Energy storage converter control method and system based on variable universe fuzzy linear active disturbance rejection

Abstract

The invention provides an energy storage converter control method and system based on variable universe fuzzy linear active disturbance rejection. The energy storage converter control method comprises the steps of collecting power grid information and a power grid phase; obtaining an error value e and an error change rate ec of a current inner loop according to the power grid information and the power grid phase; and a current inner loop adopts variable universe fuzzy linear active-disturbance-rejection control, carries out fuzzy processing on the error value e and the error change rate ec and outputs a modulation signal. The technical problems that in the prior art, when active power and reactive power of an energy storage converter are controlled through a current inner loop, linear active disturbance rejection control parameters are fixed, and self-adaptive capacity does not exist are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage converters, and in particular to a control method for an energy storage converter based on variable universe fuzzy linear auto-disturbance rejection and an energy storage converter control system based on variable universe fuzzy linear auto-disturbance rejection. Background Art

[0002] The energy storage converter is a key component for energy exchange between the energy storage unit and the power grid. It can operate in grid-connected, off-grid, and on / off-grid switching modes. Under different working modes, the energy storage converter has corresponding control strategies.

[0003] Current control strategies are commonly used in grid-connected energy storage converters, with the traditional proportional-integral (PI) control strategy being the most common. Constant power control in grid-connected energy storage converters employs a control structure that combines an outer power loop with an inner current loop, both of which provide reactive power regulation. However, the inner current loop structure couples the d-axis and q-axis components, making it difficult for energy storage converters to independently control the d-axis active power and q-axis reactive power.

[0004] However, there is at least one of the following problems in the related technology: in the existing technology, by optimizing the current control strategy of the energy storage converter, the current inner loop can realize independent control of the active and reactive power of the energy storage converter, while accelerating the response speed and tracking accuracy of the control system. However, there is a linear self-adaptive control with fixed parameters and no adaptive capability. When the load suddenly changes or the grid voltage fluctuates, it will cause a certain impact on the energy storage converter. Summary of the Invention

[0005] The present invention solves the technical problem in the prior art that when the active and reactive power of an energy storage converter is controlled through a current inner loop, the linear active disturbance rejection control parameters are fixed and there is no adaptive capability.

[0006] To solve the above problems, the present invention provides a control method for an energy storage converter based on variable universe fuzzy linear active disturbance rejection, comprising: collecting grid information and grid phase; obtaining an error value e and an error change rate ec of a current inner loop based on the grid information and grid phase; and using variable universe fuzzy linear active disturbance rejection control in the current inner loop to perform fuzzy processing on the error value e and the error change rate ec and output a modulation signal.

[0007] Compared with the existing technology, the technical effects achieved by adopting this technical solution are as follows: variable universe fuzzy linear active disturbance rejection control is applied in the current inner loop, the system's coupling quantity and unknown disturbance quantity are all treated as disturbance quantities, and the linear expansion observer in the linear active disturbance rejection is used to estimate the system disturbance in real time and compensate for it, thereby realizing independent control of the active and reactive power of the energy storage converter, while improving the stability and control accuracy of the energy storage converter control system; at the same time, the energy storage converter control method adopts a dual-loop control mode, namely a power outer loop and a current inner loop, the power outer loop adopts PI control, and the current inner loop adopts variable universe fuzzy linear active disturbance rejection control; the variable universe fuzzy linear active disturbance rejection control is used to realize dynamic adjustment of the linear active disturbance rejection parameters, reduce current tracking error and suppress grid background harmonics, shorten the system's dynamic response time, and enhance the system's anti-interference ability, which is an effective solution to improve the comprehensive performance of the energy storage converter.

