A wind turbine refined interface simulation method, system, terminal and medium

Abstract

The present application provides a method, system, terminal and medium for fine-grained interface simulation of a wind turbine, including S1, performing frequency sweeps of several preset frequency bands at the interface of the wind turbine subsystem, collecting the steady-state response value of the shaft speed, and obtaining response characteristic data; S2, obtaining the frequency response characteristic function of the wind turbine subsystem at the interface based on the response characteristic data, and obtaining a frequency response characteristic model after processing the frequency response characteristic function; S3, at the step moment of the wind turbine subsystem, based on the shaft speed and electromagnetic torque, combined with the frequency response characteristic model, calculating the frequency variable of the excitation on the shaft speed, obtaining the internal equivalent speed and using it as the interface variable of the electrical subsystem; S4, the electrical subsystem receives the internal equivalent speed, and calculates and obtains the refined shaft speed data within each step moment of itself. This solves the problem of significant difference between the shaft speed that the electrical subsystem expects to receive and the shaft speed that it actually receives.

Description

Technical Field

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

[0002] A wind turbine is a multi-coupled complex dynamic system with fast and slow time scales. The aerodynamic system and wind turbine subsystem mainly focus on low-frequency vibrations (usually in the range of 0-50Hz) caused by uneven inflow and low-speed rotation of wind machinery components. Its typical simulation step is in the millisecond level. The electrical system involves broadband characteristics caused by power electronic equipment. The frequency range can reach from zero to several thousand Hz. Its typical simulation step is in the microsecond level. In order to solve the above problems, the existing technology adopts a multi-rate interface solution based on zero-order hold, that is, the two subsystems at the interface respectively sample the data at the interface based on their own simulation step zero-order hold. Figure 1 As shown in the figure, the School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University designed a real-time wind turbine joint simulation platform based on RTDS and Bladed: the wind model, aerodynamic model, mechanical part model, pitch system model and yaw system model are established in Bladed, and the wind turbine electrical part model and control system model are established in RTDS, and the communication between Bladed and RTDS is realized with the help of PLC.

[0003] However, the above-mentioned existing technical solutions have a significant disadvantage: when 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 samples, resulting in a significant decrease in simulation accuracy. In particular, when a system failure occurs, the shaft speed of the generator will produce obvious oscillations in a short period of time. There is a significant difference between the shaft speed that the electrical subsystem expects to receive and the shaft speed that it actually receives. The system cannot fully capture the dynamic changes in speed, which ultimately leads to a decrease in the accuracy of the wind turbine fine-tuning platform simulation results. Summary of the Invention

[0004] In response to the problems in the prior art, the present invention provides a method, system, terminal and medium for fine-grained interface simulation of wind turbines, which solves the problem in the prior art that there is a significant difference between the shaft system speed expected to be received by the electrical subsystem and the actual shaft system speed received, and the system cannot fully capture the dynamic changes in the speed, which ultimately leads to a decrease in the accuracy of the simulation results of the fine-grained platform of the wind turbine.

[0005] The technical solution adopted in the present invention is as follows:

[0006] In a first aspect, the present application provides a wind turbine generator system refined interface simulation method, comprising the following steps:

[0007] Step S1: At the interface of the wind turbine subsystem of the wind turbine generator set, by performing a frequency sweep on the wind turbine subsystem in several preset frequency bands, collecting steady-state response values ​​of the shaft speed to electromagnetic torque excitation at each frequency, and obtaining a set of discrete frequency response characteristic data;

[0008] Step S2: Based on 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, and the frequency response characteristic function is subjected to matrix contraction processing to retain the mapping relationship between the electromagnetic torque and the shaft speed, thereby obtaining a frequency response characteristic model of the wind turbine subsystem;

[0009] Step S3: At each wind turbine subsystem step, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem and in combination with the frequency response characteristic model, calculate the frequency variables of the shaft speed due to other excitations other than 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;

[0010] Step S4: After receiving the internal equivalent speed, the electrical subsystem calculates the shaft speed at each step according to the electromagnetic torque and frequency response characteristic model at the current simulation moment to obtain refined electrical subsystem step shaft speed data.

[0011] Preferably, step S1 includes the following steps:

[0012] Step S1-1, selecting a frequency range and sampling points;

[0013] Step S1-2, determining the amplitude of the swept frequency excitation;

[0014] 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.

