Icing operation control method, device and wind turbine for wind turbine blade

Abstract

The present invention provides an icing operation control method, device and wind turbine for wind turbine blades. The method includes: obtaining the current operation parameters of the wind turbine and the current environmental parameters around the wind turbine blades; determining an icing risk assessment value of the wind turbine based on the current operation parameters and the current environmental parameters; and determining an icing operation strategy of the wind turbine based on the icing risk assessment value and in combination with the current operation state of the wind turbine. The icing operation control method, device and wind turbine for wind turbine blades provided by the present invention perform information fusion on data of multiple wind turbine sensors, quantitatively evaluate the icing condition of the wind turbine, and at the same time, according to the obtained icing risk assessment value, specifically formulate an optimization plan for control strategies under different operation states, solve the defect that the above-mentioned icing assessment is not accurate enough, and can effectively improve the operation safety of the unit under icing conditions and improve the power generation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy, and particularly to an icing operation control method, device and wind turbine for wind turbine blades. Background Art

[0002] Wind turbines will inevitably face harsh weather such as low temperature and freezing rain, which will result in common situations such as icing and snow accumulation on the wind turbine blades. The icing of wind turbine blades will change the shape and surface roughness of the blades, resulting in the deterioration of the aerodynamic performance of the blades and the reduction of power generation; at the same time, it will also cause the stall angle of attack to advance, and then cause the wind turbine to operate near the stall angle of attack area, affecting the operation safety and power generation efficiency of the unit. At the same time, due to the change of the aerodynamic characteristics of the blades, the rotational speed rises slowly during the starting state, and even the unit cannot be started.

[0003] The current research on the icing situation of wind turbines mainly focuses on the detection of the icing condition of wind turbine blades and the corresponding de-icing technology, while there is a lack of relevant research on the operation control of wind turbines in the icing state. Even if there is occasional research, it only evaluates the icing state by detecting the abnormality of the output power or rotational speed, and adjusts the control strategy in the power generation operation state accordingly.

[0004] The main defects of the existing operation control of wind turbines in the icing state are manifested in that the evaluation of the icing situation is relatively rough, and only single or a small number of operation parameters can be relied on to classify the icing situation, which is prone to misjudgment and affects the effect of the subsequent operation strategy. Summary of the Invention

[0005] The present invention provides an icing operation control method, device and wind turbine for wind turbine blades, which are used to solve the defect that the icing state of wind turbine blades cannot be quantitatively evaluated in the prior art and it is easy to generate misjudgment and shutdown, and can accurately calculate the icing risk assessment value of wind turbine blades, and then optimize the icing operation efficiency of the wind turbine on the premise of ensuring the equipment safety of the wind turbine.

[0006] In a first aspect, the present invention provides an icing operation control method for wind turbine blades, including:

[0007] Obtain the current operation parameters of the wind turbine and the current environmental parameters around the wind turbine blades;

[0008] Based on the current operation parameters and the current environmental parameters, determine the icing risk assessment value of the wind turbine;

[0009] Based on the icing risk assessment value and in combination with the current operation state of the wind turbine, determine the icing operation strategy of the wind turbine.

[0010] According to an ice - covered operation control method for a wind turbine blade provided by the present invention, determining the ice - covered risk assessment value of the wind turbine based on the current operation parameters and the current environmental parameters includes:

[0011] Determining at least one of the current wind energy utilization coefficient, the current output power, and the amplitude of the characteristic component of the current tower vibration signal of the wind turbine according to the current operation parameters and the current environmental parameters;

[0012] Establishing a Copula model to calculate the ice - covered risk assessment value of the wind turbine based on the Copula model; the Copula model is determined based on at least one of the first extreme value parameter, the second extreme value parameter, and the third extreme value parameter;

[0013] The first extreme value parameter is determined according to the ratio between the current wind energy utilization coefficient and the wind energy utilization coefficient of the wind turbine in the normal operation state; the second extreme value parameter is determined according to the ratio between the current output power and the output power of the wind turbine in the normal operation state; the third extreme value parameter is determined according to the ratio between the amplitude of the characteristic component of the current tower vibration signal and the amplitude of the characteristic component of the tower vibration signal of the wind turbine in the normal operation state.

[0014] According to an ice - covered operation control method for a wind turbine blade provided by the present invention, establishing a Copula model related to the first extreme value parameter, the second extreme value parameter, and the third extreme value parameter to calculate the ice - covered risk assessment value of the wind turbine based on the Copula model includes:

[0015] Substituting the first ice - covered risk parameter, the second ice - covered risk parameter, and the second ice - covered risk parameter into the Copula model to obtain the ice - covered risk assessment value;

[0016] The first ice - covered risk parameter is determined by the first extreme value parameter based on the generalized extreme value distribution function; the second ice - covered risk parameter is determined by the second extreme value parameter based on the generalized extreme value distribution function; the third ice - covered risk parameter is determined by the third extreme value parameter based on the generalized extreme value distribution function.

