Wind turbine generator refined interface simulation method and system, terminal and medium

Abstract

The invention provides a wind turbine generator refined interface simulation method and system, a terminal and a medium, and the method comprises the steps: S1, carrying out the frequency sweeping of a plurality of preset frequency bands at an interface of a wind turbine subsystem, collecting a steady-state response value of a shaft system rotating speed, and obtaining response characteristic data; s2, obtaining a frequency response characteristic function of the wind turbine subsystem at the interface according to the response characteristic data, and processing the frequency response characteristic function to obtain a frequency response characteristic model; s3, at the wind turbine subsystem step time, based on the shafting rotating speed and the electromagnetic torque, in combination with the frequency response characteristic model, calculating a frequency variable of excitation to the shafting rotating speed, and obtaining an internal equivalent rotating speed as an interface variable of the electrical subsystem; and S4, the electrical subsystem receives the internal equivalent rotating speed, and calculates and obtains refined shafting rotating speed data in each step length moment of the electrical subsystem. The problem that the shafting rotating speed expected to be received by the electrical subsystem is obviously different from the actually received shafting rotating speed is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and particularly relates to a refined interface simulation method, system, terminal and medium for a wind turbine generator set. Background Art

[0002] A wind turbine generator set is a multi-coupled complex dynamic system including fast and slow time scales. Among them, the pneumatic system and the wind turbine subsystem mainly focus on the low-frequency vibration (usually in the range of 0-50 Hz) caused by uneven inflow wind and the low-speed rotation of wind mechanical components. Its typical simulation step size is in the millisecond level. The electrical system involves the broadband characteristics caused by power electronic devices, and the frequency range can reach from zero to thousands of Hz. Its typical simulation step size is in the microsecond level. In the prior art, to solve the above problems, a multi-rate interface scheme based on zero-order hold is adopted, that is, at the interface, the two subsystems respectively sample the data at the interface based on their own simulation step sizes with zero-order hold. As Figure 1 shown, the School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University designed a set of real-time wind turbine generator set co-simulation platform based on RTDS and Bladed: among them, the wind model, pneumatic model, mechanical part model, pitch system model and yaw system model are established in Bladed, and the electrical part model and control system model of the wind turbine generator set are established in RTDS, and the communication between Bladed and RTDS is realized with the help of PLC.

[0003] However, there is a significant drawback in the above prior art solution: when the wind turbine subsystem outputs the shaft system speed according to its own large simulation step size, and the electrical subsystem samples the shaft system speed according to its own small simulation step size, the electrical subsystem obtains the same data in hundreds of samplings, resulting in a significant decrease in simulation accuracy. Especially when the system fails, the shaft system speed of the generator will oscillate significantly in a short time. There is a significant difference between the shaft system speed expected to be received by the electrical subsystem and the actually received shaft system speed, and the system cannot fully capture the dynamic changes of the speed, ultimately leading to a decrease in the accuracy of the simulation results of the refined platform of the wind turbine generator set. Summary of the Invention

[0004] Aiming at the problems in the prior art, the present invention provides a refined interface simulation method, system, terminal and medium for a wind turbine generator set, which solves the problem that there is a significant difference between the shaft system speed expected to be received by the electrical subsystem and the actually received shaft system speed in the prior art, and the system cannot fully capture the dynamic changes of the speed, ultimately leading to a decrease in the accuracy of the simulation results of the refined platform of the wind turbine generator set.

[0005] The technical solution adopted by the present invention is as follows: In the first aspect, the present application provides a refined interface simulation method for a wind turbine generator set, including the following steps: Step S1: At the interface of the wind turbine subsystem of the wind turbine generator set, by performing frequency sweeping on the wind turbine subsystem in a number of preset frequency bands, collect the steady-state response values of the shaft speed to the electromagnetic torque excitation at each frequency, and obtain a set of discrete frequency response characteristic data; Step S2: According to the discrete frequency response characteristic data, use the vector fitting method to obtain the frequency response characteristic function of the wind turbine subsystem at the interface, perform matrix contraction processing on the frequency response characteristic function, retain the mapping relationship between the electromagnetic torque and the shaft speed, and obtain the frequency response characteristic model of the wind turbine subsystem; Step S3: At each step of the wind turbine subsystem, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem, combined with the frequency response characteristic model, calculate the frequency variables of the shaft speed caused by other excitations except the interface electromagnetic torque, and obtain the internal equivalent speed as the interface variable output from the wind turbine subsystem side to the electrical subsystem; Step S4: After receiving the internal equivalent speed, at each step of the electrical subsystem, according to the electromagnetic torque at the current simulation time and the frequency response characteristic model, calculate the shaft speed to obtain the refined shaft speed data of the electrical subsystem step;

