A method and device for adaptive voltage control of wind-solar-storage DC microgrid

Abstract

This invention proposes a voltage adaptive control method and device for wind-solar-storage DC microgrids, belonging to the field of DC microgrids. The method includes: establishing quasi-virtual synchronous machine control equations for DC / AC converters and DC / DC converters using voltage-current droop control in the wind-solar-storage DC microgrid; determining the adjustment range of the equivalent virtual capacitance and virtual damping coefficient of the DC / AC converter under quasi-virtual synchronous machine control by converting the quasi-virtual synchronous machine control equations of the DC / AC converter into quasi-virtual synchronous machine control small-signal equations; and adaptively adjusting the equivalent virtual capacitance and virtual damping coefficient of the DC / AC converter and DC / DC converter based on the adjustment range, according to the voltage dynamic response and the capacity limitations of the DC / AC converter. This invention can effectively improve voltage quality, enhance the stability of new energy grid-connected systems, and effectively extend the service life of grid-connected converters in the voltage control of wind-solar-storage DC microgrids.

Description

Technical Field

[0001] This invention belongs to the field of DC microgrids, specifically relating to a method and device for adaptive voltage control of wind-solar-storage DC microgrids. Background Technology

[0002] To address the energy crisis, the development and utilization of renewable energy sources such as wind and solar power, which boast abundant reserves and are clean and pollution-free, have rapidly progressed. DC microgrids, constructed by distributed energy resources and energy storage units, can effectively achieve comprehensive energy utilization. Furthermore, the operation and control of DC systems are unaffected by frequency and power angle, effectively improving power quality and supply reliability. The stability of the DC bus voltage is the sole criterion for the stability of the DC grid; therefore, ensuring a constant DC bus voltage is crucial.

[0003] DC microgrids are low-inertia networks based on power electronic devices. Sudden changes in power output and load switching on the energy side can cause sharp fluctuations in DC bus voltage, which is even more severe in high-power DC systems, directly jeopardizing the safety and stability of grid operation. Although traditional droop control can respond quickly to voltage fluctuations, it is differential voltage regulation, and the larger the output power, the greater the voltage deviation. Furthermore, due to the typical characteristics of DC grids—"low inertia and weak damping"—the bus voltage will still fluctuate drastically under large power disturbances.

[0004] Therefore, by analogy with the virtual synchronous generator (VSG) technology widely used in AC power grids, applying virtual inertial control to grid-connected converters in DC power grids can effectively suppress DC voltage fluctuations. Consequently, some scholars have proposed an Analogous Virtual Synchronous Generator (AVSG) control method for DC voltage control to enhance the inertia of DC microgrids and smooth bus voltage fluctuations. In AVSG control, the most critical parameters are the virtual inertia and damping coefficient; adjusting these parameters can improve the system's transient stability. However, the output of new energy sources is stochastic; under fluctuations in power output on the power source side, fixed virtual inertia parameters cannot achieve optimal control. Therefore, research on adaptive control of virtual inertia and damping parameters is of great significance.

[0005] There has been considerable research on voltage control methods for wind, solar, and energy storage power generation systems both domestically and internationally, but there are still shortcomings, mainly in the following two aspects:

[0006] 1. The issue of steady-state error in voltage regulation was not considered.

[0007] Traditional AVSG control often employs droop control in the outer loop, which suffers from steady-state voltage regulation error. This problem becomes even more pronounced in high-power DC microgrids.

[0008] 2. The capacity limitations of the converter and the coordination between multiple converters were not considered.

[0009] Current virtual inertial control is mostly designed for a single converter and does not fully utilize the voltage regulation capabilities of multi-terminal converters. Furthermore, its adaptive control focuses on the deviation and rate of change of DC voltage, without considering the capacity of the converter and the coordination between multiple converters, which is not conducive to the long-term safe operation of power electronic devices. Summary of the Invention

[0010] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a voltage adaptive control method and device for wind-solar-storage DC microgrids. This invention eliminates DC voltage steady-state error through a voltage compensation stage; it simultaneously considers the effects of voltage variations and converter output power limitations in parameter adaptive control. This invention can be applied to the voltage control of wind-solar-storage DC microgrids, effectively improving voltage quality, enhancing the stability of new energy grid-connected systems, and ensuring that the grid-connected converter does not exceed its power limits during operation, thus extending its service life.

[0011] A first aspect of this invention proposes a voltage adaptive control method for a wind-solar-storage DC microgrid, comprising:

[0012] For DC / AC converters and DC / DC converters using voltage-current droop control in wind-solar-storage DC microgrids, corresponding virtual synchronous machine-like control equations are established respectively. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter.

[0013] By converting the control equations of the DC / AC converter into small-signal control equations of the DC / AC converter, and plotting the root locus diagram, the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine is determined.

[0014] Based on the aforementioned adjustment range, and according to the voltage dynamic response and the capacity limitation of the DC / AC converter, the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter are adaptively adjusted respectively to achieve adaptive control of the voltage of the wind-solar-storage DC microgrid.

[0015] In a specific embodiment of the present invention, the control equation expression of the DC / AC converter-like virtual synchronous machine is as follows:

[0016]

[0017] In the formula, i dc The current injected by the DC / AC converter into the DC microgrid; i out D is the output DC current of the DC / AC converter. v C is the virtual damping coefficient of the DC / AC converter. v The equivalent virtual capacitance of the DC / AC converter; u dcref This is the reference value for the DC bus voltage of the DC / AC converter; U n This is the rated voltage of the DC bus.

[0018] Among them, i out =K p (U n -u dc ), K p U is the droop control coefficient. dc This is the DC-side output voltage.