[0015] Preferably, 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:

[0016]

[0017] in, The independent variable is 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 represent the phase angles of the output steady-state speed response sinusoidal signal and the swept-frequency excitation sinusoidal signal respectively.

[0018] Preferably, in step S2, the frequency response characteristic function at the interface is calculated:

[0019]

[0020] Where: is the frequency response characteristic function the number of extreme points; 、 They are No. A pole and the residue corresponding to the pole; is a constant term;

[0021] for The special case on the imaginary axis, that is, .

[0022] Preferably, the frequency range of the electromagnetic torque excitation of the preset frequency band sweep in step S1 is 0 Hz to 50 Hz.

[0023] Preferably, the frequency interval of the electromagnetic torque excitation is 0.05 Hz, and the discrete frequency response characteristic data is sampled at a total of 1000 frequency points in the range of 0 Hz to 50 Hz.

[0024] Preferably, the shaft system rotational speed is calculated in step S4 by performing a time domain difference solution or a convolution operation on the frequency response characteristic function.

[0025] In a second aspect, the present application provides a wind turbine refined interface simulation system, comprising:

[0026] 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;

[0027] a frequency response modeling module for constructing a frequency response characteristic function based on the discrete frequency response characteristic data using a vector fitting method, and retaining the mapping relationship between the electromagnetic torque and the shaft speed using a matrix shrinkage technique to obtain a frequency response characteristic model of the wind turbine subsystem;

[0028] an equivalent speed calculation module for calculating, at each step of simulation of the wind turbine subsystem, frequency variables of the shaft speed due to excitations other than the electromagnetic torque, based on the frequency response characteristic model and the current shaft speed and electromagnetic torque, generating an internal equivalent speed, and transmitting the result to the electrical subsystem as an interface output variable;

[0029] The speed estimation module is used to receive the internal equivalent speed and the electromagnetic torque at 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 for the refined electrical subsystem step update.

[0030] In a third aspect, the present application provides a terminal, including:

[0031] A memory, used for storing a wind turbine generator set refined interface simulation program;

[0032] The processor is configured to implement 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.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium storing computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a wind turbine refined interface simulation method as described in the first aspect.

[0034] It can be seen from the above technical solutions that this application has the following advantages:

[0035] 1. High-precision interface coupling modeling for multi-rate joint simulation between the mechanical and electrical subsystems of wind turbines is achieved, which can improve the overall simulation accuracy of the system while maintaining the original simulation step size of the subsystem.

[0036] 2. Obtaining frequency response data through frequency sweep experiments and constructing interface frequency response characteristic functions 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 dynamic processes in the traditional zero-order hold method.

[0037] 3. The vector fitting method is used to convert discrete frequency domain data into a continuous function, which improves the fitting accuracy of frequency response modeling and facilitates subsequent dynamic estimation in the time domain simulation process.

[0038] 4. By introducing the concept of "internal equivalent speed" and the frequency domain inverse method, the influence of non-interface excitation can be accurately expressed while retaining only the interface frequency response function, effectively reducing the modeling complexity.

[0039] 5. The method of calculating the shaft speed in small steps improves the electrical subsystem's ability to capture mechanical responses to high-speed changing signals (such as fault disturbances) and improves the dynamic response performance of the simulation system.

[0040] 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 sampling points are taken to ensure that the typical low-frequency vibration range of the wind turbine is covered, thus ensuring the breadth and analytical accuracy of the frequency response function.

[0041] 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.

[0042] 8. Through the modular design of the system, the decoupling configuration of the functional modules of frequency response acquisition, modeling, equivalent speed calculation and speed estimation is realized, which is convenient for embedding into existing wind power simulation software or control systems, thereby improving engineering adaptability and deployment efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for the description. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0044] Figure 1 A design flow chart of a joint simulation platform in the prior art;

[0045] Figure 2 Schematic diagram of the structure of each subsystem of the wind turbine generator set refined interface simulation method shown in some embodiments;

[0046] Figure 3 A diagram showing a frequency response characteristic model of a wind turbine subsystem interface in a wind turbine refined interface simulation method according to some embodiments;

[0047] Figure 4 This is a flow chart of a multi-rate data interaction solution based on frequency response characteristics of a wind turbine generator refined interface simulation method shown in some embodiments. DETAILED DESCRIPTION

[0048] In order to make the application objectives, features, and advantages of this application more obvious and easy to understand, the technical solutions protected by this application will be clearly and completely described below using specific embodiments and drawings. Obviously, the embodiments described below are only part of the embodiments of this application, not all of them. Based on the embodiments in this patent, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this patent.