[0006] Preferably, Step S1 includes the following steps: Step S1-1: Select the frequency range and sampling points; Step S1-2: Determine the amplitude of the frequency sweep excitation; Step S1-3: Inject frequency sweep excitations of different frequencies in sequence at the system interface according to the selected parameters, and measure the steady-state speed response output of the system under each excitation to obtain a set of discrete frequency response characteristic data.

[0007] Preferably, in Step S1-3, the frequency sweep excitation is a standard sine signal, and calculate the sampling value of the interface frequency response characteristic function at the frequency of the frequency sweep excitation:

[0008] where, is a complex function with the independent variable ; j is the imaginary unit; is the frequency of the frequency sweep excitation; and respectively represent the amplitudes of the steady-state speed response sine signal and the frequency sweep excitation sine signal output; and respectively represent the phase angles of the steady-state speed response sine signal and the frequency sweep excitation sine signal output.

[0009] Preferably, in Step S2, calculate the frequency response characteristic function at the interface:

[0010] Wherein: is the frequency response characteristic function the number of poles; , are respectively the th pole of and the residue corresponding to this pole; is the constant term; is a special case on the imaginary axis, that is .

[0011] Preferably, the frequency range of the electromagnetic torque excitation for the preset frequency band sweeping in the step S1 is 0 Hz to 50 Hz.

[0012] Preferably, the frequency interval of the electromagnetic torque excitation is 0.05 Hz, and 1000 frequency points are sampled in total for the discrete frequency response characteristic data in the range of 0 Hz to 50 Hz.

[0013] Preferably, the calculation method of the shaft system speed in the step S4 is to solve by time domain differentiation or convolution operation of the frequency response characteristic function.

[0014] In a second aspect, the present application provides a refined interface simulation system for a wind turbine, including: a frequency response acquisition module, configured to apply an electromagnetic torque excitation with a preset frequency at the interface between the wind turbine subsystem and the electrical subsystem of the wind turbine, collect the steady-state response of the shaft system speed under each frequency excitation, and obtain discrete frequency response characteristic data; a frequency response modeling module, configured to construct a frequency response characteristic function by using a vector fitting method based on the discrete frequency response characteristic data, and retain the mapping relationship between the electromagnetic torque and the shaft system speed through a matrix contraction technique to obtain a frequency response characteristic model of the wind turbine subsystem; an equivalent speed calculation module, configured to calculate the frequency variable of other excitations on the shaft system speed except the electromagnetic torque based on the frequency response characteristic model, the current shaft system speed, and the electromagnetic torque at each step simulation moment of the wind turbine subsystem, generate an internal equivalent speed, and transmit it as an interface output variable to the electrical subsystem; a speed estimation module, configured to receive the internal equivalent speed and the electromagnetic torque at the current electrical subsystem step moment during the step simulation process of the electrical subsystem, and gradually estimate the current shaft system speed in combination with the frequency response characteristic model to obtain the shaft system speed data for refined electrical subsystem step update.

[0015] In a third aspect, the present application provides a terminal, including: A memory for storing a refined interface simulation program for a wind turbine generator set; A processor for implementing the steps of the wind turbine generator set refined interface simulation method as described in the first aspect when executing the wind turbine generator set refined interface simulation system.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium. The storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a wind turbine generator set refined interface simulation method as described in the first aspect.

[0017] It can be seen from the above technical solutions that the present application has the following advantages: 1. It realizes high-precision interface coupling modeling for multi-rate co-simulation between the mechanical and electrical subsystems of a wind turbine generator set, and can improve the overall simulation accuracy of the system while maintaining the original simulation step size of the subsystems.

[0018] 2. By obtaining frequency response data through a sweep frequency experiment and constructing an interface frequency response characteristic function, it can effectively reflect the response characteristics of the wind turbine subsystem to electromagnetic excitations of different frequencies, making up for the problem of insufficient capture of the dynamic process in the traditional zero-order hold method.

[0019] 3. Using the vector fitting method to convert discrete frequency domain data into a continuous function improves the fitting accuracy of the frequency response modeling and is convenient for subsequent dynamic estimation in the time domain simulation process.

