Inertial Synchronization Control System for Direct-Drive Wind Turbines Based on Parameter Adaptation

Abstract

The present invention provides an inertial synchronous control system for a direct-driven wind turbine generator set based on parameter adaptation, which relates to the field of power supply systems and comprises: an impact analysis module, which is used to analyze the impact of wind power fluctuation on the inertial synchronous control of the direct-driven wind turbine generator set to obtain a first analysis result, and is also used to analyze the impact of grid voltage fluctuation on the inertial synchronous control of the direct-driven wind turbine generator set to obtain a second analysis result; a strategy formulation module, which is used to generate an adaptive control strategy according to the first analysis result and the second analysis result; a synchronous control module, which is used to obtain real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency change amount and angular frequency change rate, and determine the real-time moment of inertia and the real-time damping coefficient based on the real-time wind power fluctuation data, the real-time grid voltage fluctuation data, the angular frequency change amount and the angular frequency change rate according to the adaptive control strategy, and perform inertial synchronous control of the direct-driven wind turbine generator set according to the real-time moment of inertia and the real-time damping coefficient.

Description

Technical Field

[0001] The invention relates to the field of power supply systems, and in particular to an inertial synchronous control system of a direct-drive wind turbine generator set based on parameter adaptation. Background Art

[0002] With the large-scale development and utilization of wind power, the proportion of wind power in the power grid has gradually increased. Unlike synchronous generators in the power grid, wind turbines are connected to the power grid through power electronic converters, and their decoupling effect makes it impossible for wind turbines to respond inertially. As wind power continues to be connected to the power grid, the penetration rate increases, the equivalent inertia of the power grid decreases significantly, and the frequency stability problem becomes increasingly obvious.

[0003] Under weak grid conditions, grid impedance can easily cause large fluctuations in the voltage amplitude and phase at the grid connection point of new energy units, causing phase loss of the grid-side converter of the new energy units, seriously affecting the stability of the grid-connected operation of the new energy power generation system, and even threatening the safety and stability of the power grid. To this end, researchers have actively explored and proposed some grid-following control methods with improved phase-locked loops (PLLs) and grid-building control methods without phase-locked loops suitable for weak grid environments to enhance the stability of grid-connected operation of new energy power generation systems. Compared with the grid-following control method, the converter using the grid-building control method can be regarded as a voltage source with controlled output voltage amplitude and phase, which has the ability to build internal potential by itself and is more adaptable to weak grids. There are three main grid-building control methods: droop control, virtual synchronous machine control, and matching control inertial synchronous control.

[0004] Compared with droop control and virtual synchronous machine control, inertial synchronous control does not rely on the voltage and current on the AC side. It only needs to measure the voltage of the DC side capacitor. By sensing the change of the AC side frequency through the change of the DC side capacitor voltage, the change of the phase can be tracked, and it has a faster response speed. Based on this advantage, the research on this control method and its application has also attracted more and more attention from researchers. For doubly fed wind turbines, the similarity between the grid-side converter and the synchronous generator in dynamics is utilized, and the energy in the converter DC capacitor is used to simulate the inertia of the synchronous generator rotor to achieve autonomous grid synchronization and stable operation in weak grids. This control idea is applied to direct-drive wind turbines to realize voltage source control of the grid-side converter of the wind turbine, which effectively improves the operation stability of the unit under weak grids. However, the inertial synchronous control strategy is easily interfered by factors such as grid voltage fluctuations in the process of sensing grid frequency. In particular, when the grid is in transient fault, the grid-side converter cannot control the DC bus voltage stability due to the limited output power, breaking the mechanism of DC bus voltage sensing grid frequency, which easily causes the grid-side converter to lose synchronization with the grid. Based on this, one existing technology is to reveal the dynamic coupling mechanism between the DC voltage of the grid-type converter and the grid frequency, grid voltage, and input prime mover from the perspective of damping characteristics, and propose an anti-interference control strategy for high-frequency and low-frequency interference. In view of the problem that the inertial synchronous control method cannot operate when the grid fails, a composite fault judgment method of grid voltage and DC bus voltage is adopted. When the grid fails, the DC voltage synchronous control and active power synchronous control of the wind turbine can be accurately switched to ensure the stable operation of the unit. Another existing technology analyzes the subsynchronous oscillation mechanism and characteristics of the grid-type direct-drive wind farm based on inertial synchronous control from the perspective of synchronous generator damping, which has certain reference value for future analysis of the proportion of grid-type new energy units, improvement of grid inertia damping characteristics and other related research.

[0005] The existing technology mainly focuses on the synchronous phase-locking capability with the power grid and the inertia response characteristics. Although it points out that the DC voltage of the converter under inertial synchronous control can follow the grid frequency fluctuation, it has not quantitatively studied and analyzed the relationship between the virtual inertia and damping parameters in the inertial synchronous control and factors such as grid voltage and wind power fluctuations. Moreover, the virtual inertia and damping parameters of the inertial synchronous control in the existing technology are fixed values. However, in actual applications, when the grid voltage fluctuates or the wind power fluctuates, the fixed inertia and damping parameters are obviously difficult to meet the actual engineering applications.

[0006] Therefore, in order to meet the actual engineering applications, it is very important to deeply analyze the coupling relationship between virtual inertia, damping parameters and grid voltage and wind power fluctuations, and adaptively adjust the virtual inertia and damping parameters according to the coupling relationship, so as to suppress the interference of wind power and grid voltage fluctuations on inertial synchronous control. Summary of the invention

[0007] The present invention provides an inertial synchronous control system for a direct-driven wind turbine generator set based on parameter adaptation, comprising: an impact analysis module, comprising a wind power fluctuation impact analysis unit and a grid voltage fluctuation impact analysis unit, wherein the wind power fluctuation impact analysis unit is used to analyze the impact of wind power fluctuation on the inertial synchronous control of the direct-driven wind turbine generator set to obtain a first analysis result, and the grid voltage fluctuation impact analysis unit is used to analyze the impact of grid voltage fluctuation on the inertial synchronous control of the direct-driven wind turbine generator set to obtain a second analysis result; a strategy formulation module, used to generate an adaptive control strategy according to the first analysis result and the second analysis result, wherein the adaptive control strategy is used to adaptively adjust the virtual inertia and the damping coefficient; a synchronous control module, used to obtain real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency change amount and angular frequency change rate, determine the real-time moment of inertia and the real-time damping coefficient according to the adaptive control strategy based on the real-time wind power fluctuation data, the real-time grid voltage fluctuation data, the angular frequency change amount and the angular frequency change rate, and perform inertial synchronous control of the direct-driven wind turbine generator set according to the real-time moment of inertia and the real-time damping coefficient.