[0049] Wind power plays an indispensable role in my country's low-carbon energy system. In order to reduce the levelized cost of electricity, wind turbines are gradually developing towards large-scale development, and the capacity of single units continues to increase. While the power generation capacity of large-capacity units is increased, their geometric dimensions are also greatly increased (i.e., longer blades and higher towers), resulting in greater fluctuations in wind turbine power and greater bending moments and fatigue damage to internal mechanical components.

[0050] Typically, refined wind turbine models can be divided into aerodynamic, mechanical, and electromagnetic transient models. Both aerodynamic and mechanical models belong to the same wind turbine subsystem. The aerodynamic model primarily focuses on aerodynamic torque calculations and three-dimensional inflow dynamics. The mechanical model describes the non-torsional dynamics of mechanical components such as the turbine blades, tower, and nacelle, as well as the torsional dynamics of the shaft system. The electrical subsystem model describes the electromagnetic transient characteristics of the turbine's generator, converter, transformer, filter, and collector network. The interface technology between models at different simulation rates significantly impacts the accuracy of multi-rate simulation systems, necessitating the establishment of high-precision interface models to improve simulation accuracy.

[0051] A wind turbine is a multi-coupled complex dynamic system with fast and slow time scales. The aerodynamic system and wind turbine subsystem mainly focus on low-frequency vibrations (usually in the range of 0-50Hz) caused by uneven inflow and low-speed rotation of wind machinery components. Its typical simulation step is in the millisecond level. The electrical system involves broadband characteristics caused by power electronic equipment. The frequency range can reach from zero to several thousand Hz. Its typical simulation step is in the microsecond level. In order to solve the above problems, the existing technology adopts a multi-rate interface solution based on zero-order hold, that is, the two subsystems at the interface respectively sample the data at the interface based on their own simulation step zero-order hold. Figure 1 As shown in the figure, the School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University designed a real-time wind turbine joint simulation platform based on RTDS and Bladed: the wind model, aerodynamic model, mechanical part model, pitch system model and yaw system model are established in Bladed, and the wind turbine electrical part model and control system model are established in RTDS, and the communication between Bladed and RTDS is realized with the help of PLC.

[0052] However, the above-mentioned existing technical solutions have a significant disadvantage: when 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 samples, resulting in a significant decrease in simulation accuracy. In particular, when a system failure occurs, the shaft speed of the generator will produce obvious oscillations in a short period of time. There is a significant difference between the shaft speed that the electrical subsystem expects to receive and the shaft speed that it actually receives. The system cannot fully capture the dynamic changes in speed, which ultimately leads to a decrease in the accuracy of the wind turbine fine-tuning platform simulation results.

[0053] In response to the problems in the prior art, the present invention provides a method, system, terminal and medium for fine-grained interface simulation of wind turbines, which solves the problem in the prior art that there is a significant difference between the shaft system speed expected to be received by the electrical subsystem and the actual shaft system speed received, and the system cannot fully capture the dynamic changes in the speed, which ultimately leads to a decrease in the accuracy of the simulation results of the fine-grained platform of the wind turbine.

[0054] This application provides a wind turbine generator system refined interface simulation method, including:

[0055] Step S1: At the interface of the wind turbine subsystem of the wind turbine generator set, by performing a frequency sweep on the wind turbine subsystem in several preset frequency bands, collecting steady-state response values ​​of the shaft speed to electromagnetic torque excitation at each frequency, and obtaining a set of discrete frequency response characteristic data;

[0056] Step S2: Based on 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, and the frequency response characteristic function is subjected to matrix contraction processing to retain the mapping relationship between the electromagnetic torque and the shaft speed, thereby obtaining a frequency response characteristic model of the wind turbine subsystem;

[0057] Step S3: At each wind turbine subsystem step, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem and in combination with the frequency response characteristic model, calculate the frequency variables of the shaft speed due to other excitations other than 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;

[0058] Step S4: After receiving the internal equivalent speed, the electrical subsystem calculates the shaft speed at each step according to the electromagnetic torque and frequency response characteristic model at the current simulation moment to obtain refined electrical subsystem step shaft speed data.