[0019] In a specific embodiment of the present invention, the control equation expression of the quasi-virtual synchronous machine of the DC / DC converter is as follows:

[0020]

[0021] In the formula, i b For the input current of the DC / DC converter; i b_dc C is the current flowing into the DC bus of the DC / DC converter. vb2 D is the equivalent virtual capacitance of the DC / DC converter. vb2 u is the virtual damping coefficient of the DC / DC converter. dcrefb2 This is the reference value for the output voltage of the DC / DC converter.

[0022] In a specific embodiment of the present invention, the small-signal equation expression for the quasi-virtual synchronous machine control of the DC / AC converter is as follows:

[0023]

[0024] In the formula, s is the differential operator; Δi dc (s) represents the DC current increment; Δu dcref (s) represents the DC voltage increment.

[0025] In a specific embodiment of the present invention, determining the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine includes:

[0026] Based on the aforementioned virtual synchronous machine control small-signal equations, the DC bus voltage disturbance Δu is obtained respectively. dc d-axis current disturbance Δid d-axis voltage disturbance Δu d and DC current disturbance Δi dc The relationship between them is:

[0027]

[0028] In the formula, U dc I dc These represent the rated operating voltage and rated operating current, respectively; C is the DC-side voltage regulator capacitor; U d I represents the steady-state value of the d-axis voltage component on the grid side. d This represents the steady-state value of the d-axis current component on the grid side.

[0029] Let Δi dref This represents the disturbance of the d-axis current reference value. The current loop controller uses a PI regulator, G. i (s)=k pi +k ii The small-signal equation for the d-axis current component is obtained as follows:

[0030]

[0031] In the formula, k pi k is the proportional gain of the current loop controller. ii L1 and r are the integral coefficients of the current loop controller, and L1 and r are the grid-side filter inductor and its series resistance, respectively.

[0032] The voltage compensation stage uses a PI regulator, denoted by G0(s), where G0(s) = k p0 +k i0 / s, then the control equation for the compensation voltage is:

[0033] (U n -u dc G0(s)=u dcref (6)

[0034] In the formula, k p0 k is the proportional coefficient of the regulator in the voltage compensation circuit. i0 This refers to the integral coefficient of the regulator in the voltage compensation circuit.

[0035] Using Δu dc and Δu dcref Let represent the DC bus voltage disturbance and the DC voltage reference value disturbance, respectively. After performing a Laplace transform on the control equations for the compensation voltage, we obtain:

[0036]

[0037] Based on equations (3), (4), (5), and (7), the DC-side output voltage disturbance Δu is obtained.dc (s) and output current disturbance Δi dc The closed-loop transfer function between (s) is:

[0038]

[0039] In the formula, a = K p +D v m = k pi k iv +k ii k pv ,

[0040]

[0041]

[0042] Where, k pwm The equivalent gain of the bridge voltage; k pv k iv For the voltage outer loop PI regulator parameters, a i and b j All are intermediate parameters, i = 1, ..., 5, j = 1, ..., 6;

[0043] By performing stability analysis on equation (8), the values ​​of G(s) in the virtual capacitor C are plotted respectively. v Pole distribution diagram and G(s) under varying virtual damping D v Plot the pole distribution under the change, and then plot C respectively. v D v The root locus of G(s) as it changes is used to determine C. v D v The range of values ​​for .

[0044] In one specific embodiment of the present invention, the voltage dynamic response includes four stages:

[0045] Phase 1: When the DC bus voltage change rate du dc When / dt>0 and voltage deviation Δu>0, the virtual capacitance C of the DC / AC converter is increased by relating it to the magnitude of the voltage change rate. v and the virtual capacitor C of the DC / DC converter vb2 To reduce the rate of voltage change, the virtual damping coefficient D of the DC / AC converter is reduced according to the magnitude of the voltage deviation. v To improve system response speed and reduce voltage overshoot;

[0046] Phase 2: When the DC bus voltage change rate du dc When / dt<0 and voltage deviation Δu>0, decrease C according to the magnitude of the voltage change rate. v and Cvb2 To restore the voltage to a stable value, increase D according to the magnitude of the voltage deviation. v To accelerate the rate of voltage decay;

[0047] Stage 3: When the DC bus voltage change rate du dc When / dt<0 and voltage deviation Δu<0, increase C according to the magnitude of the voltage change rate. v and C vb2 To reduce the rate of voltage change, decrease D according to the magnitude of the voltage deviation. v To accelerate voltage regulation speed;

[0048] Stage 4: When the rate of change of DC voltage du dc When / dt>0 and voltage deviation Δu<0, decrease C according to the magnitude of the voltage change rate. v and C vb2 Increase D according to the magnitude of the voltage deviation. v To smooth out voltage fluctuations.

[0049] In a specific embodiment of the present invention, the adaptive adjustment of the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter, respectively, includes:

[0050] The virtual capacitance C of the DC / AC converter v and the virtual capacitor C of the DC / DC converter vb2 The relationship for adaptive control is:

[0051]

[0052] In the formula, C 01 C is the initial value of the virtual capacitor of the DC / AC converter. 02 The initial value of the virtual capacitor for the DC / DC converter;

[0053] C vx To account for the virtual capacitance compensation value of the voltage response, C vy The expression for the compensation value of the virtual capacitor, taking into account the capacity limitation of the DC / AC converter, is as follows:

[0054]

[0055]

[0056] In the formula, k c1 k c2 k c3 For virtual capacitor adjustment parameters, Δu is the deviation of the DC voltage from the rated value; du / dt is the DC voltage change rate; k1 is the voltage change rate threshold; P is the DC / AC converter output power; PN This refers to the upper limit of the output power of the DC / AC converter.

[0057] The virtual damping coefficient D of the DC / DC converter vb2 =D0, the virtual damping coefficient D of the DC / AC converter v The adaptive adjustment based on the DC voltage deviation is as follows:

[0058]

[0059] In the formula, D0 is the initial value of the virtual damping coefficient of the DC / AC converter, and k d1 k d2 is the damping adjustment parameter, and k2 is the voltage deviation threshold.

