A method and system for identifying turbulence intensity and controlling load reduction of a wind turbine generator system

Abstract

The present invention discloses a method and system for identifying turbulence intensity and controlling load reduction of a wind turbine, comprising: collecting the front and rear accelerations of a nacelle, the rotational speed of a wind rotor and the pitch rate of the wind turbine, and performing data processing to obtain the standard deviations of the front and rear accelerations of the nacelle, the rotational speed of a wind rotor and the pitch rate of the wind turbine, and performing weighted summation calculation to output the current turbulence intensity characteristic quantity; according to the turbulence intensity characteristic quantity and the average wind speed after filtering, calculating and obtaining the maximum turbulence power setting value, the maximum turbulence rotational speed setting value and the minimum turbulence blade angle, thereby adjusting the generator power, the rotational speed of a wind rotor and the blade angle of the wind turbine, and effectively reducing the load of the unit under extreme turbulence conditions. The present invention has high reliability and does not add additional sensor measurement equipment, and is worthy of promotion.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine control, and in particular to a method, system, storage medium and computing device for identifying turbulence intensity and controlling load reduction of a wind turbine. Background Art

[0002] Throughout their lifecycle, wind turbines inevitably encounter various wind conditions. Extreme turbulence conditions are a particular type of extreme condition that must be considered in the IEC design specifications for wind turbines. Extreme turbulence conditions occur when a wind turbine encounters extremely turbulent winds during normal power generation, and the turbine cannot be shut down under these conditions. Extreme turbulence conditions often cause extreme loads on the turbine blade roots and hub, and can easily lead to blade clearance issues. Because the anemometer is mounted at the rear of the nacelle, it is obstructed by blades and affected by wake turbulence, making it impossible to accurately identify the current turbulence intensity using the nacelle wind speed. Therefore, it is not possible to effectively reduce the load in response to extreme turbulence conditions. For wind turbines equipped with a lidar (LiDAR) radar in the nacelle, the wind speed measured by the LiDAR can be used to identify turbulence intensity. However, LiDAR equipment is expensive and easily affected by environmental factors such as rain, snow, dust, and haze, resulting in low reliability. Summary of the Invention

[0003] The first purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and provide a method for turbulence intensity identification and load reduction control of a wind turbine set, calculate the measured cabin acceleration, wind rotor speed and pitch rate, obtain the turbulence intensity characteristic quantity, and achieve unit load reduction by adjusting the generator power, wind rotor speed and minimum blade angle.

[0004] A second object of the present invention is to provide a turbulence intensity identification and load reduction control system for a wind turbine generator set.

[0005] A third object of the present invention is to provide a storage medium.

[0006] A fourth object of the present invention is to provide a computing device.

[0007] The first object of the present invention is achieved by the following technical solution: a method for identifying turbulence intensity and controlling load reduction of a wind turbine generator set, performing the following operations:

[0008] The wind turbine's nacelle acceleration, rotor speed, and pitch rate are collected and processed to obtain the standard deviation of the nacelle acceleration, rotor speed, and pitch rate. After weighted summation, the current turbulence intensity characteristic is output.

[0009] According to the turbulence intensity characteristic quantity and the average wind speed after filtering, the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle are calculated; the turbulence maximum power setting value is used as the upper limit of the power setting value in the controller of the wind turbine. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to drop to the turbulence maximum power setting value; the turbulence maximum speed setting value is used as the upper limit of the rotor speed setting value in the controller of the wind turbine. When the rotor speed exceeds the turbulence maximum speed setting value, the rotor speed is controlled to drop to the turbulence maximum speed setting value; the turbulence minimum blade angle is used as the lower limit of the pitch angle command in the controller of the wind turbine. When the pitch angle command is less than the turbulence minimum blade angle, the pitch angle command is limited to not less than the turbulence minimum blade angle; finally, by adjusting the generator power, rotor speed and blade angle of the wind turbine, the load of the unit under extreme turbulence conditions is effectively reduced.

