Wind turbine variable pitch double-controller control method and device

Abstract

The present disclosure provides a wind turbine variable pitch double controller control method and device, the method comprising: determining the wind condition state of the wind turbine; obtaining the final pitch control instruction of the variable pitch control based on the preset switching algorithm and the wind condition state; if the wind condition state of the wind turbine is normal turbulent wind condition, using the output signal of the preset variable gain PI variable pitch controller as the final pitch control instruction; if it is gust wind condition, using the output signal of the preset fuzzy PI variable pitch controller as the final pitch control instruction; if it is between normal turbulent wind condition and gust wind condition, using the common output signal of the variable gain PI variable pitch controller and the fuzzy PI variable pitch controller as the final pitch control instruction. The control performance of the existing wind turbine can be optimized without increasing the cost, in addition, the wind turbine itself can adapt to high turbulence wind field represented by mountain wind field, and wind turbine vibration overspeed and other shutdowns can be avoided.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the technical field of intelligent control of wind turbines, and particularly relates to a control method and device for a wind turbine variable-pitch dual controller. BACKGROUND

[0002] With the continuous increase of wind power penetration, the continuous rise of single-machine capacity of wind turbines, and the increasing complexity of wind power system structure, the wind power technology is also required to be higher by each interest party, and therefore it is of great significance to develop key technologies for improving the performance of wind turbines. The trend of wind power parity on-grid puts forward higher requirements for the cost per kilowatt-hour of wind turbines, and improving the power generation of the already commissioned units is an important means to reduce the cost per kilowatt-hour.

[0003] The quality of each component of a large wind turbine is large, the flexibility is high, and the load bearing condition of the unit is complex, and therefore it is necessary to optimize the control of the load of the unit to ensure the safe operation of the unit. Under normal turbulent wind conditions, the PI parameters of the variable-pitch control should be reduced with the increase of the pitch angle, which can improve the dynamic performance of the variable-pitch control and reduce the fatigue load and power fluctuation caused by frequent variable-pitch. However, the market of mountain wind farms is currently booming, and the characteristics of mountain wind farms are high turbulent intensity and frequent local rising gusts. The parameter change rule of the current control strategy causes frequent overspeed failures of the wind turbine when encountering rising gusts, resulting in peak loads of the blades and the tower and high vibration failures of the unit, and the safety problem of the unit becomes an urgent task for technical research. SUMMARY

[0004] The present disclosure aims to at least solve one of the technical problems existing in the prior art, and provides a control method and device for a wind turbine variable-pitch dual controller.

[0005] In an aspect of the present disclosure, a control method for a wind turbine variable-pitch dual controller is provided, and the method comprises:

[0006] determining a wind condition state of the wind turbine;

[0007] obtaining a final pitch control instruction of variable-pitch control based on a preset switching algorithm and the wind condition state; wherein

[0008] if the wind condition state of the wind turbine is a normal turbulent wind condition, using an output signal of a preset variable-gain PI variable-pitch controller as the final pitch control instruction;

[0009] if the wind condition state of the wind turbine is a gust wind condition, using an output signal of a preset fuzzy PI variable-pitch controller as the final pitch control instruction;

[0010] If the wind condition state of the wind turbine is between normal turbulent wind condition and gust wind condition, the common output signal of the variable gain PI pitch controller and the fuzzy PI pitch controller is used as the final pitch control instruction.

[0011] In some embodiments, the determining the wind condition state of the wind turbine comprises:

[0012] According to the input of the speed error signal and the speed change rate signal of the fuzzy PI pitch controller, the wind condition state of the wind turbine is determined.

[0013] In some embodiments, the determining the wind condition state of the wind turbine according to the input of the speed error signal and the speed change rate signal of the fuzzy PI pitch controller comprises:

[0014] The wind condition switching threshold values p1 and p2 are set according to the pitch aerodynamic adjustment performance of the wind turbine, and p2>p1;

[0015] The wind condition signal is determined according to the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold value; wherein,

[0016] When the absolute value of the input signal product is less than or equal to p1, the wind condition state is determined to be normal turbulent wind condition;

[0017] When the absolute value of the input signal product is greater than p2, the wind condition state is determined to be gust wind condition.