[0008] Furthermore, the wind power fluctuation impact analysis unit analyzes the impact of wind power fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a first analysis result, including: establishing a dynamic equation of the DC side capacitor of the grid-connected system of the direct-drive wind turbine set; establishing a dynamic equation of the output power of the grid-connected inverter; under a first preset condition, performing small signal linearization processing on the dynamic equation of the output power of the grid-connected inverter to obtain a dynamic equation of the change in the output power of the first inverter, wherein the first preset condition is that the grid voltage remains unchanged and the wind power fluctuates due to changes in the ambient wind speed; establishing a state space model of inertial synchronization; and The state space model is linearized to obtain a first linearization result; the dynamic equation of the DC side capacitor of the direct-drive wind turbine grid-connected system is linearized to obtain a second linearization result; according to the dynamic equation of the change in output power of the first inverter, the first linearization result and the second linearization result, an open-loop transfer function of the angular frequency change and the wind power change is obtained; according to the open-loop transfer function of the angular frequency change and the wind power change, a closed-loop transfer function of the angular frequency change and the wind power change is obtained, wherein the first analysis result at least includes the closed-loop transfer function of the angular frequency change and the wind power change.

[0009] Furthermore, the grid voltage fluctuation impact analysis unit analyzes the impact of grid voltage fluctuations on the inertial synchronous control of the direct-drive wind turbine set to obtain a second analysis result, including: under a second preset condition, performing small signal linearization processing on the dynamic equation of the output power of the grid-connected inverter to obtain a dynamic equation for the change in the output power of the second inverter, wherein the second preset condition is that the wind power remains unchanged and the grid voltage fluctuates; according to the dynamic equation for the change in the output power of the second inverter, the first linearization result and the second linearization result, an open-loop transfer function between the change in angular frequency and the change in grid voltage is obtained; according to the open-loop transfer function between the change in angular frequency and the change in grid voltage, a closed-loop transfer function between the change in angular frequency and the change in grid voltage is obtained, wherein the second analysis result at least includes the closed-loop transfer function between the change in angular frequency and the change in grid voltage.

[0010] Furthermore, the strategy formulation module generates an adaptive control strategy based on the first analysis result and the second analysis result, including: performing a correlation analysis on the change rate of virtual inertia, damping coefficient and angular frequency to generate a correlation analysis result; obtaining an angular frequency change curve and an angular frequency change rate curve when the virtual inertia and damping coefficient are fixed, and obtaining an interval demand table based on the angular frequency change curve and the angular frequency change rate curve when the virtual inertia and damping coefficient are fixed; generating the adaptive control strategy based on the correlation analysis result, the first analysis result, the second analysis result and the interval demand table.

[0011] Furthermore, correlation analysis is performed on the virtual inertia, the damping coefficient, the rate of change of the angular frequency, and the amount of change of the angular frequency to generate a correlation analysis result, including: deforming the state space model of the inertial synchronization, and obtaining positive and negative results of the correlation between the rate of change of the angular frequency and the virtual inertia and the positive and negative results of the correlation between the amount of change of the angular frequency and the damping coefficient according to the deformation result.

[0012] Furthermore, according to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed, an interval requirement table is obtained, including: determining multiple target intervals according to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed; for each of the target intervals, determining the virtual inertia change requirement and the damping coefficient change requirement corresponding to the target interval.

[0013] Furthermore, the adaptive control strategy is:

[0014] ,

[0015] in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the change in angular frequency.

[0016] Furthermore, the adaptive control strategy is:

[0017] ,

[0018] in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the angular frequency change, is the adaptive adjustment coefficient of virtual inertia when wind power fluctuates, is the per-unit value of wind power output at the machine side, is the adaptive adjustment coefficient of virtual inertia when the grid voltage fluctuates, is the per unit value of the grid voltage, is the adaptive adjustment coefficient of the damping coefficient when the wind power fluctuates, is the adaptive adjustment coefficient of the damping coefficient when the grid voltage fluctuates, is the angular frequency threshold, Hyperbolic tangent function.

[0019] Furthermore, the closed-loop transfer function of the angular frequency change and the wind power change is:

[0020] ,

[0021] ,

[0022] ,

[0023] in, , , is the closed-loop transfer function between the angular frequency change and the wind power change, is the open-loop transfer function of the angular frequency change and wind power change, is the change in angular frequency, is the steady-state value of the grid angular frequency, is the change in wind power output on the machine side, is the differential operator, , , , , , , are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

[0024] Furthermore, the closed-loop transfer function between the angular frequency variation and the grid voltage variation is:

[0025] ,

[0026] ,

[0027] ,

[0028] in, , , is the closed-loop transfer function between the angular frequency change and the grid voltage change, is the open-loop transfer function between the angular frequency change and the grid voltage change, is the grid voltage variation. is the change in angular frequency, is the steady-state value of the grid angular frequency, is the differential operator, , , , , , , are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

[0029] Compared with the prior art, the parameter-adaptive direct-drive wind turbine inertial synchronization control system provided by the present invention has at least the following beneficial effects:

[0030] 1. By establishing a small signal mathematical model of the grid-side converter of a direct-drive wind turbine, the coupling relationship between the DC voltage and the grid voltage and the wind power fluctuation power is studied, and the eigenvalue analysis method is used to reveal the influence of virtual inertia and damping parameters on the synchronization stability of the direct-drive wind turbine grid-connected system under different wind speeds and grid voltages. An inertial synchronization control strategy with adaptive virtual inertia and damping parameters is proposed to ensure that the direct-drive wind turbine grid-connected system will not lose lock when the grid voltage and wind power fluctuate greatly, and the stable operation of the direct-drive wind turbine grid-connected system can still be maintained.

