Intelligent wind turbine control method and system

Abstract

The application discloses a kind of intelligent wind generating set control method and system, method includes steps: obtaining the operating state information of wind generating set;According to the operating state information of wind generating set, intelligent control or / and intelligent protection is carried out to wind power unit;Wherein intelligent control includes one or more of limit load shedding, fatigue load shedding or performance improvement;The intelligent protection includes the health degree and trend of evaluating operating environment and the state of unit itself, and corresponding intelligent protection measures are taken according to the evaluation result.The application carries out intelligent control and intelligent protection by depth perception, reduces the limit load and fatigue load of wind power unit, improves the power generation performance and operating reliability of wind power unit, so as to reduce the degree of wind power unit electricity cost.

Description

Technical Field

[0001] This invention mainly relates to the field of wind turbine technology, specifically to an intelligent wind turbine control method and system. Background Technology

[0002] Wind power, as a green and clean energy source, is an important component in building a new power system themed around new energy. However, onshore and offshore wind power have begun to reach grid parity, which means higher demands are placed on reducing the overall cost of wind turbines, improving power generation performance, and enhancing reliability. The control system, as the "brain" of the wind turbine generator, plays a major role in ensuring the low-load, high-performance, and high-reliability characteristics of the wind turbine.

[0003] like Figure 1 As shown, the working principle of existing variable speed and variable pitch wind turbine generator sets is as follows:

[0004] (1) When the wind turbine is running below the rated wind speed, the torque controller obtains the torque required by the generator through the torque control algorithm based on the current generator speed, maintains the optimal tip speed ratio, and thus enables the wind turbine to capture more wind energy.

[0005] (2) When the wind turbine is running at a speed above the rated wind speed, the pitch controller obtains the speed error by subtracting the current generator speed from the set generator speed, and obtains the required pitch angle through the pitch control algorithm. The pitch actuator drives the blades to pitch according to the required pitch angle command, thereby reducing wind energy capture and enabling the wind turbine to maintain rated power operation.

[0006] from Figure 1 It is known that existing wind turbine generator sets use PID control based on rotational speed. Due to the lack of perception of wind conditions, external environmental conditions, and the turbine generator's own state and trends, they cannot truly achieve predictive control and load reduction under conditions such as gusts, high turbulence, wind shear, and extreme wind conditions. They also cannot optimize turbine performance when both the turbine itself and the external environment are in good condition, and they cannot predict future conditions to form relevant predictive control, intelligent safety protection, or optimal decision-making. Therefore, existing control systems cannot meet the development requirements of wind turbine generator sets for low cost (low load and lightweight), high performance (high power, long blades), and high reliability (fault-tolerant control and early fault identification). Summary of the Invention

[0007] The technical problem to be solved by this invention is: in view of the problems existing in the prior art, this invention provides an intelligent wind turbine generator control method and system that uses deep perception to perform intelligent control and intelligent protection, reduces the ultimate load and fatigue load of wind turbine generators, improves the power generation performance and operational reliability of wind turbine generators, and thus reduces the cost per kilowatt-hour of wind turbine generators.

[0008] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows:

[0009] A method for controlling an intelligent wind turbine generator set includes the following steps:

[0010] Obtain operating status information of wind turbine generator sets;

[0011] Based on the operating status information of the wind turbine generator set, intelligent control and / or intelligent protection are implemented for the wind turbine generator set; wherein the intelligent control includes one or more of the following: ultimate load reduction, fatigue load reduction, or performance improvement; wherein the intelligent protection includes assessing the health and trend of the operating environment and the generator set's own status, and taking corresponding intelligent protection measures based on the assessment results.

[0012] Preferably, the operating status information includes hardware sensing information, virtual sensing information, and multi-data fusion information; the hardware sensing information includes wind conditions, load, clearance, and attitude; the virtual sensing information includes the wind turbine's rotational speed, power, wind speed, vibration, pitch angle, and voltage and current signals; and the multi-data fusion information includes mechanical inertia, transmission chain torsional vibration, and power generation performance.

[0013] Preferably, the extreme load reduction includes one or more of the following: gust load reduction, overspeed suppression, high turbulence load reduction, high shear load reduction, high yaw error load reduction, load-based load reduction, and clearance control.

[0014] Preferably, the specific process of gust load reduction is as follows:

[0015] 1.1) Acquire the status signals of the wind turbine generator set, including at least two of the following: wind speed, wind direction, generator speed, generator acceleration, nacelle vibration acceleration, pitch speed, generator torque change rate, and generator power change rate.

[0016] 1.2) Obtain the correlation coefficient between state information based on at least two types of state information;

[0017] 1.3) Compare the correlation coefficient with a preset threshold; if the correlation coefficient is not within the preset threshold, it is determined that the wind turbine is operating in gust mode, and pitch control is performed to reduce the ultimate load on the blades.

[0018] Preferably, in step 1.3), when the correlation coefficient is not within the preset threshold, one or more auxiliary variables are introduced for auxiliary judgment; the one or more auxiliary variables are compared with the preset auxiliary threshold, and when the one or more auxiliary variables are not within the corresponding preset auxiliary threshold, it is determined that the wind turbine is operating in gust mode.

[0019] Preferably, the specific process of overspeed suppression is as follows:

[0020] Obtain the generator speed ω of the wind turbine gen The generator speed ω gen With the speed set point ω ref Subtracting the two values ​​yields the rotational speed error, which in turn provides the PID control output value θ for the pitch speed. pid ;

[0021] Obtain the wind turbine's acceleration Acc, multiply it by the tower drag gain coefficient to obtain the tower drag pitch angle θ. damp ;

[0022] Obtain the pitch angle θ of the wind turbine. mes and generator speed overspeed ratio ω OverSpeed After adaptive fuzzy overspeed suppression, the adaptive fuzzy overspeed suppression compensated pitch angle value θ is obtained. fuzzy ;

[0023] The PID control output value θ of the propeller speed pid Tower drag pitch angle θ damp Adaptive fuzzy overspeed suppression compensation propeller pitch angle θ fuzzy The three values ​​are combined to obtain the pitch angle command value θ. ref It is then fed to the pitch actuator for pitch control.

[0024] Preferably, the specific process of adaptive fuzzy overspeed suppression is as follows:

[0025] Generator speed overspeed ratio ω OverSpeed The overspeed ratio filter value ω of the generator speed is obtained after filtering. MovOvSpd ;

[0026] Generator speed overspeed ratio filter value ω MovOvSpd With pitch angle θ mes The input observations of the fuzzy controller are fuzzified, then fuzzy inference is performed according to the fuzzy control rule table, and finally defuzzification is performed using the centroid method to obtain the control quantity U of the fuzzy controller. The control quantity U is then multiplied by the adaptive adjustment factor K. u The adaptive fuzzy overspeed suppression additional pitch rate v is obtained fuzzy v fuzzy Multiply by the step size to convert into an adaptive fuzzy overspeed suppression compensation pitch angle value θ fuzzy .

[0027] Preferably, the specific process of load-based unloading is as follows:

[0028] Obtain the real-time unit load during the operation of the wind turbine;

[0029] The unit load is compared with the standard load; when the unit load exceeds the standard load, the optimal pitch angle is obtained according to the set load and the optimal pitch angle scheduling table; the scheduling table is set according to the characteristics of the unit and specifies the optimal pitch angle under the unit load.

[0030] The optimal pitch angle is superimposed on the current pitch angle, and the lower limit of the pitch angle is adjusted to reduce the load.

[0031] Preferably, the specific process of unloading due to high yaw error is as follows:

[0032] Obtain the wind speed and yaw error values ​​of the wind turbine generator set;

[0033] The wind speed value and yaw error value are compared with their corresponding preset thresholds respectively. When both the wind speed value and the yaw error value are greater than their corresponding preset thresholds, the wind turbine performs a yaw action and enters a power-limited operation mode. When the yaw error value is greater than its corresponding preset threshold, but the wind speed value is less than its corresponding preset threshold, the wind turbine performs a yaw action and maintains normal operation mode. When both the wind speed value and the yaw error value are less than their corresponding preset thresholds, the wind turbine maintains normal operation mode.

[0034] Preferably, the power-limited operation mode specifically includes: when both the wind speed value and the yaw error value are greater than their corresponding m times the preset threshold, the wind turbine generator set starts to yaw and enters the power reduction operation mode one, and the power of the wind turbine generator set is reduced to P1; when both the wind speed value and the yaw error value are greater than their corresponding n times the preset threshold, the wind turbine generator set starts to yaw and enters the power reduction operation mode two, and the power of the wind turbine generator set is reduced to P2; where n>m, P1>P2.

