Network-constructed wind turbine control method, parameter correction method, program product

Abstract

The application provides a network-constructed wind turbine control method, a parameter correction method and a program product, wherein the time constant of a speed outer loop PI controller is adaptively and dynamically adjusted by the parameter correction method, the time constant is reduced in a response stage to realize rapid speed drop / lift and accelerate inertia support, and the time constant is increased in a recovery stage to embody slow speed recovery characteristics, inhibit power recovery and reduce secondary drop of a power grid frequency, so that the "fast response-slow recovery" characteristics are possessed in a high constant speed / constant power stage and a low constant speed stage.

Description

Technical Field

[0001] This invention belongs to the field of wind turbine operation control technology, specifically involving control methods, parameter correction methods, and program products for grid-connected wind turbines. Background Technology

[0002] With the increase in grid-connected capacity of wind turbines, a grid-connected wind turbine control strategy has been designed to address the grid frequency changes caused by the increased wind power penetration. Its main features include achieving grid synchronization without the need for a PLL (phase-locked loop) by simulating the rotor motion equations of a synchronous generator; it also possesses inertial response capabilities similar to a synchronous generator, enabling it to sense grid frequency changes and adjust wind turbine power output accordingly, achieving a "virtual inertial response" effect and exhibiting grid-friendly power generation characteristics similar to traditional synchronous generators.

[0003] However, existing network-based control strategies are not perfect in terms of speed and inertia response control during high / low constant speed and constant power phases. Specifically, current solutions for suppressing speed overshoot rely on the outer loop PI time constant of the speed control loop being within a normal value. and trigger value Switch between them and All of these are constants that have been manually set; and because Because it is a fixed value, the effects of speed control and power support are only reflected in a single parameter. The control effect is insufficient, making it difficult to achieve the control requirement of the ideal speed curve of "fast response-slow recovery". Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a grid-type wind turbine control method, parameter correction method, and program product. By adaptively and dynamically adjusting the outer loop PI time constant of the speed control, it solves the stability problem in traditional selective inertia response control and achieves ideal speed suppression and power support control effects.

[0005] The present invention achieves the above-mentioned technical objectives through the following technical means.

[0006] A parameter correction method for grid-connected wind turbines, targeting the rotor-side converter control of grid-connected wind turbines, involves dynamically adjusting the time constant of the outer loop PI controller for the wind speed:

[0007] The wind turbine's rotational speed is periodically sampled; the wind turbine's rotational speed in the current sampling period is... ;

[0008] when When the speed is at the required level for the current operating phase, the time constant for the next sampling period takes the normal value. ;

[0009] when If the rotational speed is not at the required level for the current operating phase, the time constant of the next sampling period will be adjusted in the following way:

[0010] S1, calculate the rotational speed deviation within the current sampling period. and the rate of change of rotational speed ;

[0011] S2, based on and Fuzzy logic reasoning is used to generate the change in time constant. ;

[0012] S3, based on The time constant of the next sampling period is adjusted based on the current time constant.

[0013] Furthermore, the speed deviation for The difference between the speed and the speed to be maintained during the current operating phase:

[0014]

[0015] In the formula, and These are the minimum and maximum permissible speeds of the wind turbine generator set, respectively.

[0016] Rate of change of rotational speed The calculation is as follows:

[0017]

[0018] In the formula, This represents the sampling period step size.

[0019] Furthermore, in S2, respectively for and There are multiple fuzzy sets defined; in fuzzy logic reasoning, based on and The fuzzy set into which both fall, and according to Values ​​and and Fuzzy rules between the two fuzzy sets are generated. .

[0020] Furthermore, during the low constant speed operation phase, when At that time, Conversely, based on Adjustment ;

[0021] During the high constant speed operation phase, when At that time, Conversely, based on Adjustment ;

[0022] In the formula, , , , For interval range parameters, and These are the time constants of the outer loop PI controller for the low constant speed operation phase and the high constant speed operation phase, respectively. and These are the current sampling periods. and , and The next sampling period is respectively and .