[0017] According to an ice - covered operation control method for a wind turbine blade provided by the present invention, determining at least one of the current wind energy utilization coefficient, the current output power, and the amplitude of the characteristic component of the current tower vibration signal of the wind turbine according to the current operation parameters and the current environmental parameters includes:

[0018] Select the variables of the wind energy utilization coefficient among the current operating parameters and the current environmental parameters, including wind speed, air density, current output power, and rotational speed, to calculate the current wind energy utilization coefficient using the variables of the wind energy utilization coefficient;

[0019] The current output power is selected from the operating data recorded in the SCADA system of the wind turbine;

[0020] Obtain the tower vibration signal of the wind turbine to extract the amplitude of the characteristic component of the current tower vibration signal.

[0021] According to a method for controlling the icing operation of the blades of a wind turbine provided by the present invention, based on the icing risk assessment value and combined with the current operating state of the wind turbine, determine the icing operation strategy of the wind turbine, including:

[0022] When it is determined that the current operating state of the wind turbine is the normal power generation state, determine the target blade pitch angle according to the magnitude of the icing risk assessment value;

[0023] The target blade pitch angle is to control the pitch system of the wind turbine to reduce the adjustment angle of the pitch angle of the blades of the wind turbine.

[0024] According to a method for controlling the icing operation of the blades of a wind turbine provided by the present invention, determining the target blade pitch angle according to the magnitude of the icing risk assessment value includes:

[0025] Input the icing risk assessment value into a pre-constructed list of risk assessment values and blade pitch angles to match the target blade pitch angle therefrom.

[0026] According to a method for controlling the icing operation of the blades of a wind turbine provided by the present invention, based on the icing risk assessment value and combined with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine further includes:

[0027] When it is determined that the current operating state of the wind turbine is the starting state, optimize the pitch angle adjustment curve according to the magnitude of the icing risk assessment value to determine the maximum torque coefficient;

[0028] Adjust the pitch angle of the blades of the wind turbine so that the current torque coefficient of the wind turbine is adjusted to the maximum torque coefficient.

[0029] In a second aspect, the present invention further provides a device for controlling the icing operation of the blades of a wind turbine, including:

[0030] A data acquisition module for obtaining the current operating parameters of the wind turbine and the current environmental parameters around the blades of the wind turbine;

[0031] A risk assessment module, configured to determine an icing risk assessment value of the wind turbine based on the current operating parameters and the current environmental parameters;

[0032] A strategy formulation module, configured to determine an icing operation strategy of the wind turbine based on the icing risk assessment value and in combination with the current operating state of the wind turbine.

[0033] In a third aspect, the present invention provides a wind turbine, including a generator body, in which an operation controller is provided; it further includes a memory and a program or instruction stored on the memory and executable on the operation controller, and when the program or instruction is executed by the operation controller, it executes the steps of the icing operation control method for the wind turbine blade according to any one of the first aspect.

[0034] In a fourth aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the steps of the icing operation control method for the wind turbine blade according to any one of the above.

[0035] In a fifth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the icing operation control method for the wind turbine blade according to any one of the above.

[0036] The icing operation control method, device and wind turbine provided by the present invention perform information fusion on data of multiple fan sensors, quantitatively evaluate the icing condition of the wind turbine, and at the same time, according to the obtained icing risk assessment value, specifically formulate an optimization plan for the control strategy under different operating states, solve the defect that the above-mentioned icing assessment is not accurate enough, and can effectively improve the operating safety of the unit under icing conditions and improve the power generation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a schematic flowchart of the icing operation control method for the wind turbine blade provided by the present invention;

[0039] Figure 2It is a schematic flowchart of the process for obtaining the current operating parameters of a wind turbine and the current environmental parameters around the blades of the wind turbine provided by the present invention;

[0040] Figure 3 It is a schematic flowchart of the process for determining the icing risk assessment value of a wind turbine provided by the present invention;

[0041] Figure 4 It is a schematic flowchart of the process for determining the icing operation strategy under normal power generation state provided by the present invention;

[0042] Figure 5 It is a schematic flowchart of the process for determining the icing operation strategy in startup state provided by the present invention;

[0043] Figure 6 It is a schematic structural diagram of an icing operation control device for the blades of a wind turbine provided by the present invention;

[0044] Figure 7 It is a schematic structural diagram of an electronic device provided by the present invention. Detailed Embodiments

[0045] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present invention fall within the protection scope of the present invention.

[0046] It should be noted that in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. Without further limitations, the element defined by the phrase "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0047] The terms "first", "second", etc. in this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / ", generally represents an "or" relationship between the associated objects before and after.