[0060] A second aspect of the present invention provides a voltage adaptive control device for a wind-solar-storage DC microgrid, comprising:

[0061] The virtual synchronous machine control equation construction module is used to establish corresponding virtual synchronous machine control equations for DC / AC converters and DC / DC converters with voltage-current droop control in wind-solar-storage DC microgrids. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter.

[0062] The control parameter adjustment range determination module is used to determine the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine by converting the control equation of the DC / AC converter into a small-signal control equation of the virtual synchronous machine and drawing a root locus diagram.

[0063] An adaptive adjustment module is used to adaptively adjust the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter, respectively, based on the adjustment range, the voltage dynamic response, and the capacity limit of the DC / AC converter, so as to achieve adaptive control of the voltage of the wind-solar-storage DC microgrid.

[0064] A third aspect of the present invention provides an electronic device comprising:

[0065] At least one processor; and a memory communicatively connected to said at least one processor;

[0066] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the aforementioned wind-solar-storage DC microgrid voltage adaptive control method.

[0067] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described wind-solar-storage DC microgrid voltage adaptive control method.

[0068] The features and beneficial effects of this invention are as follows:

[0069] 1) This invention adds a voltage compensation stage to the traditional control, which can realize error-free regulation of DC grid bus voltage and improve the system stability problem caused by voltage deviation.

[0070] 2) In the adaptive parameter adjustment, the present invention enables the control parameters to respond simultaneously to the dynamic voltage adjustment law and the available capacity of the converter. While suppressing voltage fluctuations, it also takes into account the long-term safe operation of the converter, which can extend the service life of the converter to a certain extent.

[0071] 3) This invention can be applied to the voltage control of wind, solar and energy storage DC microgrids, solving the problem that new energy sources do not have voltage regulation capabilities due to their "low inertia and weak damping" characteristics. Through this control, voltage quality can be effectively improved, the stability of the new energy grid-connected system can be enhanced, and the grid-connected converter can be kept within its power limit during operation, thus extending its service life. Attached Figure Description

[0072] Figure 1 This is an overall flowchart of a wind-solar-storage DC microgrid voltage adaptive control method according to an embodiment of the present invention.

[0073] Figure 2 This is a diagram showing the distribution of G(s) poles under different virtual damping conditions in a specific embodiment of the present invention.

[0074] Figure 3 This is a diagram showing the distribution of G(s) poles under different virtual capacitances in a specific embodiment of the present invention.

[0075] Figure 4 This is a simulation diagram of the system operating characteristics when the light intensity suddenly increases in a specific embodiment of the present invention.

[0076] Figure 5 This is a simulation diagram of the system operating characteristics under a sudden load increase in a specific embodiment of the present invention.

[0077] Figure 6 This is a simulation diagram of the system operating characteristics when an additional voltage compensation stage is added in a specific embodiment of the present invention.

[0078] Figure 7 This is a simulation diagram of the system operating characteristics under adaptive control considering converter capacity in a specific embodiment of the present invention. Detailed Implementation

[0079] This invention proposes a method and apparatus for adaptive voltage control of a wind-solar-storage DC microgrid. The technical solutions in the embodiments of this invention will be clearly and completely described below with reference to specific examples and accompanying drawings. Obviously, the described embodiments are merely one embodiment of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the protection scope of this invention.

[0080] A first aspect of this invention proposes a voltage adaptive control method for a wind-solar-storage DC microgrid, comprising:

[0081] For DC / AC converters and DC / DC converters using voltage-current droop control in wind-solar-storage DC microgrids, corresponding virtual synchronous machine-like control equations are established respectively. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter.

[0082] By converting the control equations of the DC / AC converter into small-signal control equations of the DC / AC converter, and plotting the root locus diagram, the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine is determined.

[0083] Based on the aforementioned adjustment range, and according to the voltage dynamic response and the capacity limitation of the DC / AC converter, the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter are adaptively adjusted respectively to achieve adaptive control of the voltage of the wind-solar-storage DC microgrid.

[0084] In a specific embodiment of the present invention, the overall process of the wind-solar-storage DC microgrid voltage adaptive control method is as follows: Figure 1 As shown, the steps include:

[0085] 1) Establish the AVSG control model;

[0086] To facilitate coordinated control of the DC grid, the DC / AC converter in this embodiment of the invention employs voltage-current droop control, thus the DC-side output current i of the DC / AC converter... out The governing equation is i out =K p (U n -u dc ), where K p U is the droop control factor. n The rated voltage of the DC bus, u dc This is the DC-side output voltage.

[0087] The AVSG control equations suitable for grid-connected DC / AC converters in DC microgrids are constructed as follows:

[0088]

[0089] In the formula, i dc The current injected by the DC / AC converter into the DC microgrid; i out D is the output DC current of the DC / AC converter. v C is the virtual damping coefficient of the DC / AC converter. v The equivalent virtual capacitance of the DC / AC converter; u dcref This is the reference value for the DC bus voltage of the DC / AC converter; U n t represents the rated voltage of the DC bus; t represents time.

[0090] The AVSG control equations for the DC / DC converter are as follows:

[0091]

[0092] In the formula, i b For the input current of the DC / DC converter; i b_dc C is the current flowing into the DC bus of the DC / DC converter. vb2 D is the equivalent virtual capacitance of the DC / DC converter. vb2 u is the virtual damping coefficient of the DC / DC converter. dcrefb2 This is the reference value for the output voltage of the DC / DC converter.

[0093] Since the input current reference value in AVSG control is obtained from droop control, which is a differential regulation, a steady-state error exists when using this control to regulate the DC bus voltage. After dynamic adjustment, the voltage cannot be restored to the initial value. In DC grids with high power ratings, the voltage deviation will be more pronounced, potentially affecting the normal operation of the load. To eliminate the steady-state error of the DC bus, this embodiment adds a voltage compensation stage to the traditional AVSG control, using a PI regulator as the compensator.