[0059] In some embodiments, step S1 includes the following steps:

[0060] Step S1-1, selecting a frequency range and sampling points;

[0061] Step S1-2, determining the amplitude of the swept frequency excitation;

[0062] 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.

[0063] Under the influence of external excitations of 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 output value of the wind turbine subsystem shaft speed at the mechanical-electrical multi-rate simulation interface. This patent first analyzes the frequency response characteristics of the wind turbine subsystem under external excitations of different frequencies based on the dynamic equations of the wind turbine subsystem, and gives the concept of the frequency response characteristic matrix.

[0064] The dynamic equations of each sub-component (blades, tower, rotor, nacelle) of the wind turbine subsystem of the wind turbine can be coupled to form the dynamic equation of the overall system:

[0065]

[0066] in, is the total mass matrix, which is composed of the masses of all components; is the total damping matrix, including air damping and structural damping; is the total stiffness matrix; It is the deformation or movement displacement of the component; yes The first derivative of is the deformation or displacement velocity of the component; yes The second derivative of 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 dimensions of the three matrices are the same, 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 nonlinear system, the matrix 、 、 The values ​​of the internal elements will change with the system status.

[0067] 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:

[0068]

[0069] in, Indicates the deformation speed or movement speed of the component, which is equal to The first derivative with respect to time. It should be emphasized that is a vector, which includes the speed of each component in the wind turbine subsystem, such as shaft speed, nacelle swing speed, etc. It is also a vector, which includes all external excitations of the wind turbine subsystem such as electromagnetic torque, aerodynamic torque, etc.

[0070] 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 a certain frequency excitation. Considering that the simulation step size is small, the system state change within each step size is also small, so the matrix 、 、 , the wind turbine subsystem is set as a linear system. When the external excitation is a standard sinusoidal signal, the speed response of the wind turbine subsystem will also be a standard sinusoidal signal with the same frequency as the excitation. Given the external excitation is , the speed response of the wind turbine subsystem under this excitation is set to , where A and B are incentives and response The amplitude of α and β are respectively and response The initial phase angle of is the frequency;

[0071] The vector composed of sinusoidal quantities is rewritten as a phasor:

[0072]

[0073]

[0074] in, express The phasor vector of express The phasor vector of

[0075] Bring both into We can get:

[0076]

[0077] Only the left side of the equation retains , the above formula can be further organized as:

[0078]

[0079]

[0080] It can be seen that for a single frequency external excitation and speed response, the frequency response characteristics of the wind turbine subsystem are expressed by the mass matrix , damping matrix and stiffness matrix The matrix composed of To express; is a complex matrix, The amplitude represents the ratio of the velocity response to the amplitude of the external excitation, and the phase angle represents the phase of the velocity response leading the external excitation.

[0081] When the external excitation is a complex signal of any form, its continuous spectrum distribution can be obtained through Fourier transform:

[0082]

[0083] in, is a complex exponential function, and the signal can be obtained through this integral operation Representation in the frequency domain ; is a frequency-dependent complex function vector, The amplitude of the signal indicates the frequency of The intensity of the component, the phase indicates the frequency of the signal The phase shift of the component.

[0084] After obtaining the spectrum 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 of each frequency component when it acts alone. In addition, each frequency component in the excitation and its response satisfy , so the total speed response of the system will also satisfy the relationship between the stimulus The spectrum distribution of the total speed response of the system is recorded as , then:

[0085]

[0086] It can be seen that although the frequency response characteristic matrix is ​​for a single simple harmonic excitation, the frequency response characteristics of the wind turbine subsystem under any complex signal input can still be expressed using the frequency response characteristic matrix. It should be emphasized that the frequency response characteristic matrix It is a frequency-dependent matrix whose 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.

[0087] The wind turbine subsystem consists of several components, and it is difficult to directly calculate the interface frequency response characteristic function by the above theoretical analysis plus matrix shrinkage method. Analytical expression for . From the previous analysis of the frequency response, we know that the amplitude of the frequency response characteristic function is equal to the ratio of the amplitude of the same frequency response to the excitation, and the phase angle is equal to the phase of the same frequency response leading the excitation. Therefore, the interface frequency response characteristic function of the wind turbine subsystem can be identified using a method similar to frequency sweeping and vector fitting in power systems. This section first introduces the precautions and steps for performing a frequency sweep on the wind turbine subsystem, and then presents the basic principles and results of vector fitting.