[0010] Furthermore, the front and rear accelerations of the wind turbine nacelle are collected and processed to obtain the standard deviation of the front and rear accelerations of the nacelle, as follows:

[0011] Measuring the front-to-back acceleration of the nacelle of the wind turbine using an acceleration sensor installed on the nacelle platform of the wind turbine. The acceleration sensor can measure the front-to-back acceleration of the nacelle platform in real time, i.e., the front-to-back acceleration of the nacelle;

[0012] The cabin fore-and-aft acceleration measured by the acceleration sensor contains signals of various frequencies. Only the low-frequency portion of the cabin fore-and-aft acceleration can be used as an effective signal for turbulence identification. Therefore, the cabin fore-and-aft acceleration needs to be filtered to remove high-frequency harmonic noise and the characteristic frequency of the drive train. This is used to define the effective cabin fore-and-aft acceleration. The specific formula is as follows:

[0013]

[0014] In the above formula, Indicates the effective front and rear acceleration of the cabin; F fa (s) represents the effective front and rear acceleration filter of the cabin, which contains a low-pass filter and a band-stop filter; represents the acceleration measurement of the front and rear of the cabin;

[0015] The effective fore-aft acceleration of the cabin is stored in a queue storage mode with first-in and last-out. The length of the storage array is set to N, and the stored data is the effective fore-aft acceleration of the cabin from the current moment to the previous N moments. The standard deviation of the fore-aft acceleration of the cabin is obtained by calculating the standard deviation. The standard deviation of the fore-aft acceleration of the cabin reflects the current turbulence intensity. A larger standard deviation corresponds to a greater turbulence intensity. The calculation formula for the standard deviation of the fore-aft acceleration of the cabin is as follows:

[0016]

[0017] In the above formula, σ fa represents the standard deviation of acceleration fore and aft of the cabin; represents the effective fore-aft acceleration of the cabin at time 1; represents the effective fore-aft acceleration of the cabin at time 2; represents the effective fore-aft acceleration of the nacelle at time N.

[0018] Furthermore, the rotor speed of the wind turbine is collected and the data is processed to obtain the standard deviation of the rotor speed, as follows:

[0019] The speed sensor is installed on the inner slip ring of the hub of the wind turbine and can measure the rotation speed of the wind turbine rotor in real time.

[0020] The rotor speed measured by the speed sensor contains signals of various frequencies. Only the low-frequency part of the rotor speed can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the rotor speed data to remove high-frequency harmonic noise and the characteristic frequency of the transmission chain and define the effective rotor speed. The specific formula is as follows:

[0021]

[0022] In the above formula, Indicates the effective speed of the wind rotor; H(s) indicates the effective speed filter of the wind rotor, which contains a low-pass filter and a band-stop filter; Indicates the measured value of the wind wheel speed;

[0023] The effective speed of the wind rotor is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective speed of the wind rotor from the current moment to the previous N moments. The standard deviation of the wind rotor speed is obtained by calculating the standard deviation. The standard deviation of the wind rotor speed reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the standard deviation of the wind rotor speed is as follows:

[0024]

[0025] In the above formula, ε r Indicates the standard deviation of the wind wheel speed; represents the effective speed of the wind wheel at time 1; represents the effective speed of the wind wheel at time 2; Represents the effective speed of the wind rotor at time N; ω0 represents the rated wind rotor speed.

[0026] Furthermore, the pitch rate of the wind turbine is collected and the data is processed to obtain the standard deviation of the pitch rate, as follows:

[0027] The pitch rate of the wind turbine is measured by a pitch encoder sensor, which is installed on the pitch bearing ring of the wind turbine. The pitch encoder sensor can measure the rotation speed of the wind turbine blades in real time, that is, the pitch rate;

[0028] The pitch rate measured by the pitch encoder sensor contains signals of various frequencies. Only the low-frequency part of the pitch rate can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the pitch rate data to remove high-frequency harmonic noise and the characteristic frequency of the transmission chain and define the effective pitch rate. The specific formula is as follows:

[0029]

[0030] In the above formula, represents the effective pitch rate; U(s) represents the effective pitch rate filter; represents the average value of the measured pitch rates of blades 1, 2, and 3;

[0031] The effective pitch rate data is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective pitch rate from the current moment to the previous N moments. The pitch rate standard deviation is obtained by calculating the standard deviation. The pitch rate standard deviation reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the pitch rate standard deviation is as follows:

[0032]

[0033] In the above formula, τ β represents the standard deviation of pitch rate; represents the effective pitch rate at time 1; represents the effective pitch rate at time 2; represents the effective pitch rate at time N.

