Method and device for controlling doubly-fed droop network-forming type wind turbine generator and storage medium

Abstract

The invention provides a doubly-fed droop net-forming type wind turbine generator control method and device and a storage medium, in active power control of a doubly-fed net-forming type wind turbine generator rotor side converter, on one hand, droop control is added, cooperative work of multiple wind turbine generators can be achieved, the power stability of a whole wind power plant is improved, and on the other hand, droop control is added to control the active power of the doubly-fed net-forming type wind turbine generator rotor side converter; a technical guarantee is provided for large-scale wind power integration; on the other hand, a variable, namely an inertia response participation coefficient, capable of directly controlling the inertia response participation degree of the unit is introduced, a self-synchronization real-time stabilization control algorithm is designed, the frequency change trend of the power grid is predicted, the inertia response participation coefficient is dynamically modified according to a frequency prediction result, and self-adjustment and self-stabilization of inertia response are achieved. Therefore, the stability of the wind turbine generator is expected in advance under the condition of large-range fluctuation of the frequency, and the operation stability under the condition of large disturbance of the power grid frequency is improved by dynamically modifying the inertia response participation coefficient.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbine control, and in particular relates to a control method, a device and a storage medium for a double-fed drooping grid-type wind turbine. Background Art

[0002] In the development of wind turbine control methods, the "grid-following" wind turbine control has dominated for quite a long time. Its main features are to obtain the grid phase angle through the PLL (phase locked loop), rely on the large grid for grid synchronization, and adopt a converter control strategy based on vector control. In this control method, the power output of the wind turbine is "decoupled" from the frequency change of the grid. The change of the grid frequency will not affect the power output of the wind turbine. It mainly relies on the synchronous generator of the thermal power plant to achieve the inertia response effect.

[0003] However, with the increase in the grid-connected capacity of wind turbines and the improvement in wind power penetration, the capacity share of synchronous generators in thermal power plants has dropped significantly. At this time, relying solely on the inertia response of synchronous generators in thermal power plants can no longer cope with the frequency change problem under the background of high-proportion wind power grid connection. For this reason, the "grid-building" control strategy of wind turbines has emerged. Its main feature is that it can achieve grid synchronization without the need for a PLL phase-locked loop by simulating the rotor motion equation of the synchronous generator; at the same time, it has an inertia response capability similar to that of a synchronous generator, and can sense grid frequency changes and adjust the wind turbine power output in a targeted manner while the grid frequency changes, achieving a "virtual inertia response" effect similar to that of a synchronous generator, reflecting the "grid-friendly" grid-connected power generation characteristics similar to those of traditional synchronous generators.

[0004] However, the existing network control strategy still has the following two problems:

[0005] One is the poor stability of multi-machine operation. The existing grid-type control strategy can achieve stable operation of a single machine, but when the number of wind turbines increases and multiple machines are involved in parallel power generation, it is difficult to achieve good coordinated control.

[0006] The second is the poor stability of inertia response. The current grid-type control strategy can only cope with small-scale grid frequency fluctuations. When the grid frequency fluctuates greatly, the wind turbine in the traditional grid-type control strategy needs to significantly increase or decrease the speed to provide power support; but this will cause the wind turbine speed to lose control and the output power to oscillate and diverge, greatly affecting the operational stability of the wind turbine. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a control method, device and storage medium for a doubly-fed drooping grid-type wind turbine generator set, so as to solve the stability problem of traditional grid-type control strategies.

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

[0009] A control method for a double-fed droop grid-type wind turbine generator set is provided, in which droop control is added to the active power control of a rotor-side converter of the double-fed grid-type wind turbine generator set.

[0010] Furthermore, in the active power control:

[0011] Torque difference ΔT e and droop control coefficient k te_gain Multiply to get the droop torque T e_gain ;

[0012] Actual grid frequencyω g With the first-order inertia link 1 / (k c s+1) to obtain the inertia response frequency ω g_kc ;

[0013] Inertia response frequency ω g_kc Same droop torque T e_gain Add together to get the virtual synchronous speed ω vsg ;ω vsg Input integrator ω b / s to get the virtual rotor angle θ vsg ; Virtual rotor angle θ vsg With rotor angle θ r Difference, get the slip angle θ slip .

[0014] Furthermore, the first-order inertia link 1 / (k c s+1), k c is the inertia response participation coefficient, and s is the Laplace operator; where:

[0015] When the grid frequency changes When k is within the threshold range, c is the initial value;

[0016] When the grid frequency changes After exceeding the threshold, k c Perform real-time dynamic correction to stabilize wind turbines.