[0088] Frequency sweeping is designed to extract the system's frequency response characteristics. The basic idea is to sequentially inject electromagnetic torque excitations of different frequencies into the wind turbine subsystem and obtain the system's shaft speed response under each frequency excitation, thereby obtaining sampled values ​​of the wind turbine subsystem's interface frequency response characteristic function at different frequencies. In some embodiments, the designed frequency sweep scheme can be divided into the following three steps:

[0089] First, select the frequency range and sampling points, that is, determine at which frequency points to perform the frequency sweep. The vibration frequency of the wind turbine subsystem generally does not exceed 50Hz, so selecting a frequency range of 0-50Hz 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 the wind turbine subsystem In some embodiments, the sampling values ​​of the function are selected at equal intervals of 0.05 Hz within the above frequency range. Sampling points. For the frequency range of 0-50Hz, there are sampling points =1000.

[0090] Next, determine the amplitude of the sweep excitation. This should be neither too large, as this may alter the system's inherent linearity, nor too small, as this may interfere with system noise and affect the accuracy of the results. Generally, a sweep excitation amplitude of 1%-10% of the variable's normal operating value can be selected; in some embodiments, 5% is used.

[0091] Finally, frequency sweep excitations of varying frequencies are injected at the system interface according to the selected parameters, and the steady-state speed response output of the system is measured for each excitation. Since the injected electromagnetic torque excitation is a standard sinusoidal signal, the speed response obtained is essentially a sinusoidal signal with the same frequency as the excitation. The sampled value of the interface frequency response characteristic function at that frequency can be calculated using the following formula:

[0092]

[0093] in, and They represent the amplitudes of the output steady-state speed response sinusoidal signal and the swept-frequency excitation sinusoidal signal respectively; and They represent the phase angles of the output steady-state speed response sinusoidal signal and the swept-frequency excitation sinusoidal signal respectively.

[0094] use The calculated sampling values ​​are all in the form of complex numbers, whose amplitude is the multiple ratio of the speed response to the excitation amplitude, and the phase angle is the angle at which the speed response leads the excitation.

[0095] Based on frequency scanning, a set of discrete interface frequency response characteristic functions can be obtained The data is a set of complex numbers whose independent variable is frequency. This data needs to be further processed to obtain a continuous expression before it can be used for system simulation.

[0096] In some embodiments, a continuous transfer function is formed based on vector fitting of discrete data. To express the interface frequency response characteristic function . Transfer function and frequency response characteristic function is essentially uniform, the frequency response Can be viewed as a transfer function The special case on the imaginary axis, that is, . Vector fitting can find an analytical transfer function , so that it The value and frequency sweep data Through this process, the frequency domain data can be converted into a transfer function in the complex frequency domain, which can be used for time domain simulation and system analysis.

[0097] Under the vector fitting method, any rational function Can be expressed in the following form:

[0098]

[0099] Where: is the boundary frequency characteristic transfer function the number of extreme points; 、 for No. A pole and the residue corresponding to the pole; is a constant term.

[0100] according to The vector fitting method will form a set of transcendental equations for the discrete sampling values ​​at each frequency, and use the least squares method to find The vector fitting method is relatively mature at present, and its more detailed solution process will not be described in detail in this embodiment.

[0101] based on The transfer function replaces , a multi-rate interface model considering the frequency response characteristics of the wind turbine subsystem can be constructed in the time domain.

[0102] In some embodiments, the wind turbine multi-rate data interaction scheme designed based on frequency response characteristics is as follows: Figure 3 As shown, compared with the traditional data interaction solution based on the ZOH method, the biggest difference of the solution proposed in this patent is that the interface frequency response characteristic model of the wind turbine subsystem (i.e. Figure 3 The part in the light green dotted box 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. Changed to internal equivalent speed , the original data interaction variable of the electrical subsystem is still the generator electromagnetic torque constant.

[0103] The initial simulation time is , the simulation step size of the wind turbine subsystem is , the simulation step size of the electrical subsystem is Consistent with the traditional ZOH method, during the simulation process, the wind turbine subsystem follows its own simulation step size. Output and receive interface variables to ensure the efficiency of simulation. The difference is that during the interaction of shaft speed, the electrical subsystem obtains a step size of Internal equivalent speed After that, in each small step Always based on the latest electromagnetic torque Accurately estimate the shaft speed in small steps Since this interface introduces the interface frequency response characteristic model of the wind turbine subsystem, the estimated shaft speed It will have higher accuracy and can effectively realize high-precision interaction between mechanical and electrical systems.