[0034] Furthermore, the obtained standard deviations of the front and rear accelerations of the nacelle, the standard deviations of the wind rotor speed, and the standard deviations of the pitch rate are weighted and summed to obtain the characteristic quantity of the current turbulence intensity, as follows:

[0035] The standard deviation of the acceleration before and after the nacelle, the standard deviation of the wind rotor speed, and the standard deviation of the pitch rate all reflect the turbulence intensity. Therefore, a weighted sum method is used to obtain a comprehensive turbulence intensity index, namely the turbulence intensity characteristic quantity. The turbulence intensity characteristic quantity is defined and calculated as follows:

[0036] I e =A fa ·σ fa +B r ·ε r +Cβ ·τ β

[0037] In the above formula, I e Represents the characteristic quantity of turbulence intensity; A fa represents the weighting coefficient of the standard deviation of acceleration before and after the cabin; σ fa represents the standard deviation of acceleration before and after the cabin; B r Represents the weighted coefficient of the standard deviation of the wind wheel speed; ε r Indicates the standard deviation of the wind wheel speed; C β represents the standard deviation of pitch rate; τ β Indicates the standard deviation of the pitch rate.

[0038] Furthermore, the turbulence power reduction coefficient is calculated based on the turbulence intensity characteristic and the filtered average wind speed. The rated output power of the generator is multiplied by the turbulence power reduction coefficient to obtain the turbulence maximum power setting value.

[0039] The value of the turbulence power reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulence power reduction coefficient by looking up the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0040]

[0041] In the above formula, μ p represents the turbulence power reduction coefficient; I e Indicates the characteristic quantity of turbulence intensity; Indicates the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_P e Represents the two-dimensional lookup table function of the turbulence power reduction coefficient;

[0042] The turbulence maximum power setting is defined as follows:

[0043] P Max =μ p ·P Rated

[0044] In the above formula, P Max Indicates the maximum turbulence power setting value; P Rated Indicates the rated output power of the generator.

[0045] Furthermore, the turbulence speed reduction coefficient is calculated based on the turbulence intensity characteristic and the filtered average wind speed. The rated speed of the wind rotor is multiplied by the turbulence speed reduction coefficient as the turbulence maximum speed setting value.

[0046] The value of the turbulence speed reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional table lookup function is set to obtain the turbulence speed reduction coefficient by looking up the table based on the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0047]

[0048] In the above formula, μ ω I represents the turbulence reduction coefficient; e Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_ω r Represents the two-dimensional lookup table function of the turbulence speed reduction coefficient;

[0049] The turbulent maximum speed setting value is defined as follows:

[0050] ω Max =μ ω ·ω Rated

[0051] In the above formula, ω Max Indicates the maximum turbulent speed setting value; ω Rated Indicates the rated speed of the wind wheel.

[0052] Furthermore, the minimum turbulent blade angle is calculated based on the turbulence intensity characteristic and the filtered average wind speed;

[0053] The value of the turbulent minimum blade angle is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulent minimum blade angle through the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0054]

[0055] In the above formula, β Min Indicates the minimum blade angle for turbulence; I e Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_β represents the two-dimensional lookup function of the minimum blade angle for turbulence.

[0056] The second object of the present invention is achieved by the following technical solution: a turbulence intensity identification and load reduction control system for a wind turbine, which is used to implement the above-mentioned turbulence intensity identification and load reduction control method for a wind turbine, comprising:

[0057] The turbulence intensity identification module is used to collect the front and rear acceleration of the wind turbine nacelle, the rotor speed and the pitch rate, and process the data to obtain the standard deviation of the front and rear acceleration of the nacelle, the standard deviation of the rotor speed and the standard deviation of the pitch rate. After performing weighted summation calculation, it outputs the current turbulence intensity characteristic value;

[0058] The turbulence load reduction control module is used to calculate the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle according to the turbulence intensity characteristic quantity and the filtered average wind speed; the turbulence maximum power setting value is used as the upper limit of the power setting value in the controller of the wind turbine set. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to be reduced to the turbulence maximum power setting value; the turbulence maximum speed setting value is used as the upper limit of the rotor speed setting value in the controller of the wind turbine set. When the rotor speed exceeds the turbulence maximum speed setting value, the rotor speed is controlled to be reduced to the turbulence maximum speed setting value; the turbulence minimum blade angle is used as the lower limit of the pitch angle instruction in the controller of the wind turbine set. When the pitch angle instruction is less than the turbulence minimum blade angle, the pitch angle instruction is limited to not less than the turbulence minimum blade angle; finally, by adjusting the generator power, rotor speed and blade angle of the wind turbine set, the load of the unit under extreme turbulence conditions is effectively reduced.

[0059] The third object of the present invention is achieved through the following technical solution: a storage medium stores a program, and when the program is executed by a processor, the above-mentioned turbulence intensity identification and load reduction control method of the wind turbine is implemented.

[0060] The fourth object of the present invention is achieved through the following technical solution: a computing device, comprising a processor and a memory for storing a program executable by the processor, wherein when the processor executes the program stored in the memory, the above-mentioned turbulence intensity identification and load reduction control method of the wind turbine is implemented.