[0048] The following will Figures 1 - 7 describe the ice accretion operation control method, device and wind turbine of the wind turbine blade provided by the embodiments of the present invention.

[0049] Figure 1 is a schematic flow chart of the ice accretion operation control method of the wind turbine blade provided by the present invention. As Figure 1 shown, it includes but is not limited to the following steps:

[0050] Step 101: Obtain the current operating parameters of the wind turbine and the current environmental parameters around the wind turbine blade.

[0051] In fluid dynamics, stall refers to a state in which the lift generated by the blade suddenly decreases when the angle of attack (which can be understood as the angle between the oncoming flow direction and the chord line) of the airfoil increases to a certain extent (reaching the stall angle of attack).

[0052] Under normal operation of the wind turbine, the stall angle of attack is generally about 15°. After the wind turbine blade is severely iced, the stall angle of attack of its upper airfoil can be advanced to 7.5° or even smaller.

[0053] Before the angle of attack of the blade exceeds the stall angle of attack, the lift of the airfoil increases with the increase of the angle of attack; however, after the angle of attack exceeds the stall angle of attack, the air flow condition on the back of the blade begins to deteriorate, and a vortex region will appear at the trailing end of the back of the blade, which will significantly reduce the lift coefficient of the blade and increase the drag coefficient of the blade, resulting in a decrease in power generation. More seriously, further icing will cause the stall angle of attack of the blade to advance in advance, the blade enters the stall region, and the aerodynamic characteristics fluctuate violently, which will cause the blade of the fan to flutter and even cause the resonance of the whole machine, damaging the fatigue life of the blade.

[0054] The ice accretion operation control method of the wind turbine blade provided by the present invention can realize the quantitative calculation of the ice accretion state of the wind turbine blade by collecting and fusing data from multiple fan sensors.

[0055] Figure 2It is a schematic flowchart of the process for obtaining the current operating parameters of a wind turbine and the current environmental parameters around the blades of the wind turbine provided by the present invention. As Figure 2 shown, the current operating parameters of the wind turbine may include, but are not limited to, one or more of the following parameters: the rotational speed of the wind turbine blades during operation (abbreviated as rotational speed), the output power of the wind turbine (abbreviated as power), the pitch angle of the wind turbine blades (abbreviated as pitch angle), the torque of the wind turbine (abbreviated as torque), and the vibration of the tower (abbreviated as vibration); the current environmental parameters mainly include at least one of the following information: environmental temperature (abbreviated as temperature), incoming flow density (abbreviated as density), current air humidity (abbreviated as humidity), and incoming flow wind speed (abbreviated as wind speed).

[0056] Optionally, the current operating parameters of the above-mentioned wind turbine can also be retrieved from the data acquisition and monitoring system (SCADA system) of the wind turbine.

[0057] Step 102: Based on the current operating parameters and the current environmental parameters, determine the icing risk assessment value of the wind turbine.

[0058] Figure 3 It is a schematic flowchart of the process for determining the icing risk assessment value of a wind turbine provided by the present invention. As Figure 3 shown, when the present invention conducts the icing risk assessment of the blades, it first comprehensively judges whether the conditions for blade icing are met according to the current season and the collected current environmental parameters, etc.

[0059] After determining that the icing conditions are met, the abnormal conditions of the wind turbine can be analyzed based on relevant data such as the output power, wind energy utilization efficiency, and tower vibration of the wind turbine, including abnormal output power analysis, abnormal wind energy utilization analysis, and abnormal tower vibration analysis, etc., and then the specific state of blade icing can be quantitatively calculated.

[0060] For example, a Copula model of three-dimensional extreme value parameters related to output power, wind energy utilization efficiency, and vibration can be established to quantitatively evaluate the icing situation, and the calculation result of the Copula model can be used as the icing risk assessment value.

[0061] Step 103: Based on the icing risk assessment value and combined with the current operating state of the wind turbine, determine the icing operation strategy of the wind turbine.

[0062] The current operating state of the wind turbine may include the start-up state, the power generation state, the shutdown state, etc. After obtaining the icing risk assessment value, a corresponding icing operation strategy can be formulated according to the current operating state of the wind turbine, so as to optimize the icing operation efficiency of the wind turbine to the greatest extent while ensuring the equipment safety of the wind turbine.

[0063] For example, when the wind turbine is in a power generation state and it is determined that the icing risk assessment value is large, the angle of attack of the wind turbine can be moved out of the angle of attack stall region by reducing the pitch angle.

[0064] The icing operation control method for wind turbine blades provided by the present invention performs information fusion on data from multiple wind turbine sensors, quantitatively evaluates the icing condition of the wind turbine, and at the same time, formulates control strategy optimization schemes under different operating conditions in a targeted manner based on the acquired icing risk assessment value, thereby solving the defect of inaccurate icing assessment mentioned above, and can effectively improve the operating safety of the unit under icing conditions and improve the power generation efficiency.

