A doubly-fed droop network type wind turbine control method and device and storage medium

Abstract

The application provides a doubly-fed droop network type wind turbine control method, device and storage medium, wherein in active power control of a rotor side converter of a doubly-fed network type wind turbine, droop control is added on one hand, cooperative work of multiple wind turbines is realized, power stability of the whole wind farm is improved, and technical support is provided for large-scale wind power grid connection; on the other hand, a variable that can directly control the participation degree of inertia response of the unit, namely an inertia response participation coefficient, is introduced, a self-synchronous real-time stability control algorithm is designed, a power grid frequency change trend is predicted, the inertia response participation coefficient is dynamically modified according to the frequency prediction result, and self-regulation and self-stabilization of the inertia response are realized. Therefore, in the case of large range frequency fluctuation, the stability of the wind turbine is expected in advance, the inertia response participation coefficient is dynamically modified, and the operation stability in the case of large power grid frequency disturbance is improved.

Description

Technical Field

[0001] This invention belongs to the field of wind turbine control technology, specifically relating to a control method, device, and storage medium for a doubly fed droop-grid wind turbine. Background Technology

[0002] For a considerable period during the development of wind turbine control methods, "grid-following" wind turbine control dominated. Its main characteristics are obtaining the grid phase angle through a PLL (phase-locked loop), relying on the large power grid for grid synchronization, and employing a converter control strategy based on vector control. In this control method, the wind turbine's power output is "decoupled" from grid frequency changes; grid frequency variations do not affect the wind turbine's power output, and the inertial response effect is primarily achieved through the synchronous generators of thermal power plants.

[0003] However, with the increase in grid-connected wind turbine capacity and the rise in wind power penetration, the proportion of synchronous generator units in thermal power plants has significantly decreased. At this point, relying solely on the inertial response of synchronous generators in thermal power plants is no longer sufficient to address frequency variations in the context of high-proportion wind power grid connection. Therefore, a "grid-based" control strategy for wind turbines has emerged. Its main characteristics are: by simulating the rotor motion equations of a synchronous generator, grid synchronization can be achieved without a PLL (phase-locked loop); simultaneously, it possesses inertial response capabilities similar to synchronous generators, enabling it to sense grid frequency changes and adjust wind turbine power output accordingly, achieving a "virtual inertial response" effect similar to that of a synchronous generator, thus exhibiting "grid-friendly" grid-connected power generation characteristics similar to traditional synchronous generators.

[0004] However, existing network-based control strategies still have the following two problems:

[0005] One issue is the poor stability of multi-unit operation. Existing grid-based control strategies can achieve stable operation of a single unit, but when the number of wind turbines increases and multiple units generate electricity in parallel, it becomes difficult to achieve good coordinated control.

[0006] Secondly, the inertial response stability is poor. Current grid-based control strategies can only cope with small-scale grid frequency fluctuations. When grid frequency fluctuations are large, wind turbines in traditional grid-based control strategies need to significantly increase or decrease their speed to provide power support; however, this will cause the wind turbine speed to run out of control, and the output power to oscillate and diverge, which will greatly affect the operational stability of the wind turbine. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a doubly-fed droop-grid wind turbine control method, device, and storage medium to solve the stability problem of traditional grid-type control strategies.

[0008] The present invention achieves the above-mentioned technical objectives through the following technical means.

[0009] A control method for a doubly-fed droop-grid wind turbine generator incorporates droop control into the active power control of the rotor-side converter of the doubly-fed grid-grid wind turbine generator.

[0010] Furthermore, in the active power control:

[0011] Torque difference ΔT e With droop control coefficient k te_gain Multiplying them together gives the droop torque T. e_gain ;

[0012] Actual frequency ω of the power grid g With first-order inertial element 1 / (k c Multiplying by s+1) yields the inertial response frequency ω. g_kc ;

[0013] Inertial response frequency ω g_kc Same droop torque T e_gain The virtual synchronous speed ω is obtained by adding them together. vsg ;ω vsg Input integrator ω b / s obtains the virtual rotor angle θ vsg Virtual rotor angle θ vsg With rotor angle θ r By subtracting the values, we obtain the slip angle θ. slip .