[0023] Furthermore, in S3, an energy function is first constructed based on the Lyapunov stability principle, and the system stability is judged based on the energy function; when the system is unstable, the adjustment of the time constant for the next sampling period is stopped.

[0024] Furthermore, the energy function is:

[0025]

[0026] In the formula, for:

[0027]

[0028] With the rate of change of the energy function As a criterion for system stability:

[0029]

[0030] in:

[0031] If the system is stable, it is determined based on the change in the time constant. Adjust the time constant of the next sampling period:

[0032]

[0033] If the system is unstable, the time constant of the next sampling period remains unchanged.

[0034]

[0035] In the formula, and These are the time constants of the outer loop PI controller for the low constant speed operation phase and the high constant speed operation phase, respectively. and These are the current sampling periods. and , and The next sampling period is respectively and .

[0036] A control method for grid-type wind turbines is proposed, which adjusts the time constant of the outer loop PI controller based on the above-mentioned parameter correction method for grid-type wind turbines, and implements rotor-side converter control of the grid-type wind turbine.

[0037] Furthermore, the following control strategy for the rotor-side converter of the grid-connected wind turbine is adopted, including:

[0038] Module 1, the outer loop adaptive correction control module for rotational speed, includes a low constant speed outer loop PI controller and a high constant speed outer loop PI controller, wherein:

[0039] During the low constant speed operation phase, the electromagnetic torque setpoint of the wind turbine is output by the low constant speed outer loop PI controller. In the low constant speed outer loop PI controller: the input is the wind turbine speed. With minimum permissible speed The difference is such that the lower limit of the integral is 0, and the upper limit of the integral is... The time constant is , For optimal power coefficient;

[0040] During the maximum power operation phase of MPPT, the electromagnetic torque setpoint of the wind turbine unit = ;

[0041] During the high constant speed operation phase, the electromagnetic torque setpoint of the wind turbine is output by the high constant speed outer loop PI controller. In the high constant speed outer loop PI controller: the input is the wind turbine speed. With the maximum permissible speed The difference, the lower limit of integration is The integral upper limit is the maximum torque of the wind turbine. The time constant is ;

[0042] Module 2, Selective Judgment Module, based on power grid frequency Wind turbine speed Perform operational status assessment and set the inertial response frequency based on the operational status. The possible values ​​of are:

[0043] When the wind turbine is in a high constant speed or constant power stage, and the grid frequency... When lifted due to load shearing, = ;

[0044] When the wind turbine is in a low constant speed phase and the grid frequency When the load decreases, = ;

[0045] In other operating states, the frequency is determined by the power grid. With first-order inertial elements Multiply to get The possible values ​​of ; where The participation factor in the inertial response. It is a Laplace operator;

[0046] Module 3, Active Power Control Module, wherein:

[0047] electromagnetic torque setpoint of wind turbine Compared with actual value By subtracting, we obtain the torque difference. ;

[0048] Equivalent synchronous angular velocity Multiply by virtual damping coefficient The virtual inertia deviation is obtained. ;

[0049] Torque difference With virtual inertia deviation The difference is processed by an integrator. Obtain the equivalent synchronous angular velocity , This is the virtual inertia coefficient;

[0050] Equivalent synchronous angular velocity With inertial response frequency Add them together to obtain the virtual synchronous angular velocity. ;

[0051] Virtual synchronous angular velocity via integrator Obtain the virtual rotor angle , The reference frequency for the power grid;

[0052] Virtual rotor angle With rotor angle By subtracting the values, we obtain the slip angle. It is used to generate pulse control signals to control the operation of the rotor-side converter.

[0053] A computer program product includes a computer program that, when executed by a processor, implements the above-described method for correcting parameters of a grid-connected wind turbine.

[0054] A computer program product includes a computer program that, when executed by a processor, implements the above-described grid-connected wind turbine control method.