[0065] Based on the content of the above embodiment, as an optional embodiment, determining the icing risk assessment value of the wind turbine based on the current operating parameters and the current environmental parameters includes:

[0066] Determine at least one of a current wind energy utilization coefficient, a current output power, and a current tower vibration signal characteristic component amplitude of the wind turbine according to the current operating parameter and the current environmental parameter;

[0067] Establishing a Copula model to calculate an icing risk assessment value of the wind turbine based on the Copula model; the Copula model is determined based on at least one of the first extreme value parameter, the second extreme value parameter, and the third extreme value parameter;

[0068] The first extreme value parameter is determined based on the ratio between the current wind energy utilization coefficient and the wind energy utilization coefficient of the wind turbine under normal operating conditions; the second extreme value parameter is determined based on the ratio between the current output power and the output power of the wind turbine under normal operating conditions; the third extreme value parameter is determined based on the ratio between the amplitude of the characteristic component of the current tower vibration signal and the amplitude of the characteristic component of the tower vibration signal of the wind turbine under normal operating conditions.

[0069] On the one hand, after the wind turbine blade is covered with ice, the shape of the blade will change, which will lead to a decrease in the wind energy utilization coefficient (also known as the Cp value), that is, the Cp value in the ice-covered state of the blade will be lower than that in the normal operating state without ice coverage. In view of this, the present invention can calculate the first extreme value parameter x1 by comparing the current wind energy utilization coefficient Cp1 with the Cp2 in the normal operating state, so as to quantify the ice-covered state of the wind turbine blade.

[0070] Specifically, the calculation formula of the first extreme value parameter x1 can be designed as:

[0071] On the other hand, after the wind turbine blade is covered with ice, the output power of the wind turbine under the same working conditions will deviate from the normal value, that is, the output power in the ice-covered state of the blade will be lower than that in the normal operating state without ice coverage. In view of this, the present invention can calculate the second extreme value parameter x2 by comparing the current output power P1 with the output power P2 in the normal operating state, so as to quantify the ice-covered state of the wind turbine blade.

[0072] Specifically, the calculation formula of the first extreme value parameter x2 can be designed as:

[0073] On the other hand, after the wind turbine blade is covered with ice, while increasing the load of the blade and tower structure, due to the non-uniform distribution of the ice covered, it will damage the mass balance during the rotation of the entire impeller, cause changes in the vibration characteristics of the impeller and its associated components, and then lead to abnormal vibration of the tower. By comparing the changes in the characteristic frequency components during operation, for example, it will cause a significant increase in the amplitude of the characteristic components of the tower vibration signal.

[0074] In view of this, the present invention can calculate the third extreme value parameter x3 by comparing the amplitude A1 of the characteristic components of the current tower vibration signal with the maximum amplitude A of the characteristic components of the tower vibration signal in the normal operating state max so as to quantify the ice-covered state of the wind turbine blade.

[0075] On the basis of the above theoretical elaboration, the present invention adopts the extreme value theory to establish a Copula model related to at least one three-dimensional extreme value parameter among the first extreme value parameter, the second extreme value parameter and the third extreme value parameter, so that the high-precision quantitative evaluation of the ice-covering risk of the wind turbine can be realized by using a limited amount of data.

[0076] It should be noted that in the present invention, only parameters such as the current wind energy utilization coefficient of the wind turbine, the current output power, and the amplitude of the characteristic component of the current tower vibration signal are described for constructing the Copula model. In actual work, other parameters that vary according to different icing conditions of the wind turbine can also be selected to participate in the construction of the Copula model, which will not be elaborated here one by one.

[0077] As an alternative embodiment, establishing a Copula model related to the first extreme value parameter, the second extreme value parameter, and the third extreme value parameter to calculate the icing risk assessment value of the wind turbine based on the Copula model includes:

[0078] Substituting the first icing risk parameter, the second icing risk parameter, and the second icing risk parameter into the Copula model to obtain the icing risk assessment value;

[0079] Among them, the first icing risk parameter can be determined based on the generalized extreme value distribution function from the first extreme value parameter; the second icing risk parameter can be determined based on the generalized extreme value distribution function from the second extreme value parameter; the third icing risk parameter can be determined based on the generalized extreme value distribution function from the third extreme value parameter.

[0080] First of all, the present invention uses the Generalized Extreme Value (GEV) distribution function to evaluate the icing risk of the wind turbine caused by a single extreme value parameter, and calculates the first icing risk parameter, the second icing risk parameter, and the third icing risk parameter respectively.