[0031] 2. Introduce wind power, grid voltage, frequency thresholds and softening functions into adaptive control to ensure that the virtual inertia and damping coefficient can be accurately adjusted and switched in real time when the grid voltage and wind power fluctuate, thereby ensuring rapid system response and improving system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0033] Figure 1 It is a module schematic diagram of an inertial synchronous control system of a direct-drive wind turbine generator system based on parameter adaptation according to some embodiments of this specification;

[0034] Figure 2 is a schematic diagram of a main circuit of a direct-drive wind turbine grid-connected system according to some embodiments of this specification;

[0035] Figure 3 is a block diagram of inertial synchronization control according to some embodiments of this specification;

[0036] Figure 4 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the wind speed suddenly changes according to the fixed virtual inertia and damping coefficient shown in some embodiments of this specification;

[0037] Figure 5 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the wind speed is fixed and the virtual inertia is changed according to some embodiments of this specification;

[0038] Figure 6 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the wind speed is fixed and the damping coefficient is changed according to some embodiments of this specification;

[0039] Figure 7 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the grid voltage suddenly changes according to the fixed virtual inertia and damping coefficient shown in some embodiments of this specification;

[0040] Figure 8 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the virtual inertia is changed under the same grid voltage as shown in some embodiments of this specification;

[0041] Fig. 9 It is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the damping coefficient is changed under the same grid voltage as shown in some embodiments of this specification;

[0042] Fig.10 is a schematic diagram of an angular frequency variation curve according to some embodiments of this specification;

[0043] Fig.11 is a schematic diagram of an angular frequency change rate curve according to some embodiments of this specification;

[0044] Fig.12 It is a block diagram of grid-connected control of a direct-drive wind turbine wind turbine set according to some embodiments of this specification;

[0045] Fig.13 is a schematic diagram of the DC side voltage change according to the first simulation working condition shown in some embodiments of this specification;

[0046] Fig.14 is a schematic diagram of the output frequency change of the first simulation working condition shown in some embodiments of this specification;

[0047] Fig.15 is a schematic diagram of the DC side voltage change according to the second simulation working condition shown in some embodiments of this specification;

[0048] Fig.16 is a schematic diagram of the output frequency change of the second simulation working condition shown in some embodiments of this specification;

[0049] Fig.17 is a schematic diagram of the DC side voltage change according to the third simulation working condition shown in some embodiments of this specification;

[0050] Fig.18 is a schematic diagram of the output frequency change of the third simulation working condition shown in some embodiments of this specification;

[0051] Fig.19 is a schematic diagram of the DC side voltage change according to the fourth simulation working condition shown in some embodiments of this specification;

[0052] Fig. 20 is a schematic diagram of output frequency change according to the fourth simulation working condition shown in some embodiments of this specification; DETAILED DESCRIPTION

[0053] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0054] Figure 2 is a schematic diagram of the main circuit of the direct-drive wind turbine grid-connected system shown in some embodiments of this specification, such as Figure 2 As shown in the figure, the main circuit of the direct-drive wind turbine grid-connected system is mainly composed of a direct-drive wind turbine, a synchronous generator, a rectifier, a DC side capacitor, a load unloading circuit, a grid-connected inverter, an LC filter, a step-up transformer, an equivalent line impedance and a three-phase power supply. Figure 2 middle, is the DC side voltage, is the DC side capacitor, is the unloading resistor, For the filter inductor, For filter capacitors, is the equivalent line impedance, for The real part of the equivalent line impedance, is the imaginary part of the equivalent line impedance.

[0055] Figure 3 is an inertial synchronous control block diagram according to some embodiments of this specification, Figure 3 middle, is the steady-state value of the DC side voltage, is the DC side voltage reference value, For new energy capacity, is the grid angular frequency, is the virtual inertia, is the damping coefficient, is the angular frequency of the direct-drive wind turbine grid-connected system, is a differential operator.

[0056] Figure 1 is a module schematic diagram of an inertial synchronous control system of a direct-drive wind turbine generator system based on parameter adaptation according to some embodiments of this specification, such as Figure 1 As shown, the inertial synchronous control system of a direct-drive wind turbine generator system based on parameter adaptation may include an impact analysis module, a strategy formulation module and a synchronous control module.

[0057] The impact analysis module may include a wind power fluctuation impact analysis unit and a grid voltage fluctuation impact analysis unit, wherein the wind power fluctuation impact analysis unit is used to analyze the impact of wind power fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a first analysis result, and the grid voltage fluctuation impact analysis unit is used to analyze the impact of grid voltage fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a second analysis result.

[0058] Preferably, the wind power fluctuation impact analysis unit analyzes the impact of wind power fluctuation on the inertial synchronous control of the direct-drive wind turbine generator set to obtain a first analysis result, including:

[0059] Establish the dynamic equation of DC side capacitance of direct-drive wind turbine grid-connected system;

[0060] Establish the dynamic equation of grid-connected inverter output power;

[0061] Under the first preset condition, a small signal linearization process is performed on the dynamic equation of the output power of the grid-connected inverter to obtain a dynamic equation of the change in the output power of the first inverter, wherein the first preset condition is that the grid voltage remains unchanged and the wind power fluctuates due to changes in the ambient wind speed;

[0062] Establish a state-space model of inertial synchronization;

[0063] Linearizing the state space model of inertial synchronization to obtain a first linearization result;

[0064] The DC side capacitance dynamic equation of the direct-drive wind turbine grid-connected system is linearized to obtain a second linearization result;

[0065] According to the dynamic equation of the change in output power of the first inverter, the first linearization result and the second linearization result, an open-loop transfer function of the change in angular frequency and the change in wind power is obtained;

[0066] A closed-loop transfer function of the angular frequency change and the wind power change is obtained according to the open-loop transfer function of the angular frequency change and the wind power change, wherein the first analysis result at least includes the closed-loop transfer function of the angular frequency change and the wind power change.