[0035] Preferably, the airspace control steps are as follows:

[0036] 5.1) Obtain the blade tip position during blade operation, and perform data cleaning on the blade tip position to obtain the effective value of the blade tip position;

[0037] 5.2) Obtain the current blade clearance value based on the effective value of the blade tip position and the current rotor azimuth angle;

[0038] 5.3) Compare the current blade clearance value with the preset threshold, and control the clearance of the wind turbine based on the comparison result.

[0039] Preferably, the specific process of step 5.3) is as follows: if the current blade clearance value is lower than the clearance control threshold, a preset compensation value is superimposed on the original pitch angle command; if the current blade clearance value is higher than the clearance control threshold, normal power generation operation continues.

[0040] Preferably, the performance improvement includes a dynamic rated speed control method for wind turbine generator sets, specifically: when the wind speed of the wind turbine generator set is within a preset threshold and the wind turbine generator set is in a non-power-limited state, the unit operates according to the dynamic rated speed control mode: the rated speed set point of the wind turbine generator set is adjusted according to the pitch angle to reduce the blade root load of the unit.

[0041] Preferably, the blade root load is pre-classified into different load levels Z1, Z2...Z k Different load levels Z1, Z2…Z k The corresponding pitch angle intervals are P1, P2...P k Different pitch angle intervals P1, P2...P k The corresponding rated speed setpoints are G1, G2...G k .

[0042] Preferably, the performance improvement includes a wind turbine operation control method based on yaw sector optimization, comprising the following steps:

[0043] The wind condition data and corresponding nacelle location information during the operation of the wind turbine are obtained to update the range of the high turbulence sector of the wind turbine.

[0044] The raw data of instantaneous acceleration of the nacelle during the operation of the wind turbine are obtained, and the raw data of instantaneous acceleration of the nacelle are preprocessed to obtain effective nacelle acceleration data;

[0045] Based on the location of the wind turbine and valid nacelle acceleration data, the control mode of the wind turbine is adjusted as follows: If the wind turbine is not located in a high-turbulence sector, the original control mode is maintained; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is less than the lower limit of the protection threshold, normal power generation is maintained within the high-turbulence sector; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is between the upper and lower limits of the protection threshold, the wind turbine yaws away from the high-turbulence sector; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is greater than the upper limit of the protection threshold, shutdown protection is triggered.

[0046] Preferably, the specific process of updating the high-turbulence sector range of the wind turbine by acquiring wind condition data and corresponding nacelle location information during wind turbine operation is as follows:

[0047] Pre-store initial high-turbulence sector information of wind turbine units;

[0048] Acquire wind condition data and corresponding nacelle location information during wind turbine operation, and calculate the turbulence intensity of all sectors; if the turbulence intensity reaches the standard value, record the sector where the nacelle is located.

[0049] The recorded sector region is compared with the initial high-turbulence sector information; if the recorded sector region is not in the initial high-turbulence sector information, the recorded sector region is added to the initial high-turbulence sector information to obtain the updated high-turbulence sector information.

[0050] Preferably, the performance improvement includes a dynamic correction control method for the wind turbine pitch angle feedforward, the specific steps of which are as follows:

[0051] Obtain the wind speed at different predetermined distances in front of the wind turbine rotor;

[0052] Based on the wind speed at different predetermined distances in front of the wind turbine, calculate the feedforward control wind speed V0 and the lead time τ equivalent to the wind turbine surface;

[0053] Obtain the air density and / or power limitation ratio of the environment where the wind turbine is located, and then update the mapping relationship between wind speed and pitch angle based on the air density and / or power limitation ratio to obtain the updated wind speed-pitch angle mapping relationship.

[0054] Based on the feedforward control wind speed V0 and the lead time τ, the target pitch angle β(t+τ) with a lead time of τ seconds is obtained from the updated wind speed-pitch angle mapping relationship.

[0055] By combining the current pitch angle β(t) of the wind turbine and the target pitch angle β(t+τ) with a lead time of τ seconds, feedforward control is performed to calculate the final pitch angle control value for pitch control.

[0056] Preferably, when performing pitch control, if speed control mode is used, the feedforward control pitch rate is:

[0057] rateRequired=[β(t+τ)-β(t)] / τ

[0058] Where β(t) is the current pitch angle; β(t+τ) is the target pitch angle τ seconds ahead, and τ is the lead time.

[0059] Preferably, the intelligent protection includes a method for monitoring and controlling wind turbine blade stall, the specific steps of which are as follows:

[0060] The wind turbine is pre-configured with wind speed-active power curves under different air densities as a reference wind speed-active power curve; the wind turbine is pre-configured with generator speed-nacelle acceleration curves under different air densities as a reference generator speed-nacelle acceleration curve.

[0061] Acquire wind turbine operating data, including air temperature, wind speed, power generation, generator speed, and nacelle acceleration;

[0062] The current air density is obtained from the air temperature; the current wind speed-active power curve of the wind turbine is obtained from the wind speed and power generation; the current generator speed-nacelle acceleration curve of the wind turbine is obtained from the generator speed and nacelle acceleration.

[0063] The current wind speed-active power curve is compared with the reference wind speed-active power curve under the current air density to obtain the first comparison result; at the same time, the current generator speed-nacelle acceleration curve is compared with the reference generator speed-nacelle acceleration curve under the current air density to obtain the second comparison result.

[0064] The first comparison result and the second comparison result are used to determine whether the wind turbine blades are stalling and the degree of stalling.

[0065] Preferably, when the first comparison result is that the current wind speed-active power curve exceeds the stall control threshold of the reference wind speed-active power curve under the current air density but is lower than the corresponding shutdown protection value, and the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the stall control threshold of the reference generator speed-nacelle acceleration curve under the current air density but is lower than the corresponding shutdown protection value, then the blade is judged to be in a general stall. When the blade is judged to be in a general stall, the additional value of the pitch angle is calculated by combining the current pitch angle and active power, and superimposed on the unified pitch output value to perform the pitch retraction action.

[0066] Preferably, if the first comparison result is that the current wind speed-active power curve exceeds the shutdown protection value of the reference wind speed-active power curve, or if the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the shutdown protection value of the reference generator speed-nacelle acceleration curve under the current air density, then the blade is judged to be in severe stall; when the blade is judged to be in severe stall, a shutdown action is performed.

[0067] The present invention also discloses an intelligent wind turbine generator control system, including a memory and a processor connected to each other, wherein the memory stores a computer program, and the computer program executes the steps of the method described above when run by the processor.

[0068] Compared with the prior art, the advantages of the present invention are as follows:

[0069] This invention utilizes deep environmental sensing (such as wind conditions, including wind speed, wind direction, turbulence, and wind shear), load sensing (loads on key components such as blade roots, main shaft, and tower), distance sensing (clearance), sound sensing, attitude sensing, image sensing, and the unit's own status sensing. Based on this, the sensed information is transmitted to the intelligent control module and the intelligent protection module respectively to achieve intelligent control and intelligent protection, reduce the ultimate load and fatigue load of the wind turbine, improve the power generation performance and operational reliability of the wind turbine, and thus reduce the levelized cost of electricity (LCOE) of the wind turbine. Attached Figure Description

[0070] Figure 1 This is a control block diagram for an existing conventional wind turbine generator set.

[0071] Figure 2 The flowchart is shown in an embodiment of the control method for the intelligent wind turbine generator set of the present invention.

[0072] Figure 3 This is a block diagram of the depth perception module of the present invention in an embodiment.

[0073] Figure 4 This is a flowchart of an embodiment of the intelligent control method of the present invention.

[0074] Figure 5 This is a flowchart of an embodiment of the intelligent protection method of the present invention.

[0075] Figure 6 This is a flowchart of the gust load reduction control method in Embodiment 1 of the present invention.

[0076] Figure 7 This is a univariate change trend graph in Embodiment 1 of the present invention.

[0077] Figure 8 This is a control block diagram of the overspeed suppression control method in Embodiment 2 of the present invention.

[0078] Figure 9 This is a control block diagram of the adaptive fuzzy overspeed suppression method in Embodiment 2 of the present invention.

[0079] Figure 10 This is a flowchart of the adaptive factor adjustment method in Embodiment 2 of the present invention.

[0080] Figure 11 This is a flowchart of the load control method in Embodiment 3 of the present invention.