[0055] The beneficial effects of this invention are as follows:

[0056] (1) This invention provides a grid-type wind turbine control method and a parameter correction method. The parameter correction method adaptively and dynamically adjusts the time constant of the outer loop PI controller of the speed. In the response phase, the time constant is reduced to achieve a rapid drop / rise of the speed and accelerate the inertia support. In the recovery phase, the time constant is increased to reflect the slow recovery characteristics of the speed, suppress power withdrawal, and reduce the secondary drop of the grid frequency. Thus, it has the characteristics of "fast response-slow recovery" in the high constant speed / constant power phase and the low constant speed phase.

[0057] (2) The present invention designs a dead zone protection mechanism. When the speed meets the safety threshold condition, the outer loop PI time constant of the speed is forcibly locked to the normal value, which forces the wind turbine to return to the stable parameter range, ensures that the speed does not exceed the limit, suppresses speed overshoot and avoids frequent false triggering.

[0058] (3) This invention uses fuzzy logic reasoning to generate the change in time constant, which has the function of predicting the trend of wind turbine speed change and realizing ultra-low delay response, which can cope with rapid disturbances such as wind speed and load change. At the same time, it constructs an energy function in combination with the ideal response requirements of fast response-slow recovery, and proposes a stability criterion based on the energy function to avoid the instability risk caused by traditional parameter switching and ensure that the system does not oscillate and become unstable during the parameter adjustment process. Attached Figure Description

[0059] Figure 1 This is a block diagram of the rotor-side converter control strategy in the grid-type wind turbine control method of the present invention;

[0060] Figure 2 A block diagram of the selective inertia response control strategy for existing doubly fed grid-connected wind turbine units;

[0061] Figure 3 A graph showing the change in wind turbine speed during the operation and control of a wind turbine unit;

[0062] Figure 4 A schematic diagram of the grid-connected model of a 2MW doubly-fed wind turbine built for this test case;

[0063] Figure 5 The curves showing the speed and torque changes of the wind turbine in this test case are shown. Detailed Implementation

[0064] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar 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.

[0065] I. Technical Solution

[0066] like Figure 2 The existing selective inertia response control strategy for doubly-fed grid-connected wind turbines (see patent document CN113765124B) suppresses speed overshoot during the inertia response recovery process by modifying the time constant of the outer-loop PI controller.

[0067] 1) When it is detected that the system is operating in a high constant speed region and the grid frequency drops, a larger time constant is used. (Reduce integral gain);

[0068] 2) When it is detected that the system is operating in a low constant speed region and the grid frequency is rising, a larger time constant is used. (Reduce integral gain);

[0069] 3) Once the rotational speed returns to the set value, switch back to the smaller normal time constant. To eliminate steady-state error;

[0070] The above time constant Typically set based on experience 100 to 150 times.

[0071] like Figure 1 The diagram shown is a control block diagram of the present invention, which is based on the above control strategy and replaces it with the improved "speed outer loop adaptive correction control module" of the present invention. Figure 2 (As shown) The existing control strategy for the rotor-side converter of a doubly fed grid wind turbine includes the "dynamic correction control module for the time constant of the outer loop of speed control" and the "outer loop of wind turbine speed control".

[0072] Therefore, the control strategy for the rotor-side converter of the grid-type wind turbine of this invention includes: ① an outer-loop adaptive speed correction control module, ② a selective judgment module, and ③ an active power control module. Among them, the ① outer-loop adaptive speed correction control module is used to output the electromagnetic torque setpoint of the wind turbine. The active power control module (③) and the selective decision module (②) are used to output the inertia response frequency. The slip angle is then output by module ③ (active power control module); finally, module ③ (active power control module) outputs the slip angle. It is used to generate pulse control signals to control the operation of the rotor-side converter.

[0073] 1. Speed ​​outer loop adaptive correction control module

[0074] There are two PI controllers: the low constant speed outer loop PI controller shown at the top of the diagram and the high constant speed outer loop PI controller shown at the bottom of the diagram.