[0067] Specifically, the dynamic equation of the DC side capacitor of the direct-drive wind turbine grid-connected system is:

[0068] ,

[0069] in, is the wind power output on the machine side, is the grid-side input power, is the DC bus capacitance, is the steady-state value of the DC side voltage, is the DC side voltage, is a differential operator.

[0070] Ignoring the power loss of the converter station, the dynamic equation of the grid-connected inverter output power is:

[0071] ,

[0072] in, is the grid-side input power, is the inverter output voltage, is the grid voltage, is the line impedance, For the power angle.

[0073] Assuming that the grid voltage is stable and the wind power fluctuates due to the change of ambient wind speed, the small signal linearization processing of the dynamic equation of the grid-connected inverter output power can be obtained:

[0074] ,

[0075] in, is the change in output power of the grid-connected inverter, is the power angle change, is the voltage change on the DC side, is the modulation ratio, is the steady-state value of the inverter output voltage, is the steady-state value of the grid voltage, is the steady-state value of the power angle.

[0076] The state space model of inertial synchronization is:

[0077] ,

[0078] in, , , is the DC side voltage, is the DC side voltage reference value is the steady-state value of the DC side voltage, is the fan capacity, is the steady-state value of the grid angular frequency, is the virtual inertia, is the damping coefficient, is the sampling time, is the angular frequency. is the grid voltage phase.

[0079] By linearizing equation (4), we can obtain:

[0080] ,

[0081] in, is the voltage change on the DC side, is the angular frequency change, is the power angle change.

[0082] By linearizing equation (1), we can obtain:

[0083] ,

[0084] in, is the change in wind power output on the machine side, is the change in grid-side input power, is the DC side voltage, is the steady-state value of the DC side voltage, is a differential operator, DC link capacitor.

[0085] Combining equations (3), (5) and (6), we can obtain:

[0086] ,

[0087] ,

[0088] From formula (7), the closed-loop transfer function of the angular frequency change and wind power change is:

[0089] ,

[0090] in, , , is the closed-loop transfer function between the angular frequency change and the wind power change, is the open-loop transfer function of the angular frequency change and wind power change, is the change in angular frequency, is the steady-state value of the grid angular frequency, is the change in wind power output on the machine side, is the differential operator, , , , , , , are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

[0091] Figure 4 It is a distribution diagram of the characteristic value of the grid-connected system of the direct-drive wind turbine when the wind speed suddenly changes according to the fixed virtual inertia and damping coefficient shown in some embodiments of this specification. The distribution diagram intuitively reflects the impact of the sudden drop in wind speed on the distribution of the characteristic value of the system. Specifically, the characteristic value tends to the right half plane of the s plane with the sudden drop in wind speed, and the magnitude of the characteristic value offset to the right half plane is positively correlated with the magnitude of the sudden drop in wind speed. In particular, when the wind speed suddenly drops to 5m / s, it can be observed through the local enlarged view that there are characteristic values ​​offset to the right half plane of the complex plane.

[0092] The following conclusions can be drawn from the above analysis: the stability of inertial synchronization gradually tends to be unstable with the sudden drop in wind speed, and the degree of instability of inertial synchronization is positively correlated with the amplitude of the sudden drop in wind speed; especially after the wind speed suddenly drops to 5m / s, characteristic roots with positive real part appear, indicating that the wind power fluctuation amplitude is too large at this time, and the inertial synchronous control can no longer accurately lock the phase and frequency information of the grid voltage, that is, the inertial synchronous control is lost.

[0093] It can be seen from formula (7) that by adjusting the virtual inertia and damping coefficient, To study the effect of virtual inertia on inertial synchronization, Figure 5This is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the wind speed is fixed and the virtual inertia is changed according to some embodiments of this specification, such as Figure 5 As shown, the wind speed is constant at 5m / s and the damping coefficient When the virtual inertia is 0.72, The eigenvalue of the right half plane of s can be shifted to the left half plane of s, that is, the appropriate increase of virtual inertia can increase the stability of inertial synchronization. Similarly, in order to study the influence of the damping coefficient on inertial synchronization, Figure 6 This is a distribution diagram of characteristic values ​​of a direct-drive wind turbine grid-connected system when the wind speed is fixed and the damping coefficient is changed according to some embodiments of this specification, such as Figure 6 As shown in the figure, when the wind speed is constant at 5 m / s and the virtual inertia is constant at 0.12, increasing the damping coefficient can also make the eigenvalue of the right half plane of s shift to the left half plane of s, that is, appropriately increasing the damping coefficient can also increase the stability of inertial synchronization.

[0094] Preferably, the grid voltage fluctuation impact analysis unit analyzes the impact of grid voltage fluctuation on the inertial synchronous control of the direct-drive wind turbine generator set to obtain a second analysis result, including:

[0095] Under the second preset condition, a small signal linearization process is performed on the dynamic equation of the output power of the grid-connected inverter to obtain a dynamic equation of the variation of the output power of the second inverter, wherein the second preset condition is that the wind power remains unchanged and the grid voltage fluctuates;

[0096] According to the dynamic equation of the change in output power of the second inverter, the first linearization result and the second linearization result, an open-loop transfer function between the change in angular frequency and the change in grid voltage is obtained;

[0097] A closed-loop transfer function between the angular frequency variation and the grid voltage variation is obtained according to the open-loop transfer function between the angular frequency variation and the grid voltage variation, wherein the second analysis result at least includes the closed-loop transfer function between the angular frequency variation and the grid voltage variation.