[0008] In one embodiment of the present invention, the current inner loop adopts variable universe fuzzy linear anti-disturbance control to adjust the error value e and the error change rate ec and output a modulation signal, including: taking the error value e and the error change rate ec as the input signal of the variable universe fuzzy controller; obtaining the input scaling factor according to the input signal and output scaling factor ; Receive input scaling factor , output scaling factor And input signal, according to the fuzzy rules, the input signal is processed by fuzzy domain to dynamically adjust the output parameters of the variable domain fuzzy controller and ; According to the output parameters and Get the modulated signal.

[0009] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: the variable universe fuzzy controller adopts the input scaling factor and output scaling factor , so that the input-output domain of the control can more accurately and adaptively track the changes of the error value e and the error change rate ec.

[0010] In one embodiment of the present invention, the fuzzy domain processing uses NB, NM, NS, ZO, PS, PM, PB7 fuzzy subsets to process the output parameters of the variable domain fuzzy controller. and Perform fuzzy domain calculations.

[0011] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: variable domain fuzzy control establishes fuzzy rules to perform fuzzy domain processing on the input signal, wherein the fuzzy domain adopts 7 membership functions NB, NM, NS, ZO, PS, PM, and PB.

[0012] In one embodiment of the present invention, the variable universe fuzzy controller selects triangular membership functions to describe the fuzzy sets.

[0013] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: the variable universe fuzzy controller selects a triangular membership function with high sensitivity to describe the fuzzy set, and dynamically adjusts the output parameters of the controller according to the fuzzy rules. and .

[0014] In one embodiment of the present invention, the input scaling factor ; Output scaling factor ;in, represents the accuracy of the control system, and (0,1), k represents the sensitivity of the control system, represents the domain value of the error value e, Represents the domain value of the error change rate ec.

[0015] Compared with the existing technology, the technical effects achieved by adopting this technical solution are as follows: when the error value e and the error change rate ec change, the membership function of the fuzzy control will be adaptively adjusted; when the error value e changes, the original control rule will be adopted; and when the error gradually decreases, the density of the control rules increases accordingly, which is equivalent to adding control rules, thereby providing high control accuracy, accelerating the error convergence speed, and compensating for the low steady-state accuracy of fuzzy linear active disturbance rejection control.

[0016] In one embodiment of the present invention, collecting grid information and grid phase includes: collecting the three-phase voltage value of the AC side of the energy storage converter and three-phase current values ; Track and lock the grid phase through the phase-locked loop; Among them, the grid information includes: three-phase voltage value and three-phase current values .

[0017] In one embodiment of the present invention, the error value e and error change rate ec of the current inner loop are obtained according to the grid information and the grid phase, including: obtaining active power P and reactive power Q according to the grid information and the grid phase; The active power error value is obtained by subtracting the active power P from the reactive power reference value. The reactive power error value is obtained by subtracting the active power error value from the reactive power Q; the active power error value and the reactive power error value are calculated by the power outer loop PI controller to obtain the active current reference value and reactive current reference value ; Set the active current reference value and active current The active current error value is obtained by subtraction, and the reactive current reference value is and reactive current The reactive current error value is obtained by difference; the error value e and the error change rate ec are obtained according to the active current error value and the reactive current error value.

[0018] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: sampling the three-phase voltage value of the AC side of the energy storage converter and three-phase current values back, and The active voltage in the two-phase rotating coordinate system is obtained by coordinate transformation , reactive voltage , active current and reactive current Component, at the same time, the phase-locked loop is used to track and lock the grid phase θ; according to the active voltage , reactive voltage , active current , reactive current Active power P and reactive power Q are calculated by using the components and grid phase θ; active power reference value and reactive power reference The active power error value and reactive power error value are obtained by subtracting them from the active power P and reactive power Q respectively. The two power error values ​​are calculated by the power outer loop PI controller to obtain the active current reference value. and reactive current reference value ; Active current reference value and reactive current reference value Active current and reactive current By comparison, the active current error value and the reactive current error value are obtained respectively, and the error value e and the error change rate ec are obtained according to the active current error value and the reactive current error value.

[0019] In one embodiment of the present invention, the phase-locked loop adopts a second-order generalized integrator.