[0018] When the absolute value of the input signal product is between p1 and p2, the wind condition state is determined to be between normal turbulent wind condition and gust wind condition.

[0019] In some embodiments, the construction process of the switching algorithm is as follows:

[0020] The switching points of the variable gain PI pitch controller and the fuzzy PI pitch controller are determined.

[0021] According to the switching points, the switching relationship of the switching algorithm is constructed.

[0022] In some embodiments, the construction of the switching relationship of the switching algorithm according to the switching points comprises:

[0023] At each switching point, a two-point cubic Hermite interpolation formula is used to construct the relationship as follows:

[0024] β0=α(p)β2+(1-α(p))β1

[0025]

[0026] Wherein: β0 is the final output of the double controller of the pitch angle demand instruction; β2 is the pitch angle demand output value of the fuzzy PI pitch controller; β1 is the pitch angle demand output value of the variable gain PI pitch controller; p is the wind condition evaluation variable, p = e × de / dt, p2 > p1 > 0, p1 is the dividing point threshold value of the normal turbulent wind condition and the switching wind condition; p2 is the dividing point threshold value of the switching wind condition and the gust wind condition.

[0027] In another aspect of the present disclosure, a control device for a wind turbine pitch double controller is provided, the device comprising:

[0028] A judgment module for determining the wind condition state of the wind turbine;

[0029] A calculation module for obtaining the final pitch control instruction of the pitch control based on a preset switching algorithm and the wind condition state; wherein,

[0030] If the wind condition state of the wind turbine is the normal turbulent wind condition, the output signal of the preset variable gain PI pitch controller is used as the final pitch control instruction;

[0031] If the wind condition state of the wind turbine is the gust wind condition, the output signal of the preset fuzzy PI pitch controller is used as the final pitch control instruction;

[0032] If the wind condition state of the wind turbine is between the normal turbulent wind condition and the gust wind condition, the common output signal of the variable gain PI pitch controller and the fuzzy PI pitch controller is used as the final pitch control instruction.

[0033] In some embodiments, the judgment module is specifically further used for:

[0034] According to the input of the speed error signal and the speed change rate signal of the fuzzy PI pitch controller, the wind condition state of the wind turbine is determined.

[0035] In some embodiments, the judgment module is specifically further used for:

[0036] The wind condition switching threshold values p1 and p2 are set according to the wind turbine pitch aerodynamic adjustment performance, wherein p2 > p1;

[0037] The wind condition signal is determined according to the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold value; wherein,

[0038] When the absolute value of the input signal product is less than or equal to p1, the wind condition state is determined to be the normal turbulent wind condition;

[0039] When the absolute value of the input signal product is greater than p2, the wind condition state is determined to be the gust wind condition.

[0040] When the absolute value of the product of the input signals is between p1 and p2, the wind condition state is determined to be between the normal turbulent wind condition and the gust wind condition.

[0041] In some embodiments, the computing module is specifically further configured to:

[0042] determine each switching point of the variable gain PI pitch controller and the fuzzy PI pitch controller;

[0043] construct a switching relationship of the switching algorithm according to each switching point.

[0044] In some embodiments, the computing module is specifically further configured to:

[0045] at each switching point, construct a relationship by using a two-point cubic Hermite interpolation formula as follows:

[0046] β0=α(p)β2+(1-α(p))β1

[0047]

[0048] wherein β0 is a pitch angle demand instruction of the final output of the double controller; β2 is a pitch angle demand output value of the fuzzy PI pitch controller; β1 is a pitch angle demand output value of the variable gain PI pitch controller; p is a wind condition state evaluation variable, p = e x de / dt, p2 > p1 > 0, p1 is a threshold value of a demarcation point between the normal turbulent wind condition and the switching wind condition; and p2 is a threshold value of a demarcation point between the switching wind condition and the gust wind condition.