[0014] Furthermore, the first-order inertial element 1 / (k c In s+1), k c Let be the inertial response participation coefficient, and s be the Laplace operator; where:

[0015] When the grid frequency change rate When within the threshold range, k c Initial value;

[0016] When the grid frequency change rate After exceeding the threshold, for k c Real-time dynamic corrections are made to stabilize the wind turbine units.

[0017] Furthermore, k is processed as follows: c Perform real-time dynamic correction:

[0018] S1, calculate the stability quantification criterion Δ t :

[0019]

[0020] Among them, D DFIGk is the damping coefficient of the wind turbine. M k is the optimal proportional coefficient for the aerodynamic components of the fan. opt k is the optimal proportional coefficient for maximum power control of the converter's MPPT. c,t Let α be the inertial response participation factor at time t, and α be the weighting factor. The estimated value of the rate of change of the power grid frequency at time t+1;

[0021] S2, Adjust the inertial response participation factor k at time t+1 c,t+1 :

[0022]

[0023] Where β is the adjustment coefficient.

[0024] Furthermore, α = 4, β = 0.9.

[0025] Furthermore, by fitting the past changes in grid frequency with respect to time, the estimated value of the rate of change of grid frequency at time t+1 is predicted. include:

[0026] Step 1: Collect the power grid frequency ω at the two most recent moments. g,t and ω g,t-1 ;

[0027] Step 2: Perform a second-order fit on the change of the power grid frequency over time to obtain the power grid frequency ω at time t. g The function of ω with respect to time t′ g,t′ =Wg(t′);

[0028] Step 3: Differentiate the function Wg(t′) and calculate the estimated rate of change of the power grid frequency at time t+1.

[0029] Furthermore, in the active power control, the actual rotational speed ω of the wind turbine generator... r The setpoint T of the electromagnetic torque of the wind turbine is obtained through the maximum power point tracking (MPPT) circuit. e * ;T e * The actual value T of the electromagnetic torque of the wind turbine e By subtracting the values, we obtain the torque difference ΔT. e ;

[0030] The rotor angle θ r The actual speed ω of the wind turbine r Input integrator ω b / s is obtained.

[0031] Furthermore, the reactive power control of the rotor-side converter is as follows:

[0032] The given value of reactive power on the stator side, Q s * With actual value Q s The difference is input to the PI controller to obtain the given value ψ of the d-axis component of the rotor flux linkage. rd * ;ψ rd * The actual value of the d-axis component of the rotor flux linkage ψ rd The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. md ;

[0033] The given value ψ of the q-axis component of the rotor flux linkage rq * Compared with the actual value ψ rq The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. mq ;

[0034] U md U mq slip angle θ slip Input the inverse coordinate transformation, and input the transformation result into SVPWM to generate a pulse control signal to control the operation of the rotor-side converter.

[0035] A control device for a doubly fed droop-grid wind turbine includes a memory and a processor;

[0036] The memory is used to store computer programs;

[0037] The processor is used to execute the computer program and, in executing the computer program, implement the above-described doubly-fed droop-grid wind turbine control method.

[0038] A storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the aforementioned doubly-fed droop-grid wind turbine control method.

[0039] The beneficial effects of this invention are as follows:

[0040] (1) This invention provides a control method for a doubly fed droop-grid wind turbine. By adding droop control to the active power control loop, multiple wind turbines can work together, improving the power stability of the entire wind farm and providing technical support for large-scale wind power grid connection.

[0041] (2) Introduce a variable that can directly control the degree of participation of the unit's inertial response, namely the inertial response participation coefficient k. c A self-synchronizing real-time stabilizing control algorithm was designed to predict the trend of power grid frequency changes and dynamically modify the inertial response participation coefficient k based on the frequency prediction results. cThis enables self-adjustment and self-stabilization of the inertial response. Consequently, under conditions of large frequency fluctuations, the stability of the wind turbine can be anticipated in advance, and operational stability under large grid frequency disturbances can be improved by dynamically modifying the inertial response participation coefficient. Attached Figure Description

[0042] Figure 1 This is a control block diagram of a doubly-fed droop-grid wind turbine in an embodiment of this application;

[0043] Figure 2 This is a flowchart of the self-synchronous real-time stabilization control algorithm in the embodiments of this application;

[0044] Figure 3 This is a schematic diagram of the simulation structure in the embodiments of this application;

[0045] Figure 4 The simulation results are shown in the figure for traditional network control.