[0081] Figure 12 This is a load-pitch angle scheduling component curve diagram in Embodiment 3 of the present invention.

[0082] Figure 13 This is a flowchart of the load reduction method in Embodiment 4 of the present invention.

[0083] Figure 14 This is a flowchart of the power reduction operation method in Embodiment 4 of the present invention.

[0084] Figure 15 This is a flowchart of the active airspace control method in Embodiment 5 of the present invention.

[0085] Figure 16 This is a flowchart of the logical judgment method in Embodiment 5 of the present invention.

[0086] Figure 17 This is a flowchart of the method for generating each rated speed in Embodiment Six of the present invention.

[0087] Figure 18 This is a flowchart of the control method in Embodiment Six of the present invention.

[0088] Figure 19 This is a flowchart of the high-turbulence sector update method in Embodiment 7 of the present invention.

[0089] Figure 20 This is a flowchart of the control method in Embodiment 7 of the present invention.

[0090] Figure 21 This is a control block diagram of a wind turbine generator in Embodiment 8 of the present invention.

[0091] Figure 22 This is a block diagram of the lidar feedforward control function in Embodiment 8 of the present invention.

[0092] Figure 23 This is a block diagram of dynamic compensation for pitch angle feedforward in Embodiment 8 of the present invention.

[0093] Figure 24 This is a graph showing the wind speed-pitch angle scheduling lookup table before and after the update in Embodiment 8 of the present invention.

[0094] Figure 25 The flowchart below shows the control method of Embodiment Nine of the present invention.

[0095] Figure 26 This is a flowchart of the method for generating various reference curves in Embodiment 9 of the present invention.

[0096] Figure 27 This is a flowchart of the logical judgment in Embodiment Nine of the present invention. Detailed Implementation

[0097] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0098] like Figure 2 As shown, the intelligent wind turbine generator control method of this invention comprises the following steps:

[0099] Obtain operating status information of wind turbine generator sets;

[0100] Based on the operating status information of the wind turbine generator set, intelligent control and / or intelligent protection are implemented for the wind turbine generator set; wherein the intelligent control includes one or more of the following: ultimate load reduction, fatigue load reduction, or performance improvement; wherein the intelligent protection includes assessing the health and trend of the operating environment and the generator set's own status, and taking corresponding intelligent protection measures based on the assessment results.

[0101] like Figure 3 As shown, this embodiment of the invention also provides an intelligent wind turbine generator control system, specifically including a depth perception module, an intelligent control module, and an intelligent protection module;

[0102] The depth perception module consists of a hardware perception system and a virtual perception system. The hardware perception system uses LiDAR, load sensor, clearance radar, tilt sensor, sound sensor and video equipment to perceive intelligent characteristics such as wind conditions, load, distance, attitude, sound and video.

[0103] The virtual sensing system utilizes the speed, power, wind speed, vibration, pitch angle, voltage and current signals of traditional wind turbine generators, combined with the hardware sensing system, to construct new detection variables such as mechanical inertia, transmission chain torsional vibration, and power generation performance through multi-data fusion.

[0104] The quantities measured by the hardware sensing system and the virtual sensing system are processed, features are extracted and identified to realize the external environment (wind conditions) and its trend perception, self-state perception and its trend perception, and self-capability perception and its trend perception of the intelligent wind turbine generator set, as shown in Figure 3.

[0105] like Figure 4 As shown, after processing by the depth perception module, the data is sent to the intelligent module and the intelligent protection module. The intelligent control algorithm module performs intelligent control based on the perceived data and its trends, specifically as follows:

[0106] Ultimate load reduction, including gust load reduction, overspeed suppression, high turbulence load reduction, high shear load reduction, high yaw error load reduction, load-based load reduction, and related algorithms for airspace control, achieves a reduction of more than 10% in the dominant ultimate load and an increase of about 15% in airspace safety margin.

[0107] Fatigue load reduction: LiDAR can be used to detect the wind speed in front of the wind turbine in advance, and LiDAR feedforward control algorithm can be developed; load sensor can be used to detect the stress state of the wind turbine, and intelligent control algorithms such as independent pitch control can be developed, which can reduce the main fatigue load by about 10%.

[0108] Performance Enhancement: By utilizing sensing information, the system implements power generation enhancement control algorithms such as optimal wind response, optimal speed-torque control, dynamic power enhancement, and extended operating wind speed, resulting in a 2-5% increase in power generation.

[0109] like Figure 5As shown, the intelligent protection module, combined with the sensing information from the deep perception module, assesses the health and trends of the operating environment and the unit's own status. The comprehensive assessment results are divided into three levels: normal, slightly abnormal, and severely abnormal. Based on the severity, if the assessment conclusion is normal, the wind turbine operates normally; if the assessment result is slightly abnormal, the wind turbine operates with reduced performance; and if the assessment result is severely abnormal, the unit is shut down. This achieves intelligent protection for the wind turbine, preventing it from operating with defects and enabling early identification of sub-health conditions.

[0110] This invention uses a deep sensing module to perceive environmental conditions (such as wind conditions, including wind speed, wind direction, turbulence, and wind shear), load conditions (loads on key components such as blade roots, main shaft, and tower), distance (clearance), sound, attitude, image, and the unit's own status. Based on this, the perceived information is transmitted to the intelligent control module and the intelligent protection module to achieve intelligent control and intelligent protection, reduce the ultimate load and fatigue load of the wind turbine, improve the power generation performance and operational reliability of the wind turbine, and thus reduce the levelized cost of electricity (LCOE) of the wind turbine.

[0111] This invention provides a computer-readable storage medium storing a computer program thereon, which, when run by a processor, executes the steps of the method described above. This invention further provides an intelligent wind turbine generator control system, including a memory and a processor interconnected, wherein the memory stores a computer program, which, when run by a processor, executes the steps of the method described above.

[0112] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. The memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0113] Example 1:

[0114] like Figure 6 As shown, the specific steps for gust wind load reduction are as follows:

[0115] 1.1) Acquire the status signals of the wind turbine generator set, including at least two of the following: wind speed, wind direction, generator speed, generator acceleration, nacelle vibration acceleration, pitch speed, generator torque change rate, and generator power change rate.

[0116] 1.2) Obtain the correlation coefficient between state information based on at least two types of state information;

[0117] 1.3) Compare the correlation coefficient with the preset threshold; if the correlation coefficient is not within the preset threshold, it is determined that the wind turbine is operating in gust mode, and pitch control is performed to reduce the ultimate load on the blades.

[0118] This invention obtains corresponding correlation coefficients based on two or more sets of state information, and uses these correlation coefficients as sufficient conditions for detecting and judging gusts. By using one or more sets of state information to predict the trend of gusts in wind turbine generators, the arrival of gusts can be predicted earlier than a single signal (such as speed or acceleration). When the arrival of gusts is predicted in advance, pitch control can be triggered in advance to reduce the extreme blade load and tower overturning moment of wind turbine generators under extreme gust conditions with wind direction changes, thus ensuring the safety and reliability of wind turbine generators under extreme gust conditions.

[0119] In one specific embodiment, in step 1.3), when the correlation coefficient is not within a preset threshold, one or more auxiliary variables are introduced for auxiliary judgment. These auxiliary variables are compared with preset auxiliary thresholds. If one or more auxiliary variables are not within their corresponding preset auxiliary thresholds, the wind turbine is determined to be operating in gust mode. The auxiliary variables include one or more of the following: generator speed, nacelle vibration acceleration, or wind direction yaw error angle. During actual turbine operation, these auxiliary variables are used as auxiliary judgment conditions to avoid or minimize malfunctions of the pitch system. This invention, by introducing auxiliary variables for auxiliary judgment, can greatly improve the accuracy of judgment under gust conditions and effectively avoid malfunctions of the pitch angle under normal operating conditions.

[0120] In step 1.3), while performing pitch control, the pitch speed is increased to the maximum pitch speed limit or set value, the generator torque is maintained at the rated torque, and the generator operating speed is reduced according to the pitch angle, thereby reducing the blade ultimate load of the wind turbine under extreme gust conditions with variable direction.