[0075] Combination Figure 3 The wind turbine operation control process is shown below: When the wind speed starts to increase from the cut-in wind speed (the minimum speed at which the wind turbine is allowed to generate electricity), the wind turbine speed needs to be controlled. First, it proceeds through the lowest speed stage, then through the MPPT stage, the high constant speed stage, and finally the constant power stage. Among these:

[0076] (1) The wind turbine is in the low constant speed operation stage

[0077] The electromagnetic torque setpoint of the wind turbine is output by the low constant speed outer loop PI controller. ;

[0078] In the low constant speed outer loop PI controller: the input is the wind turbine speed. With minimum permissible speed The difference ( The lower limit for points is 0, and the upper limit for points is... The time constant is ;

[0079] in, For optimal power factor, The parameter correction method described below will be used for dynamic adaptive adjustment.

[0080] Output via low constant speed outer loop PI controller The power is fed into the active power control module to control the wind turbine speed. Maintain at the minimum permissible speed At the same time, the selective judgment module enables the wind turbine to have selective inertia response capability, and respond unidirectionally to the load shedding condition.

[0081] (2) The wind turbine is in the maximum power operation phase of MPPT.

[0082] Wind turbine speed at this stage At the minimum permissible speed With the maximum permissible speed Between, the electromagnetic torque setpoint of the wind turbine unit = .

[0083] (3) The wind turbine is in the high constant speed operation stage

[0084] The electromagnetic torque setpoint of the wind turbine is output by the high constant speed outer loop PI controller. ;

[0085] In the high constant speed outer loop PI controller: the input is the wind turbine speed. With the maximum permissible speed The difference ( The lower limit of the integral is The integral upper limit is the maximum torque of the wind turbine. The time constant is ;

[0086] in, The parameter correction method described below will be used for dynamic adaptive adjustment.

[0087] Output via high constant speed outer loop PI controller The power is fed into the active power control module to control the wind turbine speed. Maintain at the maximum permissible speed At the same time, the selective judgment module enables the wind turbine to have selective inertia response capability, responding unidirectionally to the load input condition.

[0088] 2. Selective Judgment Module

[0089] Based on power grid frequency Wind turbine speed Perform operational status assessment and set the inertial response frequency based on the operational status. The possible values ​​of are:

[0090] 1) When the wind turbine is in a high constant speed or constant power stage, and the grid frequency is... When lifted due to load shearing, = ;

[0091] 2) When the wind turbine is in the low constant speed stage and the grid frequency is... When the load decreases, = ;

[0092] 3) Under other operating conditions, the frequency of the power grid shall prevail. With first-order inertial elements Multiply to get The possible values ​​of ; where The participation factor in the inertial response. It is the Laplace operator.

[0093] 3. Active power control module

[0094] 1.1) Electromagnetic torque setpoint of wind turbine Compared with actual value By subtracting, we obtain the torque difference. :

[0095]

[0096] 1.2) Equivalent synchronous angular velocity Multiply by virtual damping coefficient The virtual inertia deviation is obtained. :

[0097]

[0098] 2) Torque difference With virtual inertia deviation The difference ( ), via integrator Obtain the equivalent synchronous angular velocity , This is the virtual inertia coefficient;

[0099] 3) Equivalent synchronous angular velocity With inertial response frequency Add them together to obtain the virtual synchronous angular velocity. :

[0100]

[0101] 4) Virtual synchronous angular velocity via integrator Obtain the virtual rotor angle , The reference frequency for the power grid;

[0102] 5) Virtual rotor angle With rotor angle By subtracting the values, we obtain the slip angle. :

[0103]

[0104] 4. Parameter Correction Method for Grid-Type Wind Turbines

[0105] The time constants of the two speed outer loop PI controllers in the aforementioned speed outer loop adaptive correction control module and Adaptive adjustment is performed using the following method:

[0106] 1) Periodically sample the rotational speed of the wind turbine generator, and record the current sampling period (the period of sampling). The wind turbine speed (in sampling periods) is Meanwhile, let the time constant of the current low constant speed outer loop PI controller be denoted as . The time constant of the high constant speed outer loop PI controller is ;

[0107] 2) If the required rotational speed is reached during the current operating phase, then the next sampling period (the...) The time constant (for each sampling period) is taken as a standard value. ,Right now:

[0108] ① During the low constant speed operation phase, At the lowest speed, then ;

[0109] ② High constant speed operation stage, At the highest speed, then ;

[0110] In the same technology , which is the standard value of the time constant of the outer loop PI controller for rotational speed.