[0094] 2) Based on step 1), establish the control equations for the DC / AC converter and determine the adjustment range of the equivalent virtual capacitor and virtual damping coefficient for the virtual synchronous machine control.

[0095] In this embodiment, the state variable in the AVSG control equation shown in equation (1), namely the DC-side output voltage u of the DC / AC converter, is... dc Output current i dcRewritten as the sum of steady-state quantities and small disturbances, linearized near the steady-state point, ignoring second-order and higher disturbance terms, and after Laplace transform, the AVSG control small-signal equation of the DC / AC converter is obtained as follows:

[0096]

[0097] In the formula, s is the differential operator; Δi dc (s) represents the DC current increment; Δu dcref (s) represents the DC voltage increment.

[0098] In this embodiment, the inner current loop employs dq-axis decoupled control and operates at unity power factor. Therefore, the q-axis current component i of the inner current loop... q =0, and from the power balance, the DC bus voltage disturbance Δu can be obtained respectively. dc d-axis current disturbance Δi d d-axis voltage disturbance Δu d and DC current disturbance Δi dc The relationship between them is:

[0099]

[0100] In the formula, U dc I dc These represent the rated operating voltage and rated operating current, respectively; C is the DC-side voltage regulator capacitor; U d I represents the steady-state value of the d-axis voltage component on the grid side. d This represents the steady-state value of the d-axis current component on the grid side.

[0101] Let Δi dref This represents the disturbance of the d-axis current reference value. The current loop controller uses a PI regulator G. i (s)=k pi +k ii / s, where k pi k is the proportional gain of the current loop controller. ii Let be the integral coefficient of the current loop controller, and s be the differential operator. The small-signal equation for the d-axis current component is obtained as follows:

[0102]

[0103] In the formula, L1 and r are the grid-side filter inductor and its series resistance, respectively.

[0104] It should be noted that in this embodiment, the grid-connected control consists of an outer voltage loop control and an inner current loop control. The improved AVSG control designed in this embodiment is the controller on the outer voltage loop; the inner current loop adopts dq decoupling control, that is, the current is decomposed into two coordinate axes. The controller of the inner current loop adopts a PI regulator, and the q-axis current component is 0. Therefore, only the d-axis current component equation is analyzed.

[0105] The voltage compensation stage uses a PI regulator, denoted by G0(s), where G0(s) = k p0 +k i0 / s, where k p0 k is the proportional coefficient of the regulator in the voltage compensation circuit. i0 Let be the integral coefficient of the regulator in the voltage compensation circuit, and s be the differential operator. Then the control equation for the compensation voltage is:

[0106] (U n -u dc G0(s)=u dcref (6)

[0107] Using Δu dc and Δu dcref Let represent the DC bus voltage disturbance and the DC voltage reference value disturbance, respectively. After performing a Laplace transform on the control equations for the compensation voltage, we obtain:

[0108]

[0109] Based on equations (3), (4), (5), and (7), and ignoring the series resistance of the filter inductor, the DC-side output voltage disturbance Δu is obtained. dc (s) and output current disturbance Δi dc The closed-loop transfer function between (s) is:

[0110]

[0111] In the formula, a = K p +D v m = k pi k iv +k ii k pv ,

[0112]

[0113]

[0114] Where, k pwm The equivalent gain of the bridge voltage; k pv k iv For the voltage outer loop PI regulator parameters, a i and bj All are intermediate parameters, i = 1, ..., 5, j = 1, ..., 6.

[0115] Stability analysis is performed on equation (8). First, the stability of G(s) under virtual capacitance C is given. v Pole distribution diagram and G(s) under varying virtual damping D v Plot the pole distribution under the change, and then plot C respectively. v D v The root locus of G(s) as it changes is used to determine C. v D v The selection range makes C v D v The system's stable operation will not be affected during subsequent adaptive adjustments.

[0116] Figure 2 The virtual damping parameter D is shown in a specific embodiment of the present invention. v The pole distribution of G(s) as the value increases from 100 to 800 is shown in the figure. The arrows in the figure point in the direction of D. v The direction of the pole shift of G(s) as it increases. Figure 2 The horizontal and vertical axes represent the real part σ and imaginary part ω of the pole, respectively. The symbol "X" in the figure represents D. v The location of the poles changes with each increment. Figure 2 It can be seen that D v The larger the value, the farther the poles of change (i.e., the poles on the real axis) are from the imaginary axis, and the greater the system stability.

[0117] Figure 3 This is a diagram showing the G(s) pole distribution under different virtual capacitances in a specific embodiment of the present invention. Figure 3 (a) is C v Pole distribution of G(s) as the F-value increases from 1 μF to 60 μF. Figure 3 (b) is C v Pole distribution of G(s) as the F-frequency increases from 50 μF to 2000 μF. Figure 3 (a) It is known that in C v As the number of poles increases, one pole gradually moves closer to the imaginary axis, weakening the system's stability. The remaining poles change relatively little and are all located in the left half-plane. Figure 3 (b) It is known that when the virtual capacitance C v If the size increases further, one pair of conjugate poles will enter the right half-plane, causing the system to become unstable.

[0118] C v D v The parameter values ​​affect system stability. Each parameter setting corresponds to a pole in the graph, i.e., "X". When the system is unstable, "X" will be in the right half of the graph, therefore C needs to be determined.v D v The selection range should be such that the parameters do not affect the stable operation of the system during subsequent adaptive adjustment; that is, the parameter settings should keep "X" in the left half of the graph.