[0020] 4. By introducing the concept of "internal equivalent rotational speed" and the frequency domain backstepping mechanism, it realizes the accurate expression of the influence of non-interface excitations under the condition of only retaining the interface frequency response function, effectively reducing the modeling complexity.

[0021] 5. By using the method of calculating the shaft system rotational speed step by step within a small step size, it improves the ability of the electrical subsystem to capture the mechanical response under high-speed changing signals (such as fault disturbances), and improves the dynamic response performance of the simulation system.

[0022] 6. The electromagnetic torque excitation frequency range is set to 0 Hz - 50 Hz, with an interval of 0.05 Hz, and a total of 1000 points are sampled, ensuring coverage of the typical low-frequency vibration range of the wind turbine generator set and guaranteeing the breadth and analytical accuracy of the frequency response function.

[0023] 7. The proposed interface modeling method can adapt to different types of mechanical structures, has strong versatility, and is suitable for the integrated deployment of various wind power simulation platforms and control algorithms.

[0024] 8. Through system modular design, decoupled configuration of each functional module such as frequency response acquisition, modeling, equivalent rotational speed calculation, and rotational speed estimation is realized, which is convenient for embedding into existing wind power simulation software or control systems, improving engineering adaptability and deployment efficiency. Brief Description of the Drawings

[0025] In order to more clearly illustrate the technical solutions of the present application, the accompanying drawings required in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0026] Figure 1 is the design flow chart of the co-simulation platform in the prior art; Figure 2 is the schematic diagram of the subsystem structures of the refined interface simulation method for wind turbine units shown in some embodiments; Figure 3 is the model diagram of the frequency response characteristic of the wind turbine subsystem interface of the refined interface simulation method for wind turbine units shown in some embodiments; Figure 4 is the flow chart of the multi-rate data interaction scheme based on the frequency response characteristic of the refined interface simulation method for wind turbine units shown in some embodiments. Detailed Embodiments

[0027] In order to make the application purpose, features, and advantages of the present application more obvious and understandable, the technical solutions protected by the present application will be clearly and completely described below by using specific embodiments and the accompanying drawings. Obviously, the embodiments described below are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in this patent, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this patent.

[0028] Wind power plays an indispensable role in China's low-carbon energy system. In order to reduce the levelized cost of electricity, wind turbine units are gradually developing towards large-scale, with the single-unit capacity continuously increasing. While the power generation of large-capacity units increases, their geometric dimensions also increase significantly (i.e., longer blades and higher towers), resulting in a greater amplitude of power fluctuations in the wind turbines and greater bending moments and fatigue damage on the internal mechanical components.

[0029] Under normal circumstances, the refined model of a wind turbine can be divided into: an aerodynamic dynamic model, a mechanical dynamic model, and an electromagnetic transient model. Among them, the aerodynamic dynamic model and the mechanical dynamic model belong to the wind turbine subsystem. The aerodynamic dynamic model mainly focuses on aerodynamic torque calculation, three-dimensional inflow wind dynamics, etc.; the mechanical dynamic model describes the non-torsional dynamics of the mechanical components such as the blades, tower, and nacelle of the unit and the torsional dynamics of the shafting; the electrical subsystem model describes the electromagnetic transient characteristics of the generator, converter, transformer, filter, and collector network of the unit. The interface technology between different simulation rate models will significantly affect the accuracy of the multi-rate simulation system, and a high-precision interface model needs to be established to improve the simulation accuracy.

[0030] A wind turbine is a multi-coupled complex dynamic system containing fast and slow time scales. Among them, the aerodynamic system and the wind turbine subsystem mainly focus on the low-frequency vibrations (usually in the range of 0 - 50 Hz) caused by the uneven inflow wind and the low-speed rotation of the wind mechanical components. Its typical simulation step size is in the millisecond level, while the electrical system involves the broadband characteristics caused by power electronic devices, and the frequency range can reach from zero to several thousand Hz. Its typical simulation step size is in the microsecond level. In the existing technology, a multi-rate interface scheme based on zero-order hold is adopted to solve the above problems, that is, at the interface, the two subsystems respectively sample the data at the interface based on their own simulation step sizes with zero-order hold. As Figure 1 shown, the School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University designed a real-time wind turbine co-simulation platform based on RTDS and Bladed: among them, the wind model, aerodynamic model, mechanical part model, pitch system model, and yaw system model are established in Bladed, the electrical part model and control system model of the wind turbine are established in RTDS, and the communication between Bladed and RTDS is realized with the help of PLC.