[0049] The control method and device of the wind turbine pitch double controller of the present disclosure do not increase hardware devices, are optimization development of wind turbine control algorithms, can optimize the control performance of existing wind turbines without increasing costs under the background of wind power grid parity, have great benefits for upgrading a large number of old wind turbines, and can also be conveniently applied to newly installed wind turbines. The benefits are convenience of application, universality, and great economic benefits. In addition, the wind turbine itself can adapt to high-turbulence wind fields represented by mountain wind fields, avoid wind turbine vibration overspeed and shutdown, increase the available hours of the wind turbine, and improve the wind power. Finally, for the wind turbine itself, the wind turbine load is reduced, the fatigue life of the wind turbine is ensured, and the safety of the wind turbine is improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 a flowchart of the control method of the wind turbine pitch double controller of an embodiment of the present disclosure;

[0051] Figure 2 a wind turbine gain coefficient schematic diagram of another embodiment of the present disclosure;

[0052] Figure 3 A fuzzy control flow chart for another embodiment of the present disclosure;

[0053] Figure 4 A function graph of a fan for another embodiment of the present disclosure;

[0054] Figure 5 A variable pitch double-controller integrated control flow chart for another embodiment of the present disclosure;

[0055] Figure 6 A structural schematic diagram of a control device of a variable pitch double-controller of a wind turbine for another embodiment of the present disclosure. DETAILED DESCRIPTION

[0056] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the present disclosure will be further described in detail below in combination with the drawings and specific embodiments.

[0057] The following will be described in view of the background of the present disclosure.

[0058] The current variable gain PI variable pitch control cannot cope with rapidly changing gust wind conditions, causing high turbulence wind field wind turbine overspeed failure, frequent vibration failure, leading to a decrease in the number of hours the fan can be used, increasing the load of the unit, leading to safety hazards in the unit.

[0059] The fan fuzzy PI variable pitch control has good rapid following and robustness for rapidly changing gust wind conditions, but it is not good enough in control accuracy and cannot always be used as the main variable pitch control algorithm for wind turbines.

[0060] Using different controllers at different wind speed characteristics to control and take advantage of each other is the best choice, but how to automatically switch controllers and smoothly switch controllers in the entire control process is a key technical problem to be solved.

[0061] In view of the defects of the existing variable pitch control technical solutions that cannot adapt to rapidly changing wind conditions, the present disclosure provides a double-controller automatic switching variable pitch control scheme, which automatically and smoothly switches the entire wind turbine operation moment variable pitch action instruction output through traditional variable gain PI variable pitch control and fuzzy PI variable pitch control according to the input changes, and realizes the variable pitch control of the wind turbine.

[0062] Due to the nonlinear aerodynamic characteristics of the fan, under normal turbulent wind conditions, a variable gain PI variable pitch control should be used to improve the variable pitch control performance. Under rapidly changing gust wind conditions, the variable parameter PI control can no longer meet the control requirements, which may cause wind turbine overspeed, vibration and other unit failures. At this time, through input judgment, smoothly switch to the fuzzy PI variable pitch controller control, so that the fuzzy PI takes over the control instruction, realizes the fault-free operation of the fan, reduces the load of the fan under high turbulent wind conditions, increases the safety factor of the fan, improves the service life of the fan, and increases the power generation capacity.

[0063] Based on this, the core idea of the present disclosure is that: through the wind condition switching control algorithm, under normal turbulent wind, the normal variable pitch control is used, and under gust wind condition, the fuzzy PI variable pitch control is used, so as to realize the rapid variable pitch under gust wind condition, avoid the occurrence of too high peak load, and improve the comprehensive control effect of the wind turbine variable pitch.

[0064] The embodiments of the present disclosure will be described in detail below.

[0065] An aspect of the present embodiment, as shown in Figure 1 The method S100 includes:

[0066] S110, determining the wind condition state of the wind turbine.

[0067] S120, based on the preset switching algorithm and the wind condition state, obtaining the final pitch control instruction of the variable pitch control; wherein,

[0068] If the wind condition state of the wind turbine is normal turbulent wind condition, the output signal of the preset variable gain PI variable pitch controller is used as the final pitch control instruction.