[0081]

[0082] where x i,max is the maximum value within the sampling time, ξ, μ, σ are the distribution parameters of the GEV function, and can be determined through experiments for the same wind turbine. For the convenience of description, F i (x i ; ξ, μ, σ) will be simplified to F i,max subsequently. That is, the first icing risk parameter, the second icing risk parameter, and the third icing risk parameter corresponding to x1 - x3 are F1 - F3 respectively. i

[0083] Then, establish a Copula model related to three - dimensional extreme value parameters, and its functional expression is:

[0084] C(y1,y2,y3) = C(F1(x 1,max ),F2(x 2,max ),F3(x 3,max ));

[0085] Optionally, if the Joe Copula model is selected as the Copula model for actual application in the present invention, the calculation function of the icing risk assessment value can be determined:

[0086]

[0087] Wherein, k1 and k2 are constant terms to be identified in the Joe Copula model, which can be determined by experiments for the same wind turbine.

[0088] The icing operation control method for the wind turbine blade provided by the present invention provides a theoretical basis for quantitatively calculating the icing risk assessment value by reasonably selecting the wind energy utilization coefficient, output power, and the amplitude of the characteristic components of the tower vibration signal that change significantly due to blade icing, and performing multivariate correlation analysis based on the Copula model. It can ensure that the calculated icing risk assessment value truly reflects the actual icing state of the blade, and the calculation result is verified by experiments to have high accuracy.

[0089] Based on the content of the above embodiments, as an optional embodiment, determining at least one of the current wind energy utilization coefficient, current output power, and the amplitude of the characteristic components of the current tower vibration signal of the wind turbine according to the current operating parameters and the current environmental parameters includes:

[0090] Selecting the variables of the wind energy utilization coefficient in the current operating parameters and the current environmental parameters, including wind speed, air density, current output power, and rotational speed, to calculate the current wind energy utilization coefficient using the variables of the wind energy utilization coefficient; the current output power is selected from the operating data recorded in the SCADA system of the wind turbine; obtaining the tower vibration signal of the wind turbine to extract the amplitude of the characteristic components of the current tower vibration signal.

[0091] Specifically, the present invention provides a method for calculating the wind energy utilization coefficient, and its calculation formula can be expressed as:

[0092]

[0093] Wherein, Cp is the wind energy utilization coefficient, P is the current output power, ρ is the air density, R is the wind wheel radius, v is the wind speed, and η is the power conversion efficiency of the wind turbine.

[0094] Wherein, the current output power P can be selected from the operating data recorded in the SCADA system of the wind turbine; the air density ρ and the wind speed v can be detected in real time by pre-set sensors; both the wind wheel radius R and the power conversion efficiency η of the wind turbine can be obtained by looking up the table according to the model of the wind turbine.

[0095] Since many parameters in the above-mentioned ice accretion risk calculation model of wind turbines need to be identified through actual operation data, when using the above-mentioned ice accretion risk calculation model, if the working atmospheric environment of the wind turbine changes greatly, directly using the data collected by sensors will cause deviations in the calculation results. For example, when the atmospheric temperature and pressure are different, even if the parameters such as the rotational speed and pitch angle of the wind turbine are the same, the output power generated is also different. Therefore, it is necessary to correct the performance parameters of the wind turbine using atmospheric environment parameters to ensure that at different times, if the corrected parameters are the same, the wind turbines at the two times can be regarded as operating under the same working condition, thereby ensuring the accuracy of the ice accretion risk assessment of the wind turbine.

[0096] The correction is carried out using similarity criteria. For example, the rotational speed is corrected to The air flow rate is corrected to In the formula, w, m, p, and T are the wind turbine rotational speed, air flow rate, atmospheric pressure, and atmospheric temperature respectively. The subscript cor represents the corrected data, the superscript * represents the total temperature and total pressure, and the subscript 0 represents the reference state or standard state. The parameters of these reference states are known and fixed and are used as the comparison benchmark. Others such as speed correction and density correction are carried out in a similar manner.

[0097] It should be noted that after obtaining the current operation parameters of the wind turbine and the current environment parameters around the wind turbine blades, the present invention further includes: using the collected current environment parameters to perform similarity correction on the current operation parameters to eliminate abnormal data therein.

[0098] For example, the incoming flow wind speed value range is determined according to the current environment parameters, and the current operation parameters collected at time points outside the incoming flow wind speed value range are taken as abnormal data.

[0099] For another example, on the basis of setting the incoming flow wind speed value range, an active power threshold is also set, and the current operation parameters collected at time points within the incoming flow wind speed value range but with active power less than the active power threshold are taken as abnormal data.

[0100] Furthermore, for the method of extracting the corresponding vibration signal characteristic components from the collected vibration signals of the tower, a feature extraction method based on Empirical Mode Decomposition (EMD) can be adopted to obtain a finite number of Intrinsic Mode Function (IMF) components related to the tower vibration signal. Each decomposed IMF component contains local characteristic signals of different time scales of the original vibration signal. Finally, Hilbert transform is performed on each IMF component to obtain the instantaneous tower vibration signal characteristic components, and then the amplitudes of the tower vibration signal characteristic components are statistically calculated.