[0111] 2.1) In a purely theoretical case where the influence of noise is not considered, the " "at the lowest speed" means The " "At the highest speed" means .

[0112] 2.2) However, in practice, the presence of noise can lead to frequent false triggering. Therefore, this embodiment further sets up the following "dead zone protection mechanism," wherein:

[0113] ① During the low constant speed operation phase, The condition for determining the lowest speed is:

[0114]

[0115] ② High constant speed operation stage, The condition for determining the highest speed is:

[0116]

[0117] In the formula, and The dead zone range parameter is the lowest speed. and This is the dead zone range parameter for the highest speed.

[0118] 2.3) For example, the minimum permissible speed is usually taken as the rated speed of the wind turbine. 60% of The maximum permissible speed is taken as 120% of Based on this, in this embodiment , , , The average value is 0.02. ,but:

[0119] ① During the low constant speed operation phase, hour, ;

[0120] ② High constant speed operation stage, hour, .

[0121] 3) If the speed is not at the required speed for the current operating stage, then:

[0122] 3.1) Calculate the rotational speed deviation within the current sampling period. and the rate of change of rotational speed :

[0123]

[0124]

[0125] In the formula, This represents the wind turbine rotational speed from the previous sampling period. This is the sampling period step size (i.e., the time span between two adjacent sampling times).

[0126] 3.2) Using fuzzy logic reasoning, based on speed deviation and the rate of change of rotational speed As a fuzzy input, the change in the time constant of the outer loop PI controller for the speed is generated in the next sampling period. ;in:

[0127] 3.2.1) Define four fuzzy sets “NB”, “NS”, “PS”, and “PB” to characterize the speed deviation. Size range, fuzzy set and The hierarchical relationships between them are shown in Table 1 below:

[0128] Table 1: Speed ​​Deviation fuzzy set parameter range

[0129]

[0130] The table normalizes the rotation speed to the pu value unit. The parameter range of the specific fuzzy set can be adjusted according to the actual situation.

[0131] 3.2.2) Define five fuzzy sets “NB”, “NS”, “ZO”, “PS”, and “PB” to characterize the rate of change of rotational speed. Size range, fuzzy set and The hierarchical relationships between them are shown in Table 2 below:

[0132] Table 2: Rate of Change in Rotation Speed fuzzy set parameter range

[0133]

[0134] 3.2.3) The fuzzy rule base is shown in Table 3 below:

[0135] Table 3: Fuzzy Rules

[0136]

[0137] For example, when The fuzzy set that falls into is NB. When the fuzzy set it falls into is NS, then ΔT takes the value -0.25. .

[0138] 3.3) Based on the change in time constant Adjust the time constant of the next sampling period:

[0139] ① During the low constant speed operation phase, ;

[0140] ② High constant speed operation stage, .

[0141] 3.3.1) Due to the variation of the time constant of the outer loop PI controller, the stability of the entire system will be affected, which may cause the system to oscillate and diverge, and thus the system will not be able to operate normally.

[0142] To avoid the aforementioned problems, this embodiment provides the following further improvements: An energy function is constructed based on the Lyapunov stability principle, and system stability is determined based on this energy function. When the system is unstable, the adjustment of the time constant for the next sampling period is stopped to ensure that the system does not experience system oscillation instability. Wherein:

[0143] The energy function is:

[0144]

[0145] In the formula, for:

[0146]

[0147] With the rate of change of the energy function As a criterion for system stability:

[0148]

[0149] in:

[0150] ① If the system is stable, it is determined based on the change in the time constant. Adjust the time constant of the next sampling period:

[0151]

[0152] ② If the system is unstable, the time constant of the next sampling period remains unchanged.

[0153]

[0154] The above-mentioned parameter correction method for grid-type wind turbines is repeatedly executed, and the time constant of the outer loop PI controller for the speed is adaptively and dynamically adjusted within each sampling period.