[0119] As can be seen from the stability analysis above, with the virtual damping parameter D v Increasing the value of D improves system stability; therefore, in this embodiment, D is set in adaptive control. v A value greater than 100 ensures a certain stability margin. However, as C... v As C increases, the stability of the system gradually decreases. v If the value is too large, it may even lead to instability. Therefore, to ensure stable system operation, the size of the virtual capacitor should be limited in AVSG adaptive control. The virtual capacitor adjustment process should satisfy the following:

[0120]

[0121] 3) Adaptive adjustment of control parameters.

[0122] In this embodiment, the adaptive adjustment control parameters include: adaptive adjustment control parameters based on voltage dynamic response and adaptive adjustment control parameters based on converter capacity limitations.

[0123] The adaptive adjustment of control parameters based on voltage dynamic response includes:

[0124] According to the virtual inertial control equations (1) and (2), by adjusting the magnitude of the virtual capacitor and the virtual damper, the deviation and rate of change of the DC bus voltage can be changed, thereby improving the dynamic response characteristics of the DC voltage. Based on the fluctuation curve of the bus voltage after disturbance, this embodiment divides the voltage change into the following four stages:

[0125] Phase 1: DC bus voltage change rate du dc If dt > 0 and voltage deviation Δu > 0, the virtual capacitance C of the DC / AC converter can be increased by relating it to the magnitude of the voltage change rate. v and the virtual capacitor C of the DC / DC converter vb2 To reduce the rate of voltage change, the virtual capacitance C is increased. v While it can help smooth voltage fluctuations, it also prolongs the system's response time. Therefore, the virtual damping D of the DC / AC converter should be reduced according to the magnitude of the voltage deviation. v To improve system response speed and reduce voltage overshoot;

[0126] Phase 2: DC bus voltage change rate du dc When / dt<0 and voltage deviation Δu>0, as the deviation gradually decreases, C needs to be reduced according to the magnitude of the voltage change rate.v and C vb2 This allows the voltage to recover to a stable value as quickly as possible, while simultaneously increasing D according to the magnitude of the voltage deviation. v This further accelerates the rate of voltage decay;

[0127] Phase 3: DC bus voltage change rate du dc When / dt<0 and voltage deviation Δu<0, the adjustment process is similar to the first stage described above. The virtual inertia C needs to be increased according to the magnitude of the voltage change rate. v and C vb2 To reduce the rate of voltage change, the virtual damping coefficient D is reduced according to the magnitude of the voltage deviation. v To accelerate voltage regulation speed;

[0128] Stage 4: DC bus voltage change rate du dc When / dt>0 and voltage deviation Δu<0, the adjustment process is similar to the second stage, reducing C by relating the magnitude of the voltage change rate. v and C vb2 Increase the virtual damping coefficient D according to the magnitude of the voltage deviation. v Smooth out voltage fluctuations.

[0129] The adaptive adjustment of control parameters based on converter capacity limitations includes:

[0130] The DC / AC converter undertakes the primary voltage regulation task, and ensuring its normal operation is crucial for maintaining system safety, stability, and power balance. However, the capacity of the DC / AC converter limits the power output of the AC mains. If the DC / AC converter always outputs power at its maximum capacity, it may affect the converter's lifespan. Furthermore, when the system experiences large disturbances, its instantaneous output power may become excessive, even reaching its own limit, forcing it to switch to power-limited operation and thus losing its voltage regulation capability. Therefore, the impact of the converter's output power limitation can be considered in virtual inertia adaptive control. As the converter's output power approaches its upper limit, the virtual inertia value should decrease as the remaining capacity of the DC / AC converter decreases, while the DC / DC converter's inertia increases by the same amount to maintain the overall inertia level of the DC grid.

[0131] Specifically, the virtual capacitor C of the DC / AC converter v and the virtual capacitor C of the DC / DC converter vb2 The relationship for adaptive control is:

[0132]

[0133] In the formula, C 01 C is the initial value of the virtual capacitor of the DC / AC converter. 02 C represents the initial value of the virtual capacitor of the DC / DC converter.vx To account for the compensation value of the virtual capacitance in the voltage response, C vy The specific calculation formula for the compensation value of the virtual capacitor, which takes into account the capacity limitation of the DC / AC converter, is as follows:

[0134]

[0135]

[0136] In the formula, k c1 k c2 k c3 For the virtual capacitor adjustment parameters, in this embodiment, a value of 10 is used. -6 1 and 1; Δu is the deviation of the DC voltage from the rated value; du / dt is the DC voltage change rate; k1 is the voltage change rate threshold; P is the output power of the DC / AC converter; P N This represents the upper limit of the output power of the DC / AC converter.

[0137] The virtual damping coefficient of the DC / DC converter is a fixed value D. vb2 =D0, the virtual damping coefficient D of the DC / AC converter v The adaptive adjustment based on the DC voltage deviation is as follows:

[0138]

[0139] In the formula, D0 is the initial value of the virtual damping coefficient of the DC / AC converter, and k d1 k d2 For damping adjustment parameters, in this embodiment, k1 and k2 are taken as 0.0028 and 1 respectively; k2 is the voltage deviation threshold.

[0140] The application effect of the method described in this invention will be explained in detail below with reference to the simulation results of a specific embodiment.

[0141] In a specific embodiment of the present invention, a basic model of a wind-solar-storage system is constructed. The wind turbine unit is connected to the DC grid via AC / DC and DC / DC converters. Under normal circumstances, it operates in maximum power point tracking (MPPT) mode to ensure maximum utilization of wind energy. The photovoltaic cell array is connected to the DC grid via a DC / DC converter, generally operating in MPPT mode, but can operate in reduced power mode under special circumstances. The energy storage unit consists of a battery connected to the DC bus via a bidirectional DC / DC converter, enabling charge and discharge control. During normal system operation, it works with the grid-connected converter to control the DC bus voltage. A grid-connected bidirectional DC / AC converter is used on the grid side. When the wind-solar-storage DC grid is operating normally, it works with the battery-side converter to participate in voltage regulation to maintain a stable DC bus voltage; when the grid-connected converter's output power reaches the upper or lower limit, it switches to current-limiting mode. Simulation settings are performed according to the parameters shown in Table 1.