[0020] Compared with the existing technology, the technical effects achieved by adopting this technical solution are: the second-order generalized integral phase-locked loop has a higher locking ability for the grid voltage and grid phase than the traditional synchronous coordinate system phase-locked loop; the second-order generalized integral phase-locked loop can have almost no overshoot in the dynamic response when the frequency changes suddenly, and can accurately detect information such as grid phase, frequency and amplitude.

[0021] On the other hand, an embodiment of the present invention also provides an energy storage converter control system based on variable universe fuzzy linear auto-disturbance rejection, the energy storage converter control system is used to implement the energy storage converter control method based on variable universe fuzzy linear auto-disturbance rejection as any one of the first embodiments, the energy storage converter control system includes: a data acquisition module, the data acquisition module is used to collect grid information and grid phase; a processing module, the processing module is used to obtain the error value e and error change rate ec of the current inner loop according to the grid information and grid phase; a control module, the control module is used to adopt variable universe fuzzy linear auto-disturbance rejection control for the current inner loop, perform fuzzy processing on the error value e and the error change rate ec and output a modulation signal.

[0022] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: the energy storage converter control system based on variable universe fuzzy linear auto-disturbance rejection in this embodiment is used to implement the energy storage converter control method based on variable universe fuzzy linear auto-disturbance rejection as in any embodiment of the present invention, so it has all the beneficial effects of the energy storage converter control method based on variable universe fuzzy linear auto-disturbance rejection as in any embodiment of the present invention, which will not be repeated here.

[0023] After adopting the technical solution of the present invention, the following technical effects can be achieved: (1) Apply variable domain fuzzy linear active disturbance rejection control in the current inner loop, treat the system's coupling and unknown disturbance quantities as disturbance quantities, and use the linear extended observer in the linear active disturbance rejection to estimate the system disturbance in real time and compensate for it, thereby achieving independent control of the active and reactive power of the energy storage converter and improving the stability and control accuracy of the energy storage converter control system. (2) The control method of the energy storage converter is a dual-loop control method, namely the power outer loop and the current inner loop. The power outer loop adopts PI control, and the current inner loop adopts variable universe fuzzy linear active disturbance rejection control. The variable universe fuzzy linear active disturbance rejection control is used to achieve dynamic adjustment of the linear active disturbance rejection parameters, reduce the current tracking error and suppress the background harmonics of the power grid, reduce the dynamic response time of the system, and enhance the anti-interference ability of the system. It is an effective solution to improve the comprehensive performance of the energy storage converter. (3) The variable universe fuzzy controller selects a triangular membership function with high sensitivity to describe the fuzzy set and dynamically adjusts the output parameters of the controller according to the fuzzy rules. and ; (4) The second-order generalized integral phase-locked loop has a higher locking capability for grid voltage and grid phase than the traditional synchronous coordinate system phase-locked loop. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings to be used in describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive efforts. Figure 1 A flow chart of a method for controlling an energy storage converter based on variable universe fuzzy linear active disturbance rejection provided in the first embodiment of the present invention; Figure 2 This is a main circuit topology diagram of the energy storage converter of the present invention; Figure 3 This is a block diagram of the variable universe fuzzy linear active disturbance rejection control system of the present invention; Figure 4 This is a block diagram of the variable universe fuzzy linear active disturbance rejection control strategy of the present invention; Figure 5 This is a block diagram of the current loop PI control in the prior art; Figure 6 It is a block diagram of the telescopic transformation of the variable domain of the present invention; Figure 7 This is a schematic block diagram of the structure of an energy storage converter control system based on variable universe fuzzy linear active disturbance rejection provided by the second embodiment of the present invention.