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] 1. Based on the collected front and rear accelerations of the wind turbine nacelle, the rotor speed and the pitch rate, the present invention proposes a turbulence intensity identification method by constructing turbulence intensity characteristic quantities. The method has high reliability and does not require additional sensor measurement equipment.

[0063] 2. Based on the turbulence intensity characteristic quantity, the present invention constructs the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle. By adjusting the generator power, wind rotor speed and blade angle of the wind turbine, the load of the wind turbine under extreme turbulence conditions can be effectively reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is an architecture diagram of the system of the present invention. DETAILED DESCRIPTION

[0065] The present invention will be described in further detail below with reference to the embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0066] Example 1

[0067] This embodiment discloses a method for identifying turbulence intensity and controlling load reduction of a wind turbine generator set, which specifically performs the following operations:

[0068] 1) The wind turbine nacelle front and rear acceleration, rotor speed, and pitch rate are collected and processed to obtain the standard deviation of the nacelle front and rear acceleration, rotor speed, and pitch rate. After weighted summation, the current turbulence intensity characteristic is output as follows:

[0069] a. Collect the front and rear accelerations of the wind turbine nacelle and process the data to obtain the standard deviation of the front and rear accelerations of the nacelle, as follows:

[0070] Measuring the front-to-back acceleration of the nacelle of the wind turbine using an acceleration sensor installed on the nacelle platform of the wind turbine. The acceleration sensor can measure the front-to-back acceleration of the nacelle platform in real time, i.e., the front-to-back acceleration of the nacelle;

[0071] The cabin fore-and-aft acceleration measured by the acceleration sensor contains signals of various frequencies. Only the low-frequency portion of the cabin fore-and-aft acceleration can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the cabin fore-and-aft acceleration data to remove high-frequency harmonic noise and the characteristic frequency of the drive train. This is used to define the effective cabin fore-and-aft acceleration. The specific formula is as follows:

[0072]

[0073] In the above formula, Indicates the effective front and rear acceleration of the cabin; F fa (s) represents the effective front and rear acceleration filter of the cabin, which contains a low-pass filter and a band-stop filter; represents the acceleration measurement of the front and rear of the cabin;

[0074] The effective fore-aft acceleration of the cabin is stored in a queue storage mode with first-in and last-out. The length of the storage array is set to N, and the stored data is the effective fore-aft acceleration of the cabin from the current moment to the previous N moments. The standard deviation of the fore-aft acceleration of the cabin is obtained by calculating the standard deviation. The standard deviation of the fore-aft acceleration of the cabin reflects the current turbulence intensity. A larger standard deviation corresponds to a greater turbulence intensity. The calculation formula for the standard deviation of the fore-aft acceleration of the cabin is as follows:

[0075]

[0076] In the above formula, σ fa represents the standard deviation of acceleration fore and aft of the cabin; represents the effective fore-aft acceleration of the cabin at time 1; represents the effective fore-aft acceleration of the cabin at time 2; represents the effective fore-aft acceleration of the nacelle at time N.

[0077] b. Collect the rotor speed of the wind turbine and process the data to obtain the standard deviation of the rotor speed, as follows:

[0078] The speed sensor is installed on the inner slip ring of the hub of the wind turbine and can measure the rotation speed of the wind turbine rotor in real time.

[0079] The rotor speed measured by the speed sensor contains signals of various frequencies. Only the low-frequency part of the rotor speed can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the rotor speed data to remove high-frequency harmonic noise, characteristic frequencies of the transmission chain, etc., and define the effective rotor speed. The specific formula is as follows:

[0080]

[0081] In the above formula, Indicates the effective speed of the wind rotor; H(s) indicates the effective speed filter of the wind rotor, which contains a low-pass filter and a band-stop filter; Indicates the measured value of the wind wheel speed;

[0082] The effective speed of the wind rotor is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective speed of the wind rotor from the current moment to the previous N moments. The standard deviation of the wind rotor speed is obtained by calculating the standard deviation. The standard deviation of the wind rotor speed reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the standard deviation of the wind rotor speed is as follows:

[0083]

[0084] In the above formula, ε r Indicates the standard deviation of the wind wheel speed; represents the effective speed of the wind wheel at time 1; represents the effective speed of the wind wheel at time 2; Represents the effective speed of the wind rotor at time N; ω0 represents the rated wind rotor speed.

