A multi-machine equivalent method for doubly-fed wind power plants considering impedance characteristics and synchronization mechanism

Abstract

The application discloses a multi-machine equivalent method of a doubly-fed wind power station considering impedance characteristics and a synchronization mechanism, and steps of the method comprise the following steps: 1, a mathematical model of a doubly-fed wind power single-machine grid-connected system based on a virtual synchronization mechanism is established, and a single-machine system small disturbance impedance analysis model is derived through the mathematical model; 2, system impedance characteristics under different parameter change conditions are analyzed by using the single-machine system small disturbance impedance model; and 3, according to the single-machine impedance analysis result, a multi-machine equivalent method of the doubly-fed wind power station based on the virtual synchronization mechanism is proposed. The application can take into account the precision and efficiency by using multiple equivalent units to equivalently replace the doubly-fed wind power station, so that reference can be provided for grid-connected operation and maintenance of the doubly-fed wind power station system.

Description

Technical Field

[0001] This invention belongs to the field of power system stability analysis, specifically relating to a multi-unit equivalent method for doubly fed wind farms that considers impedance characteristics and synchronization mechanisms. Background Technology

[0002] With the grid connection of wind power and other new energy units, my country's power system is gradually becoming a new power system dominated by new energy sources. Doubly fed induction generators (DFIGs) dominate the wind turbine market due to their low cost and high reliability. In traditional power grids, synchronous machines are the main source of system inertia. However, with the increasing proportion of new energy sources, the proportion of synchronous machines is decreasing, leading to problems such as insufficient inertia in the new power system. Most wind turbines use phase-locked loop (PLL) synchronization mechanisms for grid connection. DFIGs under this mechanism cannot respond to frequency changes like synchronous machines, failing to provide support to the system. When the system experiences a large power loss, frequency instability can easily occur, leading to system collapse.

[0003] Because doubly-fed induction generator (DFIG) wind turbines generate significantly less power than synchronous generators, practical DFIG wind farms often have dozens or even hundreds of turbines. Stability analysis of these farms requires a farm model. Detailed modeling of each turbine within the farm is extremely difficult. However, grouping the farm into equivalent units before modeling and simulation effectively completes the analysis. Grouping equivalent units replace the entire farm with one or a few equivalent turbines, maintaining similar characteristics before and after the equivalent unit model. Traditional single-unit equivalent models do not consider factors such as synchronization mechanisms, resulting in low accuracy and large errors, and are now outdated in engineering applications. Summary of the Invention

[0004] This invention aims to address the shortcomings of existing technologies by proposing a multi-unit equivalent method for doubly-fed wind farms that considers impedance characteristics and synchronization mechanisms. This method provides inertia support for the power system, accurately grasps the impedance characteristics of the wind power system and the factors affecting stability, and enables practical analysis of the farms. This provides significant scientific research and engineering application value for the stability analysis of new energy farms under future power systems.

[0005] The present invention solves the technical problem by adopting the following technical solution:

[0006] The multi-unit equivalent method for doubly-fed wind farms that considers impedance characteristics and synchronization mechanisms, as described in this invention, includes the following steps:

[0007] Step 1: Establish a mathematical model for a doubly-fed wind turbine single-unit grid-connected system based on a virtual synchronization mechanism:

[0008] Step 1.1: Use a virtual synchronization mechanism to simulate the working process of a synchronous generator, obtain the rotor motion equation and reactive voltage equation, and use them to control the active and reactive power of a doubly-fed wind power unit.

[0009] Step 1.2: Only consider the impact of the rotor-side converter on the grid-connected system of a single doubly-fed wind turbine, and ignore the impact of the grid-side converter on the grid-connected system of a single doubly-fed wind turbine, so as to establish a control model of the rotor-side converter based on the virtual synchronization mechanism.

[0010] Step 1.3: Model the induction motor and transmission line in the doubly fed wind power single-unit grid-connected system, so as to form a complete system model together with the control model;

[0011] Step 2: Establish a small disturbance impedance model for a doubly-fed wind turbine single-unit grid-connected system and perform impedance analysis:

[0012] Step 2.1: On the complete system model, determine the equilibrium point of each state variable, and inject a small disturbance signal at the equilibrium point to obtain the open-loop impedance models of the induction motor, the virtual synchronization mechanism, the voltage outer loop and the current inner loop respectively.