[0121] In step 1.2), the principle of the correlation calculation method is as follows:

[0122] For any discrete time series {X1, X2, X3, X4, ..., X... n}, x t and x t+k This corresponds to two separate sets of samples. k is the number of sample lags (k is a positive integer greater than or equal to 1 and less than the sample ΔT period). x t Let {x1, x2, x3, x4, ... x} be the sampled data {x1, x2, x3, x4, ... x} after a time lag of k data points within a time period ΔT. i ...x t}, and x t+k For the sampled data {x} within the time period ΔT 1+k +x 2+k +x 3+k ...x i+k ...xt+k The trend of the univariate change is shown in the figure. Figure 7 As shown, its correlation coefficient α is given by the following formula:

[0123]

[0124] In the formula: x t+k x represents the numerical value at time (t+k) in a discrete time series; t x represents the value at time t in a discrete time series; i+k -x i+k-1 For x within a period of ΔT i+k Time and time x i+k-1 The difference in values; α is the univariate correlation trend coefficient, where 0 indicates a weak correlation trend and 1 indicates a strong correlation trend.

[0125] In practical applications, the specific calculation process for the correlation coefficient between N types of state information is as follows:

[0126]

[0127] Where β is the correlation coefficient between N variables, Var1 is variable 1, Var2 is variable 2, VarN is variable N, and Var variables are wind speed, wind direction, generator speed, generator acceleration, nacelle vibration acceleration, pitch speed, generator torque change rate or generator power change rate; abs is the absolute value, and Max is the maximum value.

[0128] For example, the correlation coefficient is the correlation coefficient between wind direction and generator acceleration. The specific calculation process is as follows:

[0129]

[0130] Where β is the correlation coefficient between wind direction and generator acceleration, Dir is the wind direction, and AccGen is the generator acceleration.

[0131] This invention acquires wind direction and generator acceleration, calculates the correlation coefficient in the time domain, and uses this correlation coefficient to determine when the pitch actuator should act in advance. This reduces the ultimate load on the blades of the wind turbine under extreme gust conditions with changing wind direction, effectively reducing the weight of the wind turbine blades, tower, and overall system, thus improving the economic efficiency of the wind turbine. In practical applications, the correlation coefficients between two, three, or more signals can be used to identify the gust conditions of the wind turbine. Different signals correspond to different standard values ​​(preset thresholds).

[0132] Example 2

[0133] like Figure 8As shown, the specific steps for overspeed suppression are as follows:

[0134] Obtain the generator speed ω gen After filtering, it is then compared with the speed setpoint ω. ref Subtracting the values ​​yields the rotational speed error. This error is then used as the input to the pitch speed PID controller. After calculation and limiting by the PID controller, the pitch speed PID control output value θ is obtained. pid ;

[0135] After performing a lead-lag filter on the acceleration Acc measured by the vibration monitor, the tower drag pitch angle θ is calculated by multiplying it by the tower drag gain coefficient. damp ;

[0136] Based on the measured pitch angle and the calculated generator speed overspeed ratio, the adaptive fuzzy overspeed suppression compensated pitch angle value θ is obtained after adaptive fuzzy overspeed suppression. fuzzy ;

[0137] The PID control output value θ of the propeller speed pid Tower drag pitch angle θ damp Adaptive fuzzy overspeed suppression compensation pitch angle θ fuzzy The three values ​​are combined to obtain the pitch angle command value θ. ref The feed is delivered to the pitch actuator, which then operates according to the input pitch command value θ. ref Perform pitch control.

[0138] like Figure 9 As shown, the specific process of the adaptive fuzzy overspeed suppression method is as follows:

[0139] ω OverSpeed The overspeed ratio of the generator speed. The generator speed overspeed ratio is obtained by filtering to obtain ω. MovOvSpd θ mes The measured pitch angle;

[0140] Generator speed overspeed ratio filter value ω MovOvSpd With pitch angle θ mes As the input observation of the fuzzy controller, v fuzzy The control input for the fuzzy controller is the generator speed, overspeed ratio, and filter value ω. MovOvSpd The universe of discourse is [0,20], and the fuzzy subset is {ZO, PS, PM, PB}, where ZO is 0, PS is positive small, PM is positive medium, and PB is positive large. Fuzzification is performed using a triangular membership function; the input quantity is the paddle pitch angle θ. mesThe domain of the fuzzy control is [0, 20], and the fuzzy subset is {ZO, PS, PM, PB}. Fuzzification is performed using a triangular membership function. The domain of the output pitch speed is [0, 3], and the fuzzy subset is {ZO, PS, PM, PB}. Fuzzification is performed using a Gaussian membership function. A fuzzy rule table is developed based on engineering experience. Fuzzy inference is performed using Mamdani's Max-Min algorithm, and defuzzification is performed using the centroid method to obtain the fuzzy controller's control quantity U. The fuzzy control quantity U is then multiplied by an adaptive adjustment factor K. u The adaptive fuzzy overspeed suppression additional pitch rate v is obtained fuzzy v fuzzy Multiply by the step size to convert into an adaptive fuzzy overspeed suppression compensation pitch angle value θ fuzzy .

[0141] Among them, the regulation factor K u Overspeed ratio filter value ω of generator speed MovOvSpd It has a strong correlation, such as K. u If the value is too small, the ability to suppress overspeed is weak, and overspeed faults are prone to occur under strong gusts of wind; such as K u If the value is too large, the output value of the fuzzy overspeed controller will be large, the overspeed suppression time will be too long, which will affect the power generation performance of the unit and increase the fatigue load on the tower base; therefore, K u The value of is crucial to control performance, and its specific adjustment method is as follows:

[0142] like Figure 10 As shown, the generator speed overspeed ratio ω OverSpeed After filtering, it becomes ω MovOvSpd The overspeed ratio updated at step k is ω. MovOvSpd (k), the overspeed ratio is updated at step k+1 as ω. MovOvSpd (k+1), calculate the rate of change of overspeed ratio ω MovOvSpd (k+1)-ω MovOvSpd (k) / ΔT, where ΔT is the sampling period; if the overspeed ratio ω MovOvSpd (k) is less than the threshold ω1, K u Set to 0; if the overspeed ratio ω MovOvSpd (k) is greater than or equal to the threshold ω1, according to ω MovOvSpd (k) and ω MovOvSpd (k+1)-ω MovOvSpd The product of (k) / ΔT is used to adaptively set K. u Value; where ω MovOvSpd (k) is large and ω MovOvSpd (k+1)-ω MovOvSpd When (k) / ΔT is positive, K u Increasing the value of ω quickly suppresses the increase in rotational speed; MovOvSpd (k) is small and greater than the threshold ω1, ω MovOvSpd(k+1)-ω MovOvSpd When (k) / ΔT is positive, K u The value is moderate; ω MovOvSpd (k) is large and ω MovOvSpd (k+1)-ω MovOvSpd When (k) / ΔT is negative, K u The value is moderate; ω MovOvSpd (k) is small and greater than the threshold ω1, ω MovOvSpd (k+1)-ω MovOvSpd When (k) / ΔT is negative, K u The value is relatively small.

[0143] This invention employs fuzzification and fuzzy rule design based on generator speed overspeed ratio and pitch angle. Through fuzzy inference and defuzzification, fuzzy control output values ​​are obtained. These output values ​​are then multiplied by an adaptive adjustment factor to obtain an additional pitch rate value. The pitch rate, multiplied by the time step, is converted into an additional pitch angle. This additional pitch angle is then superimposed on traditional closed-loop PID control to reduce generator speed. This invention does not rely on a precise controlled object model, overcomes the influence of complex multivariable nonlinear factors, exhibits strong robustness and anti-interference capabilities, and requires no additional hardware cost.

[0144] This invention employs a fuzzy overspeed suppression and identification method based on generator speed overspeed ratio and pitch angle characteristic variables to effectively identify overspeed conditions in extreme turbulence and gusty winds. The invention designs an adaptive fuzzy overspeed suppression controller that adaptively adjusts pitch according to different overspeed conditions defined for the unit, thereby suppressing overspeed while reducing the unit's ultimate load. It also exhibits strong robustness and is suitable for complex nonlinear systems.

[0145] Example 3

[0146] like Figure 11 As shown, the specific process of load-based unloading is as follows:

[0147] 3.1) Obtain the real-time unit load during the operation of the wind turbine;

[0148] 3.2) Compare the unit load with the standard load; when the unit load exceeds the standard load, obtain the optimal pitch angle according to the set load and the optimal pitch angle scheduling table; the scheduling table is set according to the characteristics of the unit and specifies the optimal pitch angle under the unit load.

[0149] 3.3) Superimpose the optimal pitch angle onto the current pitch angle and adjust the lower limit of the pitch angle to reduce the load.