[0017] Furthermore, k is c To make real-time dynamic corrections:

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

[0019]

[0020] Among them, D DFIGis the damping coefficient of the wind turbine; k M is the optimal proportional coefficient of the fan aerodynamic part, k opt k is the optimal proportional coefficient of the converter MPPT maximum power control, c,t is the inertia response participation coefficient at time t, α is the weight coefficient, is the estimated value of the grid frequency change rate at time t+1;

[0021] S2, adjust the inertia response participation coefficient k at time t+1 c,t+1 :

[0022]

[0023] Where β is the adjustment coefficient.

[0024] Further, α=4, β=0.9.

[0025] Furthermore, by fitting the time-dependent function of the grid frequency at past moments, the grid frequency change rate at time t+1 is estimated: include:

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

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

[0028] Step 3: Derivative the function Wg(t′) to calculate the estimated value of the grid frequency change rate at time t+1

[0029] Furthermore, in the active power control, the actual speed of the wind turbine is r Through the maximum power tracking MPPT link, the given value T of the electromagnetic torque of the wind turbine is obtained. e * ; T e * The actual value of electromagnetic torque of wind turbine T e Make a difference and get the torque difference ΔT e ;

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

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

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

[0033] The given value of the q-axis component of the rotor flux is ψ rq * 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 double-fed drooping grid-type wind turbine control device, comprising 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 implement the above-mentioned double-fed drooping grid-type wind turbine control method when executing the computer program.

[0038] A storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to execute the above-mentioned control method for a doubly-fed drooping grid-type wind turbine set.

[0039] The beneficial effects of the present invention are:

[0040] (1) The present invention provides a control method for a doubly-fed droop-grid-type wind turbine set. By adding droop control to the active power control loop, the coordinated operation of multiple wind turbine sets can be achieved, the power stability of the entire wind farm can be improved, and technical support can be provided for large-scale wind power grid connection.

[0041] (2) Introduce a variable that can directly control the degree of participation of the unit inertia response, namely, the inertia response participation coefficient k c , and design a self-synchronous real-time stabilization control algorithm to predict the frequency change trend of the power grid, and dynamically modify the inertia response participation coefficient k according to the frequency prediction results c, achieving self-regulation and self-stabilization of inertia response. In this way, the stability of wind turbines can be anticipated in advance when the frequency fluctuates over a large range, and the operation stability can be improved in the case of large disturbances in the grid frequency by dynamically modifying the inertia response participation coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a control block diagram of a double-fed drooping grid-type wind turbine in an embodiment of the present application;

[0043] Figure 2 This is a flow chart of the self-synchronous real-time stabilization control algorithm in the embodiment of the present application;

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

[0045] Figure 4 This is the simulation result diagram of traditional network control;

[0046] Figure 5 This is a simulation result diagram of the control method of the present invention. DETAILED DESCRIPTION

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

[0048] 1. Methods

[0049] The control method of the doubly-fed drooping grid-type wind turbine set proposed in the present invention redesigns the control strategy of the rotor-side converter based on the existing control method of the doubly-fed grid-type wind turbine set:

[0050] On the one hand, it enables the doubly-fed wind turbine to achieve droop control while retaining the basic capacity of the grid-forming type, thereby improving the stability of multiple machines during operation.

[0051] On the other hand, the inertia response participation coefficient is introduced, and a self-synchronization real-time stabilization control algorithm is designed and proposed in a targeted manner. The grid frequency change trend is predicted according to information such as the grid frequency. The inertia response participation coefficient is modified dynamically in real time based on the expected frequency change trend, so that the wind turbine has the ability of self-synchronization and real-time stabilization, improves the ability to cope with large-scale fluctuations in grid frequency, and ensures the stability of wind turbine operation.

[0052] like Figure 1As shown in FIG. 1 , the control strategy of the rotor side converter includes active power control and reactive power control. In the figure, DFIG stands for Doubly Fed Induction Generator, RSC stands for Rotor Side Converter, and U dc Indicates the DC voltage on the DC side of the converter, U g Indicates the grid voltage, P s Indicates the active power on the stator side, Q s Represents the stator side reactive power (actual value), ω r is the actual speed of the wind turbine, I r is the rotor current.