[0013] Step 2.2: Based on the inherent relationship between the various open-loop impedance models, obtain the impedance model of the doubly fed wind power single-unit grid-connected system based on the virtual synchronization mechanism in the dq rotating coordinate system.

[0014] Step 2.3: Transform the impedance model in the dq rotating coordinate system into the positive and negative sequence impedance model in the abc stationary coordinate system using impedance transformation theory;

[0015] Step 2.4: Establish a grid impedance model based on the grid impedance in a doubly-fed wind turbine single-unit grid-connected system;

[0016] Step 2.5: Sequentially change the virtual inertia coefficient, damping coefficient, and grid impedance parameters in the virtual synchronization mechanism to obtain the positive sequence impedance amplitude-frequency curve and phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system, as well as the positive sequence impedance amplitude-frequency curve and phase frequency characteristic curve of the grid impedance model.

[0017] Step 2.6: Based on the relationship between the positive sequence impedance amplitude-frequency curve of the doubly fed wind turbine single unit grid-connected system and the positive sequence impedance amplitude-frequency curve of the grid impedance model, and the relationship between the phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system and the phase frequency characteristic curve of the grid impedance model, the influence of different parameters on the stability of the doubly fed wind turbine single unit grid-connected system is analyzed using the stability criterion, and the impedance analysis results of the doubly fed wind turbine single unit grid-connected system are obtained.

[0018] Step 3: Select the clustering indicators and obtain their data:

[0019] Step 3.1: Based on the impedance analysis results of the doubly fed wind turbine single-unit grid-connected system, the virtual inertia coefficient, damping coefficient, wind speed of each doubly fed wind turbine, and the distance between each doubly fed wind turbine and the grid connection point are used as the equivalent grouping index for the multi-unit grid at the site.

[0020] Step 3.2: Query the wind farm design plan to obtain the distance between each doubly fed wind turbine and the grid connection point;

[0021] Step 3.3: Obtain wind speed data for each doubly-fed wind turbine using the anemometer on the wind turbine.

[0022] Step 3.4: Based on the measured data, the complete system model is processed using the identification algorithm to obtain the virtual inertia coefficient and damping coefficient of each doubly fed wind turbine.

[0023] Step 4: Multi-unit equivalent analysis of a doubly-fed wind farm:

[0024] Step 4.1: Standardize the cluster index data of each unit in the collected doubly fed wind farm and filter out abnormal data to obtain preprocessed cluster index data;

[0025] Step 4.2: Use the elbow method to obtain the optimal number of clusters K for the field;

[0026] Step 4.3: Based on the optimal number of clusters K and the preprocessed cluster index data, randomly select cluster centers and use the K-means algorithm to iterate through the cluster centers to obtain the division results of the doubly fed wind turbine groups in the doubly fed wind farm and the optimal cluster center of each doubly fed wind turbine group.

[0027] Step 4.4: Based on the division results of the doubly fed wind farm, each cluster in the division results is regarded as an equivalent unit, and the parameters of each equivalent unit are calculated. Thus, the doubly fed wind farm is equivalently represented by K equivalent units, and the multi-unit equivalent of the doubly fed wind farm is completed.

[0028] The present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the multi-machine equivalent method, and the processor is configured to execute the program stored in the memory.

[0029] The present invention discloses a computer-readable storage medium on which a computer program is stored, wherein the computer program is executed by a processor to perform the steps of the multi-machine equivalent method.

[0030] Compared with existing technologies, the beneficial effects of this invention are reflected in:

[0031] 1. This invention utilizes a virtual synchronization mechanism to control the grid connection of a doubly-fed wind power system. The virtual synchronization mechanism simulates the operation of a synchronous machine, which can provide corresponding inertia support for the power system and prevent problems such as instability caused by low system inertia.

[0032] 2. This invention uses a small-disturbance impedance model to analyze a doubly-fed wind power system, obtains the impedance characteristics of a doubly-fed wind power system based on a synchronization mechanism, understands the influence of various parameters on the stability of the wind power system, and provides theoretical support for the equivalent grouping index of the wind farm.