[0150] This invention provides real-time measurement of turbine load, enabling real-time control and adjustment of the load based on the most intuitive measurement results. This ensures that the turbine can adjust in real time according to its current operating status, reducing the load on the wind turbine, improving operational stability, extending the turbine's service life, maximizing power generation efficiency while reducing load, and fully tapping the turbine's power generation performance potential. The adjustment of the turbine load based on the optimal pitch angle is highly efficient. The above method is highly versatile and can be quickly expanded and adapted based on the measured turbine load data.

[0151] Specifically, the unit load in the Mx and My directions is measured by multiple measuring units fixed to the blade root. Fiber optic sensors are used in these measuring units to improve measurement accuracy and operational reliability. Preferably, three fiber optic sensors are used. However, in other embodiments, two, four, or more sensors may be employed.

[0152] After step 3.1), the measured unit load is cleaned. Specifically, the measured unit load is high-pass filtered to remove noise and obtain a more accurate data signal. Then, the maximum value of the three blade load measurements is taken. Next, a 100ms sliding filter is performed every 500ms. Finally, the obtained data is processed by control delay (because the pitch angle control has a delay characteristic, the data after sliding filtering needs to be processed accordingly) to obtain effective control load data.

[0153] By performing multi-dimensional data cleaning on the unit's measured loads as described above, the reliability of the unit's load data is ensured while fully considering the input delay of the control system, thus guaranteeing control effectiveness and reducing unit malfunctions.

[0154] Specifically, in step 3.2), the standard load includes a first standard load and a second standard load, the second standard load being greater than the first standard load, and the first standard load and the second standard load forming a hysteresis; when the unit load exceeds the first standard load, optimal pitch angle scheduling is performed; if the unit load is less than the second standard load, normal power generation operation is performed; if the unit load exceeds the maximum unit load value, it will enter a protection shutdown state.

[0155] The core idea of ​​optimal pitch angle scheduling is to design corresponding pitch angle scheduling based on the real-time load of the unit and superimpose it onto the currently measured pitch angle to adjust the lower limit of the controlled pitch angle. Specifically, optimal pitch angle scheduling is performed according to the set load and the optimal pitch angle scheduling table. The scheduling table is set according to the characteristics of the unit, specifying the optimal pitch angle size under a specific load and setting corresponding parameters such as pitch rate. In the control process of step 3.3), optimal pitch angle scheduling is performed according to the scheduling table and superimposed on the current optimal pitch angle, thereby reducing wind load by limiting the lower limit of the pitch angle. If the current optimal pitch angle scheduling has reached its maximum value, and the wind speed continues to increase, the unit enters protection mode and shuts down to protect the unit.

[0156] In step 3.3), the optimal pitch angle is superimposed onto the current pitch angle, and then the specific execution process of pitch angle control is as follows: Figure 3 As shown, the specific modes include, but are not limited to, the following three modes:

[0157] Mode 1, such as Figure 12 As shown in (a), the pitch angle scheduling component is linearly controlled based on the real-time unit load, and the upper and lower limits of the pitch angle scheduling component are set.

[0158] Mode 2, such as Figure 12 As shown in (b), two-dimensional interpolation control of the pitch angle scheduling component is performed based on the real-time unit load. A two-dimensional interpolation table of load-pitch angle is designed. The pitch angle scheduling component is designed in segments according to the measured load, and the upper and lower limits of the pitch angle scheduling component are set.

[0159] Mode 3, such as Figure 12 As shown in (c), high-order scheduling of pitch angle scheduling components is performed based on real-time unit load. Fast scheduling design is carried out for large load characteristics, and upper and lower limits of pitch angle scheduling components are set.

[0160] The above modes can be selected according to the actual situation on site, and the control process is simple.

[0161] Example 4

[0162] like Figure 13-14 As shown, the specific process of unloading under high yaw error is as follows:

[0163] 4.1) During the operation of the wind turbine, obtain the wind speed and yaw error values ​​of the wind turbine; where the yaw error value is the angle between the incoming wind direction and the position of the nacelle.

[0164] 4.2) Compare the wind speed value and yaw error value with their corresponding preset thresholds respectively; when both the wind speed value and the yaw error value are greater than their corresponding preset thresholds, the wind turbine performs a yaw action and enters a power-limited operation mode; when the yaw error value is greater than its corresponding preset threshold, but the wind speed value is less than its corresponding preset threshold, the wind turbine performs a yaw action and maintains normal operation mode; when both the wind speed value and the yaw error value are less than their corresponding preset thresholds, the wind turbine maintains normal operation mode.

[0165] To more effectively reduce the tower load on the wind turbine generator set during operation under conditions of large yaw error, in step 4.2), the power-limited operation mode specifically includes: when both the wind speed value and the yaw error value are greater than their corresponding m times the preset threshold, the wind turbine generator set begins to yaw and enters the power reduction operation mode one, with the wind turbine generator set power reduced to P1; when both the wind speed value and the yaw error value are greater than their corresponding n times the preset threshold, the wind turbine generator set begins to yaw and enters the power reduction operation mode two, with the wind turbine generator set power reduced to P2, such as... Figure 14 As shown; where n>m, P1>P2. Specifically, where n=m+1.

[0166] Specifically, in step 4.1), after obtaining the wind speed value and yaw error value, the wind speed value and yaw error value are filtered to ensure the reliability of the data, thereby improving the reliability of subsequent load reduction.

[0167] The preset thresholds for wind speed values ​​correspond to the preset thresholds for yaw error values. These preset thresholds are pre-set in a wind speed-yaw error value scheduling table. Specifically, as shown in Table 1: in the wind speed-yaw error value scheduling table, when the preset thresholds for wind speed values ​​are 0 m / s, 5 m / s, 10 m / s, and 35 m / s, the corresponding preset thresholds for yaw error values ​​are 1.1345 rad, 1.1345 rad, 0.7850 rad, and 0.523 rad, respectively.

[0168] Table 1 Wind Speed-Yaw Error Value Scheduling Table

[0169]

[0170] By using the different threshold ranges of the wind speed-yaw error value scheduling table, the unit adopts a segmented power reduction operation mode, which more effectively reduces the tower load when the unit operates under large yaw conditions.

[0171] Example 5

[0172] like Figure 15 As shown, the specific steps for airspace control are as follows:

[0173] During wind turbine operation, the instantaneous position of the blade tip is monitored in real time to obtain the raw data of the instantaneous position of the blade tip;

[0174] Data cleaning of the raw data of the instantaneous position of the blade tip mainly includes: bandpass filtering of the obtained raw data of the instantaneous position of the blade tip, then sliding filtering every 100ms, and finally delay processing of the obtained data to obtain the effective value of the blade tip position.

[0175] The current blade clearance value is obtained based on the effective value of the blade tip position and the current rotor azimuth angle. Specifically, taking blade 1 as an example, when the rotor azimuth angle is 180 degrees, the blade tip of blade 1 is closest to the tower, and the clearance value of blade 1 can be calculated based on the current blade tip position. Similarly, the clearance value of blade 2 is the rotor azimuth angle of (180+120) degrees, and the clearance value of blade 3 is the rotor azimuth angle of (180+240) degrees.

[0176] The control system makes logical judgments based on the calculated blade clearance value, specifically as follows: Figure 16 As shown, if the current blade clearance value is lower than the clearance control threshold, a preset compensation value is superimposed on the original pitch angle command; if the current blade clearance value is higher than the clearance control threshold, normal power generation operation continues; if the current blade clearance value is lower than the shutdown protection threshold, shutdown protection is performed.

[0177] The wind turbine active clearance control method of the present invention monitors the instantaneous position of the blade tip in real time and actively performs pitch compensation when the clearance is insufficient, thereby ensuring the blade clearance of the wind turbine under extreme wind conditions such as high turbulence, and ensuring the safety and stability of the unit operation; moreover, the above method is simple to operate and has strong versatility.

[0178] Example 6

[0179] like Figure 17-18 As shown, the performance improvement includes a dynamic rated speed control method for large wind turbine generator sets, and the specific steps are as follows:

[0180] First, the blade root load is divided into different levels Z1, Z2...Z according to the magnitude of the blade root load. k Then, the blade root load distribution under different pitch angles was statistically analyzed, and the pitch angle intervals corresponding to the load levels were P1, P2...P k The rated speed setpoints are set to G1, G2...G according to the pitch angle range. k The rated speed setpoint of the wind turbine generator is adjusted based on the load distribution using the pitch angle. Specifically, when the pitch angle increases, the rated speed setpoint is correspondingly lowered; similarly, when the pitch angle decreases, the rated speed setpoint is correspondingly increased.