[0098] Specifically, assuming that the wind power remains unchanged and the grid voltage fluctuates, the small signal linearization processing of equation (2) can be obtained:

[0099] ,

[0100] in, is the change in grid-side input power, is the power angle change, is the voltage change on the DC side, is the modulation ratio, is the steady-state value of the inverter output voltage, is the steady-state value of the grid voltage, is the steady-state value of the power angle, is the line impedance.

[0101] Combining equations (5), (6) and (9), we can get:

[0102] ,

[0103] ,

[0104] From formula (10), the closed-loop transfer function between the angular frequency change and the grid voltage change can be obtained as:

[0105] ,

[0106] in, , , is the closed-loop transfer function between the angular frequency change and the grid voltage change, is the open-loop transfer function between the angular frequency change and the grid voltage change, is the grid voltage variation. is the change in angular frequency, is the steady-state value of the grid angular frequency, is the differential operator, , , , , , , are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

[0107] Figure 7 It is a distribution diagram of the characteristic values ​​of the direct-drive wind turbine grid-connected system when the grid voltage suddenly changes according to the fixed virtual inertia and damping coefficient shown in some embodiments of this specification, such as Figure 7As shown in the figure, the influence of grid voltage fluctuation on inertial synchronous control is similar to that of wind power fluctuation. The characteristic root tends to the right half plane of the s plane as the grid voltage drops suddenly, making the stability of inertial synchronous control gradually weakened. Moreover, the speed at which the characteristic value shifts to the right half plane is positively correlated with the amplitude of the grid voltage drop. Especially when the grid voltage drops suddenly to 0.5pu, it can be observed through the local enlarged view that there are characteristic values ​​shifted to the right half plane of the complex plane, indicating that the inertial synchronous control has lost lock at this time.

[0108] It can be seen from formula (10) that by adjusting the virtual inertia and damping coefficient, The characteristic value of , thereby changing the influence of grid voltage fluctuation on inertial synchronization. In order to study the influence of virtual inertia on inertial synchronization, Figure 8 This is a distribution diagram of the characteristic values ​​of the direct-drive wind turbine grid-connected system when the virtual inertia is changed under the same grid voltage as shown in some embodiments of this specification, such as Figure 8 As shown, the grid voltage is always 0.5pu. When the value is 0.72, increasing the virtual inertia can make the eigenvalue of the right half plane of s shift to the left half plane of s, that is, appropriately increasing the virtual inertia can increase the stability of inertial synchronization. The impact on inertial synchronization, Fig. 9 It is a distribution diagram of the characteristic values ​​of the direct-drive wind turbine grid-connected system when the damping coefficient is changed under the same grid voltage as shown in some embodiments of this specification, such as Fig. 9 As shown, the grid voltage is always 0.5pu. Increasing the damping coefficient under the condition of being constant at 0.12 can also make the eigenvalue of the right half plane of s shift to the left half plane of s, that is, appropriately increasing the damping coefficient can also increase the stability of inertial synchronization.

[0109] In summary, we can get:

[0110] (1) Both wind power fluctuations and grid voltage fluctuations will affect the stability of inertial synchronous control. Moreover, as the amplitude of wind power fluctuations and grid voltage fluctuations increases, the stability of inertial synchronous control becomes weaker. When the amplitude of wind power fluctuations and grid voltage fluctuations reach a certain value, inertial synchronization will lose lock, causing the direct-drive wind turbine grid-connected system to become disordered.

[0111] (2) By adjusting the virtual inertia and damping coefficient in the inertial synchronization control, the characteristic root distribution of the direct-drive wind turbine grid-connected system can be changed, and the inertial synchronization instability problem caused by wind power fluctuations and grid voltage fluctuations can be suppressed to a certain extent.

[0112] The strategy formulation module can be used to generate an adaptive control strategy based on the first analysis result and the second analysis result, wherein the adaptive control strategy is used to adaptively adjust the virtual inertia and the damping coefficient.

[0113] Specifically include:

[0114] Conduct correlation analysis on the virtual inertia, damping coefficient, and the rate of change of angular frequency and the amount of change of angular frequency to generate correlation analysis results;

[0115] Obtaining an angular frequency variation curve and an angular frequency variation rate curve when the virtual inertia and the damping coefficient are fixed, and obtaining an interval demand table according to the angular frequency variation curve and the angular frequency variation rate curve when the virtual inertia and the damping coefficient are fixed;

[0116] An adaptive control strategy is generated according to the correlation analysis result, the first analysis result, the second analysis result and the interval demand table.

[0117] Preferably, correlation analysis is performed on the rate of change of the virtual inertia and the damping coefficient and the amount of change of the angular frequency to generate a correlation analysis result, including:

[0118] The state space model of inertial synchronization is deformed, and according to the deformation results, the positive and negative results of the correlation between the angular frequency change rate and the virtual inertia and the positive and negative results of the correlation between the angular frequency change amount and the damping coefficient are obtained.

[0119] Specifically, the state space model of inertial synchronization is deformed, and the following deformation results can be obtained:

[0120] ,

[0121] in, , , is the voltage change on the DC side, is the rate of change of angular frequency, is the fan capacity, is the steady-state value of the DC side voltage, is the sampling time, is the DC side capacitor.

[0122] From formula (12), we can see that at any working point , , are constant values, The DC voltage fluctuation caused by wind power fluctuation or grid voltage fluctuation is implicitly included in and as well as and Therefore, as long as we follow this and Adjustment of changes in and The size of Adjust it and ensure it is within the allowable range, thereby ensuring the stable phase lock of inertial synchronization.

[0123] Preferably, according to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed, an interval demand table is obtained, including:

[0124] According to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed, a plurality of target intervals are determined; for each target interval, the virtual inertia change requirement and the damping coefficient change requirement corresponding to the target interval are determined.