[0033] 3. The impedance analysis results of the single-unit system of this invention determine the cluster index, and the identification algorithm and other methods are used to obtain data and use clustering to replace the station with multiple equivalent units. The equivalent value takes into account both efficiency and accuracy, and has higher applicability in engineering. Attached Figure Description

[0034] Figure 1 This is a block diagram illustrating the principle of the virtual synchronization mechanism used in this invention.

[0035] Figure 2 This is a block diagram of the rotor-side converter control system of the unit in this invention;

[0036] Figure 3 This is the small disturbance impedance model of the doubly fed wind turbine single-unit grid-connected system in this invention;

[0037] Figure 4 This is a topology diagram of the doubly fed wind farm system in this invention;

[0038] Figure 5 This is a magnified comparative analysis of the active power of three types of power station models in the examples of this invention;

[0039] Figure 6 This is a magnified comparison of the reactive power of three types of power station models in the examples of this invention. Detailed Implementation

[0040] In this embodiment, a multi-unit equivalent method for a doubly fed wind farm considering impedance characteristics and synchronization mechanisms is carried out according to the following steps:

[0041] Step 1: Establish a mathematical model of a doubly fed wind power unit grid-connected system based on a virtual synchronization mechanism;

[0042] A doubly fed wind power single-unit grid-connected system mainly consists of a doubly fed induction motor, a back-to-back PWM converter, transmission lines, a virtual synchronization mechanism, and other components.

[0043] Step 1.1: This doubly-fed induction generator (DFIG) wind turbine single-unit grid-connected system adopts a virtual synchronization mechanism for grid synchronization to provide inertia support to the grid and improve system stability. The virtual synchronization mechanism simulates the working process of a synchronous machine, introducing rotor motion equations and reactive power voltage equations to control active and reactive power. Its control block diagram is shown below. Figure 1 As shown, mathematical models (1) and (2) can be established:

[0044]

[0045]

[0046] In equations (1) and (2), T j D and P represent the virtual inertia and damping coefficient introduced by the virtual synchronization mechanism, respectively; s_ref P s These represent the reference value and the actual output value of the stator active power, respectively; ω vsg ,ω1,ω b These represent the virtual angular velocity, grid angular velocity, and system angular velocity reference values ​​output under the virtual synchronization mechanism, respectively; θvsg is the stator voltage angle obtained through control; U s_ref U s These represent the reference amplitude and actual output value of the stator voltage, respectively; k pv k iv Q represents the reactive power ratio and integral coefficient, respectively; s_ref Q s These represent the reference value and the actual output value of the stator reactive power, respectively.

[0047] Step 1.2: The doubly fed induction motor in the doubly fed wind power single-unit grid-connected system can be represented by the mathematical models of magnetic flux and electromagnetic torque, equations (3)-(5):

[0048]

[0049] In equation (3): u rd u rq u sd u sq These represent the components of the rotor and stator voltages on the d and q axes, respectively; i rd i rq i sd i sq ψ represents the components of the rotor and stator currents along the d and q axes, respectively; rd ψ rq ψ sd ψ sq These represent the components of the rotor and stator flux linkages along the d and q axes, respectively; R r R s Represents the equivalent rotor and stator resistance; ω sr =ω s -ω r , which represents the difference between the stator angular velocity and the rotor angular velocity.

[0050]

[0051] In equation (4): L m Indicates the mutual inductance between the stator and rotor; L s L rThese represent the self-inductance of the stator and rotor windings, respectively.

[0052]

[0053] In equation (5): n p To represent the extreme logarithm, in this embodiment, n p =3.

[0054] Step 1.3: When performing small disturbance modeling analysis on a single-unit doubly-fed induction generator (DFIG) wind turbine grid-connected system, only the influence of rotor-side converter control on the grid-connected system needs to be considered, while the influence of grid-side converter control on the DFIG wind turbine grid-connected system can be ignored. The block diagram of the rotor-side converter control system is as follows: Figure 2 As shown, establish the mathematical model shown in equation (6);

[0055]

[0056] In equation (6): k p1 k i1 k p2 k i2 These represent the proportional and integral coefficients of the outer and inner loops in the rotor-side converter control, respectively, where σ is the generator leakage flux coefficient; i rd—ref i rq_ref These represent the reference values ​​for the components of the rotor and stator currents on the d and q axes, respectively; z1, z2, z3, and z4 all represent state variables.