[0085] c. Collect the pitch rate of the wind turbine and process the data to obtain the standard deviation of the pitch rate, as follows:

[0086] The pitch rate of the wind turbine is measured by a pitch encoder sensor, which is installed on the pitch bearing ring of the wind turbine. The pitch encoder sensor can measure the rotation speed of the wind turbine blades in real time, that is, the pitch rate;

[0087] The pitch rate measured by the pitch encoder sensor contains signals of various frequencies. Only the low-frequency part of the pitch rate can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the pitch rate data to remove high-frequency harmonic noise, characteristic frequency of the transmission chain, etc., and define the effective pitch rate. The specific formula is as follows:

[0088]

[0089] In the above formula, represents the effective pitch rate; U(s) represents the effective pitch rate filter; represents the average value of the measured pitch rates of blades 1, 2, and 3;

[0090] The effective pitch rate data is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective pitch rate from the current moment to the previous N moments. The pitch rate standard deviation is obtained by calculating the standard deviation. The pitch rate standard deviation reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the pitch rate standard deviation is as follows:

[0091]

[0092] In the above formula, τ β represents the standard deviation of pitch rate; represents the effective pitch rate at time 1; represents the effective pitch rate at time 2; represents the effective pitch rate at time N.

[0093] d. Perform a weighted sum calculation on the obtained standard deviations of the front and rear accelerations of the nacelle, the rotor speed, and the pitch rate to obtain the characteristic value of the current turbulence intensity, as follows:

[0094] The standard deviation of the acceleration before and after the nacelle, the standard deviation of the wind rotor speed, and the standard deviation of the pitch rate all reflect the turbulence intensity. Therefore, a weighted sum method is used to obtain a comprehensive turbulence intensity index, namely the turbulence intensity characteristic quantity. The turbulence intensity characteristic quantity is defined and calculated as follows:

[0095] I e =A fa ·σ fa +B r ·ε r +C β ·τβ

[0096] In the above formula, I e Represents the characteristic quantity of turbulence intensity; A fa represents the weighting coefficient of the standard deviation of acceleration before and after the cabin; σ fa represents the standard deviation of acceleration before and after the cabin; B r Represents the weighted coefficient of the standard deviation of the wind rotor speed; ·ε r Indicates the standard deviation of the wind wheel speed; C β represents the standard deviation of pitch rate; τ β Indicates the standard deviation of the pitch rate.

[0097] 2) Based on the turbulence intensity characteristic and the filtered average wind speed, the maximum turbulence power setting value, the maximum turbulence speed setting value, and the minimum turbulence blade angle are calculated to adjust the generator power, rotor speed, and blade angle of the wind turbine to effectively reduce the load of the unit under extreme turbulence conditions. The details are as follows:

[0098] a. Calculate the turbulence power reduction coefficient based on the turbulence intensity characteristic and the filtered average wind speed. Multiply the generator rated output power by the turbulence power reduction coefficient as the turbulence maximum power setting value.

[0099] The value of the turbulence power reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulence power reduction coefficient by looking up the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0100]

[0101] In the above formula, μ p represents the turbulence power reduction coefficient; I e Represents the characteristic quantity of turbulence intensity; v represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_P e Represents the two-dimensional lookup table function of the turbulence power reduction coefficient;

[0102] The turbulence maximum power setting is defined as follows:

[0103] P Max =μ p ·P Rated

[0104] In the above formula, P Max Indicates the maximum turbulence power setting value; P Rated Indicates the rated output power of the generator;

[0105] The turbulence maximum power setting value is used as the upper limit of the power setting value in the controller. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to drop to the turbulence maximum power setting value.

[0106] b. Calculate the turbulence speed reduction coefficient based on the turbulence intensity characteristic and the filtered average wind speed, and multiply the rated speed of the wind rotor by the turbulence speed reduction coefficient as the turbulence maximum speed setting value;

[0107] The value of the turbulence speed reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional table lookup function is set to obtain the turbulence speed reduction coefficient by looking up the table based on the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0108]

[0109] In the above formula, μ ω I represents the turbulence reduction coefficient; e Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_ω r Represents the two-dimensional lookup table function of the turbulence speed reduction coefficient;

[0110] The turbulent maximum speed setting value is defined as follows:

[0111] ω Max =μ ω ·ω Rated

[0112] In the above formula, ω Max Indicates the maximum turbulent speed setting value; ω Rated Indicates the rated speed of the wind wheel;

[0113] The maximum turbulence speed setting value is used as the upper limit of the wind wheel speed setting value in the controller. When the wind wheel speed exceeds the maximum turbulence speed setting value, the wind wheel speed is controlled to drop to the maximum turbulence speed setting value.