[0125] Fig.10 is a schematic diagram of an angular frequency variation curve according to some embodiments of this specification, Fig.11 is a schematic diagram of an angular frequency change rate curve according to some embodiments of this specification, such as Fig.10 and Fig.11 As shown in the figure, the attenuation trajectory of the angular frequency change and change rate curve is subdivided into four intervals with significant characteristics. to is interval 1, to For interval 2, to For interval 3, to is interval 4. The changing pattern of angular frequency in each interval is different, that is, the inertia and damping required by the system in each interval are also different. If you want to restore the system to stability quickly, then the inertia and damping in each interval need to change with the change of angular frequency.

[0126] like Fig.10 As shown in the figure, in interval 1, the angular frequency change rate and change amount are both positive, indicating that the angular frequency is deviating from the steady-state value of the grid frequency. and Suppress the rate and amount of change of angular frequency, and slow down the trend of angular frequency deviating from the steady-state value of grid frequency.

[0127] Interval 2: The rate of change of the angular frequency is negative, and the amount of change is positive, indicating that the angular frequency changes toward the steady-state value of the grid frequency. and The rate of change and amount of change of the angular frequency increase, and the angular frequency is accelerated to approach the steady-state value of the grid angular frequency. However, in the environment where a high proportion of new energy is connected to the grid, the low damping state is often accompanied by the risk of oscillation. To avoid such potential oscillations, only the value of ,Keep constant.

[0128] Interval 3: Both the rate of change and the amount of change of the angular frequency are negative. Similar to interval 1, the angular frequency is running at a value that deviates from the steady-state value of the grid frequency. and Suppress the rate and amount of change of the angular frequency, and slow down the trend of the angular frequency deviating from the steady-state value of the grid frequency.

[0129] Interval 4: The rate of change of the angular frequency is negative, and the amount of change is positive. Similar to interval 2, the angular frequency changes toward the steady-state value of the grid frequency. Therefore, as in interval 2, the decrease ,Keep , the acceleration angular frequency approaches the steady-state value of the grid angular frequency.

[0130] Based on the above analysis, the virtual inertia in inertial synchronous control and the damping coefficient The requirements in different intervals are shown in Table 1.

[0131]

[0132] Preferably, the adaptive control strategy is:

[0133] ,

[0134] in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the change in angular frequency.

[0135] When wind power and grid voltage fluctuate, the system angular frequency will fluctuate. As can be seen from formula (13), when the angular frequency fluctuates, the moment of inertia and damping coefficient make corresponding adjustments by sensing the fluctuation of the angular frequency, thereby suppressing the fluctuation of the angular frequency and quickly restoring the angular frequency to stability. However, through analysis, formula (13) still has the following problems:

[0136] (1) Parameter adjustment has hysteresis

[0137] First, in equation (13), the differential term needs to be introduced when calculating the rate of change of the angular frequency, which results in hysteresis. Secondly, the fluctuation of wind power and grid voltage first causes the fluctuation of DC side voltage, which is then transmitted through the inertial synchronous control mechanism, indirectly causing the dynamic change of the system angular frequency. Therefore, the control strategy that only adjusts the moment of inertia and damping coefficient based on angular frequency fluctuation has an inherent hysteresis in its response mechanism in the process of dealing with the influence of wind power and grid voltage fluctuation on inertial synchronous control.

[0138] (2) Parameter switching error

[0139] Depend on Fig.11 It can be seen from the local enlarged figure that even under the stable operation conditions of the system, small but significant fluctuations in the angular frequency can still be observed. Small fluctuations in the angular frequency can cause misjudgment in the adjustment logic of the moment of inertia and damping coefficient, resulting in unnecessary parameter switching.

[0140] (3) Great impact on the system

[0141] It can also be seen from formula (13) that at the moment when the system is disturbed and adaptive control is switched, the moment of inertia and damping coefficient are equivalent to a sudden increase or decrease of a constant, that is, a step signal is artificially introduced into the system, and the step response has a great impact on the system.

[0142] Based on the above problems, the adaptive control strategy can be optimized as follows:

[0143] ,

[0144] in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the angular frequency change, is the adaptive adjustment coefficient of virtual inertia when wind power fluctuates, is the per-unit value of wind power output at the machine side, is the adaptive adjustment coefficient of virtual inertia when the grid voltage fluctuates, is the per unit value of the grid voltage, is the adaptive adjustment coefficient of the damping coefficient when the wind power fluctuates, is the adaptive adjustment coefficient of the damping coefficient when the grid voltage fluctuates, is the angular frequency threshold, is the hyperbolic tangent function.

[0145] It can be seen from formula (14) that (1) when the wind power and grid voltage fluctuate, and The amplitude of the fluctuation of wind power and grid voltage can be sensed and quantified in advance, and then real-time and accurate parameter control can be implemented according to the specific situation of the fluctuation, thereby reducing the lag problem presented in equation (13). (2) Threshold constraints are imposed on the system angular frequency deviation, and only when the angular frequency deviation exceeds the preset threshold The parameter switching mechanism is triggered under the working condition, which effectively solves the problem of parameter mis-switching in equation (13). (3) The hyperbolic tangent function tanh(x) is introduced as a softening function to ensure and The switching can be smoothed at the moment of switching, thereby reducing the impact of the parameter switching in formula (13) on the system.

[0146] Fig.12 This is a direct-drive wind turbine wind turbine grid-connected control block diagram according to some embodiments of this specification, such as Fig.12 As shown, the synchronous control module can be used to obtain real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency change and angular frequency change rate, and determine the real-time virtual inertia and real-time damping coefficient based on the real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency change and angular frequency change rate according to the adaptive control strategy, and perform inertial synchronous control of the direct-drive wind turbine set according to the real-time virtual inertia and the real-time damping coefficient.