[0101] Compared with the prior art which only uses atmospheric temperature and humidity as the basis for judging the icing risk level and lacks the consideration of the individual differences of the wind turbines, the icing operation control method of the wind turbine blades provided by the present invention comprehensively considers the operating parameters of the wind turbine, including output power, wind energy utilization rate, vibration and other parameters on the basis of collecting environmental parameters, and can further improve the evaluation accuracy of the icing state of the blades.

[0102] Figure 4 It is a schematic flow chart of determining the icing operation strategy in the normal power generation state provided by the present invention. As Figure 4 shown, based on the icing risk assessment value and combined with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine includes:

[0103] When it is determined that the current operating state of the wind turbine is the normal power generation state, determine the target pitch angle according to the size of the icing risk assessment value; wherein, the target pitch angle is to control the pitch system of the wind turbine to reduce the adjustment angle of the pitch angle of the wind turbine blades.

[0104] Specifically, the present invention can judge whether the wind turbine is operating in the stall angle of attack region according to the size of the icing risk assessment value.

[0105] After it is judged that the current is in the stall angle of attack region, the pitch angle of the wind turbine blades can be reduced by comparing the control of the pitch system, so that the wind turbine can get out of the stall angle of attack region and improve the operating efficiency.

[0106] It should be noted that when it is judged according to the icing risk assessment value that the icing of the blades has reached a certain degree (i.e., C(y1, y2, y3) > icing risk threshold), the wind turbine is controlled to stop to avoid damage to the equipment itself. Among them, the icing risk threshold can be determined according to tests.

[0107] Furthermore, determining the target pitch angle according to the size of the icing risk assessment value may include: inputting the icing risk assessment value into a pre-constructed list of risk assessment values and pitch angles to match the target pitch angle therefrom.

[0108] Table 1 List of Risk Assessment Values and Pitch Angles

[0109]

[0110]

[0111] Table 1 is a list of risk assessment values and pitch angles provided by the present invention. As shown in Table 1, when it is determined that the wind turbine is in a normal power generation state (i.e., in the operation stage), the corresponding target pitch angle can be found according to the interval to which the calculated icing risk assessment value belongs.

[0112] The icing operation control method for the wind turbine blades provided by the present invention optimizes the pitch angle through a quantitative icing risk assessment value, and the control is more precise.

[0113] Figure 5 It is a schematic flow chart for determining the icing operation strategy in the starting state provided by the present invention. As Figure 5 shown, based on the icing risk assessment value and combined with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine further includes:

[0114] When it is determined that the current operating state of the wind turbine is the starting state, optimize the pitch angle adjustment curve according to the magnitude of the icing risk assessment value, that is, θ com = f(λ, C), where θ com is the pitch angle command during the starting process, λ is the tip speed ratio, and C is the risk assessment value; the optimization objective is to obtain the maximum torque coefficient to improve the starting performance of the fan; adjust the pitch angle of the wind turbine blades so that the current torque coefficient of the wind turbine is adjusted to the maximum torque coefficient.

[0115] The starting process of wind power generation is as follows: when the wind blows towards the blades, aerodynamic forces are generated on the blades to drive the blades to rotate, and then the speed of the blade rotation is increased through a speed increaser to prompt the generator to start generating electricity.

[0116] It should be noted that the reason for adding a speed increaser is that since the wind turbine is in the starting state, the starting speed of the blades is relatively low, and the magnitude and direction of the wind will also change, which makes the starting speed unstable. Therefore, before driving the generator, by adding a speed increaser (such as a gearbox) that increases the speed of the blades to the rated speed of the generator, and then adding a speed regulating mechanism to keep the speed stable, and then connecting it to the generator; the generator transmits the constant speed obtained from the blades through speed increase to the power generation mechanism for uniform operation, thus converting mechanical energy into electrical energy. At the same time, in the starting state, considering that it is necessary to increase the starting speed of the blades, the pitch angle of the wind turbine blades can be appropriately increased, but at the same time, considering the factor of large starting resistance, for the adjustment of the pitch angle size, the rated torque coefficient of the blades also needs to be comprehensively considered.

[0117] The above steps only consider the startup process of the wind turbine under ice-free conditions. However, in the case of ice-covered blades, it is necessary to first optimize the pitch angle adjustment curve in combination with the magnitude of the ice-covering risk assessment value, so as to obtain the optimal torque coefficient (i.e., the maximum torque coefficient).

[0118] Furthermore, adjust the pitch angle of the wind turbine blade according to the determined maximum torque coefficient, so that the current torque coefficient of the wind turbine is adjusted to the maximum torque coefficient.