[0181] For example: Table 1 shows the corresponding settings of blade root load level, pitch angle and speed setpoint for a certain model, where Z is the blade root design load.

[0182] Table 1. Correspondence between Speed ​​Setpoints

[0183] Load rating (kN) (Z, Z+2000) Greater than (Z+2000) Pitch angle range (deg) (0，5) (5，10) Rated speed setpoint (rpm) 1650 1550

[0184] Based on the actual conditions of the unit, the entry conditions for the dynamic rated speed control method are set as follows:

[0185] like Figure 18 As shown, the dynamic rated speed control is set to enter the wind speed W. in and exit wind speed W out Among them, the wind speed W in = (rated wind speed - 3) m / s, exit wind speed W out = (rated wind speed + 3) m / s, the specific setting can be determined according to the actual site conditions. When the real-time wind speed W meets W in <W<W out Furthermore, the unit is in an unrestricted power state and operates according to the above-mentioned dynamic rated speed control method.

[0186] This invention dynamically adjusts the rated speed setpoint of the wind turbine generator by statistically analyzing the blade root load at different pitch angles. The wind turbine operates at different rated speeds at different pitch angles, achieving dynamic adjustment of the rated speed and effectively reducing blade root load, thus ensuring safe operation. Simultaneously, wind speed and power limitation condition judgments are incorporated. When these conditions are not met, control is resumed using the original control mode (fixed rated speed), effectively reducing power generation loss during rated speed adjustment. This method is simple to apply, highly versatile, and can be used on multiple power platforms.

[0187] Example 7

[0188] like Figures 19-20 As shown, the performance improvement includes a wind turbine operation control method based on yaw sector optimization, comprising the following steps:

[0189] The unit has pre-stored initial high-turbulence sector division information; the initial high-turbulence sector division information is specifically obtained based on previous geographical location surveys and turbulence intensity calculations;

[0190] During unit operation, wind condition data (including wind speed and wind direction) and corresponding nacelle position information are measured and recorded in real time, and the turbulence intensity of all sectors is calculated; when the turbulence intensity reaches the standard value, the sector (within 30°) where the nacelle is located is recorded.

[0191] The recorded sector area is compared with the initial high turbulence sector information. If the recorded sector is not in the initial storage high turbulence sector, the recorded sector location information is added to the high turbulence sector information database for automatic correction and improvement of the high turbulence sector range.

[0192] During the operation of the wind turbine, the instantaneous acceleration data of the nacelle is collected by the vibration acceleration sensor in the nacelle, and the collected nacelle acceleration data is filtered to obtain effective acceleration data in the driving direction / non-driving direction.

[0193] Based on the location of the wind turbine (whether it is in a high-turbulence area) and the nacelle acceleration data, it is determined whether to switch the control mode. Specifically, if the wind turbine is not in a high-turbulence sector, the original control mode is maintained; if the wind turbine is in a high-turbulence sector and the nacelle acceleration value is less than the lower limit of the protection threshold, normal power generation is maintained in the high-turbulence area; if the wind turbine is in a high-turbulence sector and the nacelle acceleration value is between the upper and lower limits of the protection threshold, the wind turbine yaws to leave the high-turbulence sector; if the wind turbine is in a high-turbulence sector and the nacelle acceleration value is greater than the upper limit of the protection threshold, the wind turbine triggers shutdown protection.

[0194] In the aforementioned nacelle acceleration data judgment process, acceleration data in the drive direction and acceleration data in the non-drive direction are judged separately to improve the accuracy and reliability of subsequent judgments. Specifically, if the wind turbine is not in a high-turbulence sector, the original control mode is maintained; if the wind turbine is in a high-turbulence sector, and both the drive direction acceleration data and the non-drive direction acceleration data are less than the corresponding lower protection threshold, normal power generation is maintained in the high-turbulence region; if the wind turbine is in a high-turbulence sector, and either the drive direction acceleration data or the non-drive direction acceleration data is between the upper and lower limits of the corresponding protection threshold, the wind turbine yaws away from the high-turbulence sector; if the wind turbine is in a high-turbulence sector, and either the drive direction acceleration data or the non-drive direction acceleration data is greater than the upper limit of the protection threshold, the wind turbine triggers shutdown protection.

[0195] This invention automatically corrects and improves the initially defined high-turbulence sector range based on real-time wind conditions and nacelle position data during wind turbine operation; when the wind turbine enters the high-turbulence sector, it automatically judges the wind turbine status and switches to different control modes to maximize wind energy utilization and improve the wind turbine's safety performance.

[0196] Example 8

[0197] like Figures 21-23 As shown, the dynamic correction control method for wind turbine pitch angle feedforward in this embodiment of the invention is as follows:

[0198] 1) Install a lidar on the nacelle of the wind turbine generator set. The lidar emits a laser beam (typically a 4-beam lidar, with a measurement distance of about 200 meters) in front of the wind rotor to measure the wind speed at different distances in front of the wind rotor. Generally, 5-10 different distances are selected, depending on the specific actual situation.

[0199] 2) Utilize lidar to measure wind speeds at different distances and calculate the equivalent feedforward control wind speed V0 and lead time τ (typically 3-5s) at the wind turbine surface; or use Newton's method (a conventional method) to calculate the equivalent wind speed at the wind turbine surface based on the wind speed at the radar measurement location.

[0200] 3) Dynamic compensation for pitch angle feedforward control based on feedforward control wind speed. The core issue is to obtain an accurate pitch angle feedforward amount based on the feedforward wind speed, combined with the operating environment and status of the wind turbine generator.

[0201] The formula for calculating wind energy capture is:

[0202]

[0203] In the above formula, P turbine ρ is the wind turbine's capture capacity, A is the wind turbine's rotor diameter, Cp is the rotor capture coefficient, and V is the wind speed.

[0204] When the wind turbine generator set P turbine To reach the set power, energy capture is reduced by changing Cp (achieved through blade pitch control). This is strongly correlated with air density. Therefore, when the wind speed is known (in the case of pitch control operation), the theoretical pitch angle required by the wind turbine is mainly affected by air density and whether the unit is power-limited. In other words, the problem that dynamic correction and compensation need to solve is to accurately construct the "wind speed-pitch angle" scheduling lookup value.

[0205] Detailed execution process as follows Figure 23 As shown, the air density is first corrected. The method for calculating air density is as follows:

[0206]

[0207] In the above formula: ρ - annual average air density, kg / m3; T - annual average air absolute temperature on the Kelvin scale (°C + 273); P is the average atmospheric pressure, kPa; R is the gas constant (287 J / kg·K).

[0208] Next, the rated power is corrected according to the power limiting ratio of the wind turbine generator set, specifically as follows:

[0209] powre_new_rated=k_lim it×P rated

[0210] In the formula, Power_new_rated is the rated power value after power limiting, k_limit is the power limiting ratio, ranging from 0-100%, and P rated Rated power designed for wind turbine generator sets.

[0211] Finally, the "wind speed-pitch angle" scheduling lookup table is dynamically updated based on the corrected air density and the rated power after power limitation, and the target pitch angle β(t+τ) with a lead of τ seconds is obtained by looking up the table.

[0212] Specifically, as shown in the wind energy capture calculation formula, the wind speed-pitch angle scheduling lookup table is preset based on air density and the rated power after power limiting. Taking a 6.25MW turbine model as an example, the standard air density is 1.225 kg / m³. 3 The wind speed-pitch angle curve for unlimited power is as follows: Figure 24 The curve on the right; when the air density is 1.1 kg / m³ 3 The wind speed-pitch angle curve at 80% power limitation ratio is as follows: Figure 24 As shown in the curve on the left. If air density and power limiting factors are not considered, the pitch angle with a lead of τ seconds is β0(t+τ), while it should actually be β(t+τ). There is a large deviation between the two, which will cause control deviation of the pitch angle.

[0213] 4) Combining the current pitch angle β(t) at time t and the target pitch angle β(t+τ) with a lead time of τ seconds, feedforward control is performed to calculate the dynamically corrected and compensated pitch angle feedforward amount δ=β(t+τ)-β0(t+τ). This is then superimposed on the pitch angle β0(t+τ) under standard air density and unrestricted power conditions and sent to the pitch actuator. If the pitch system adopts speed control mode, the feedforward control pitch rate is:

[0214] rateRequired=[β(t+τ)-β(t)] / τ

[0215] Where β(t) is the current pitch angle; β(t+τ) is the target pitch angle τ seconds ahead, and τ is the lead time.