[0069] If the wind condition state of the wind turbine is gust wind condition, the output signal of the preset fuzzy PI variable pitch controller is used as the final pitch control instruction.

[0070] If the wind condition state of the wind turbine is between normal turbulent wind condition and gust wind condition, the common output signal of the variable gain PI variable pitch controller and the fuzzy PI variable pitch controller is used as the final pitch control instruction.

[0071] Specifically, the variable gain PI variable pitch controller is designed as follows:

[0072] The aerodynamic characteristics of the wind turbine have strong nonlinear characteristics, and there is a nonlinear relationship between the wind speed and the pitch angle. When the wind speed approaches the rated wind speed, the pitch angle is close to 0, at this time, the wind turbine aerodynamic torque is not sensitive to the pitch angle, and when the wind speed is higher, the pitch angle increases, the wind turbine aerodynamic torque is more sensitive to the pitch angle, and the intuitive performance is that in the higher wind speed range, a small change in the pitch angle can cause a large change in the aerodynamic torque. The nonlinear characteristics of the wind turbine result in that the single PI variable pitch controller with fixed gain cannot guarantee satisfactory control performance of the unit at different operating points.

[0073] When the PI controller setting parameters are large, the pitch angle control at higher wind speed may have overshoot, resulting in increased unit speed and power fluctuations, and at the same time, causing increased unit fatigue load; on the contrary, when the PI controller setting parameters are small, the pitch angle control at lower wind speed may have a slow response speed, which not only causes increased unit speed and power fluctuations, but also has a higher risk of unit overspeed.

[0074] In view of the nonlinear characteristics of the wind turbine aerodynamic characteristics, dynamically adjusting the parameters of the variable pitch controller can achieve stable control performance of the unit at different wind speeds, reduce the speed and power fluctuations of the unit above the rated wind speed, and reduce the fatigue load caused by the pitch action. The method of dynamically adjusting the load is to calculate the sensitivity of the pitch angle change to the wind turbine aerodynamic torque according to the wind turbine aerodynamic characteristics, and design a trend table of the sensitivity of the aerodynamic torque to the pitch angle at different pitch angles. This trend table can be used as a variable gain PI control curve table for table lookup. When the pitch angle increases, the parameters of the variable pitch controller are obtained through table lookup, so that the unit has basically consistent regulation time, overshoot and other control performance indicators at different wind speeds. In summary, the variable gain controller design is as follows:

[0075] 1. At 0 degree pitch angle, design appropriate variable pitch PI control parameters according to the control principle, as the reference variable pitch control PI parameters, denoted as kp, ki.

[0076] 2. Calculate the sensitivity of the pitch angle change to the wind turbine aerodynamic torque at different pitch angles, and design a trend table of the sensitivity of the aerodynamic torque to the pitch angle change at different pitch angles.

[0077] 3. Linear interpolation is performed to obtain the kp, ki pitch angle gain coefficients at all pitch angles.

[0078] The gain coefficients of the sample wind turbine are shown in Table 1: Figure 2

[0079] ​4. With the pitch angle feedback value as input, the current gain value is obtained by looking up the gain coefficient table, so as to change the current kp, ki control parameters, and carry out variable gain pitch control.

[0080] Specifically, the fuzzy PI variable pitch controller is designed:

[0081] Fuzzy logic control belongs to the category of intelligent control. Compared with the classical control strategy, it does not need to establish an accurate mathematical model of the controlled object, and can produce satisfactory control effect on complex objects or objects that are difficult to establish an accurate mathematical model. It has the advantages of good robustness, strong anti-interference ability and fast dynamic response. However, the fuzzy controller is difficult to eliminate the steady-state error of the system, and the control precision is not ideal, and there will be a blind area and a dead zone near the control point. The combination of fuzzy control and PI control can realize the complementary advantages of both.