[0155] II. Test

[0156] like Figure 4 As shown, a grid-connected model of a 2MW doubly-fed wind turbine was built in the RTDS real-time digital simulator. The relevant parameters of the doubly-fed wind turbine are shown in Tables 4 and 5.

[0157] Table 4: Parameters of a 2MW Wind Turbine

[0158]

[0159] Table 5: Electrical Parameters of 2MW Doubly Fed Wind Turbine Units

[0160]

[0161] Taking the high constant speed operation phase as an example, the control method of the grid-connected wind turbine of this invention is compared with the traditional selective grid-connected wind turbine control method. The ambient wind speed is set to 10.5 m / s. After the system has been running for 6 seconds, a temporary load of 2MW is applied. The changes in the speed and torque of the wind turbine during the inertial response are observed. The results are as follows: Figure 5 As shown.

[0162] Traditional control methods can achieve selective inertia response, responding to load conditions and preventing speed overshoot in the later stages of speed recovery. However, when observing the speed curve, a "fast response-slow recovery" dynamic curve is not generated, and the speed still recovers quickly.

[0163] Under the control method of this invention, by introducing dynamic adjustment of the PI parameter, the wind turbine speed can be better controlled to exhibit a dynamic curve of "fast response-slow recovery". Specifically, in the early stage of the inertial response, the speed drops rapidly, and the electromagnetic torque increases rapidly, providing sufficient inertial response support to the power grid. In the later stage of the inertial response, the speed recovery process is slower, exhibiting a dynamic characteristic of "fast response-slow recovery" that meets the needs of the power grid.

[0164] III. Devices, storage media, and software products

[0165] 1. Based on the same inventive concept as the above-mentioned grid-type wind turbine control method and parameter correction method, this application also provides an electronic device, which includes a processor and a memory. The memory stores computer-readable code, wherein when the computer-readable code is executed by the processor, the grid-type wind turbine control method and parameter correction method of the present invention are implemented.

[0166] The memory includes non-volatile storage media and internal memory. The non-volatile storage media can store the operating system and computer-readable code. This computer-readable code includes program instructions that, when executed, cause the processor to execute grid-connected wind turbine control methods and parameter correction methods. 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; when executed by the processor, this computer-readable code causes the processor to execute grid-connected wind turbine control methods and parameter correction methods.

[0167] 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.

[0168] 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.

[0169] 3. This application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implement the grid-type wind turbine control method and parameter correction method of the present invention.

[0170] 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.

[0171] 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 method for parameter correction of a grid-connected wind turbine generator, characterized in that: For the rotor-side converter control of grid-connected wind turbines, the time constant of the outer loop PI controller for speed is dynamically adjusted: The wind turbine's rotational speed is periodically sampled; the wind turbine's rotational speed in the current sampling period is... ; when When the speed is at the required level for the current operating phase, the time constant for the next sampling period takes the normal value. ; when If the rotational speed is not at the required level for the current operating phase, the time constant of the next sampling period will be adjusted in the following way: S1, calculate the rotational speed deviation within the current sampling period. and the rate of change of rotational speed ; S2, based on and Fuzzy logic reasoning is used to generate the change in time constant. ,in: Based on their respective value ranges, respectively for and Divide into multiple fuzzy sets; The fuzzy rule is set as follows: based on and Different combinations of the two fuzzy sets are set accordingly. Values; In fuzzy logic reasoning, based on and The fuzzy sets to which both fall are generated according to fuzzy rules. ; S3, based on The time constant of the next sampling period is adjusted based on the current time constant.

2. The parameter correction method for grid-type wind turbines according to claim 1, characterized in that: The speed deviation for The difference between the speed and the speed to be maintained during the current operating phase: In the formula, and These are the minimum and maximum permissible speeds of the wind turbine generator set, respectively. Rate of change of rotational speed The calculation is as follows: In the formula, This represents the sampling period step size.