[0053] 1. Active power control

[0054] 1.1) Actual speed of wind turbine ω r Through the maximum power point tracking (MPPT) link, the given value T of the electromagnetic torque of the wind turbine is obtained. e * ;

[0055] 1.2) T e * The actual value of electromagnetic torque of wind turbine T e Make a difference and get the torque difference ΔT e ;

[0056] 1.3) Torque difference ΔT e The droop control coefficient k of the wind turbine te_gain Multiply to get the droop torque T e_gain Based on this, droop control is added to the control of doubly-fed grid-connected wind turbines;

[0057] 2) Actual grid frequency ω g With 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, s is the Laplace operator;

[0058] 3.1) Inertia response frequency ω g_kc Same droop torque T e_gain Add together to get the virtual synchronous speed ω vsg ;

[0059] 3.2)ω vsg Input integrator ω b / s to get the virtual rotor angle θ vsg , integrator ω b / s inωb is the grid reference frequency;

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

[0061] 2. Reactive power control

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

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

[0064] 2) Given value of the q-axis component of the rotor flux ψ rq * 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 by: Based on the slip angle θ slip The rotor current I r Perform coordinate system conversion from abc to dq, and then calculate the flux to obtain the d-axis component ψ of the generator rotor flux rd and the 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) to generate a pulse control signal to control the operation of the rotor side converter (RSC).

[0067] 3. Inertia response participation coefficient k c

[0068] 1) When the grid frequency changes When it is within the predetermined threshold range, the inertia response participation coefficient k c According to the preset initial value k c,0 Participate in wind turbine control;

[0069] 2) When the grid frequency changes After exceeding the threshold, refer to Figure 2 As shown, the inertia response participation coefficient k c Dynamic correction is performed according to the following self-synchronous real-time stabilizing control algorithm:

[0070] Step 1: For the current moment (time t), collect the grid frequency ω at the last two moments (time t and time t-1) g,t and ω g,t-1 ; The specific sampling channel can be through a PLL phase-locked loop or other frequency sensor, and the above time is the sampling time of the sensor;

[0071] Step 2: Based on the grid frequency sampling data, the second-order fitting method is used to perform a second-order fitting on the change of the grid frequency over time to obtain the grid frequency ω at time t. g Function ω of the change of time t′ g,t′ =Wg(t′); In addition to the second-order function used for fitting, other higher-order functions can also be used for fitting. In the corresponding step 1, the past power grid frequency data corresponding to the order needs to be collected.

[0072] Step 3: Derivative the function Wg(t′) to calculate the estimated value of the grid frequency change rate at the next moment (t+1 moment)

[0073]

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

[0075]

[0076] Among them, D DFIG is the damping coefficient of the wind turbine; k M is the optimal proportional coefficient of the fan aerodynamic part, k opt k is the optimal proportional coefficient of the converter MPPT maximum power control, c,t is the inertia response participation coefficient at the current moment (time t), α is the weight coefficient, which is set to 4 in this embodiment;

[0077] Step 5, based on Δ t According to the numerical situation, adjust the inertia response participation coefficient k at the next moment (t+1 moment) c,t+1 :

[0078]

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

[0080] If Δ t >0, indicating that the stability condition is met and the wind turbine is expected to be able to operate normally at the next sampling moment, so the inertia response participation coefficient at the next moment remains unchanged;

[0081] If Δ t ≤0, indicating that the stability condition is not met. It is expected that the wind turbine will be out of control at the next sampling moment, and it is necessary to take correction measures for the inertia response participation coefficient. In this embodiment, k c,t+1 Assign the current k c,t 90% of.

[0082] As time goes by, the inertia response participation coefficient k is modified according to steps 1 to 5. c , until the wind turbine is forced to return to the stable operating range.

[0083] 2. Simulation Test

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

[0085] Table 1: 2MW wind turbine parameters

[0086]

[0087] Table 2: Electrical parameters of 2MW doubly-fed wind turbine

[0088]

[0089] The specific simulation test results are as follows Figure 4 and Figure 5 As shown. Figure 4 The figure shows the curves of the grid frequency and active power changing with time under the existing grid control strategy. The figure shows that when a large load is put into the grid system and a large range of frequency fluctuations occur, the wind turbine generator system has obvious power oscillation, causing the system to lose control.

[0090] Figure 5The figure shows the curves of the grid frequency, active power and inertia response participation coefficient changing with time under the control method of the present invention. Under the control strategy of the present invention, the large-scale frequency fluctuations are successfully coped with by dynamically correcting the inertia response participation coefficient, and the stable operation of the wind turbine is achieved.