[0025] Description of reference numerals: 100 - energy storage converter control system; 101 - data acquisition module; 102 - processing module; 103 - control module. DETAILED DESCRIPTION

[0026] To make the above-mentioned objectives, features, and advantages of the present invention more clearly understood, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0027] [Example 1] See also Figure 1 , which is a flow chart of a method for controlling an energy storage converter based on variable universe fuzzy linear active disturbance rejection provided by the first embodiment of the present invention. The method for controlling an energy storage converter includes: S100: collects grid information and grid phase; S200: Obtaining an error value e and an error change rate ec of a current inner loop according to grid information and grid phase; S300: The current inner loop adopts variable universe fuzzy linear active disturbance rejection control, performs fuzzy processing on the error value e and the error change rate ec, and outputs a modulation signal.

[0028] In a specific embodiment, see Figure 2 The energy storage converter utilizes a bidirectional three-level NPC topology. This means that the converter uses a bidirectional three-level NPC converter to exchange energy between the lithium battery's DC power and the grid, achieving bidirectional energy flow. When the lithium battery's DC power is converted to AC power and transmitted to the grid, the converter operates in discharge mode. When the grid's AC power is rectified to DC power and stored in the lithium battery, the converter operates in charging mode. As shown in the main circuit topology diagram of the energy storage converter, the converter's main circuit consists of a lithium battery, DC bus capacitors, a bidirectional three-level NPC converter, a filter inductor, filter capacitors, and a grid-side equivalent resistor.

[0029] See also Figure 5 In the traditional current inner-loop control strategy, the d-axis current and the q-axis current are coupled and influence each other, and the accuracy and stability of the system are related to the filter inductance on the main circuit network side. In actual operating conditions, the quality of the system control performance is related to the filter inductance value, and at the same time, the current inner loop cannot achieve independent control of active and reactive power.

[0030] See also Figure 3 and Figure 4 , linear active disturbance rejection control is used for optimization in the current inner loop, and the mathematical model of the current inner loop of the energy storage converter is given. Fuzzy represents the variable universe fuzzy controller, LESO represents the linear extended state observer, and de / dt represents the rate of change of the error value e. Variable universe fuzzy linear active disturbance rejection control is applied to the current inner loop, treating all the system coupling quantities and unknown disturbance quantities as disturbance quantities. The linear extended state observer in the linear active disturbance rejection is used to estimate the system disturbance in real time and compensate for it, realizing independent control of the active and reactive power of the energy storage converter, while improving the stability and control accuracy of the energy storage converter control system. Since the d and q axes of the current inner loop are symmetrical, the d-axis current is taken as an example: ; This formula is the first-order differential equation of the current loop d-axis; where L is the filter inductor, R is the grid-side equivalent resistance, is the grid voltage frequency, is the d-axis current component, is the q-axis current component, is the grid-side voltage conversion value, is the d-axis voltage component.

[0031] The above formula can be used to derive the formula for the first-order linear active disturbance rejection control of the current inner loop d-axis: Where y , , , , y is the d-axis component of the inner loop current, It is the total disturbance of the sum of the coupling term of the d-axis, the internal disturbance of its own parameter uncertainty term, and the external disturbance of the grid side about the d-axis component. is the d-axis control system gain.

[0032] The state equation of the linear extended state observer for the d-axis current is written as follows: Where, for The derivative of is the estimated value of the d-axis current component, for The estimated value of for The derivative of and is the gain coefficient of the linear extended state observer. We can get and The characteristic formula is: d ; The above formula can be transformed into: , where s is the eigenvalue, is the bandwidth of the linear extended state observer; the parameter and Can be equivalent to 、 , it can be seen that The value of can be adjusted according to the bandwidth of the linear extended state observer. Write the linear state error control formula of the d-axis: Where, is the proportionality coefficient, = ,parameter The closed-loop bandwidth of the system can be At this time, the first-order linear active disturbance rejection control parameter of the d-axis current is 、 The design process is completed, but parameter value adjustment is difficult.