[0082] Fuzzy control combines theories such as rule-based expert system, fuzzy set and control principle. Unlike traditional control methods, it does not need to accurately model the controlled system, but establishes rules for fuzzy control through the experience and behavior of experts. Fuzzy control is a nonlinear control method suitable for the control of nonlinear systems such as wind power systems. It has simple algorithm, fast execution and strong robustness due to its inherent parallel processing mechanism. Practical fuzzy control system needs to solve problems such as expert knowledge representation, control rule, fuzzy reasoning and defuzzification calculation.

[0083] The design process of the fuzzy PI controller for wind turbine variable pitch is as follows:

[0084] 1. Input selection: 2 input quantities are designed, which are the unit motor speed error e and the change rate ec of the speed, according to the characteristics of the sample wind turbine motor speed fluctuation. The basic universe of discourse is set as [-130rpm, 130rpm] and [-15rpm / s, 15rpm / s].

[0085] 2. Definition of input fuzzy universe of discourse: the input basic universe of discourse is divided into {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}, and the fuzzy subsets are {NL, NM, NS, ZO, PS, PM, PL}.

[0086] 3. Fuzzy controller output: the output of the fuzzy controller is the fuzzy gain parameter K, which is multiplied by the reference value of the proportional parameter of the fuzzy PI controller.

[0087] 4. Design form of fuzzy PI controller: the parameters of the fuzzy PI controller can be represented by the following formula:

[0088] KP=kp×K (1)

[0089] kp is the initial design value of the proportional parameter, which is tuned by conventional PI control parameters at 0 degree of pitch angle, and the initial design parameter is the same as the variable gain reference parameter kp.

[0090] 5. Output fuzzy domain definition: the basic domain of the output quantity K is [1, 3], the fuzzy domain of the controller output quantity is: {0, 1, 2, 3}, and the fuzzy subsets are: {ZO, PS, PM, PL}.

[0091] 6. Fuzzy and defuzzy function selection: in order to make the speed control more stable, a smooth Gaussian function is used as the membership function. The barycenter method is used as the defuzzy method.

[0092] 7. Fuzzy control control rule making: under the gust wind condition, the proportional coefficient of the PI controller is determined according to the size and direction of the speed error and the speed error change rate. The basic change law is that when the speed error and the speed error change rate are in the same direction, the greater the values of the two are, the greater the proportional coefficient of the PI controller should be, so as to achieve the purpose of fast pitching under the gust wind condition, so as to suppress the overspeed of the wind wheel; when the speed error and the speed error change rate are in the same direction, the proportional coefficient of the PI controller is maintained at the reference set value, so as to prevent the dynamic performance of the pitch control from being poor, and bring additional fatigue load and speed fluctuation.

[0093] According to the requirements of the gust wind condition pitch control, the fuzzy PI control rule is determined as shown in Table 1.

[0094] Table 1 Fuzzy control rule table

[0095]

[0096] 8. Fuzzy control parameter input, processing and output flow: the fuzzy control flow chart is shown in Figure 3 .

[0097] In some embodiments, the determining the wind condition state of the wind turbine comprises:

[0098] According to the input of the speed error signal and the speed change rate signal of the fuzzy PI pitch controller, the wind condition state of the wind turbine is determined.

[0099] In some embodiments, the determining the wind condition state of the wind turbine according to the input of the speed error signal and the speed change rate signal of the fuzzy PI pitch controller comprises:

[0100] According to the wind turbine pitch aerodynamic adjustment performance, the wind condition switching threshold p1 and p2 are set, and p2 > p1;

[0101] According to the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold, the wind condition signal is judged; wherein,

[0102] When the absolute value of the product of the input signals is less than or equal to p1, the wind condition is determined to be normal turbulent wind condition.

[0103] When the absolute value of the product of the input signals is greater than p2, the wind condition is determined to be a gust wind condition.

[0104] When the absolute value of the product of the input signals is between p1 and p2, the wind condition is determined to be between normal turbulent wind conditions and gust wind conditions.

[0105] In some implementations, the switching algorithm is constructed as follows:

[0106] Determine the switching points of the variable gain PI pitch controller and the fuzzy PI pitch controller;

[0107] Based on each of the switching points, construct the switching relationship of the switching algorithm.