[0142] Table 1 System simulation parameter settings in a specific embodiment of the present invention

[0143]

[0144] 1. Comparison of bus voltage fluctuations under different control methods;

[0145] 1) Simulation comparison of sudden increase in light intensity;

[0146] In this embodiment, the system operates at rated load and constant wind speed. At t=7s, the light intensity suddenly increases from 600lx to 900lx, causing the bus voltage to rise initially. After a brief adjustment, it returns to its initial value, resulting in the simulation curve shown below. Figure 4 As shown, where Figure 4 (a) is a schematic diagram of system power variation. Figure 4 (b) is a schematic diagram of the bus voltage variation. Figure 4 (a) shows that at t=7s, the solar radiation intensity increases abruptly, while the wind speed and load power remain unchanged; from Figure 4 (b) It can be seen that at t=7s, due to the sudden increase in the output power of the energy side, the voltage oscillates. When only the traditional droop control is used, the adjustment time is the longest, about 0.6s, and the voltage fluctuation is the most obvious, with the maximum voltage deviation reaching 22V. When the fixed parameter AVSG control is used, the voltage fluctuation is suppressed, and the maximum voltage deviation is 18V. When the adaptive control method of this embodiment is used, the voltage fluctuation can be further suppressed, the voltage deviation is the smallest, about 11V, and the adjustment time is shortened to 0.4s.

[0147] 2) Simulation comparison of sudden load increase;

[0148] In this embodiment, wind speed and solar intensity are constant. At t=7s, the load suddenly increases from 5MW to 10MW, and the simulation curve is as follows. Figure 5 As shown, where Figure 5 (a) is a schematic diagram of system power variation. Figure 5 (b) is a schematic diagram of the bus voltage variation. Figure 5 (a) It is known that the load suddenly increases at t=7s, while the output power of the wind turbine and photovoltaic system remains unchanged. From... Figure 5 (b) It can be seen that the voltage drops first at t=7s, and then recovers to the initial value after a short adjustment process. When using the traditional droop control method, the voltage adjustment time is the longest and the overshoot is the largest, about 35V. When using the fixed parameter AVSG control, the voltage adjustment time is shortened and the fluctuation amplitude is significantly reduced. When using the parameter adaptive control, the voltage overshoot is the smallest, about 13V, and the voltage change rate is also the smallest, and the voltage fluctuation is significantly suppressed.

[0149] 2. The function of the voltage compensation circuit;

[0150] In this embodiment, at t=7s, the light intensity is suddenly increased from 600lx to 900lx. The simulation curve of the system's operating characteristics after adding a voltage compensation circuit is shown below. Figure 6 As shown in the figure, the dashed line represents parameter adaptive control without voltage compensation, and the solid line represents adaptive control with voltage compensation. Figure 6 (a) is a schematic diagram of DC bus voltage variation. Figure 6 (b) is a schematic diagram showing the input power variation of the DC / AC converter. Figure 6 (a) It can be seen that at t=7s, the sudden increase in light intensity causes voltage oscillation. Without voltage compensation, the voltage stabilizes at approximately 8.5s, but a steady-state error exists in the bus voltage, and this error increases with the input power. After voltage compensation is added, the DC voltage returns to a constant value at approximately 7.5s, and both voltage overshoot and settling time decrease. Figure 6 (b) It can be seen that at t=7s, due to the sudden increase in system input power, the input power of the DC / AC converter also increases suddenly. With voltage compensation, the input power tends to stabilize after about 0.2s, while without voltage compensation, the input power takes about 0.8s to recover and stabilize. Therefore, the voltage compensation stage can not only eliminate voltage regulation steady-state error, but also improve the dynamic characteristics of the system after disturbance.

[0151] 3. Consider the role of adaptive parameter control for converter capacity;

[0152] In this embodiment, with other parameters remaining constant, t = 7s, and the light intensity suddenly increasing by 600 lx, the dynamic response of the system under adaptive control considering the converter capacity is as follows: Figure 7 As shown, where Figure 7(a) is a schematic diagram of the input power variation of the DC / AC converter. Figure 7 (b) is a schematic diagram of the DC bus voltage variation. Figure 7 (a) As shown by the dashed line, when the adjustment of the virtual inertia of the DC / AC converter does not consider the converter's capacity constraint, the input power of the converter suddenly increases under a large disturbance, approximately 7.1s (where the dashed line in the figure represents the absence of capacity constraint, and the solid line represents the presence of capacity constraint; before this moment, the converter's power has not yet reached the limit, and the power change pattern is the same, hence the first part of the curves overlap), its instantaneous power exceeds the rated capacity by 15MW, and the converter immediately switches to power-limited operation; at this moment, the power waveform undergoes a sudden change; while by Figure 7 (a) As shown in the solid line, considering capacity limitations, the active power fluctuates at t=7s, but stabilizes after approximately 0.3s of adjustment. Figure 7 As shown by the dashed line in (b), when using adaptive control without capacity constraints, at t = 7.1s, the DC / AC converter loses its voltage regulation capability and switches from battery DC / DC converter to constant voltage operation to maintain bus voltage stability, but the adjustment time is relatively long, recovering to the initial value in about 9.5s; Figure 7 (b) As shown in the figure, after considering the converter constraints, the converter provides inertia to the system while trying not to exceed its power limit, so that it still has the ability to regulate voltage under large disturbances. The bus voltage tends to stabilize after about 8 seconds.

[0153] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0154] To achieve the above embodiments, a second aspect of the present invention provides a voltage adaptive control device for a wind-solar-storage DC microgrid, comprising:

[0155] The virtual synchronous machine control equation construction module is used to establish corresponding virtual synchronous machine control equations for DC / AC converters and DC / DC converters with voltage-current droop control in wind-solar-storage DC microgrids. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter.