[0147] Fig.12 middle, is the instantaneous value of the three-phase voltage, is the instantaneous value of the three-phase current, for The shaft voltage component, is the dq axis current component, The grid voltage phase locked by inertial synchronous control, is the transformation from the abc coordinate system to the dq coordinate system, is the transformation from the dq coordinate system to the abc coordinate system, is the instantaneous value of the three-phase voltage on the grid side, is the dq axis voltage component on the grid side, is the reference value of the d-axis current, is the reference value of q-axis current, is the maximum allowable current, is the measured value of the effective value of the grid voltage, It is the reference value of the effective value of the grid voltage.

[0148] In order to evaluate the effectiveness of the adaptive control strategy proposed in this invention, PACAD / EMTDC was used to build the following Fig.12 The simulation model of the wind turbine generator system is verified. Specifically, when the direct-drive wind turbine generator system is connected to the grid under normal conditions, it operates in mode 1, and the inverter adopts voltage and current dual-loop control. When a grid voltage grounding fault occurs in the grid, it operates in mode 2, and the inverter adopts a reactive power priority control strategy to stabilize the grid connection point voltage, ensuring that reactive power support can be provided to the grid during the fault to help the grid voltage recover quickly.

[0149] In order to verify the effectiveness of the adaptive control strategy in suppressing angular frequency fluctuations and inertial synchronization loss problems when wind power fluctuates, simulations were carried out on two different operating conditions in which the wind speed of the direct-drive wind turbine dropped suddenly from its rated value of 10m / s to 7m / s and 6m / s in the range of 2 seconds to 4 seconds. Figures 13 to 16 The simulated waveforms of DC voltage and frequency when the wind speed suddenly changes to 7m / s and 6m / s are respectively Figures 13 to 16 It can be seen that without the introduction of parameter adaptive control, when the wind speed suddenly changes to 7m / s, the inertial synchronous control can stabilize the DC side voltage and frequency, but the adjustment time and overshoot of the DC side voltage and system frequency are large, which seriously affects the response speed of the system; when the wind speed suddenly changes to 6m / s, the DC side voltage is completely unstable, resulting in the inertial synchronous control mechanism being unable to accurately obtain the frequency and phase information of the grid voltage by sensing the DC side voltage, thereby causing inertial synchronous lock loss and causing system disorder. When the system introduces the unimproved adaptive control strategy, when the wind speed suddenly changes to 7m / s and 6m / s, not only can the DC side voltage be maintained stable, but also the adjustment time and overshoot of the DC side voltage are greatly reduced, which speeds up the response speed of the system, thereby ensuring that the inertial synchronous control mechanism accurately obtains the frequency and phase information of the grid voltage by sensing the DC side voltage. It can be seen that by changing the virtual inertia and damping coefficient, the inertial synchronous lock loss problem caused by wind power fluctuations can indeed be suppressed. Compared with the unimproved adaptive control strategy, the improved strategy reduces the overshoot and adjustment time of the DC side voltage and frequency, and makes the system respond faster, indicating that the virtual inertia and damping coefficient can improve the real-time and response performance of the control strategy by sensing and quantifying the amplitude of wind power fluctuations in advance, and then implementing real-time and precise parameter adjustment according to the specific circumstances of the fluctuations.

[0150] In order to verify the effect of adaptive control strategy in suppressing frequency fluctuation and inertial synchronous control lock failure when the grid voltage fluctuates, two three-phase grid voltage symmetrical grounding fault experiments are designed. The grid voltage is reduced from the rated value of 1pu to 0.8pu and 0.2pu at 3 seconds respectively, and the duration is set to 1 second to simulate grid voltage fluctuations of different degrees. Figures 17 to 20They are the simulated waveforms of DC side voltage and frequency when the grid voltage drops to 0.8pu and 0.2pu respectively. Figures 17 to 20 It can be seen that when the grid voltage drops to 0.8pu, the DC side voltage and system frequency can be kept stable whether without adaptive control strategy or with two adaptive control strategies (before and after improvement). However, the two adaptive control strategies can significantly reduce the adjustment time and overshoot of the DC side voltage and system frequency during the grid voltage mutation and recovery stage, thereby prompting the system to quickly recover to a stable state and ensure the smooth transmission of power. Compared with the control strategy before improvement, the improved control strategy makes the adjustment time and overshoot of the DC side voltage and system frequency system lower, and the system response speed is faster. When the grid voltage drops to 0.2pu, without the adaptive control strategy, the DC side voltage is out of control, which causes the inertial synchronous control to fail to sense the grid frequency and phase information through the DC side voltage, causing the inertial synchronous control to lose lock and cause the system to become disordered. Both adaptive control strategies can effectively stabilize the DC side voltage by dynamically adjusting the virtual inertia and damping coefficient, ensuring that the inertial synchronous control mechanism can still accurately obtain the frequency and phase information of the grid voltage by sensing the DC side voltage, so that the system can quickly recover stability during the fault. Compared with the adaptive control strategy before improvement, the improved strategy makes the overshoot and adjustment time of DC side voltage and system output frequency smaller at the moment of fault and recovery, and the response speed is faster. It shows that virtual inertia and damping coefficient can improve the real-time and response performance of control strategy by sensing and quantifying the amplitude of grid voltage fluctuation in advance, and then implementing real-time and accurate parameter control according to the specific situation of fluctuation.