[0108] In some implementations, constructing the switching relationship of the switching algorithm based on each of the switching points includes:

[0109] At each of the aforementioned switching points, the following relation is constructed using the two-point cubic Hermite interpolation formula:

[0110] β0=α(p)β2+(1-α(p))β1

[0111]

[0112] Where: β0 is the final pitch angle requirement command output by the dual controllers; β2 is the pitch angle requirement output value of the fuzzy PI pitch controller; β1 is the pitch angle requirement output value of the variable gain PI pitch controller; p is the wind condition assessment variable. p＝e× de / dt, p2>p1>0, where p1 is the threshold value separating normal turbulent wind conditions from switching wind conditions; p2 is the threshold value separating switching wind conditions from gust wind conditions. The graph of the above relationship is shown in this example fan as follows: Figure 4 As shown.

[0113] Specifically, when p≤p1, the pitch controller output is equivalent to variable gain PI control; when p≥p2, the pitch controller output is equivalent to fuzzy PI control corresponding to gust wind conditions; when p is between p1 and p2, it is the transition range of the two controllers, and the output weights of the two controllers are distributed according to the above relationship. The actual control parameter settings of p1 and p2 need to be determined according to the aerodynamic performance of the wind turbine of a specific unit. In this example, p1 is 3 and p2 is 5. Different values ​​of p1 and p2 will change the function graph of α(p). In addition to being determined by the aerodynamic performance of the wind turbine, subtle changes in its value test the control engineer's control experience in this field.

[0114] The overall control flow of the pitch dual controller is as follows: Figure 5 As shown:

[0115] The pitch control dual controller uses a variable gain PI controller and a fuzzy PI controller, and obtains the final pitch control command for pitch control through a switching algorithm. Figure 5 The variable gain PI controller parameters shown are as follows: Figure 2 The currently used parameters kp and ki are obtained from a table. Based on the nonlinear aerodynamic characteristics of the propeller blades, the PI controller parameters are changed in real time during normal turbulent wind speed changes. The output of this controller is denoted as β1. The fuzzy PI controller is a two-input, single-output type, using the speed error and speed change rate as input signals to achieve pitch control under gust wind conditions and prevent unit overspeed. The output of this controller is denoted as β2. The switching algorithm uses the product of the speed error and the speed error change rate as the signal to judge the wind condition, so as to coordinate the control effect under normal turbulent wind conditions and gust wind conditions. When the wind condition is judged to be gust wind, the output signal of the fuzzy PI controller is used as the pitch signal; when the wind condition is judged to be non-gust wind, the output value of the variable gain PI controller is used. Both operate simultaneously in transitional wind conditions.

[0116] The disclosed control method for wind turbine pitch control with dual controllers does not require additional hardware. It represents an optimized development of wind turbine control algorithms. In the context of grid parity for wind power, it optimizes the control performance of existing wind turbines without increasing costs, significantly benefiting the upgrade of numerous older turbines and facilitating application to newly installed turbines. Its advantages lie in its ease of use, universality, and substantial economic benefits. Furthermore, it enables the wind turbine to adapt to high-turbulence wind fields, such as mountainous areas, preventing shutdowns due to vibration and overspeed, increasing turbine uptime, and improving wind power output. Finally, the disclosed control method reduces turbine load, ensures turbine fatigue life, and enhances turbine safety.

[0117] Another aspect of this disclosure, such as Figure 6 As shown, a control device 100 for a dual-controller system for wind turbine pitch control is provided. This device 100 can employ the control method described above. The device 100 includes:

[0118] The judgment module 110 is used to determine the wind condition status of the wind turbine.

[0119] The calculation module 120 is used to obtain the final pitch control command for variable pitch control based on a preset switching algorithm and the wind conditions; wherein,

[0120] If the wind condition of the wind turbine is normal turbulent wind condition, the output signal of the preset variable gain PI pitch controller is used as the final pitch control command.