[0033] The variable universe fuzzy linear active disturbance rejection control in this application introduces variable universe control, and adapts to changes in the input signal by adjusting the fuzzy universe, thereby optimizing the problem of adjusting the linear active disturbance rejection control parameters. At the same time, the energy storage converter control method adopts a dual-loop control mode, namely a power outer loop and a current inner loop. The power outer loop adopts PI control, and the current inner loop adopts variable universe fuzzy linear active disturbance rejection control. Dynamic adjustment of the linear active disturbance rejection parameters is achieved through variable universe fuzzy linear active disturbance rejection control, reducing current tracking error and suppressing grid background harmonics, reducing the system's dynamic response time, and enhancing the system's anti-interference ability. This is an effective solution to improve the comprehensive performance of the energy storage converter.

[0034] Furthermore, S300 includes: S310: Using the error value e and the error change rate ec as input signals of the variable universe fuzzy controller; S320: Obtaining an input scaling factor based on the input signal and output scaling factor ; S330: Receive input scaling factor , output scaling factor And input signal, according to the fuzzy rules, the input signal is processed by fuzzy domain to dynamically adjust the output parameters of the variable domain fuzzy controller and ; S340: According to the output parameters and Get the modulated signal.

[0035] Furthermore, input the scaling factor ; Output scaling factor ;in, Indicates the accuracy of the control system and (0,1), k represents the sensitivity of the control system, represents the domain value of the error value e, Represents the domain value of the error change rate ec.

[0036] Specifically, the variable universe fuzzy controller uses the input scaling factor and output scaling factor , so that the input and output domain of the control can more accurately and adaptively track the changes of the error value e and the error change rate ec. According to the input scaling factor and output scaling factor The expression of is: , k>0, the size of the k value reflects the sensitivity of the control method. The larger the k value, the faster the domain changes.

[0037] When the error value e and the error change rate ec change, the membership function of the fuzzy control will be adaptively adjusted; when the error value e changes, the original control rule will be adopted; and when the error gradually decreases, the density of the control rules increases accordingly, which is equivalent to adding control rules, thereby providing high control accuracy, accelerating the error convergence speed, and compensating for the low steady-state accuracy of fuzzy linear active disturbance rejection control.

[0038] Preferably, after S340, the PWM wave is generated by the modulation signal to control the switch tube to turn off. Figure 4 , and is the modulating signal, is the d-axis voltage command value of the modulation signal, is the q-axis voltage command value of the modulation signal.

[0039] Furthermore, the fuzzy domain processing uses NB, NM, NS, ZO, PS, PM, PB7 fuzzy subsets to process the output parameters of the variable domain fuzzy controller. and Perform fuzzy domain calculations.

[0040] Specifically, variable domain fuzzy control establishes fuzzy rules to process the input signal in fuzzy domain, where the fuzzy domain uses 7 membership functions NB, NM, NS, ZO, PS, PM, and PB. According to the adjustment rules of the controller parameters, the output parameters are obtained. and The fuzzy rules are shown in Table 1: Table 1 See also Figure 3 and Figure 6 , the energy storage converter control system introduces fuzzy rules and membership functions, and adjusts the parameters of the linear active disturbance rejection (i.e. and ) for real-time adjustment. The system error value e and the first-order differential signal ec of the error value e (that is, the error change rate ec) are the input signals of the variable universe fuzzy controller. The fuzzy domain is adjusted to adjust the output parameters of the fuzzy domain and the variable universe fuzzy controller. 、 . Figure 6 In , -E is the minimum value of the domain after the initial domain is expanded, and E is the minimum value of the domain after the initial domain is expanded; is the minimum value of the domain after the initial domain is shrunk, is the maximum value of the domain after the initial domain is shrunk.

[0041] In the energy storage converter control method, the output parameters of the variable universe fuzzy controller and the controller parameters tuned by the linear active disturbance rejection are superimposed as the real-time control parameters of the variable universe fuzzy linear active disturbance rejection controller. The expression is: = ; = Where, and are the parameters of the linear active disturbance rejection controller, i.e., the real-time control parameters of the variable universe fuzzy linear active disturbance rejection controller; and are the initial fixed parameters of the linear ADRC controller, i.e., the controller parameters after the linear ADRC tuning is completed; and is the output parameter of the variable universe fuzzy controller.