[0216] By combining air density and the power limiting ratio of the wind turbine generator set, dynamic compensation is performed on the pitch angle feedforward to ensure the stability and accuracy of the feedforward control system, reduce the fatigue load and extreme load of the wind turbine generator set (the fatigue load at the tower base My can be reduced by about 8%, and the ultimate load under extreme gust conditions can be reduced by at least 10%), achieve lightweighting of the wind turbine generator set, and reduce the cost per kilowatt-hour of the wind turbine generator set.

[0217] This invention updates the wind speed-pitch angle mapping relationship in advance based on the air density and / or power limitation ratio of the wind turbine's environment. By measuring the wind speed at different distances in front of the rotor, the equivalent feedforward control wind speed V0 and lead time τ are obtained at the rotor surface. From the updated wind speed-pitch angle mapping relationship, the target pitch angle β(t+τ) with a lead time of τ seconds is obtained. Combined with the current pitch angle β(t) of the wind turbine and the target pitch angle β(t+τ) with a lead time of τ seconds, feedforward control is performed to calculate the final pitch angle control quantity for pitch control. This ensures the stability and accuracy of the feedforward control system, thereby reducing the fatigue load and ultimate load of the wind turbine. This invention also enables the lightweighting of wind turbines and reduces the levelized cost of electricity (LCOE) of wind turbines.

[0218] Specifically, this invention involves installing an additional lidar on the wind turbine to measure the wind speed at a certain distance in front of the rotor (typically around 200 meters, depending on the lidar installed). This allows the wind turbine to sense the incoming wind speed in front of the rotor in advance, typically a few seconds (usually 3-5 seconds). A feedforward control algorithm is then constructed, and combined with air density, the wind turbine's power limiting status, and the proportional gain, the pitch angle feedforward is corrected and compensated. This ensures the stability and accuracy of the feedforward control system, reduces fatigue loads and loads under extreme conditions on the wind turbine, thereby lowering the levelized cost of electricity (LCOE) of the wind turbine.

[0219] Example 9

[0220] like Figure 25-27 As shown, intelligent protection includes a method for monitoring and controlling wind turbine blade stall, with the following specific steps:

[0221] The wind turbine is pre-configured with wind speed-active power curves under different air densities as a reference wind speed-active power curve; the wind turbine is pre-configured with generator speed-nacelle acceleration curves under different air densities as a reference generator speed-nacelle acceleration curve.

[0222] The operation data of the wind turbine is acquired and cleaned. Specifically, bandpass filtering is performed on each data point, followed by 100ms sliding filtering to obtain the effective data for each variable. The operation data includes air temperature, wind speed, power generation, generator speed, and nacelle acceleration.

[0223] The current air density is obtained from the air temperature; the current wind speed-active power curve of the wind turbine is obtained from the wind speed and power generation; the current generator speed-nacelle acceleration curve of the wind turbine is obtained from the generator speed and nacelle acceleration.

[0224] The current wind speed-active power curve is compared with the reference wind speed-active power curve under the current air density to obtain the first comparison result; at the same time, the current generator speed-nacelle acceleration curve is compared with the reference generator speed-nacelle acceleration curve under the current air density to obtain the second comparison result.

[0225] The first comparison result and the second comparison result are used to determine whether the wind turbine blades are stalling and the degree of stalling.

[0226] Specifically, when the first comparison result is that the current wind speed-active power curve exceeds the stall control threshold of the reference wind speed-active power curve under the current air density but is lower than the corresponding shutdown protection value, and the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the stall control threshold of the reference generator speed-nacelle acceleration curve under the current air density but is lower than the corresponding shutdown protection value, then the blade is judged to be in a general stall. At this time, the additional value of the pitch angle is calculated by combining the current pitch angle and active power, and superimposed on the unified pitch output value to perform the pitch retraction action.

[0227] If the first comparison result is that the current wind speed-active power curve exceeds the shutdown protection value of the reference wind speed-active power curve, or if the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the shutdown protection value of the reference generator speed-nacelle acceleration curve under the current air density, then the blade is judged to be in severe stall, and a shutdown action is executed.

[0228] In general, the stall judgment condition is that the first comparison result and the second comparison result simultaneously reach the stall control threshold but are lower than the shutdown protection value, then control action is taken; in case of severe stall, either of the two conditions reaches the shutdown protection value, then the machine is shut down.

[0229] The above process is actively judged and executed by the main control program, and corresponding scheduling and control actions are performed without increasing other hardware costs, so that the load reduction effect can be achieved at a lower cost.

[0230] This invention monitors the blade stall status in real time based on real-time monitoring data of wind turbine operation, ensuring that the unit can make timely adjustments according to the current operating status, maximizing power generation while ensuring safe operation of the unit, and fully tapping the power generation potential.

[0231] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A control method for an intelligent wind turbine generator set, characterized in that, Including the following steps: Obtain operating status information of wind turbine generator sets; Based on the operating status information of the wind turbine generator set, intelligent control and / or intelligent protection are implemented for the wind turbine generator set; wherein the intelligent control includes one or more of the following: ultimate load reduction, fatigue load reduction, or performance improvement; wherein the intelligent protection includes assessing the health and trend of the operating environment and the generator set's own status, and taking corresponding intelligent protection measures based on the assessment results; Intelligent protection includes methods for monitoring and controlling wind turbine blade stall, with the following specific steps: The wind turbine is pre-configured with wind speed-active power curves under different air densities as a reference wind speed-active power curve; the wind turbine is pre-configured with generator speed-nacelle acceleration curves under different air densities as a reference generator speed-nacelle acceleration curve. Acquire wind turbine operating data, including air temperature, wind speed, power generation, generator speed, and nacelle acceleration; The current air density is obtained based on the temperature. The current wind speed-active power curve of the wind turbine is obtained based on wind speed and power generation; the current generator speed-nacelle acceleration curve of the wind turbine is obtained based on generator speed and nacelle acceleration. The current wind speed-active power curve is compared with the reference wind speed-active power curve under the current air density to obtain the first comparison result; at the same time, the current generator speed-nacelle acceleration curve is compared with the reference generator speed-nacelle acceleration curve under the current air density to obtain the second comparison result. The first comparison result and the second comparison result are used to determine whether the wind turbine blades are stalling and the corresponding degree of stalling. If the first comparison result is that the current wind speed-active power curve exceeds the stall control threshold of the reference wind speed-active power curve under the current air density but is lower than the corresponding shutdown protection value, and the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the stall control threshold of the reference generator speed-nacelle acceleration curve under the current air density but is lower than the corresponding shutdown protection value, then the blade is judged to be in a general stall. When the blade is judged to be in a general stall, the additional value of the pitch angle is calculated by combining the current pitch angle and active power, and superimposed on the unified pitch output value to perform the pitch retraction action.

2. The intelligent wind turbine generator control method according to claim 1, characterized in that, The operational status information includes hardware sensing information, virtual sensing information, and multi-data fusion information; the hardware sensing information includes wind conditions, load, clearance, and attitude; the virtual sensing information includes the wind turbine's rotational speed, power, wind speed, vibration, pitch angle, and voltage and current signals; and the multi-data fusion information includes mechanical inertia, transmission chain torsional vibration, and power generation performance.

3. The intelligent wind turbine generator control method according to claim 1 or 2, characterized in that, This includes one or more of the following: extreme load reduction, gust load reduction, overspeed suppression, high turbulence load reduction, high shear load reduction, high yaw error load reduction, load-based load reduction, and clearance control.

4. The intelligent wind turbine generator control method according to claim 3, characterized in that, The specific process of gust load reduction is as follows: 1.1) Acquire the status signals of the wind turbine generator set, including at least two of the following: wind speed, wind direction, generator speed, generator acceleration, nacelle vibration acceleration, pitch speed, generator torque change rate, and generator power change rate. 1.2) Obtain the correlation coefficient between state information based on at least two types of state information; 1.3) Compare the correlation coefficient with a preset threshold; if the correlation coefficient is not within the preset threshold, it is determined that the wind turbine is operating in gust mode, and pitch control is performed to reduce the ultimate load on the blades.

5. The intelligent wind turbine generator control method according to claim 4, characterized in that, In step 1.3), if the correlation coefficient is not within the preset threshold, one or more auxiliary variables are introduced for auxiliary judgment; the one or more auxiliary variables are compared with the preset auxiliary threshold, and if the one or more auxiliary variables are not within the corresponding preset auxiliary threshold, it is determined that the wind turbine is operating in gust mode.