[0031] However, there is a significant drawback in the above existing technical solutions: during the process that the wind turbine subsystem outputs the shaft speed according to its own large simulation step size and the electrical subsystem samples the shaft speed according to its own small simulation step size, the electrical subsystem obtains the same data in hundreds of samplings, resulting in a significant decrease in simulation accuracy. Especially when a fault occurs in the system, the shaft speed of the generator will oscillate significantly in a short time. There is a significant difference between the shaft speed that the electrical subsystem expects to receive and the actual received shaft speed, and the system cannot fully capture the dynamic changes of the speed, ultimately leading to a decrease in the accuracy of the simulation results of the refined wind turbine platform.

[0032] The present invention aims at the problems in the existing technology and provides a refined interface simulation method, system, terminal, and medium for a wind turbine, which solves the problem that there is a significant difference between the shaft speed that the electrical subsystem in the existing technology expects to receive and the actual received shaft speed, and the system cannot fully capture the dynamic changes of the speed, ultimately leading to a decrease in the accuracy of the simulation results of the refined wind turbine platform.

[0033] This application provides a refined interface simulation method for a wind turbine generator set, including: Step S1: At the interface of the wind turbine subsystem of the wind turbine generator set, by performing frequency sweeping on the wind turbine subsystem in a number of preset frequency bands, collecting the steady-state response values of the shaft speed to the electromagnetic torque excitation at each frequency, and obtaining a set of discrete frequency response characteristic data; Step S2: According to the discrete frequency response characteristic data, using the vector fitting method to obtain the frequency response characteristic function of the wind turbine subsystem at the interface, performing matrix contraction processing on the frequency response characteristic function, retaining the mapping relationship between the electromagnetic torque and the shaft speed, and obtaining the frequency response characteristic model of the wind turbine subsystem; Step S3: At each time step of the wind turbine subsystem, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem, combined with the frequency response characteristic model, calculating the frequency variables of the shaft speed caused by other excitations except the interface electromagnetic torque, obtaining the internal equivalent speed and using it as the interface variable output from the wind turbine subsystem side to the electrical subsystem; Step S4: After receiving the internal equivalent speed, at each time step of the electrical subsystem, according to the electromagnetic torque at the current simulation time and the frequency response characteristic model, calculating the shaft speed to obtain the refined shaft speed data of the electrical subsystem at each time step.

[0034] In some embodiments, Step S1 includes the following steps: Step S1-1: Select the frequency range and sampling points; Step S1-2: Determine the amplitude of the frequency-sweeping excitation; Step S1-3: Inject frequency-sweeping excitations with different frequencies in sequence at the system interface according to the selected parameters, and measure the steady-state speed response output of the system under each excitation to obtain a set of discrete frequency response characteristic data.

[0035] Under the influence of external excitations with different frequencies, the wind turbine subsystem will exhibit different response characteristics. The frequency response characteristic modeling of the wind turbine subsystem is to extract the correlation between the response characteristics of the wind turbine subsystem and the excitation frequency, map the time-domain dynamic response to the frequency domain, and establish an equivalent model of the wind turbine subsystem. This equivalent model will be used to predict and estimate the shaft speed output value of the wind turbine subsystem at the mechanical-electrical multi-rate simulation interface. This patent first analyzes the frequency response characteristics of the wind turbine subsystem under the action of external excitations with different frequencies based on the dynamic equation of the wind turbine subsystem, and gives the concept of the frequency response characteristic matrix.

[0036] The dynamic equations of each sub-component (blade, tower, rotor, nacelle) of the wind turbine subsystem of the wind turbine generator set can be coupled to form the dynamic equation of the overall system as:

[0037] Among them, is the total mass matrix, which is jointly composed of the masses of each component; is the total damping matrix, including air damping and structural damping; is the total stiffness matrix; is the deformation or motion displacement of the component; is the first derivative of, that is, the deformation or motion displacement velocity of the component; is the second derivative of, that is, the deformation or motion displacement acceleration of the component; is the total external force acting on the system, including aerodynamic force, gravity, torque, etc. , , The three matrices have the same dimension. The number of rows is equal to the number of external excitations, and the number of columns is equal to the number of mechanical components. Considering that the wind turbine subsystem itself is a non-linear system, therefore, the values of the elements inside the matrices , , will change with the different system states.