[0046] Figure 5 The figure shows the simulation results of the control method of the present invention. Detailed Implementation

[0047] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein similar or identical reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0048] I. Methods

[0049] The control method for doubly-fed droop-grid wind turbines proposed in this invention redesigns the control strategy for the rotor-side converter based on existing doubly-fed grid-grid wind turbine control methods.

[0050] On the one hand, it enables doubly fed wind turbines to achieve droop control while retaining the basic grid-connected capabilities, thereby improving the stability of multi-unit operation.

[0051] On the other hand, an inertial response participation coefficient is introduced, and a self-synchronizing real-time stabilization control algorithm is designed and proposed. Based on information such as grid frequency, the grid frequency change trend is predicted, and the inertial response participation coefficient is dynamically modified in real time based on the expected frequency change trend. This enables the wind turbine to have self-synchronizing real-time stabilization capability, improves its ability to cope with large-scale fluctuations in grid frequency, and ensures the stability of wind turbine operation.

[0052] like Figure 1As shown, the control strategy of the rotor - side converter includes active - power control and reactive - power control. In the figure, DFIG represents a doubly - fed induction generator, RSC represents a rotor - side converter, U dc represents the DC voltage on the DC side of the converter, U g represents the grid voltage, P s represents the active power on the stator side, Q s represents the actual value of the reactive power on the stator side, ω r is the actual rotational speed of the wind turbine, I r is the rotor current.

[0053] 1. Active - power control

[0054] 1.1) The actual rotational speed ω r of the wind turbine passes through the maximum - power - point tracking (MPPT) link to obtain the given value T e * of the electromagnetic torque of the wind turbine;

[0055] 1.2) T e * is subtracted from the actual value T e of the electromagnetic torque of the wind turbine to obtain the torque difference ΔT e ;

[0056] 1.3) The torque difference ΔT e is multiplied by the droop - control coefficient k te_gain of the wind turbine to obtain the droop torque T e_gain , and based on this, droop control is added to the control of the doubly - fed grid - forming wind turbine;

[0057] 2) The actual grid frequency ω g is multiplied by the first - order inertia link 1 / (k c s + 1) to obtain the inertia - response frequency ω g_kc , where k c is the inertia - response participation coefficient and s is the Laplace operator;

[0058] 3.1) The inertia - response frequency ω g_kc is added to the droop torque T e_gain to obtain the virtual synchronous rotational speed ω vsg ;

[0059] 3.2) ω vsg is input into the integrator ω b / s to obtain the virtual rotor angle θ vsg , and in the integrator ω b / s, ωb The reference frequency for the power grid;

[0060] 3.3) Virtual rotor angle θ vsg With rotor angle θ r By subtracting the values, we obtain the slip angle θ. slip , where the rotor angle θ r The actual speed ω of the wind turbine r Input integrator ω b / s is obtained.

[0061] 2. Reactive power control

[0062] 1.1) Stator-side reactive power setpoint Q s * With actual value Q s The difference is input to the PI controller to obtain the given value ψ of the d-axis component of the rotor flux linkage. rd * ;

[0063] 1.2) Given value ψ of the d-axis component of rotor flux linkage rd * Compared with the actual value ψ rd The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. md ;

[0064] 2) The given value ψ of the q-axis component of the rotor flux linkage rq * Compared with the actual value ψ rq The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. mq ;

[0065] ψ rd and ψ rq It can be obtained in the following way: based on the slip angle θ slip Rotor current I r Perform a coordinate transformation from abc to dq, and then calculate the flux linkage to obtain the d-axis component ψ of the generator rotor flux linkage. rd and q-axis component ψ rq .

[0066] 3) Will U md U mq slip angle θ slip Input the inverse coordinate transformation and input the transformation result into SVPWM (Space Vector Pulse Width Modulation) module to generate pulse control signals to control the operation of the rotor-side converter (RSC).

[0067] 3. Inertial response participation factor k c

[0068] 1) When the grid frequency change rate When within a predetermined threshold range, the inertial response participation factor k c According to the preset initial value k c,0 Participate in wind turbine control;

[0069] 2) When the grid frequency change rate After exceeding the threshold, refer to Figure 2 As shown, the inertial response participation factor k c Dynamic correction is performed using the following self-synchronizing real-time stabilizing control algorithm:

[0070] Step 1: For the current time (time t), collect the power grid frequency ω from the two most recent times (time t and time t-1). g,t and ω g,t-1 The specific sampling channel can be a PLL phase-locked loop or other frequency sensors; the above times are the sampling times of the sensors.