[0057] Step 1.4: In a doubly fed wind power single-unit grid-connected system, the wind turbine is connected to the power grid via a long-distance series compensation transmission line after passing through a step-up transformer. Its mathematical model is shown in equations (7) and (8):

[0058]

[0059]

[0060] In equations (7) and (8): R L X L C L These represent the resistance, reactance, and capacitance values ​​of the series-compensated transmission line, respectively; i d i q These represent the d-axis and q-axis components of the current in the series compensation circuit, respectively; u cd u cq These represent the voltage components of the series capacitor on the d and q axes, respectively; u bd u bq These represent the components of the connected infinite grid voltage on the d and q axes, respectively.

[0061] Step 2: Based on the mathematical model obtained in Step 1, obtain its equilibrium point. Inject a small disturbance signal at the equilibrium point to derive the small disturbance model of the doubly-fed induction generator (DFIG) wind power grid-connected system:

[0062] Step 2.1: Based on the wind speed input to the wind power system, obtain the system's equilibrium point and inject a small disturbance signal at the equilibrium point;

[0063] Step 2.2: After injecting the small signal, the mathematical models of voltage and current double closed-loop control in the control of induction motor, virtual synchronization mechanism, and rotor-side converter are linearized respectively, so as to establish the small disturbance equations of voltage and current double closed-loop control in the dq rotating coordinate system in the control of induction motor, virtual synchronization mechanism, and rotor-side converter, and obtain the open-loop impedance model respectively.

[0064] Step 2.3: Based on the inherent relationship between the open-loop impedance models, obtain the impedance model of the doubly-fed induction generator (DFIG) single-unit grid-connected wind power system based on the virtual synchronization mechanism in the dq rotating coordinate system. The open-loop impedance model of this system can be obtained as follows: Figure 3 As shown, Figure 3 The specific transfer functions in the open-loop impedance model of a doubly fed wind turbine single-unit grid-connected system are as follows;

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] G 11 =G dq G vsg (16)

[0073]

[0074] in:

[0075]

[0076]

[0077]

[0078] Step 2.4: Using the impedance transformation theory shown in equation (21), the impedance model in the dq rotating coordinate system is transformed into a positive and negative sequence impedance model in the stationary abc coordinate system:

[0079]

[0080] In equation (21): Z + (s) is the input angular frequency ω in the stationary abc coordinate system. Δ When a sinusoidal small disturbance signal is received, the frequency ω of the stationary abc coordinate system relative to itself is... Δ The response of Z; and Z - (s) is the frequency (2ω0-ω) in the stationary abc coordinate system. Δ The response of ); ω0 represents the power frequency angular frequency.

[0081] Step 2.5: Establish the grid impedance model, and then change the virtual inertia coefficient, damping coefficient and grid impedance coefficient in the virtual synchronization mechanism respectively to obtain the positive sequence amplitude-frequency curve and phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system and the positive sequence amplitude-frequency curve and phase frequency characteristic curve of the grid impedance.

[0082] Step 2.6: Based on the relationship between the positive sequence impedance amplitude-frequency curve of the doubly fed wind turbine single unit grid-connected system and the positive sequence impedance amplitude-frequency curve of the grid impedance model, and the relationship between the phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system and the phase frequency characteristic curve of the grid impedance model, the influence of changes in virtual inertia coefficient, damping coefficient, and grid impedance coefficient on grid-connected stability is analyzed using stability criteria, and the impedance analysis results of the doubly fed wind turbine single unit grid-connected system are obtained.

[0083] Step 3: Select the clustering indicators and obtain their data:

[0084] Step 3.1: Based on the impedance analysis results of the single-unit grid-connected doubly-fed wind turbine system, the virtual inertia coefficient, damping coefficient, wind speed of each doubly-fed wind turbine, and the distance between each doubly-fed wind turbine and the grid connection point are used as the equivalent grouping index for the multi-unit grid at the site.