[0091] 3. Devices and Storage Media

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

[0093] Among them, the memory includes a non-volatile storage medium and an internal memory; the non-volatile storage medium can store an operating system and a computer-readable code. The computer-readable code includes program instructions, which, when executed, can enable the processor to execute a control method for a double-fed drooping grid-type wind turbine. The processor is used to provide computing and control capabilities to support the operation of the entire electronic device. The memory provides an environment for the operation of the computer-readable code in the non-volatile storage medium, and when the computer-readable code is executed by the processor, the processor can execute the control method for a double-fed drooping grid-type wind turbine.

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

[0095] 2. The present application also provides a readable storage medium, which may be an internal storage unit of the electronic device described in the aforementioned embodiment, such as a 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, secure digital card, etc. equipped on the electronic device.

[0096] In the description of the present invention, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0097] The present invention is not limited to the above-mentioned embodiments. Any obvious improvement, substitution or deformation that can be made by those skilled in the art without departing from the essential content of the present invention belongs to the protection scope of the present invention.

Claims

1. A control method for a double-fed drooping grid-type wind turbine generator set, characterized in that: In the active power control of the rotor-side converter of the doubly-fed grid-connected wind turbine, droop control is added.

2. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 1 is characterized in that: In the active power control: Torque difference ΔT e and droop control coefficient k te_gain Multiply to get the droop torque T e_gain ; Actual grid frequencyω g With the first-order inertia link 1 / (k c s+1) to obtain the inertia response frequency ω g_kc ; Inertia response frequency ω g_kc Same droop torque T e_gain Add together to get the virtual synchronous speed ω vsg ;ω vsg Input integrator ω b / s to get the virtual rotor angle θ vsg ; Virtual rotor angle θ vsg With rotor angle θ r Difference, get the slip angle θ slip .

3. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 2 is characterized in that: The first-order inertia link 1 / (k c s+1), k c is the inertia response participation coefficient, and s is the Laplace operator; where: When the grid frequency changes When k is within the threshold range, c is the initial value; When the grid frequency changes After exceeding the threshold, k c Perform real-time dynamic correction to stabilize wind turbines.

4. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 3 is characterized in that: k is calculated as follows c To make real-time dynamic corrections: S1, calculate the quantitative stability criterion Δ t : Among them, D DFIG is the damping coefficient of the wind turbine; k M is the optimal proportional coefficient of the fan aerodynamic part, k opt k is the optimal proportional coefficient of the converter MPPT maximum power control, c,t is the inertia response participation coefficient at time t, α is the weight coefficient, is the estimated value of the grid frequency change rate at time t+1; S2, adjust the inertia response participation coefficient k at time t+1 c,t+1 : Where β is the adjustment coefficient.

5. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 4 is characterized in that: α＝4，β＝0.9。 6. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 4 is characterized in that: By fitting the time-varying function of the grid frequency at past moments, the estimated value of the grid frequency change rate at time t+1 is estimated include: Step 1: Collect the grid frequency ω at the last two moments g,t and ω g,t-1 ; Step 2: Perform a second-order fitting on the change of the grid frequency over time to obtain the grid frequency ω at time t. g Function ω of the change of time t′ g,t′ =Wg(t′); Step 3: Derivative the function Wg(t′) to calculate the estimated value of the grid frequency change rate at time t+1 7. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 2 is characterized in that: In the active power control, the actual speed of the wind turbine is r Through the maximum power tracking MPPT link, the given value T of the electromagnetic torque of the wind turbine is obtained. e * ; T e * The actual value of electromagnetic torque of wind turbine T e Make a difference and get the torque difference ΔT e ; The rotor angle θ r The actual speed of the wind turbine is ω r Input integrator ω b / s obtained.

8. The control method of the doubly-fed drooping grid-type wind turbine generator set according to claim 1, characterized in that: The reactive power control of the rotor side converter is: Stator side reactive power set value Q s * With the actual value Q s The difference is input into the PI controller to obtain the given value ψ of the rotor flux d-axis component rd * ; ψ rd * The actual value of the rotor flux d-axis component ψ rd The difference is input into the PI controller to obtain the input U of the inverse coordinate transformation md ; The given value of the q-axis component of the rotor flux is ψ rq * 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.

9. A double-fed drooping grid-type wind turbine control device, 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 implement the control method of the doubly-fed drooping grid-type wind turbine set as claimed in any one of claims 1 to 8 when executing the computer program.

10. A storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the processor executes the control method of a doubly-fed drooping grid-type wind turbine set according to any one of claims 1 to 8.

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