[0071] Step 2: Based on the grid frequency sampling data, use the second-order fitting method to perform a second-order fitting on the change of grid frequency over time, and obtain the grid frequency ω at time t. g The function of ω with respect to time t′ g,t′ =Wg(t′); In addition to using a second-order function for fitting as described above, other higher-order functions can also be used for fitting. In the corresponding step 1, a number of past time grid frequency data corresponding to the order need to be collected.

[0072] Step 3: Differentiate the function Wg(t′) to calculate the estimated rate of change of the power grid frequency at the next time step (t+1).

[0073]

[0074] Step 4: Calculate the stability quantification criterion Δ according to the following formula. t :

[0075]

[0076] Among them, D DFIG k is the damping coefficient of the wind turbine. M k is the optimal proportional coefficient for the aerodynamic components of the fan. opt k is the optimal proportional coefficient for maximum power control of the converter's MPPT. c,t The inertial response participation coefficient at the current time (time t), where α is the weighting coefficient, which is set to 4 in this embodiment;

[0077] Step 5, based on Δ t Based on the numerical situation, adjust the inertial response participation factor k at the next time step (t+1). c,t+1 :

[0078]

[0079] Where β is the adjustment coefficient, which is set to 0.9 in this embodiment;

[0080] If Δ t If the value is >0, it means that the stability condition is met, and the wind turbine is expected to continue to operate normally until the next sampling time. Therefore, the inertial response participation coefficient remains unchanged at the next time.

[0081] If Δ t If k ≤ 0, it indicates that the stability condition is not met, and the wind turbine is expected to run away from control at the next sampling time. Therefore, correction measures need to be taken for the inertial response participation coefficient. In this embodiment, k is... c,t+1 Assign the value to the current k c,t 90%.

[0082] As time progresses, the inertial response participation factor k is cyclically adjusted according to steps 1 to 5. c This continues until the wind turbines are forced back to a stable operating range.

[0083] II. Simulation Test

[0084] like Figure 3 As shown, a 2MW doubly-fed wind turbine grid-connected model was built in the RTDS (Real-Time Digital Simulation) simulator. The specific parameters are shown in Tables 1 and 2 below:

[0085] Table 1: Parameters of a 2MW Wind Turbine

[0086]

[0087] Table 2: Electrical Parameters of 2MW Doubly Fed Wind Turbine Units

[0088]

[0089] Specific simulation test results are as follows: Figure 4 and Figure 5 As shown. Among them Figure 4 The figure shows the curves of grid frequency and active power changing over time under the existing grid-type control strategy. The figure reflects that when a large load is connected to the grid system and a wide range of frequency fluctuations occur, the wind turbines experience significant power oscillations, leading to system out of control.

[0090] Figure 5The figure shows the time-varying curves of grid frequency, active power, and inertial response participation coefficient under the control method of the present invention. Under the control strategy of the present invention, the large-scale frequency fluctuations are successfully handled by dynamically correcting the inertial response participation coefficient, thus achieving stable operation of the wind turbine.

[0091] III. Devices and Storage Media

[0092] 1. This application also provides an electronic device, which includes a processor and a memory, wherein computer-readable code is stored in the memory, wherein when the computer-readable code is executed by the processor, the doubly-fed droop-grid wind turbine control method of the present invention is implemented.

[0093] The memory includes non-volatile storage media and internal memory. The non-volatile storage media can store the operating system and computer-readable code. The computer-readable code includes program instructions that, when executed, cause the processor to perform the doubly-fed droop-grid wind turbine control method. The processor provides computational and control capabilities to support the operation of the entire electronic device. The memory provides an environment for the execution of the computer-readable code in the non-volatile storage media, which, when executed by the processor, causes the processor to perform the doubly-fed droop-grid wind turbine control method.

[0094] It should be understood that a processor can be a central processing unit, other general-purpose processors, digital signal processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, transistor logic devices, discrete hardware components, etc. Among them, a general-purpose processor can be a microprocessor or any conventional processor.

[0095] 2. This application also provides a readable storage medium, which may be an internal storage unit of the electronic device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, smart memory card, or secure digital card equipped on the electronic device.