[0119] The ice-covering operation control method for the wind turbine blade provided by the present invention first identifies the ice-covering state of the blade, quantitatively determines the ice-covering degree, and controls the pitch system to adjust different pitch angles according to the obtained ice-covering risk assessment value, so that the wind turbine gets out of the stall angle of attack area, improves the operation efficiency, and when the ice on the blade reaches a certain degree, shuts down for protection. In addition, when the wind turbine is in the startup state, according to the ice-covering condition, with the maximum torque coefficient as the target, the pitch angle is adjusted and the curve is optimized to improve the startup performance.

[0120] Compared with the existing method that only optimizes the ice-covering operation countermeasures under normal power generation conditions, the ice-covering operation control method for the wind turbine blade provided by the present invention can also solve the problem of difficult startup under ice-covering conditions.

[0121] Figure 6 is a schematic structural diagram of the ice-covering operation control device for the wind turbine blade provided by the present invention, as Figure 6 shown, mainly including but not limited to a data acquisition module 11, a risk assessment module 12, and a strategy formulation module 13, where:

[0122] The data acquisition module 11 is mainly used to obtain the current operation parameters of the wind turbine and the current environmental parameters around the wind turbine blade;

[0123] The risk assessment module 12 is mainly used to determine the ice-covering risk assessment value of the wind turbine based on the current operation parameters and the current environmental parameters;

[0124] The strategy formulation module 13 is mainly used to determine the ice-covering operation strategy of the wind turbine based on the ice-covering risk assessment value and in combination with the current operation state of the wind turbine.

[0125] It should be noted that the ice-covering operation control device for the wind turbine blade provided by the embodiments of the present invention can execute the ice-covering operation control method for the wind turbine blade described in any of the above embodiments during specific operation, and this embodiment will not be elaborated here.

[0126] Based on the above embodiments, the present invention further provides a wind turbine, which mainly includes a generator body, and an operation controller is provided in the generator body; it further includes a memory and a program or instruction stored on the memory and executable on the operation controller. When the program or instruction is executed by the operation controller, it executes the steps of the icing operation control method for the wind turbine blades provided in the above embodiments.

[0127] The icing operation control device for wind turbine blades and the wind turbine provided by the present invention perform information fusion on data of multiple wind turbine sensors, quantitatively evaluate the icing condition of the wind turbine, and at the same time, according to the obtained icing risk assessment value, specifically formulate an optimization plan for the control strategy under different operating states, solve the defect that the above icing assessment is not accurate enough, and can effectively improve the operating safety of the unit under icing conditions and improve the power generation efficiency.

[0128] Figure 7 is a schematic structural diagram of the electronic device provided by the present invention, as Figure 7 shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communication interface 720, and the memory 730 complete mutual communication through the communication bus 740. The processor 710 can call the logical instructions in the memory 730 to execute the icing operation control method for the wind turbine blades, and the method includes: obtaining the current operating parameters of the wind turbine and the current environmental parameters around the wind turbine blades; based on the current operating parameters and the current environmental parameters, determining the icing risk assessment value of the wind turbine; based on the icing risk assessment value and in combination with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine.

[0129] In addition, when the logic instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0130] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the icing operation control method for a wind turbine blade provided by the above-mentioned various methods. The method includes: obtaining the current operating parameters of the wind turbine and the current environmental parameters around the wind turbine blade; based on the current operating parameters and the current environmental parameters, determining the icing risk assessment value of the wind turbine; based on the icing risk assessment value and in combination with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine.

[0131] On yet another hand, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the icing operation control method for a wind turbine blade provided by the above-mentioned various embodiments. The method includes: obtaining the current operating parameters of the wind turbine and the current environmental parameters around the wind turbine blade; based on the current operating parameters and the current environmental parameters, determining the icing risk assessment value of the wind turbine; based on the icing risk assessment value and in combination with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine.

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0133] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0134] Finally, 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 them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the icing operation of a wind turbine blade, characterized in that, Including: Obtaining the current operating parameters of the wind turbine and the current environmental parameters around the blades of the wind turbine; Based on the current operating parameters and the current environmental parameters, determining the icing risk assessment value of the wind turbine; Based on the icing risk assessment value and in combination with the current operating state of the wind turbine, determining the icing operation strategy of the wind turbine; The determining the icing risk assessment value of the wind turbine based on the current operating parameters and the current environmental parameters includes: According to the current operating parameters and the current environmental parameters, determining at least one of the current wind energy utilization coefficient, the current output power, and the amplitude of the characteristic component of the current tower vibration signal of the wind turbine; Establishing a Copula model to calculate the icing risk assessment value of the wind turbine based on the Copula model; the Copula model is determined based on at least one of a first extreme value parameter, a second extreme value parameter, and a third extreme value parameter; The first extreme value parameter is determined according to the ratio between the current wind energy utilization coefficient and the wind energy utilization coefficient of the wind turbine in the normal operating state; The second extreme value parameter is determined according to the ratio between the current output power and the output power of the wind turbine in the normal operating state; the third extreme value parameter is determined according to the ratio between the amplitude of the characteristic component of the current tower vibration signal and the amplitude of the characteristic component of the tower vibration signal of the wind turbine in the normal operating state.