[0085] Step 3.2: Query the wind farm design plan to obtain the distance between each turbine and the grid connection point within the doubly-fed wind farm;

[0086] Step 3.3: The input wind speed of each unit in the doubly fed wind farm can be obtained by the anemometer on the top of the tower or on the rotating blades;

[0087] Step 3.4: Regarding the selection of the virtual inertia coefficient and damping coefficient, the factory parameters obtained from the manufacturer are first used as initial values ​​and calculated in a detailed single-unit model in conjunction with the unit's input wind speed and other operating conditions to obtain the calculated output power value. Then, the measured output power of the unit is used as the optimization target of the particle swarm optimization algorithm, and the virtual inertia coefficient and damping coefficient, as well as these two parameters, are continuously changed until the difference between the calculated value and the actual value meets the termination condition. Finally, the virtual inertia coefficient and damping coefficient obtained after calculation and identification by the particle swarm optimization algorithm can be considered to conform to the actual situation.

[0088] Step 4: Perform multi-unit equivalent analysis on the doubly-fed wind farm:

[0089] Step 4.1: Input the cluster index data of each unit in the doubly fed wind farm. Due to the inconsistency of the units of the input sample data, the results may have a large mean deviation. Standardize the sample data and filter out the abnormal data to obtain the preprocessed cluster index data.

[0090] Step 4.2: The number of clusters K has a great influence on the results of the K-means clustering algorithm. Therefore, before clustering, the elbow method is used to obtain the optimal number of clusters K for the station.

[0091] Step 4.3: Based on the optimal number of clusters K and the preprocessed data, randomly select cluster centers and use the K-means algorithm to iterate through the cluster centers to obtain the division results of the doubly fed wind turbine groups in the doubly fed wind farm and the cluster centers of each doubly fed wind turbine group.

[0092] Step 4.4: Based on the station clustering results, each cluster in the division results is treated as an equivalent unit, and the station is replaced by K equivalent units.

[0093] Step 4.5: Calculate the equivalent unit parameters. The electrical parameters are calculated using the capacity-weighted method. The virtual inertia coefficient and damping coefficient of the equivalent unit are represented by the cluster center data. The input wind speed of the equivalent unit is calculated using the following formula (22). The equivalent parameters of the collector line need to be calculated by first converting the trunk topology to a radial topology using formula (23), and then using the equal power loss method of formula (24).

[0094]

[0095]

[0096]

[0097] In equation (22): v eq v iS represents the equivalent wind speed of the equivalent unit and the actual wind speed of the i-th unit in the turbine group, respectively; Geq S Gi Let represent the apparent power of the equivalent unit and the apparent power of the i-th unit in the group, respectively.

[0098] In equations (23) and (24): Z ln Z represents the impedance of the collector line of the nth unit in a trunk topology after being converted to a radial topology; i P is the collector line impedance of the i-th unit in the trunk topology; i Z represents the output power of the i-th unit in the trunk topology; eq Z is the equivalent impedance of the collector line; li The impedance of the collector line of the i-th unit in this group is transformed.

[0099] Step 4.6: Based on the calculation results of the equivalent calculation parameters, a multi-unit equivalent model of the doubly-fed induction generator (DFIG) wind farm is built in MATLAB / Simulink. A detailed farm model and a traditional single-unit equivalent model are used for comparative analysis to evaluate the effectiveness of the multi-unit equivalent model. The actual topology of the DFIG wind farm used in this embodiment is as follows: Figure 4 As shown;

[0100] Step 4.7: Perform a 2-second offline simulation in MATLAB / Simulink. At t=1s, change the power grid from a strong grid to a weak grid. The active and reactive power waveforms can be locally magnified and compared as follows. Figure 5 , Figure 6 As shown, error analysis is then performed to evaluate the multi-machine equivalent effect.

[0101] Table 1 Parameters of a Single Doubly Fed Wind Turbine Unit Connected to the Grid

[0102]

[0103] Table 1 shows the specific values ​​of each component and control parameter in the doubly fed wind turbine grid-connected system used in this embodiment.