[0038] Since the interface model established in this patent mainly focuses on the speed response of each component of the wind turbine subsystem, the above formula is rewritten as:

[0039] Among them, represents the deformation speed or motion speed of the component, which is equal to the first derivative with respect to time. It should be emphasized that is a vector, including the speeds of each component inside the wind turbine subsystem such as shaft system rotation speed, nacelle swing speed, etc.; is also a vector, including all external excitations of the wind turbine subsystem such as electromagnetic torque, aerodynamic torque, etc.

[0040] Analyze the frequency response characteristics of the wind turbine subsystem, that is, the relationship between the steady-state output and input of the system under the excitation of a certain frequency. Considering that the simulation step size is small and the system state changes are also small within each step size range, therefore, the changes of the matrices , , can be ignored. When the wind turbine subsystem is set as a linear system and the external excitations are all standard sine signals, the speed response of the wind turbine subsystem will also be a standard sine signal with the same frequency as the excitation. Given the external excitation as , and the speed response of the wind turbine subsystem under this excitation is set as , where A and B are the excitation and the response Amplitude; α and β are the initial phase angles of the excitation and the response respectively; is the frequency; The vector composed of sinusoidal quantities is rewritten in the phasor representation as:

[0041]

[0042] Among them, represents the phasor vector of; represents the phasor vector of; Substituting both into we can get:

[0043] Only keep on the left side of the equation, and further organize the above formula as:

[0044]

[0045] It can be seen that for the external excitation and speed response of a single frequency, the frequency response characteristics of the wind turbine subsystem are represented by the matrix composed of the mass matrix , the damping matrix and the stiffness matrix together; is a complex matrix, The amplitude of represents the ratio of the speed response to the amplitude of the external excitation, and the phase angle represents the phase by which the speed response leads the external excitation.

[0046] When the external excitation is a complex signal of any form, its continuous frequency spectrum distribution is obtained through Fourier transform:

[0047] Among them, is the complex exponential function, and through this integral operation, the representation of the signal in the frequency domain can be obtained ; is a complex function vector related to the frequency, The amplitude of represents the intensity of the component with frequency in the signal, and the phase represents the phase shift of the component with frequency in the signal.

[0048] After obtaining the spectral distribution of the excitation signal, the frequency response characteristics of the system can be further analyzed based on the superposition principle. According to the superposition principle: the total speed response of the system is equal to the superposition of the responses when each frequency component acts alone. And for each frequency component in the excitation and its response, they all satisfy Therefore, the total speed response of the system and the excitation will also satisfy . Denote the spectral distribution of the total speed response of the system as , then there is:

[0049] It can be seen that although the frequency response characteristic matrix is for a single harmonic excitation, under the input of any complex signal, the frequency response characteristics of the wind turbine subsystem can still be represented by the frequency response characteristic matrix . It should be emphasized that the frequency response characteristic matrix is a matrix related to frequency, and its values at different frequencies characterize the frequency response characteristics of the wind turbine subsystem at different frequencies. As the complexity of the wind turbine subsystem increases, the dimension of the frequency response characteristic matrix will gradually increase.

[0050] The wind turbine subsystem of the fan contains several components, and it is difficult to directly calculate the analytical expression of the interface frequency response characteristic function by the above theoretical analysis plus matrix contraction method. From the previous analysis of frequency response, the amplitude of the frequency response characteristic function is equal to the ratio of the amplitudes of the response and the excitation at the same frequency, and the phase angle is equal to the phase by which the response at the same frequency leads the excitation. Therefore, the interface frequency response characteristic function of the wind turbine subsystem can be identified by a method similar to frequency scanning and vector fitting in the power system. This section first introduces the precautions and steps for frequency scanning of the wind turbine subsystem of the wind turbine, and then gives the basic idea of vector fitting and the fitting results.

[0051] Frequency scanning aims to extract the frequency response characteristics of the system. Its basic idea is to inject electromagnetic torque excitations with different frequencies into the wind turbine subsystem in turn, and obtain the shaft speed response of the system under each frequency excitation, so as to obtain the sampling values of the interface frequency response characteristic function of the wind turbine subsystem at different frequencies. In some embodiments, the designed frequency scanning scheme can be divided into the following 3 steps: First, select the frequency range and sampling points, that is, determine at which frequency points to perform frequency sweeping. The vibration frequency of the wind turbine subsystem generally does not exceed 50 Hz, so selecting the frequency range of 0 - 50 Hz can cover most of the frequency characteristics of the wind turbine subsystem. At the same time, in order to ensure the accuracy of the simulation results, it is necessary to obtain sufficient sampling values of the function of the wind turbine subsystem. In some embodiments, select equidistantly at intervals of 0.05 Hz within the above frequency range sampling points. For the frequency range of 0 - 50 Hz, there are = 1000 sampling points.