3. The parameter correction method for grid-type wind turbines according to claim 2, characterized in that: During the low constant speed operation phase, when At that time, Conversely, based on Adjustment ; During the high constant speed operation phase, when At that time, Conversely, based on Adjustment ; In the formula, , , , For interval range parameters, and These are the time constants of the outer loop PI controller for the low constant speed operation phase and the high constant speed operation phase, respectively. and These are the current sampling periods. and , and The next sampling period is respectively and .

4. The parameter correction method for grid-type wind turbines according to claim 2, characterized in that: In S3, an energy function is first constructed based on the Lyapunov stability principle, and the system stability is judged based on the energy function; when the system is unstable, the adjustment of the time constant for the next sampling period is stopped.

5. The parameter correction method for grid-type wind turbines according to claim 4, characterized in that: The energy function is: In the formula, for: With the rate of change of the energy function As a criterion for system stability: in: If the system is stable, it is determined based on the change in the time constant. Adjust the time constant of the next sampling period: If the system is unstable, the time constant of the next sampling period remains unchanged. In the formula, and These are the time constants of the outer loop PI controller for the low constant speed operation phase and the high constant speed operation phase, respectively. and These are the current sampling periods. and , and The next sampling period is respectively and .

6. A control method for a grid-connected wind turbine generator, characterized in that: Based on the parameter correction method for grid-type wind turbines according to any one of claims 1 to 5, the time constant of the outer loop PI controller for speed is adjusted to implement rotor-side converter control of the grid-type wind turbine.

7. The control method for grid-connected wind turbine generators according to claim 6, characterized in that: Rotor-side converter control strategies include: Module 1, the outer loop adaptive correction control module for rotational speed, includes a low constant speed outer loop PI controller and a high constant speed outer loop PI controller, wherein: During the low constant speed operation phase, the electromagnetic torque setpoint of the wind turbine is output by the low constant speed outer loop PI controller. In the low constant speed outer loop PI controller: the input is the wind turbine speed. With minimum permissible speed The difference is such that the lower limit of the integral is 0, and the upper limit of the integral is... The time constant is , For optimal power coefficient; During the maximum power operation phase of MPPT, the electromagnetic torque setpoint of the wind turbine unit = ; During the high constant speed operation phase, the electromagnetic torque setpoint of the wind turbine is output by the high constant speed outer loop PI controller. In the high constant speed outer loop PI controller: the input is the wind turbine speed. With the maximum permissible speed The difference, the lower limit of integration is The integral upper limit is the maximum torque of the wind turbine. The time constant is ; Module 2, Selective Judgment Module, based on power grid frequency Wind turbine speed Perform operational status assessment and set the inertial response frequency based on the operational status. The possible values ​​of are: When the wind turbine is in a high constant speed or constant power stage, and the grid frequency... When lifted due to load shearing, = ; When the wind turbine is in a low constant speed phase and the grid frequency When the load decreases, = ; In other operating states, the frequency is determined by the power grid. With first-order inertial elements Multiply to get The possible values ​​of ; where The participation factor in the inertial response. It is a Laplace operator; Module 3, Active Power Control Module, wherein: electromagnetic torque setpoint of wind turbine Compared with actual value By subtracting, we obtain the torque difference. ; Equivalent synchronous angular velocity Multiply by virtual damping coefficient The virtual inertia deviation is obtained. ; Torque difference With virtual inertia deviation The difference is processed by an integrator. Obtain the equivalent synchronous angular velocity , This is the virtual inertia coefficient; Equivalent synchronous angular velocity With inertial response frequency Add them together to obtain the virtual synchronous angular velocity. ; Virtual synchronous angular velocity via integrator Obtain the virtual rotor angle , The reference frequency for the power grid; Virtual rotor angle With rotor angle By subtracting the values, we obtain the slip angle. It is used to generate pulse control signals to control the operation of the rotor-side converter.

8. A computer program product, characterized in that: The method includes a computer program that, when executed by a processor, implements the parameter correction method for grid-type wind turbines as described in any one of claims 1 to 5.

9. A computer program product, characterized in that: It includes a computer program that, when executed by a processor, implements the grid-type wind turbine control method as described in claim 6 or 7.

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