[0151] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A direct-drive wind turbine inertial synchronous control system based on parameter adaptation, characterized in that: include: The impact analysis module includes a wind power fluctuation impact analysis unit and a grid voltage fluctuation impact analysis unit, wherein the wind power fluctuation impact analysis unit is used to analyze the impact of wind power fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a first analysis result, and the grid voltage fluctuation impact analysis unit is used to analyze the impact of grid voltage fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a second analysis result; A strategy formulation module, used for generating an adaptive control strategy according to the first analysis result and the second analysis result, wherein the adaptive control strategy is used for adaptively adjusting the virtual inertia and the damping coefficient; A synchronous control module, used for acquiring real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency variation and angular frequency variation rate, determining real-time moment of inertia and real-time damping coefficient based on the real-time wind power fluctuation data, real-time grid voltage fluctuation data, angular frequency variation and angular frequency variation rate according to the adaptive control strategy, and performing inertial synchronous control of the direct-drive wind turbine set according to the real-time moment of inertia and the real-time damping coefficient; The wind power fluctuation impact analysis unit analyzes the impact of wind power fluctuation on the inertial synchronous control of the direct-drive wind turbine generator set to obtain a first analysis result, including: Establish the dynamic equation of DC side capacitance of direct-drive wind turbine grid-connected system; Establish the dynamic equation of grid-connected inverter output power; Under a first preset condition, a small signal linearization process is performed on the dynamic equation of the grid-connected inverter output power to obtain a dynamic equation of the change in the output power of the first inverter, wherein the first preset condition is that the grid voltage remains unchanged and the wind power fluctuates due to changes in the ambient wind speed; Establish a state-space model of inertial synchronization; Linearizing the state space model of the inertial synchronization to obtain a first linearization result; Linearizing the dynamic equation of the DC side capacitance of the direct-drive wind turbine grid-connected system to obtain a second linearization result; According to the dynamic equation of the change in output power of the first inverter, the first linearization result and the second linearization result, an open-loop transfer function of the change in angular frequency and the change in wind power is obtained; The closed-loop transfer function of the angular frequency change and the wind power change is obtained according to the open-loop transfer function of the angular frequency change and the wind power change, wherein the first analysis result at least includes the closed-loop transfer function of the angular frequency change and the wind power change; the grid voltage fluctuation impact analysis unit analyzes the impact of the grid voltage fluctuation on the inertial synchronous control of the direct-drive wind turbine set to obtain a second analysis result, including: Under the second preset condition, a small signal linearization process is performed on the dynamic equation of the grid-connected inverter output power to obtain a dynamic equation of the variation of the second inverter output power, wherein the second preset condition is that the wind power remains unchanged and the grid voltage fluctuates; Obtaining an open-loop transfer function between the angular frequency variation and the grid voltage variation according to the dynamic equation of the variation of the output power of the second inverter, the first linearization result, and the second linearization result; A closed-loop transfer function between the angular frequency change and the grid voltage change is obtained according to the open-loop transfer function between the angular frequency change and the grid voltage change, wherein the second analysis result at least includes the closed-loop transfer function between the angular frequency change and the grid voltage change.

2. The parameter-adaptive direct-drive wind turbine inertial synchronous control system according to claim 1, characterized in that: The strategy formulation module generates an adaptive control strategy according to the first analysis result and the second analysis result, including: Conduct correlation analysis on the change rate and change amount of the virtual inertia and damping coefficient and the angular frequency, and generate correlation analysis results; Obtaining an angular frequency change amount curve and an angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed, and obtaining an interval demand table according to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed; The adaptive control strategy is generated according to the correlation analysis result, the first analysis result, the second analysis result and the interval demand table.

3. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to claim 2, characterized in that: Perform correlation analysis on the rate of change of virtual inertia, damping coefficient and angular frequency to generate correlation analysis results, including: The state space model of the inertial synchronization is deformed, and according to the deformation result, the positive and negative results of the correlation between the rate of change of the angular frequency and the virtual inertia and the positive and negative results of the correlation between the rate of change of the angular frequency and the damping coefficient are obtained.

4. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to claim 2, characterized in that: According to the angular frequency change amount curve and the angular frequency change rate curve when the virtual inertia and damping coefficient are fixed, an interval demand table is obtained, including: Determining a plurality of target intervals according to an angular frequency change amount curve and an angular frequency change rate curve when the virtual inertia and the damping coefficient are fixed; For each of the target intervals, a virtual inertia change requirement and a damping coefficient change requirement corresponding to the target interval are determined.

5. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to any one of claims 2 to 4, characterized in that: The adaptive control strategy is: ， in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the change in angular frequency.

6. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to any one of claims 2 to 4, characterized in that: The adaptive control strategy is: ， in, is the virtual inertia, is the initial value of the virtual inertia, is the adjustment coefficient of the virtual inertia when the angular frequency change rate changes, is the angular frequency of the direct-drive wind turbine grid-connected system, is the steady-state value of the grid angular frequency, is the damping coefficient, is the initial value of the damping coefficient, is the adjustment coefficient of the damping coefficient when the angular frequency changes, is the change in angular frequency, is the adaptive adjustment coefficient of virtual inertia when wind power fluctuates, is the per-unit value of wind power output at the machine side, is the adaptive adjustment coefficient of virtual inertia when the grid voltage fluctuates, is the per unit value of the grid voltage, is the adaptive adjustment coefficient of the damping coefficient when the wind power fluctuates, is the adaptive adjustment coefficient of the damping coefficient when the grid voltage fluctuates, is the angular frequency threshold, is the hyperbolic tangent function.

7. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to any one of claims 1 to 4, characterized in that: The closed-loop transfer function of the angular frequency change and the wind power change is: ， in, is the closed-loop transfer function between the angular frequency change and the wind power change, is the open-loop transfer function of the angular frequency change and wind power change, is the change in angular frequency, is the steady-state value of the grid angular frequency, is the change of wind power output on the machine side, S is the differential operator, are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, m is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

8. The parameter adaptive direct-drive wind turbine inertial synchronous control system according to claim 7, characterized in that: The closed-loop transfer function between the angular frequency variation and the grid voltage variation is: ， in, is the closed-loop transfer function between the angular frequency change and the grid voltage change, is the open-loop transfer function between the angular frequency change and the grid voltage change, is the grid voltage variation, is the change in angular frequency, is the steady-state value of the grid angular frequency, S is the differential operator, are coefficients, is the equivalent line impedance, is the steady-state value of the DC bus voltage, is the DC bus capacitance, m is the modulation ratio, is the steady-state value of the grid voltage, is the steady-state power angle, is a sine function, is the steady-state value of the inverter output voltage, is the cosine function, is the virtual inertia, is the damping coefficient, is the fan capacity, is the sampling time.

Images