2. The icing operation control method for a wind turbine blade according to claim 1, characterized in that The establishing a Copula model to calculate the icing risk assessment value of the wind turbine based on the Copula model includes: Substituting at least one of a first icing risk parameter, a second icing risk parameter, and a third icing risk parameter into the Copula model to obtain the icing risk assessment value; The first icing risk parameter is determined based on the generalized extreme value distribution function from the first extreme value parameter; the second icing risk parameter is determined based on the generalized extreme value distribution function from the second extreme value parameter; the third icing risk parameter is determined based on the generalized extreme value distribution function from the third extreme value parameter.

3. The icing operation control method for a wind turbine blade according to claim 1, characterized in that According to the current operating parameters and the current environmental parameters, determining at least one of the current wind energy utilization coefficient, the current output power, and the amplitude of the characteristic component of the current tower vibration signal of the wind turbine includes: Selecting the wind energy utilization coefficient variables in the current operating parameters and the current environmental parameters, including wind speed, air density, current output power, and rotational speed, to calculate the current wind energy utilization coefficient using the wind energy utilization coefficient variables; The current output power is selected from the operation data recorded in the SCADA system of the wind turbine; Obtaining the tower vibration signal of the wind turbine to extract the amplitude of the characteristic component of the current tower vibration signal.

4. The icing operation control method for a wind turbine blade according to claim 1, characterized in that, The determining the icing operation strategy of the wind turbine based on the icing risk assessment value and in combination with the current operating state of the wind turbine includes: When it is determined that the current operating state of the wind turbine is the normal power generation state, determine the target pitch angle according to the magnitude of the icing risk assessment value; The target pitch angle is to control the pitch system of the wind turbine to reduce the adjustment angle of the pitch angle of the wind turbine blade.

5. The icing operation control method for a wind turbine blade according to claim 4, characterized in that, The determining the target pitch angle according to the magnitude of the icing risk assessment value includes: Input the icing risk assessment value into a pre-constructed list of risk assessment values and pitch angles to match the target pitch angle therefrom.

6. The icing operation control method for a wind turbine blade according to claim 1, characterized in that, The determining the icing operation strategy of the wind turbine based on the icing risk assessment value and in combination with the current operating state of the wind turbine further includes: When it is determined that the current operating state of the wind turbine is the starting state, optimize the pitch angle adjustment curve according to the magnitude of the icing risk assessment value to determine the maximum torque coefficient; Adjust the pitch angle of the wind turbine blade so that the current torque coefficient of the wind turbine is adjusted to the maximum torque coefficient.

7. An icing operation control device for a wind turbine blade, characterized in that, including: A data acquisition module for acquiring the current operating parameters of the wind turbine and the current environmental parameters around the wind turbine blade; A risk assessment module for determining the icing risk assessment value of the wind turbine based on the current operating parameters and the current environmental parameters, specifically including: determining at least one of the current wind energy utilization coefficient, the current output power, and the amplitude of the characteristic component of the current tower vibration signal of the wind turbine according to the current operating parameters and the current environmental parameters; establishing a Copula model to calculate the icing risk assessment value of the wind turbine based on the Copula model; the Copula model is determined based on at least one of a first extreme value parameter, a second extreme value parameter, and a third extreme value parameter; the first extreme value parameter is determined according to the ratio between the current wind energy utilization coefficient and the wind energy utilization coefficient of the wind turbine in the normal operating state; the second extreme value parameter is determined according to the ratio between the current output power and the output power of the wind turbine in the normal operating state; the third extreme value parameter is determined according to the ratio between the amplitude of the characteristic component of the current tower vibration signal and the amplitude of the characteristic component of the tower vibration signal of the wind turbine in the normal operating state; A strategy formulation module for determining the icing operation strategy of the wind turbine based on the icing risk assessment value and in combination with the current operating state of the wind turbine.

8. A wind turbine, characterized in that, It includes a generator body, and an operation controller is arranged in the generator body; it also includes a memory and a program or instruction stored on the memory and executable on the operation controller, and when the program or instruction is executed by the operation controller, it executes the steps of the icing operation control method of the wind turbine blade according to any one of claims 1 to 6.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the icing operation control method of the wind turbine blade according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the icing operation control method for a wind turbine blade according to any one of claims 1 to 6.

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