[0104] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0105] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

Claims

1. A multi-unit equivalent method for a doubly-fed wind farm considering impedance characteristics and synchronization mechanisms, characterized in that, Includes the following steps: Step 1: Establish a mathematical model for a doubly-fed wind turbine single-unit grid-connected system based on a virtual synchronization mechanism: Step 1.1: Use a virtual synchronization mechanism to simulate the working process of a synchronous generator, obtain the rotor motion equation and reactive voltage equation, and use them to control the active and reactive power of a doubly-fed wind power unit. Step 1.2: Only consider the impact of the rotor-side converter on the grid-connected system of a single doubly-fed wind turbine, and ignore the impact of the grid-side converter on the grid-connected system of a single doubly-fed wind turbine, so as to establish a control model of the rotor-side converter based on the virtual synchronization mechanism. Step 1.3: Model the induction motor and transmission line in the doubly fed wind power single-unit grid-connected system, so as to form a complete system model together with the control model; Step 2: Establish a small disturbance impedance model for a doubly-fed wind turbine single-unit grid-connected system and perform impedance analysis: Step 2.1: On the complete system model, determine the equilibrium point of each state variable, and inject a small disturbance signal at the equilibrium point to obtain the open-loop impedance models of the induction motor, the virtual synchronization mechanism, the voltage outer loop and the current inner loop respectively. Step 2.2: Based on the inherent relationship between the various open-loop impedance models, obtain the impedance model of the doubly fed wind power single-unit grid-connected system based on the virtual synchronization mechanism in the dq rotating coordinate system. Step 2.3: Transform the impedance model in the dq rotating coordinate system into the positive and negative sequence impedance model in the abc stationary coordinate system using impedance transformation theory; Step 2.4: Establish a grid impedance model based on the grid impedance in a doubly-fed wind turbine single-unit grid-connected system; Step 2.5: Sequentially change the virtual inertia coefficient, damping coefficient, and grid impedance parameters in the virtual synchronization mechanism to obtain the positive sequence impedance amplitude-frequency curve and phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system, as well as the positive sequence impedance amplitude-frequency curve and phase frequency characteristic curve of the grid impedance model. Step 2.6: Based on the relationship between the positive sequence impedance amplitude-frequency curve of the doubly fed wind turbine single unit grid-connected system and the positive sequence impedance amplitude-frequency curve of the grid impedance model, and the relationship between the phase frequency characteristic curve of the doubly fed wind turbine single unit grid-connected system and the phase frequency characteristic curve of the grid impedance model, the influence of different parameters on the stability of the doubly fed wind turbine single unit grid-connected system is analyzed using the stability criterion, and the impedance analysis results of the doubly fed wind turbine single unit grid-connected system are obtained. Step 3: Select the clustering indicators and obtain their data: Step 3.1: Based on the impedance analysis results of the doubly fed wind turbine single-unit grid-connected system, the virtual inertia coefficient, damping coefficient, wind speed of each doubly fed wind turbine, and the distance between each doubly fed wind turbine and the grid connection point are used as the equivalent grouping index for the multi-unit grid at the site. Step 3.2: Query the wind farm design plan to obtain the distance between each doubly fed wind turbine and the grid connection point; Step 3.3: Obtain wind speed data for each doubly-fed wind turbine using the anemometer on the wind turbine. Step 3.4: Based on the measured data, the complete system model is processed using the identification algorithm to obtain the virtual inertia coefficient and damping coefficient of each doubly fed wind turbine. Step 4: Multi-unit equivalent analysis of a doubly-fed wind farm: Step 4.1: Standardize the cluster index data of each unit in the collected doubly fed wind farm and filter out abnormal data to obtain preprocessed cluster index data; Step 4.2: Use the elbow method to obtain the optimal number of clusters K for the field; Step 4.3: Based on the optimal number of clusters K and the preprocessed cluster index data, randomly select cluster centers and use the K-means algorithm to iterate through the cluster centers to obtain the division results of the doubly fed wind turbine groups in the doubly fed wind farm and the optimal cluster center of each doubly fed wind turbine group. Step 4.4: Based on the division results of the doubly fed wind farm, each cluster in the division results is regarded as an equivalent unit, and the parameters of each equivalent unit are calculated. Thus, the doubly fed wind farm is equivalently represented by K equivalent units, and the multi-unit equivalent of the doubly fed wind farm is completed.

2. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor in executing the multi-machine equivalent method of claim 1, wherein the processor is configured to execute the program stored in the memory.

3. A computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to perform the steps of the multi-machine equivalent method of claim 1.

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