[0114] c. Calculate the minimum turbulent blade angle based on the turbulence intensity characteristic and the filtered average wind speed;

[0115] The value of the turbulent minimum blade angle is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulent minimum blade angle through the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows:

[0116]

[0117] In the above formula, β Min Indicates the minimum blade angle for turbulence; Ie Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_β represents the two-dimensional lookup table function of the minimum blade angle for turbulence;

[0118] The turbulence minimum blade angle is used as the lower limit of the pitch angle command in the controller. When the pitch angle command is less than the turbulence minimum blade angle, the limited pitch angle command is not lower than the turbulence minimum blade angle.

[0119] Example 2

[0120] This embodiment discloses a turbulence intensity identification and load reduction control system for a wind turbine generator set, which is used to implement the turbulence intensity identification and load reduction control method for a wind turbine generator set described in Example 1. Figure 1 As shown, the system includes the following functional modules:

[0121] The turbulence intensity identification module is used to collect the front and rear acceleration of the wind turbine nacelle, the rotor speed and the pitch rate, and process the data to obtain the standard deviation of the front and rear acceleration of the nacelle, the standard deviation of the rotor speed and the standard deviation of the pitch rate. After performing weighted summation calculation, it outputs the current turbulence intensity characteristic value;

[0122] The turbulence load reduction control module is used to calculate the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle according to the turbulence intensity characteristic quantity and the filtered average wind speed; the turbulence maximum power setting value is used as the upper limit of the power setting value in the controller of the wind turbine set. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to be reduced to the turbulence maximum power setting value; the turbulence maximum speed setting value is used as the upper limit of the rotor speed setting value in the controller of the wind turbine set. When the rotor speed exceeds the turbulence maximum speed setting value, the rotor speed is controlled to be reduced to the turbulence maximum speed setting value; the turbulence minimum blade angle is used as the lower limit of the pitch angle instruction in the controller of the wind turbine set. When the pitch angle instruction is less than the turbulence minimum blade angle, the pitch angle instruction is limited to not less than the turbulence minimum blade angle; finally, by adjusting the generator power, rotor speed and blade angle of the wind turbine set, the load of the unit under extreme turbulence conditions is effectively reduced.

[0123] Example 3

[0124] This embodiment discloses a storage medium storing a program. When the program is executed by a processor, the method for identifying turbulence intensity and controlling load reduction of a wind turbine generator set described in Embodiment 1 is implemented.

[0125] The storage medium in this embodiment can be a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), a USB flash drive, a mobile hard disk, or the like.

[0126] Example 4

[0127] This embodiment discloses a computing device, including a processor and a memory for storing a program executable by the processor. When the processor executes the program stored in the memory, the turbulence intensity identification and load reduction control method for the wind turbine generator described in Example 1 is implemented.

[0128] The computing device described in this embodiment may be a desktop computer, a laptop computer, a smart phone, a PDA handheld terminal, a tablet computer, a programmable logic controller (PLC), or other terminal devices with a processor function.

[0129] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for identifying turbulence intensity and controlling load reduction of a wind turbine generator system, characterized in that: Do the following: The wind turbine's nacelle acceleration, rotor speed, and pitch rate are collected and processed to obtain the standard deviation of the nacelle acceleration, rotor speed, and pitch rate. After weighted summation, the current turbulence intensity characteristic is output. According to the turbulence intensity characteristic quantity and the average wind speed after filtering, the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle are calculated; the turbulence maximum power setting value is used as the upper limit of the power setting value in the controller of the wind turbine set. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to be reduced to the turbulence maximum power setting value; the turbulence maximum speed setting value is used as the upper limit of the rotor speed setting value in the controller of the wind turbine set. When the rotor speed exceeds the turbulence maximum speed setting value, the rotor speed is controlled to be reduced to the turbulence maximum speed setting value; the turbulence minimum blade angle is used as the lower limit of the pitch angle instruction in the controller of the wind turbine set. When the pitch angle instruction is less than the turbulence minimum blade angle, the pitch angle instruction is limited to not less than the turbulence minimum blade angle; finally, by adjusting the generator power, rotor speed and blade angle of the wind turbine set, the load of the unit under extreme turbulence conditions is effectively reduced; The obtained standard deviations of the front and rear accelerations of the nacelle, the rotor speed, and the pitch rate are weighted and summed to obtain the current turbulence intensity characteristic, as follows: The standard deviation of the acceleration before and after the nacelle, the standard deviation of the wind rotor speed, and the standard deviation of the pitch rate all reflect the turbulence intensity. Therefore, a weighted sum method is used to obtain a comprehensive turbulence intensity index, namely the turbulence intensity characteristic quantity. The turbulence intensity characteristic quantity is defined and calculated as follows: I e =A fa ·s fa +B r ·e r +C β ·t β In the above formula, I e Represents the characteristic quantity of turbulence intensity; A fa represents the weighting coefficient of the standard deviation of acceleration before and after the cabin; σ fa represents the standard deviation of acceleration before and after the cabin; B r represents the weighting coefficient of the standard deviation of the wind rotor speed; ε r Indicates the standard deviation of the wind wheel speed; C β represents the weighting coefficient of the pitch rate standard deviation; τ β Indicates the standard deviation of the pitch rate.

2. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, characterized in that: The front and rear accelerations of the wind turbine nacelle are collected and processed to obtain the standard deviation of the front and rear accelerations of the nacelle, as follows: Measuring the front-to-back acceleration of the nacelle of the wind turbine using an acceleration sensor installed on the nacelle platform of the wind turbine. The acceleration sensor can measure the front-to-back acceleration of the nacelle platform in real time, i.e., the front-to-back acceleration of the nacelle; The cabin fore-and-aft acceleration measured by the acceleration sensor contains signals of various frequencies. Only the low-frequency portion of the cabin fore-and-aft acceleration can be used as an effective signal for turbulence identification. Therefore, the cabin fore-and-aft acceleration needs to be filtered to remove high-frequency harmonic noise and the characteristic frequency of the drive train. This is used to define the effective cabin fore-and-aft acceleration. The specific formula is as follows: In the above formula, Indicates the effective front and rear acceleration of the cabin; F fa (s) represents the effective front and rear acceleration filter of the cabin, which contains a low-pass filter and a band-stop filter; represents the acceleration measurement of the front and rear of the cabin; The effective fore-aft acceleration of the cabin is stored in a queue storage mode with first-in and last-out. The length of the storage array is set to N, and the stored data is the effective fore-aft acceleration of the cabin from the current moment to the previous N moments. The standard deviation of the fore-aft acceleration of the cabin is obtained by calculating the standard deviation. The standard deviation of the fore-aft acceleration of the cabin reflects the current turbulence intensity. A larger standard deviation corresponds to a greater turbulence intensity. The calculation formula for the standard deviation of the fore-aft acceleration of the cabin is as follows: In the above formula, σ fa represents the standard deviation of acceleration fore and aft of the cabin; represents the effective fore-aft acceleration of the cabin at time 1; represents the effective fore-aft acceleration of the cabin at time 2; represents the effective fore-aft acceleration of the nacelle at time N.

3. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, characterized in that: The rotor speed of the wind turbine is collected and processed to obtain the standard deviation of the rotor speed, as follows: The speed sensor is installed on the inner slip ring of the hub of the wind turbine and can measure the rotation speed of the wind turbine rotor in real time. The rotor speed measured by the speed sensor contains signals of various frequencies. Only the low-frequency part of the rotor speed can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the rotor speed data to remove high-frequency harmonic noise and the characteristic frequency of the transmission chain and define the effective rotor speed. The specific formula is as follows: In the above formula, Indicates the effective speed of the wind rotor; H(s) indicates the effective speed filter of the wind rotor, which contains a low-pass filter and a band-stop filter; Indicates the measured value of the wind wheel speed; The effective speed of the wind rotor is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective speed of the wind rotor from the current moment to the previous N moments. The standard deviation of the wind rotor speed is obtained by calculating the standard deviation. The standard deviation of the wind rotor speed reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the standard deviation of the wind rotor speed is as follows: In the above formula, ε r Indicates the standard deviation of the wind wheel speed; represents the effective speed of the wind wheel at time 1; represents the effective speed of the wind wheel at time 2; Represents the effective speed of the wind rotor at time N; ω0 represents the rated wind rotor speed.

4. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, wherein: The pitch rate of the wind turbine is collected and the data is processed to obtain the standard deviation of the pitch rate, as follows: The pitch rate of the wind turbine is measured by a pitch encoder sensor, which is installed on the pitch bearing ring of the wind turbine. The pitch encoder sensor can measure the rotation speed of the wind turbine blades in real time, that is, the pitch rate; The pitch rate measured by the pitch encoder sensor contains signals of various frequencies. Only the low-frequency part of the pitch rate can be used as an effective signal for turbulence identification. Therefore, it is necessary to filter the pitch rate data to remove high-frequency harmonic noise and the characteristic frequency of the transmission chain and define the effective pitch rate. The specific formula is as follows: In the above formula, represents the effective pitch rate; U(s) represents the effective pitch rate filter; represents the average of the measured pitch rates of the first, second, and third blades; The effective pitch rate data is stored in a queue storage mode with the first input and the last output. The length of the storage array is set to N, and the stored data is the effective pitch rate from the current moment to the previous N moments. The pitch rate standard deviation is obtained by calculating the standard deviation. The pitch rate standard deviation reflects the current turbulence intensity. The larger the standard deviation, the greater the turbulence intensity. The calculation formula of the pitch rate standard deviation is as follows: In the above formula, τ β represents the standard deviation of pitch rate; represents the effective pitch rate at time 1; represents the effective pitch rate at time 2; represents the effective pitch rate at time N.

5. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, characterized in that: The turbulence power reduction coefficient is calculated based on the turbulence intensity characteristic and the filtered average wind speed. The rated output power of the generator is multiplied by the turbulence power reduction coefficient to obtain the turbulence maximum power setting value. The value of the turbulence power reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulence power reduction coefficient by looking up the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows: In the above formula, μ p represents the turbulence power reduction coefficient; I e Indicates the characteristic quantity of turbulence intensity; Indicates the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_P e Represents the two-dimensional lookup table function of the turbulence power reduction coefficient; The turbulence maximum power setting is defined as follows: P Max =μ p ·P Rated In the above formula, P Max Indicates the maximum turbulence power setting value; P Rated Indicates the rated output power of the generator.

6. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, characterized in that: The turbulence speed reduction coefficient is calculated based on the turbulence intensity characteristic and the filtered average wind speed. The rated speed of the wind rotor is multiplied by the turbulence speed reduction coefficient as the turbulence maximum speed setting value. The value of the turbulence speed reduction coefficient is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional table lookup function is set to obtain the turbulence speed reduction coefficient by looking up the table based on the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows: In the above formula, μ ω I represents the turbulence reduction coefficient; e Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_ω r Represents the two-dimensional lookup table function of the turbulence speed reduction coefficient; The turbulent maximum speed setting value is defined as follows: oh Max =μ ω ·oh Rated In the above formula, ω Max Indicates the maximum turbulent speed setting value; ω Rated Indicates the rated speed of the wind wheel.

7. The method for identifying turbulence intensity and controlling load reduction of a wind turbine according to claim 1, characterized in that: The minimum turbulent blade angle is calculated based on the turbulence intensity characteristic and the filtered average wind speed; The value of the turbulent minimum blade angle is not only related to the turbulence intensity characteristic quantity, but also to the average wind speed after filtering. Therefore, a two-dimensional lookup table function is set to obtain the turbulent minimum blade angle through the turbulence intensity characteristic quantity and the average wind speed after filtering. The specific formula is as follows: In the above formula, β Min Indicates the minimum blade angle for turbulence; I e Indicates the characteristic quantity of turbulence intensity; Represents the average wind speed after filtering, which is the wind speed measured in the cabin after low-pass filtering; Lookup_β represents the two-dimensional lookup function of the minimum blade angle for turbulence.

8. A turbulence intensity identification and load reduction control system for a wind turbine, characterized in that: A method for identifying turbulence intensity and controlling load reduction of a wind turbine generator system according to any one of claims 1 to 7, comprising: The turbulence intensity identification module is used to collect the front and rear acceleration of the wind turbine nacelle, the rotor speed and the pitch rate, and process the data to obtain the standard deviation of the front and rear acceleration of the nacelle, the standard deviation of the rotor speed and the standard deviation of the pitch rate. After performing weighted summation calculation, it outputs the current turbulence intensity characteristic value; The turbulence load reduction control module is used to calculate the turbulence maximum power setting value, the turbulence maximum speed setting value and the turbulence minimum blade angle according to the turbulence intensity characteristic quantity and the filtered average wind speed; the turbulence maximum power setting value is used as the upper limit of the power setting value in the controller of the wind turbine set. When the generator power exceeds the turbulence maximum power setting value, the generator power is controlled to be reduced to the turbulence maximum power setting value; the turbulence maximum speed setting value is used as the upper limit of the rotor speed setting value in the controller of the wind turbine set. When the rotor speed exceeds the turbulence maximum speed setting value, the rotor speed is controlled to be reduced to the turbulence maximum speed setting value; the turbulence minimum blade angle is used as the lower limit of the pitch angle instruction in the controller of the wind turbine set. When the pitch angle instruction is less than the turbulence minimum blade angle, the pitch angle instruction is limited to not less than the turbulence minimum blade angle; finally, by adjusting the generator power, rotor speed and blade angle of the wind turbine set, the load of the unit under extreme turbulence conditions is effectively reduced.

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