[0156] The control parameter adjustment range determination module is used to determine the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine by converting the control equation of the DC / AC converter into a small-signal control equation of the virtual synchronous machine and drawing a root locus diagram.

[0157] An adaptive adjustment module is used to adaptively adjust the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter, respectively, based on the adjustment range, the voltage dynamic response, and the capacity limit of the DC / AC converter, so as to achieve adaptive control of the voltage of the wind-solar-storage DC microgrid.

[0158] It should be noted that the foregoing explanation of an embodiment of a wind-solar-storage DC microgrid voltage adaptive control method also applies to a wind-solar-storage DC microgrid voltage adaptive control device of this embodiment, and will not be repeated here. According to an embodiment of the present invention, a wind-solar-storage DC microgrid voltage adaptive control device establishes corresponding virtual synchronous machine-like control equations for the DC / AC converter and DC / DC converter using voltage-current droop control in the wind-solar-storage DC microgrid. The control equations include a voltage compensation stage and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter. By converting the virtual synchronous machine-like control equations of the DC / AC converter into virtual synchronous machine-like control small-signal equations and plotting root locus diagrams, the adjustment range of the equivalent virtual capacitance and virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine is determined. Based on the adjustment range, and according to the voltage dynamic response and the capacity limitation of the DC / AC converter, the equivalent virtual capacitance and virtual damping coefficient corresponding to the DC / AC converter and DC / DC converter are adaptively adjusted to achieve adaptive control of the wind-solar-storage DC microgrid voltage. This enables effective improvement of voltage quality and stability of the new energy grid-connected system in the voltage control of wind, solar and energy storage DC microgrids, while ensuring that the grid-connected converter does not exceed its power limit during operation and extends its service life.

[0159] To implement the above embodiments, a third aspect of the present invention provides an electronic device, comprising:

[0160] At least one processor; and a memory communicatively connected to said at least one processor;

[0161] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the aforementioned wind-solar-storage DC microgrid voltage adaptive control method.

[0162] To implement the above embodiments, a fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described wind-solar-storage DC microgrid voltage adaptive control method.

[0163] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0164] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform a wind-solar-storage DC microgrid voltage adaptive control method according to the above embodiments.

[0165] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0166] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0167] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0168] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0169] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0170] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0171] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0172] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0173] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for adaptive voltage control of a wind-solar-storage DC microgrid, characterized in that, include: For DC / AC converters and DC / DC converters using voltage-current droop control in wind-solar-storage DC microgrids, corresponding virtual synchronous machine-like control equations are established respectively. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter. By converting the control equations of the DC / AC converter into small-signal control equations of the DC / AC converter, and plotting the root locus diagram, the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine is determined. Based on the aforementioned adjustment range, and according to the voltage dynamic response and the capacity limitation of the DC / AC converter, the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter are adaptively adjusted respectively to achieve adaptive control of the voltage of the wind-solar-storage DC microgrid. The control equations for the quasi-virtual synchronous machine of the DC / AC converter are expressed as follows: （1） In the formula, i dc The current injected by the DC / AC converter into the DC microgrid; i out D is the output DC current of the DC / AC converter. v C is the virtual damping coefficient of the DC / AC converter. v The equivalent virtual capacitance of the DC / AC converter; u dcref This is the reference value for the DC bus voltage of the DC / AC converter; U n This is the rated voltage of the DC bus. Among them, i out =K p (U n -u dc ), K p U is the droop control coefficient. dc This is the DC-side output voltage; The control equations for the virtual synchronous machine-like DC / DC converter are expressed as follows: （2） In the formula, i b For the input current of the DC / DC converter; i b_dc C is the current flowing into the DC bus of the DC / DC converter. vb2 D is the equivalent virtual capacitance of the DC / DC converter. vb2 u is the virtual damping coefficient of the DC / DC converter. dcrefb2 This is the reference value for the output voltage of the DC / DC converter. The small-signal equation expression for the virtual synchronous machine control of the DC / AC converter is as follows: （3） In the formula, s is the differential operator; ∆i dc (s) represents the DC current increment; ∆u dcref (s) represents the DC voltage increment; The voltage compensation stage uses a PI regulator, denoted by G0(s), where G0(s) = k p0 +k i0 / s, then the control equation for the compensation voltage is: （6） In the formula, k p0 k is the proportional coefficient of the regulator in the voltage compensation circuit. i0 This is the integral coefficient of the regulator in the voltage compensation circuit.

2. The method according to claim 1, characterized in that, The adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine includes: Based on the aforementioned virtual synchronous machine control small-signal equations, the DC bus voltage disturbance ∆u is obtained respectively. dc d-axis current disturbance ∆i d d-axis voltage disturbance ∆u d and DC current disturbance ∆i dc The relationship between them is: （4） In the formula, U dc I dc These represent the rated operating voltage and rated operating current, respectively; C is the DC-side voltage regulator capacitor; U d I represents the steady-state value of the d-axis voltage component on the grid side. d This represents the steady-state value of the d-axis current component on the grid side. Let ∆i dref This represents the disturbance of the d-axis current reference value. The current loop controller uses a PI regulator, G. i (s)=k pi +k ii The small-signal equation for the d-axis current component is obtained as follows: （5） In the formula, k pi k is the proportional gain of the current loop controller. ii L1 represents the integral coefficient of the current loop controller, and L2 and r represent the grid-side filter inductor and its series resistance, respectively. Using ∆u dc and ∆u dcref Let represent the DC bus voltage disturbance and the DC voltage reference value disturbance, respectively. After performing a Laplace transform on the control equations for the compensation voltage, we obtain: （7） Based on equations (3), (4), (5), and (7), the DC-side output voltage disturbance ∆u is obtained. dc (s) and output current disturbance ∆i dc The closed-loop transfer function between (s) is: （8） In the formula, , , Where, k pwm The equivalent gain of the bridge voltage; k pv k iv For the voltage outer loop PI regulator parameters, a i and b j All are intermediate parameters, i=1,…,5, j=1,…,6; By performing stability analysis on equation (8), the values ​​of G(s) in the virtual capacitor C are plotted. v Pole distribution diagram and G(s) under varying virtual damping D v Plot the pole distribution under the change, and then plot C respectively. v D v The root locus of G(s) as it changes is used to determine C. v D v The range of values ​​for .