6. The intelligent wind turbine generator control method according to claim 3, characterized in that, The specific process of overspeed suppression is as follows: Obtain the generator speed of the wind turbine , to increase generator speed With speed set point Subtracting the values ​​yields the rotational speed error, which in turn provides the output value for the pitch speed PID control. ; Obtain the acceleration of the wind turbine Multiply by the tower drag gain coefficient to obtain the tower drag pitch angle value. ; Obtain the pitch angle of the wind turbine and generator speed overspeed ratio After adaptive fuzzy overspeed suppression, the adaptive fuzzy overspeed suppression compensated pitch angle value is obtained. ; The output value of the PID control for pitch speed Tower drag pitch angle value Adaptive fuzzy overspeed suppression compensation pitch angle The three values ​​are combined to obtain the pitch angle command value. It is then fed to the pitch actuator for pitch control.

7. The intelligent wind turbine generator control method according to claim 6, characterized in that, The specific process of adaptive fuzzy overspeed suppression is as follows: Generator speed overspeed ratio The generator speed overspeed ratio filter value is obtained after filtering. ; Generator speed overspeed ratio filter value With pitch angle The input observations of the fuzzy controller are fuzzified, then fuzzy inference is performed according to the fuzzy control rule table, and finally defuzzification is performed using the centroid method to obtain the control quantity of the fuzzy controller. Control quantity Multiply by adaptive adjustment factor Obtain adaptive fuzzy overspeed suppression additional pitch rate , Multiply by the step size to convert into an adaptive fuzzy overspeed suppression compensation pitch angle value .

8. The intelligent wind turbine generator control method according to claim 3, characterized in that, The specific process of load-based unloading is as follows: Obtain the real-time unit load during the operation of the wind turbine; The unit load is compared with the standard load; when the unit load exceeds the standard load, the optimal pitch angle is obtained according to the set load and the optimal pitch angle scheduling table; the scheduling table is set according to the characteristics of the unit and specifies the optimal pitch angle under the unit load. The optimal pitch angle is superimposed on the current pitch angle, and the lower limit of the pitch angle is adjusted to reduce the load.

9. The intelligent wind turbine generator control method according to claim 3, characterized in that, The specific process for unloading due to high yaw error is as follows: Obtain the wind speed and yaw error values ​​of the wind turbine generator set; The wind speed value and yaw error value are compared with their corresponding preset thresholds respectively. When both the wind speed value and the yaw error value are greater than their corresponding preset thresholds, the wind turbine performs a yaw action and enters a power-limited operation mode. When the yaw error value is greater than its corresponding preset threshold, but the wind speed value is less than its corresponding preset threshold, the wind turbine performs a yaw action and maintains normal operation mode. When both the wind speed value and the yaw error value are less than their corresponding preset thresholds, the wind turbine maintains normal operation mode.

10. The intelligent wind turbine generator control method according to claim 9, characterized in that, The power-limited operation mode specifically includes: when both the wind speed value and the yaw error value are greater than their corresponding m times the preset threshold, the wind turbine generator starts to yaw and enters the power reduction operation mode one, and the power of the wind turbine generator is reduced to P1; when both the wind speed value and the yaw error value are greater than their corresponding n times the preset threshold, the wind turbine generator starts to yaw and enters the power reduction operation mode two, and the power of the wind turbine generator is reduced to P2; where n>m, P1>P2.

11. The intelligent wind turbine generator control method according to claim 3, characterized in that, Steps for airspace control: 5.1) Obtain the blade tip position during blade operation, and perform data cleaning on the blade tip position to obtain the effective value of the blade tip position; 5.2) Obtain the current blade clearance value based on the effective value of the blade tip position and the current rotor azimuth angle; 5.3) Compare the current blade clearance value with the preset threshold, and control the clearance of the wind turbine based on the comparison result.

12. The intelligent wind turbine generator control method according to claim 11, characterized in that, The specific process of step 5.3) is as follows: if the current blade clearance value is lower than the clearance control threshold, a preset compensation value is superimposed on the original pitch angle command; if the current blade clearance value is higher than the clearance control threshold, normal power generation operation continues.

13. The intelligent wind turbine generator control method according to claim 1 or 2, characterized in that, Performance improvements include a dynamic rated speed control method for wind turbine generator sets. Specifically, when the wind speed of the wind turbine generator set is within a preset threshold and the wind turbine generator set is in an unrestricted power state, the unit operates according to the dynamic rated speed control method: the rated speed set point of the wind turbine generator set is adjusted according to the pitch angle to reduce the blade root load of the unit.

14. The intelligent wind turbine generator control method according to claim 13, characterized in that, The blade root load is pre-classified into different load levels Z1, Z2...Z k Different load levels Z1, Z2…Z k The corresponding pitch angle intervals are P1, P2...P k Different pitch angle intervals P1, P2...P k The corresponding rated speed setpoints are G1, G2...G k .

15. The intelligent wind turbine generator control method according to claim 3, characterized in that, Performance improvements include wind turbine operation control methods based on yaw sector optimization, comprising the following steps: The wind condition data and corresponding nacelle location information during the operation of the wind turbine are obtained to update the range of the high turbulence sector of the wind turbine. The raw data of instantaneous acceleration of the nacelle during the operation of the wind turbine are obtained, and the raw data of instantaneous acceleration of the nacelle are preprocessed to obtain effective nacelle acceleration data; Based on the location of the wind turbine and valid nacelle acceleration data, the control mode of the wind turbine is adjusted as follows: If the wind turbine is not located in a high-turbulence sector, the original control mode is maintained; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is less than the lower limit of the protection threshold, normal power generation is maintained within the high-turbulence sector; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is between the upper and lower limits of the protection threshold, the wind turbine yaws away from the high-turbulence sector; if the wind turbine is located in a high-turbulence sector and the nacelle acceleration data is greater than the upper limit of the protection threshold, shutdown protection is triggered.

16. The intelligent wind turbine generator control method according to claim 15, characterized in that, The specific process of updating the high-turbulence sector range of the wind turbine by acquiring wind condition data and corresponding nacelle location information during wind turbine operation is as follows: Pre-store initial high-turbulence sector information of wind turbine units; Acquire wind condition data and corresponding nacelle location information during wind turbine operation, and calculate the turbulence intensity of all sectors; if the turbulence intensity reaches the standard value, record the sector where the nacelle is located. The recorded sector region is compared with the initial high-turbulence sector information; if the recorded sector region is not in the initial high-turbulence sector information, the recorded sector region is added to the initial high-turbulence sector information to obtain the updated high-turbulence sector information.

17. The intelligent wind turbine generator control method according to claim 3, characterized in that, Performance improvements include a dynamic correction control method for the wind turbine pitch angle feedforward, the specific steps of which are as follows: Obtain the wind speed at different predetermined distances in front of the wind turbine rotor; Based on the wind speed at different predetermined distances in front of the wind turbine, calculate the equivalent feedforward control wind speed V0 and lead time applied to the wind turbine surface. ; Obtain the air density and / or power limitation ratio of the environment where the wind turbine is located, and then update the mapping relationship between wind speed and pitch angle based on the air density and / or power limitation ratio to obtain the updated wind speed-pitch angle mapping relationship. Based on the feedforward control wind speed V0 and lead time The advanced wind speed is obtained from the updated wind speed-pitch angle mapping. Target pitch angle in seconds ; Combining the current pitch angle β(t) and lead of the wind turbine Target pitch angle in seconds Feedforward control is performed to calculate the final pitch angle control value for pitch control.

18. The intelligent wind turbine generator control method according to claim 17, characterized in that, When performing pitch control, if speed control mode is used, the feedforward control pitch rate is: Where β(t) is the current pitch angle; In advance Target pitch angle in seconds, For ahead of time.

19. The intelligent wind turbine generator control method according to claim 1, characterized in that, If the first comparison result is that the current wind speed-active power curve exceeds the shutdown protection value of the reference wind speed-active power curve, or if the second comparison result is that the current generator speed-nacelle acceleration curve exceeds the shutdown protection value of the reference generator speed-nacelle acceleration curve under the current air density, then the blade is judged to be in severe stall; when the blade is judged to be in severe stall, a shutdown action is executed.

20. A smart wind turbine generator control system, comprising a memory and a processor interconnected, wherein the memory stores a computer program, characterized in that, The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-19.

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