[0052] Secondly, determine the amplitude of the swept - frequency excitation. The amplitude of the swept - frequency excitation should not be too large, as being too large may change the original linear characteristics of the system; nor should it be too small, as being too small may be affected by system noise interference, thus affecting the accuracy of the results. Generally, 1% - 10% of the value when the variable is working properly can be selected as the amplitude of the swept - frequency excitation. In some embodiments, it is taken as 5%.

[0053] Finally, inject swept - frequency excitations of different frequencies into the system interface in sequence according to the selected parameters, and measure the steady - state rotational speed response output of the system under each excitation. Since the injected electromagnetic torque excitation is a standard sine signal, the obtained rotational speed response is basically a sine signal with the same frequency as the excitation. At this time, the sampling value of the interface frequency response characteristic function at this frequency can be calculated by the following formula:

[0054] where, and respectively represent the amplitudes of the steady - state rotational speed response sine signal and the swept - frequency excitation sine signal output; and respectively represent the phase angles of the steady - state rotational speed response sine signal and the swept - frequency excitation sine signal output.

[0055] Using The calculated sampling values are all in the form of complex numbers. Its amplitude is the multiple ratio of the rotational speed response to the excitation amplitude, and the phase angle is the angle by which the rotational speed response leads the excitation.

[0056] Based on frequency scanning, a set of discrete sampling values of the interface frequency response characteristic function can be obtained. This set of data is a set of complex number sets with frequency as the independent variable. Further processing of this data is required to obtain a continuous expression form in order to serve system simulation.

[0057] In some embodiments, a continuous transfer function is formed based on the vector fitting of discrete data to represent the interface frequency response characteristic function . The transfer function and the frequency response characteristic function are essentially unified. The frequency response can be regarded as a special case of the transfer function on the imaginary axis, that is, . Vector fitting can find an analytical transfer function , so that its value at is the same as the swept - frequency data Highly consistent. Through this process, the frequency-domain data can be converted into the transfer function of the complex frequency domain, which can be used for time-domain simulation and system analysis.

[0058] Under the vector fitting method, any rational function can be expressed in the following form:

[0059] In the formula: is the transfer function of the boundary frequency characteristic the number of poles; , is the th pole of and the residue corresponding to this pole; is the constant term.

[0060] According to the discrete sampling values at each frequency, the vector fitting method will form a set of transcendental equations and use the least squares method to obtain the unknown parameters in. The vector fitting method is currently relatively mature, and more of its solution processes will not be elaborated in this embodiment.

[0061] Based on the transfer function of to replace , a multi-rate interface model considering the frequency response characteristics of the wind turbine subsystem in the time domain can be constructed.

[0062] In some embodiments, the designed multi-rate data interaction scheme for wind turbines based on frequency response characteristics is as Figure 3 shown. Compared with the traditional data interaction scheme based on the ZOH method, the biggest difference in the scheme proposed in this patent is that the interface frequency response characteristic model of the wind turbine subsystem of the wind turbine (i.e., Figure 3 the part within the light green dashed box in) is applied to the interaction process of the shaft speed. Since there is no problem of insufficient accuracy in the electromagnetic torque interaction process, this patent does not make any modifications to it. Correspondingly, the original data interaction variable of the wind turbine subsystem is changed to the internal equivalent speed , and the original data interaction variable of the electrical subsystem remains the generator electromagnetic torque unchanged.

[0063] Record the initial simulation time as , the simulation step of the wind turbine subsystem is , and the simulation step of the electrical subsystem is . Consistent with the traditional ZOH method, during the simulation, the wind turbine subsystem follows its own simulation step Output and receiving interface variables ensure the efficiency of the simulation. The difference lies in the interaction process of the shaft speed. During this process, when the electrical subsystem obtains the internal equivalent speed with a step size of , at each small time step , based on the latest electromagnetic torque , the shaft speed of the small time step will be accurately estimated. Since this interface introduces the interface frequency response characteristic model of the wind turbine subsystem, the estimated shaft speed will have high accuracy and can effectively achieve high-precision interaction between the mechanical and electrical systems.