[0096] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0097] This invention is not limited to the above-described embodiments. Any obvious improvements, substitutions, or modifications that can be made by those skilled in the art without departing from the essence of this invention are within the scope of protection of this invention.

Claims

1. A control method for a doubly-fed droop-grid wind turbine generator, characterized in that: In the active power control of the rotor-side converter of the doubly fed grid wind turbine, droop control is added; In the active power control: Torque difference ΔT e With droop control coefficient k te_gain Multiply to obtain the droop torque T e_gain ; Actual frequency ω of the power grid g With first-order inertial element 1 / (k c Multiplying by s+1) yields the inertial response frequency ω. g_kc ; Inertial response frequency ω g_kc Same droop torque T e_gain The virtual synchronous speed ω is obtained by adding them together. vsg ;ω vsg Input integrator ω b / s obtains the virtual rotor angle θ vsg Virtual rotor angle θ vsg With rotor angle θ r By subtracting the values, we obtain the slip angle θ. slip ; The first-order inertial element 1 / (k c In s+1), k c Let be the inertial response participation coefficient, and s be the Laplace operator; where: When the grid frequency change rate When within the threshold range, k c Initial value; When the grid frequency change rate If the threshold is exceeded, k is adjusted as follows: c Real-time dynamic adjustments are made to stabilize the wind turbine units. S1, calculate the stability quantification criterion Δ t : Among them, D DFIG k is the damping coefficient of the wind turbine. M k is the optimal proportional coefficient for the aerodynamic components of the fan. opt k is the optimal proportional coefficient for maximum power control of the converter's MPPT. c,t Let α be the inertial response participation factor at time t, and α be the weighting factor. The estimated value of the rate of change of the power grid frequency at time t+1; S2, Adjust the inertial response participation factor k at time t+1 c,t+1 : Where β is the adjustment coefficient.

2. The control method for a doubly-fed droop-grid wind turbine generator according to claim 1, characterized in that: α＝4，β＝0.9。 3. The control method for a doubly-fed droop-grid wind turbine generator according to claim 1, characterized in that: By fitting the function of the change in power grid frequency with respect to time in the past, the estimated value of the rate of change of power grid frequency at time t+1 is predicted. include: Step 1: Collect the power grid frequency ω at the two most recent moments. g,t and ω g,t-1 ; Step 2: Perform a second-order fit on the change of the power grid frequency over time to obtain the power grid frequency ω at time t. g The function of ω with respect to time t′ g,t′ =Wg(t′); Step 3: Differentiate the function Wg(t′) and calculate the estimated rate of change of the power grid frequency at time t+1.

4. The control method for a doubly-fed droop-grid wind turbine generator according to claim 1, characterized in that: In the active power control, the actual speed ω of the wind turbine generator is... r The setpoint T of the electromagnetic torque of the wind turbine is obtained through the maximum power point tracking (MPPT) circuit. e * ; T e * The actual value T of the electromagnetic torque of the wind turbine e By subtracting the values, we obtain the torque difference ΔT. e ; The rotor angle θ r The actual speed ω of the wind turbine r Input integrator ω b / s is obtained.

5. The control method for a doubly-fed droop-grid wind turbine generator according to claim 1, characterized in that: The reactive power control of the rotor-side converter is as follows: The given value of reactive power on the stator side, Q s * With actual value Q s The difference is input to the PI controller to obtain the given value ψ of the d-axis component of the rotor flux linkage. rd * ; ψ rd * The actual value of the d-axis component of the rotor flux linkage ψ rd The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. md ; The given value ψ of the q-axis component of the rotor flux linkage rq * Compared with the actual value ψ rq The difference is input to the PI controller to obtain the input U of the inverse coordinate transformation. mq ; U md U mq slip angle θ slip Input the inverse coordinate transformation, and input the transformation result into SVPWM to generate a pulse control signal to control the operation of the rotor-side converter.

6. A control device for a doubly-fed droop-grid wind turbine generator, characterized in that: Including memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program and, when executing the computer program, implement the doubly fed droop-grid wind turbine control method as described in any one of claims 1 to 5.

7. A storage medium, characterized in that: The system contains a computer program that, when executed by a processor, causes the processor to perform the doubly-fed droop-grid wind turbine control method as described in any one of claims 1 to 5.

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