3. The method according to claim 2, characterized in that, The voltage dynamic response includes four stages: Phase 1: When the DC bus voltage change rate du dc When / dt>0 and voltage deviation ∆u>0, the virtual capacitance C of the DC / AC converter is increased by relating it to the magnitude of the voltage change rate. v and the virtual capacitor C of the DC / DC converter vb2 To reduce the rate of voltage change, the virtual damping coefficient D of the DC / AC converter is reduced according to the magnitude of the voltage deviation. v To improve system response speed and reduce voltage overshoot; Phase 2: When the DC bus voltage change rate du dc When / dt<0 and voltage deviation ∆u>0, decrease C according to the magnitude of the voltage change rate. v and C vb2 To restore the voltage to a stable value, increase D according to the magnitude of the voltage deviation. v To accelerate the rate of voltage decay; Stage 3: When the DC bus voltage change rate du dc When / dt<0 and voltage deviation ∆u<0, increase C according to the magnitude of the voltage change rate. v and C vb2 To reduce the rate of voltage change, decrease D according to the magnitude of the voltage deviation. v To accelerate voltage regulation speed; Stage 4: When the rate of change of DC voltage du dc When / dt>0 and voltage deviation ∆u<0, decrease C according to the magnitude of the voltage change rate. v and C vb2 Increase D according to the magnitude of the voltage deviation. v To smooth out voltage fluctuations.

4. The method according to claim 3, characterized in that, The adaptive adjustment of the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter respectively includes: The virtual capacitance C of the DC / AC converter v and the virtual capacitor C of the DC / DC converter vb2 The relationship for adaptive control is: In the formula, C 01 C is the initial value of the virtual capacitor of the DC / AC converter. 02 The initial value of the virtual capacitor for the DC / DC converter; C vx To account for the virtual capacitance compensation value of the voltage response, C vy The expression for the compensation value of the virtual capacitor, taking into account the capacity limitation of the DC / AC converter, is as follows: In the formula, k c1 k c2 k c3 For virtual capacitor adjustment parameters, This refers to the deviation of the DC voltage from its rated value. k1 is the DC voltage change rate; k1 is the voltage change rate threshold; P is the DC / AC converter output power; P N This refers to the upper limit of the output power of the DC / AC converter. The virtual damping coefficient D of the DC / DC converter vb2 =D0, the virtual damping coefficient D of the DC / AC converter v The adaptive adjustment based on the DC voltage deviation is as follows: In the formula, D0 is the initial value of the virtual damping coefficient of the DC / AC converter, and k d1 k d2 is the damping adjustment parameter, and k2 is the voltage deviation threshold.

5. A voltage adaptive control device for a wind-solar-storage DC microgrid, characterized in that, include: The virtual synchronous machine control equation construction module is used to establish corresponding virtual synchronous machine control equations for DC / AC converters and DC / DC converters with voltage-current droop control in wind-solar-storage DC microgrids. The control equations include a voltage compensation link and consider the equivalent virtual capacitance and virtual damping coefficient of the corresponding converter. The control parameter adjustment range determination module is used to determine the adjustment range of the equivalent virtual capacitance and the virtual damping coefficient of the DC / AC converter controlled by the virtual synchronous machine by converting the control equation of the DC / AC converter into a small-signal control equation of the virtual synchronous machine and drawing a root locus diagram. An adaptive adjustment module is used to adaptively adjust the equivalent virtual capacitance and the virtual damping coefficient corresponding to the DC / AC converter and the DC / DC converter respectively, based on the adjustment range, the voltage dynamic response and the capacity limit of the DC / AC converter, so as to realize the adaptive control of the voltage of the wind-solar-storage DC microgrid. The control equations for the quasi-virtual synchronous machine of the DC / AC converter are expressed as follows: （1） In the formula, i dc The current injected by the DC / AC converter into the DC microgrid; i out D is the output DC current of the DC / AC converter. v C is the virtual damping coefficient of the DC / AC converter. v The equivalent virtual capacitance of the DC / AC converter; u dcref This is the reference value for the DC bus voltage of the DC / AC converter; U n This is the rated voltage of the DC bus. Among them, i out =K p (U n -u dc ), K p U is the droop control coefficient. dc This is the DC-side output voltage; The control equations for the virtual synchronous machine-like DC / DC converter are expressed as follows: （2） In the formula, i b For the input current of the DC / DC converter; i b_dc C is the current flowing into the DC bus of the DC / DC converter. vb2 D is the equivalent virtual capacitance of the DC / DC converter. vb2 u is the virtual damping coefficient of the DC / DC converter. dcrefb2 This is the reference value for the output voltage of the DC / DC converter. The small-signal equation expression for the virtual synchronous machine control of the DC / AC converter is as follows: （3） In the formula, s is the differential operator; ∆i dc (s) represents the DC current increment; ∆u dcref (s) represents the DC voltage increment; The voltage compensation stage uses a PI regulator, denoted by G0(s), where G0(s) = k p0 +k i0 / s, then the control equation for the compensation voltage is: （6） In the formula, k p0 k is the proportional coefficient of the regulator in the voltage compensation circuit. i0 This is the integral coefficient of the regulator in the voltage compensation circuit.

6. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method according to any one of claims 1-4.

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