[0121] If the wind condition state of the wind turbine is gust wind condition, an output signal of a preset fuzzy PI pitch controller is used as the final pitch control instruction;

[0122] If the wind condition state of the wind turbine is between normal turbulent wind condition and gust wind condition, a common output signal of a variable gain PI pitch controller and a fuzzy PI pitch controller is used as the final pitch control instruction.

[0123] The control device of the wind turbine pitch dual controller of the present disclosure does not increase hardware devices, is an optimized development of the wind turbine control algorithm, and can optimize the control performance of the existing wind turbine without increasing the cost under the background of the flat price of wind power, has great benefits for upgrading a large number of old wind turbines, and can also be conveniently applied to newly installed wind turbines. The benefits are convenience, universality, and great economic benefits. In addition, the wind turbine itself can adapt to high-turbulence wind fields represented by mountain wind fields, avoid wind turbine vibration overspeed and shutdown, increase the available hours of the wind turbine, and improve the wind power. Finally, the control method of the present disclosure can reduce the load of the wind turbine, ensure the fatigue life of the wind turbine, and improve the safety of the wind turbine.

[0124] In some embodiments, the determining module 110 is specifically further configured to:

[0125] According to the input speed error signal and the speed change rate signal of the fuzzy PI pitch controller, the wind condition state of the wind turbine is determined.

[0126] In some embodiments, the determining module 110 is specifically further configured to:

[0127] According to the wind turbine pitch aerodynamic adjustment performance, wind condition switching thresholds p1 and p2 are set, where p2 > p1;

[0128] According to the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold, the wind condition signal is determined; wherein,

[0129] When the absolute value of the input signal product is less than or equal to p1, the wind condition state is determined to be normal turbulent wind condition;

[0130] When the absolute value of the input signal product is greater than p2, the wind condition state is determined to be gust wind condition.

[0131] When the absolute value of the input signal product is between p1 and p2, the wind condition state is determined to be between normal turbulent wind condition and gust wind condition.

[0132] In some embodiments, the calculating module 120 is specifically further configured to:

[0133] determining each switching point of the variable gain PI pitch controller and the fuzzy PI pitch controller;

[0134] According to each switching point, a switching relationship of the switching algorithm is constructed.

[0135] In some embodiments, the computing module 120 is further configured to:

[0136] At each switching point, a two-point cubic Hermite interpolation formula is used to construct a relationship as follows:

[0137] β0=α(p)β2+(1-α(p))β1

[0138]

[0139] wherein β0 is a final output of the dual controller; β2 is a pitch angle demand output value of the fuzzy PI pitch controller; β1 is a pitch angle demand output value of the variable gain PI pitch controller; p is a wind condition evaluation variable, p = e x de / dt, p2 > p1 > 0, p1 is a threshold value of a demarcation point between normal turbulent wind condition and switching wind condition; and p2 is a threshold value of a demarcation point between switching wind condition and gust wind condition.

[0140] It can be understood that the above embodiments are only exemplary embodiments for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Various modifications and improvements can be made by those of ordinary skill in the art without departing from the spirit and essence of the present disclosure, and these modifications and improvements are also considered to be within the protection scope of the present disclosure.

Claims

1. A control method for a wind turbine pitch control dual controller, characterized in that, The method includes: Determine the wind condition status of the wind turbine unit; Based on the preset switching algorithm and the wind conditions, the final pitch control command for variable pitch control is obtained; wherein, If the wind condition of the wind turbine is normal turbulent wind condition, the output signal of the preset variable gain PI pitch controller is used as the final pitch control command. If the wind condition of the wind turbine is a gust, the output signal of the preset fuzzy PI pitch controller is used as the final pitch control command. If the wind condition of the wind turbine is between normal turbulent wind and gusty wind, then the common output signal of the variable gain PI pitch controller and the fuzzy PI pitch controller is used as the final pitch control command. Determining the wind condition status of the wind turbine includes: The wind condition of the wind turbine is determined based on the speed error signal and speed change rate signal input to the fuzzy PI pitch controller. The step of determining the wind condition of the wind turbine based on the speed error signal and speed change rate signal input to the fuzzy PI pitch controller includes: The wind condition switching thresholds p1 and p2 are set according to the pitch aerodynamic regulation performance of the wind turbine, where p2 > p1; The wind condition signal is determined based on the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold; wherein, When the absolute value of the product of the input signals is less than or equal to p1, the wind condition is determined to be normal turbulent wind condition. When the absolute value of the product of the input signals is greater than p2, the wind condition is determined to be a gust wind condition. When the absolute value of the product of the input signals is between p1 and p2, the wind condition is determined to be between normal turbulent wind conditions and gust wind conditions.