[0104] Calculate internal equivalent speed . The exact calculation formula is 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 No acquisition. Therefore, based on The analytical solution method fails. Considering that for the wind turbine subsystem, the shaft speed at each data interaction moment is Therefore, the shaft speed can be updated based on the large step size. and interface frequency response characteristic function Reverse , and its formula in the frequency domain is: ;

[0105] in, is the Fourier transform of the internal equivalent speed; 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.

[0106] It should be noted that It is only updated once at the large step data interaction time and passed to the electrical subsystem as an interaction variable. During the iterative update process, the value of this variable remains unchanged.

[0107] In some embodiments, the present application provides a wind turbine generator system refined interface simulation system, including:

[0108] 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;

[0109] a frequency response modeling module for constructing a frequency response characteristic function based on the discrete frequency response characteristic data using a vector fitting method, and retaining the mapping relationship between the electromagnetic torque and the shaft speed using a matrix shrinkage technique to obtain a frequency response characteristic model of the wind turbine subsystem;

[0110] an equivalent speed calculation module for calculating, at each step of simulation of the wind turbine subsystem, frequency variables of the shaft speed due to excitations other than the electromagnetic torque, based on the frequency response characteristic model and the current shaft speed and electromagnetic torque, generating an internal equivalent speed, and transmitting the result to the electrical subsystem as an interface output variable;

[0111] The speed estimation module is used to receive the internal equivalent speed and the electromagnetic torque at 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 for the refined electrical subsystem step update.

[0112] In some embodiments, the present application provides a terminal, including:

[0113] A memory, used for storing a wind turbine generator set refined interface simulation program;

[0114] The processor is configured to implement 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.

[0115] In some embodiments, the present application provides a computer-readable storage medium storing computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the wind turbine refined interface simulation method.

[0116] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are suggested in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

[0117] In addition, unless expressly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are for illustrative purposes only, and 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 are consistent with the spirit 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 by software solutions, such as installing the described system on an existing server or mobile device.

[0118] Similarly, it should be noted that, in order to simplify the presentation of this specification and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this specification sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not imply that the subject matter of this specification requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single disclosed embodiment.

[0119] In some embodiments, numbers describing the quantity of components and attributes are used. 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 numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may vary according to the required features of the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the settings of such numerical values ​​are as accurate as possible within the feasible range.

[0120] Finally, it should be understood that the embodiments described in this specification are intended only 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 may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated 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 frequency sweep on the wind turbine subsystem in several preset frequency bands, collecting steady-state response values ​​of the shaft speed to electromagnetic torque excitation at each frequency, and obtaining a set of discrete frequency response characteristic data; Step S2: Based on 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, and the frequency response characteristic function is subjected to matrix contraction processing to retain the mapping relationship between the electromagnetic torque and the shaft speed, thereby obtaining a frequency response characteristic model of the wind turbine subsystem; Step S3: At each wind turbine subsystem step, based on the known shaft speed and electromagnetic torque of the wind turbine subsystem and in combination with the frequency response characteristic model, calculate the frequency variables of the shaft speed due to other excitations other than 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 receiving the internal equivalent speed, the electrical subsystem calculates the shaft speed at each step 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 system 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 system 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 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 represent the phase angles of the output steady-state speed response sinusoidal signal and the swept-frequency excitation sinusoidal signal respectively.

4. The wind turbine generator system 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 extreme points; 、 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 system 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 system 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 system 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 for constructing a frequency response characteristic function based on the discrete frequency response characteristic data using a vector fitting method, and retaining the mapping relationship between the electromagnetic torque and the shaft speed using a matrix shrinkage technique to obtain a frequency response characteristic model of the wind turbine subsystem; an equivalent speed calculation module for calculating, at each step of simulation of the wind turbine subsystem, frequency variables of the shaft speed due to excitations other than the electromagnetic torque, based on the frequency response characteristic model and the current shaft speed and electromagnetic torque, generating an internal equivalent speed, and transmitting the result 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 at 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 for the refined electrical subsystem step update.

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

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