[0064] Calculate the internal equivalent speed . The exact calculation formula of has been given in . However, in some embodiments, only the frequency response characteristics of the wind turbine subsystem at the interface are identified, that is, only the interface frequency response characteristic function is obtained. The elements corresponding to other variables in the system frequency response characteristic matrix, such as are not acquired. Therefore, the analytical solution method based on fails. Considering that for the wind turbine subsystem, the shaft speed at each data interaction moment is known. Therefore, based on the shaft speed updated with a large time step and the interface frequency response characteristic function , can be deduced. Its formula in the frequency domain is: ; where is the Fourier transform of the internal equivalent speed; is the Fourier transform of the shaft speed calculated inside the wind turbine subsystem; is the Fourier transform of the electromagnetic torque inside the wind turbine subsystem.

[0065] It should be noted that is updated only once at the data interaction moment with a large time step and is passed to the electrical subsystem as an interaction variable. During the iterative update process of the electrical subsystem according to its own small simulation time step , the value of this variable remains unchanged.

[0066] In some embodiments, the present application provides a refined interface simulation system for a wind turbine, including: A frequency response acquisition module, configured to apply an electromagnetic torque excitation with a preset frequency to the wind turbine subsystem at the interface between the wind turbine subsystem and the electrical subsystem of the wind turbine, collect the steady-state response of the shaft speed under each frequency excitation, and obtain discrete frequency response characteristic data; A frequency response modeling module, configured to construct a frequency response characteristic function by using a vector fitting method based on the discrete frequency response characteristic data, and retain the mapping relationship between the electromagnetic torque and the shaft system speed through a matrix contraction technique, so as to obtain a frequency response characteristic model of the wind turbine subsystem; An equivalent speed calculation module, configured to calculate, at each step simulation moment of the wind turbine subsystem, the frequency variable of the shaft system speed caused by other excitations except the electromagnetic torque based on the frequency response characteristic model, the current shaft system speed, and the electromagnetic torque, generate an internal equivalent speed, and transmit it as an interface output variable to the electrical subsystem; A speed estimation module, configured to receive the internal equivalent speed and the electromagnetic torque at the current electrical subsystem step moment during the step simulation process of the electrical subsystem, and gradually estimate the current shaft system speed in combination with the frequency response characteristic model, so as to obtain the shaft system speed data for refined electrical subsystem step update.

[0067] In some embodiments, the present application provides a terminal, including: A memory, configured to store a refined interface simulation program for a wind turbine generator set; A processor, configured to implement the steps of the refined interface simulation method for a wind turbine generator set as described in the first aspect when executing the refined interface simulation system for a wind turbine generator set.

[0068] In some embodiments, the present application provides a computer-readable storage medium. The storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the refined interface simulation method for a wind turbine generator set.

[0069] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are proposed in this specification, so such modifications, improvements, and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0070] Moreover, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numerical and alphabetical characters, or the use of other names described in this specification are not used to limit the order of the processes and methods of this specification. Although some currently useful embodiments of the invention have been discussed through various examples in the above disclosure, it should be understood that such details are for illustrative purposes only. The appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on existing servers or mobile devices.

[0071] Similarly, it should be noted that, in order to simplify the presentation of the disclosure in this specification and thus help the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of this specification, various features are sometimes grouped into one embodiment, drawing, or description thereof. However, this method of disclosure does not mean that the features required by the subject matter of this specification are more than those mentioned in the claims. In fact, the features of the embodiments are less than all the features of the individual embodiments disclosed above.

[0072] In some embodiments, numbers are used to describe the components and the quantity of attributes. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately", or "substantially" in some examples. Unless otherwise stated, "about", "approximately", or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and such approximate values may vary according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are made as precise as possible within the feasible range.

[0073] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification can be considered to be consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments clearly introduced and described in this specification.

