correction factor set for pitch control. This is the set minimum ice-melting power. This represents the minimum ice-melting power at the leaf root. This represents the minimum ice-melting power in the middle section of the blade. This represents the minimum ice-melting power at the blade tip. This is the maximum set ice-melting power. This indicates the maximum ice-melting power at the leaf root. This indicates the maximum ice-melting power in the middle section of the blade. This indicates the maximum ice-melting power at the blade tip. This represents the ice-melting power value. This represents the ice-melting power value of the leaf root section. This indicates the de-icing power value of the middle section of the blade. This indicates the ice-melting power value of the blade tip.

7. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 6, characterized in that... Step S5, which calculates the real-time de-icing power of the target wind turbine blades based on the optimized correction coefficients obtained in step S4, specifically includes the following steps: The real-time de-icing power of the target wind turbine blades was calculated. for .

8. The method for calculating the air-thermal de-icing power of wind turbine blades according to claim 7, characterized in that... Step S6 involves using the real-time de-icing power obtained in step S5, combined with the current real-time rotational speed of the target wind turbine blades, to calculate the air-thermal de-icing power of the wind turbine blades. This specifically includes the following steps: If the real-time rotational speed of the target fan blades If the value is greater than or equal to the first set value, the calculated real-time de-icing power will be reduced by a set ratio; at this time, the de-icing will be assisted by the centrifugal force of the target fan blades. If the real-time rotational speed of the target fan blades If the value is less than or equal to the second set value, the calculated real-time ice melting power will be increased by a set ratio; at this time, the increased power is used to compensate for the centrifugal force of the target wind turbine blades. If the target wind turbine blades undergo pitch control, the real-time de-icing power of the target wind turbine blades will be measured at a pre-set time before the pitch control action. Update.

9. A system for calculating the power of air-thermal de-icing of wind turbine blades as described in any one of claims 1 to 8, characterized in that... It includes a data acquisition module, an initial calculation module, a correction calculation module, a coefficient optimization module, an ice melting calculation module, and a power calculation module; the data acquisition module, initial calculation module, correction calculation module, coefficient optimization module, ice melting calculation module, and power calculation module are connected in series; the data acquisition module is used to acquire the data information of the target wind turbine and upload the data information to the initial calculation module; The initial calculation module is used to calculate the critical de-icing power and linear velocity of the target wind turbine blade based on the received data and the acquired data, and then upload the data to the correction calculation module. The correction calculation module is used to calculate the centrifugal stress correction coefficient and pitch correction coefficient of the target wind turbine blade based on the received data information, and then upload the data information to the coefficient optimization module. The coefficient optimization module is used to optimize the obtained correction coefficients based on the received data information and upload the data information to the ice melting calculation module; The ice melting calculation module is used to calculate the real-time ice melting power of the target wind turbine blades based on the received data and the optimized correction coefficients, and then upload the data to the power generation calculation module. The power calculation module is used to calculate the gas-thermal de-icing power of the wind turbine blades based on the received data information, the obtained real-time de-icing power, and the current real-time rotational speed of the target wind turbine blades.

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