2. The method according to claim 1, characterized in that, The construction process of the switching algorithm is as follows: Determine the switching points of the variable gain PI pitch controller and the fuzzy PI pitch controller; Based on each of the switching points, construct the switching relationship of the switching algorithm.

3. The method according to claim 2, characterized in that, The step of constructing the switching relationship formula of the switching algorithm based on each switching point includes: At each of the aforementioned switching points, the following relation is constructed using the two-point cubic Hermite interpolation formula: β0=α(p)β2+(1-α(p))β1 Where: β0 is the pitch angle requirement command finally output by the dual controllers; β2 is the pitch angle requirement output value of the fuzzy PI pitch controller; β1 is the pitch angle requirement output value of the variable gain PI pitch controller; p is the wind condition evaluation variable, p=e×de / dt, p2>p1>0, p1 is the threshold value of the dividing point between normal turbulent wind conditions and switching wind conditions; p2 is the threshold value of the dividing point between switching wind conditions and gust wind conditions.

4. A control device for a dual-controller pitch control system for a wind turbine generator, characterized in that, The device includes: The judgment module is used to determine the wind condition status of the wind turbine. The calculation module is used to obtain the final pitch control command for variable pitch control based on a preset switching algorithm and the wind conditions; wherein, If the wind condition of the wind turbine is normal turbulent wind condition, the output signal of the preset variable gain PI pitch controller is used as the final pitch control command. If the wind condition of the wind turbine is a gust, the output signal of the preset fuzzy PI pitch controller is used as the final pitch control command. If the wind condition of the wind turbine is between normal turbulent wind and gusty wind, then the common output signal of the variable gain PI pitch controller and the fuzzy PI pitch controller is used as the final pitch control command. The judgment module is further used for: The wind condition of the wind turbine is determined based on the speed error signal and speed change rate signal input to the fuzzy PI pitch controller. The judgment module is further used for: The wind condition switching thresholds p1 and p2 are set according to the pitch aerodynamic regulation performance of the wind turbine, where p2 > p1; The wind condition signal is determined based on the relationship between the product of the speed error signal and the speed change rate signal and the switching threshold; wherein, When the absolute value of the product of the input signals is less than or equal to p1, the wind condition is determined to be normal turbulent wind condition. When the absolute value of the product of the input signals is greater than p2, the wind condition is determined to be a gust wind condition. When the absolute value of the product of the input signals is between p1 and p2, the wind condition is determined to be between normal turbulent wind conditions and gust wind conditions.

5. The apparatus according to claim 4, characterized in that, The computing module is further used for: Determine the switching points of the variable gain PI pitch controller and the fuzzy PI pitch controller; Based on each of the switching points, construct the switching relationship of the switching algorithm.

6. The apparatus according to claim 5, characterized in that, The computing module is further used for: At each of the aforementioned switching points, the following relation is constructed using the two-point cubic Hermite interpolation formula: β0=α(p)β2+(1-α(p))β1 Where: β0 is the pitch angle requirement command finally output by the dual controllers; β2 is the pitch angle requirement output value of the fuzzy PI pitch controller; β1 is the pitch angle requirement output value of the variable gain PI pitch controller; p is the wind condition evaluation variable, p=e×de / dt, p2>p1>0, p1 is the threshold value of the dividing point between normal turbulent wind conditions and switching wind conditions; p2 is the threshold value of the dividing point between switching wind conditions and gust wind conditions.

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