Claims

1. A wind turbine refined interface simulation method, characterized in that: The following steps are involved: Step S1, at the interface of the wind turbine subsystem of the wind turbine generator set, by performing a plurality of preset frequency band sweeps on the wind turbine subsystem, collecting steady-state response values ​​of the shaft speed to electromagnetic torque excitations of each frequency, and obtaining a set of discrete frequency response characteristic data; Step S2, according to the discrete frequency response characteristic data, a vector fitting method is used to obtain a frequency response characteristic function of the wind turbine subsystem at the interface, the frequency response characteristic function is subjected to matrix shrinkage processing, a mapping relationship between the electromagnetic torque and the shaft speed is retained, and a frequency response characteristic model of the wind turbine subsystem is obtained; Step S3, at each wind turbine subsystem step time, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem, combined with the frequency response characteristic model, calculate the frequency variables of the shaft speed due to other excitations except the interface electromagnetic torque, obtain the internal equivalent speed and use it as the interface variable output by the wind turbine subsystem to the electrical subsystem; Step S4: After the electrical subsystem receives the internal equivalent speed, at each step of itself, the shaft speed is calculated according to the electromagnetic torque and frequency response characteristic model at the current simulation moment to obtain refined electrical subsystem step shaft speed data.

2. The wind turbine generator set refined interface simulation method according to claim 1, characterized in that: Step S1 includes the following steps: Step S1-1, selecting a frequency range and sampling points; Step S1-2, determining the amplitude of the swept frequency excitation; Step S1-3: inject frequency sweep excitations of different frequencies in sequence at the system interface according to the selected parameters, and measure the steady-state speed response output of the system under each excitation to obtain a set of discrete frequency response characteristic data.

3. The wind turbine generator set refined interface simulation method according to claim 2, characterized in that: In step S1-3, the frequency sweep excitation is a standard sinusoidal signal, and the sampling value of the interface frequency response characteristic function at the frequency of the frequency sweep excitation is calculated: in, The independent variable is The complex function of ; j is the imaginary unit; is the frequency of the swept frequency excitation; and They represent the amplitudes of the output steady-state speed response sinusoidal signal and the swept-frequency excitation sinusoidal signal respectively; and They respectively represent the phase angles of the output steady-state speed response sinusoidal signal and the swept frequency excitation sinusoidal signal.

4. The wind turbine generator set refined interface simulation method according to claim 3, characterized in that: In step S2, the frequency response characteristic function at the interface is calculated: Where: is the frequency response characteristic function The number of poles; , They are No. A pole and the residue corresponding to the pole; is a constant term; for The special case on the imaginary axis, that is, .

5. The wind turbine generator set refined interface simulation method according to claim 1, characterized in that: The frequency range of the electromagnetic torque excitation of the preset frequency sweep in step S1 is 0 Hz to 50 Hz.

6. The wind turbine generator set refined interface simulation method according to claim 5, characterized in that: The frequency interval of the electromagnetic torque excitation is 0.05 Hz, and the discrete frequency response characteristic data is sampled at 1000 frequency points in the range of 0 Hz to 50 Hz.

7. The wind turbine generator set refined interface simulation method according to claim 1, characterized in that: The shaft system rotation speed is calculated in step S4 by performing a time domain difference solution or a convolution operation on the frequency response characteristic function.

8. A wind turbine refined interface simulation system, characterized in that: include: The frequency response acquisition module is used to apply electromagnetic torque excitation of a preset frequency to the wind turbine subsystem at the interface between the wind turbine subsystem and the electrical subsystem of the wind turbine set, collect the steady-state response of the shaft speed under each frequency excitation, and obtain discrete frequency response characteristic data; A frequency response modeling module is used to construct a frequency response characteristic function based on the discrete frequency response characteristic data by using a vector fitting method, and retain the mapping relationship between the electromagnetic torque and the shaft speed by using a matrix contraction technology to obtain a frequency response characteristic model of the wind turbine subsystem; An equivalent speed calculation module is used to calculate the frequency variables of the shaft speed caused by other excitations other than the electromagnetic torque at each step simulation moment of the wind turbine subsystem based on the frequency response characteristic model and the current shaft speed and electromagnetic torque, generate an internal equivalent speed, and transmit it to the electrical subsystem as an interface output variable; The speed estimation module is used to receive the internal equivalent speed and the electromagnetic torque of the current electrical subsystem step time during the step simulation process of the electrical subsystem, and gradually estimate the current shaft system speed in combination with the frequency response characteristic model to obtain the shaft system speed data updated by the refined electrical subsystem step.

9. A terminal, characterized in that: include: A memory, used for storing a wind turbine generator set refined interface simulation program; A processor is used to implement the steps of the wind turbine generator set refined interface simulation method as claimed in any one of claims 1 to 7 when executing the wind turbine generator set refined interface simulation system.

10. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. When the computer reads the computer instructions in the storage medium, the computer executes the wind turbine generator set refined interface simulation method as claimed in any one of claims 1 to 7.

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