[0042] Furthermore, the variable universe fuzzy controller selects triangular membership functions to describe the fuzzy sets.

[0043] Specifically, the variable universe fuzzy controller selects a triangular membership function with high sensitivity to describe the fuzzy set and dynamically adjusts the output parameters of the controller according to the fuzzy rules. and .

[0044] Furthermore, S100 includes: S110: Collect the three-phase voltage value of the AC side of the energy storage converter and three-phase current values ; S120: Tracks and locks the grid phase through a phase-locked loop; Among them, the grid information includes: three-phase voltage value and three-phase current values .

[0045] Furthermore, S200 includes: S210: Obtaining active power P and reactive power Q according to grid information and grid phase; S220: Active power reference value The active power error value is obtained by subtracting the active power P from the reactive power reference value. Subtract the reactive power Q to obtain the reactive power error value; S230: The active power error value and the reactive power error value are calculated by the power outer loop PI controller to obtain the active current reference value and reactive current reference value ; S240: Set the active current reference value and active current The active current error value is obtained by subtraction, and the reactive current reference value is and reactive current Make the difference to obtain the reactive current error value; S250: Obtain an error value e and an error change rate ec according to the active current error value and the reactive current error value.

[0046] Specifically, the three-phase voltage value of the AC side of the energy storage converter is sampled and three-phase current values back, and The active voltage in the two-phase rotating coordinate system is obtained by coordinate transformation , reactive voltage , active current and reactive current Component, at the same time, the phase-locked loop is used to track and lock the grid phase θ; according to the active voltage , reactive voltage , active current , reactive current Active power P and reactive power Q are calculated by using the components and grid phase θ; active power reference value and reactive power reference The active power error value and reactive power error value are obtained by subtracting them from the active power P and reactive power Q respectively. The two power error values ​​are calculated by the power outer loop PI controller to obtain the active current reference value. and reactive current reference value ; Active current reference value and reactive current reference value Active current and reactive current By comparison, the active current error value and the reactive current error value are obtained respectively, and the error value e and the error change rate ec are obtained according to the active current error value and the reactive current error value. , ; , .

[0047] Furthermore, the phase-locked loop adopts a second-order generalized integrator.

[0048] Specifically, the phase-locked loop (PLL) uses a second-order generalized integrator to accurately track and lock the grid voltage amplitude and grid phase θ. This second-order generalized integrator PLL has a higher locking capability for grid voltage and phase than a traditional synchronous frame PLL. It also offers virtually zero overshoot in the dynamic response to sudden frequency changes, enabling precise detection of grid phase, frequency, and amplitude.

[0049] [Example 2] See also Figure 7 This embodiment also provides an energy storage converter control system 100 based on variable universe fuzzy linear active disturbance rejection. The energy storage converter control system 100 is used to implement the energy storage converter control method based on variable universe fuzzy linear active disturbance rejection in Example 1. The energy storage converter control system includes: a data acquisition module 101, a processing module 102, and a control module 103. The data acquisition module 101 is used to collect grid information and grid phase; the processing module 102 is used to obtain the error value e and the error change rate ec of the current inner loop based on the grid information and the grid phase; the control module 103 is used to use variable universe fuzzy linear active disturbance rejection control for the current inner loop, perform fuzzy processing on the error value e and the error change rate ec, and output a modulation signal.

[0050] In a specific embodiment, the data acquisition module 101, processing module 102 and control module 103 of the energy storage converter control system 100 based on variable universe fuzzy linear auto-disturbance rejection cooperate to implement the energy storage converter control method based on variable universe fuzzy linear auto-disturbance rejection as described in the first embodiment above, which will not be repeated here.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A control method for an energy storage converter based on variable universe fuzzy linear active disturbance rejection, characterized in that: The energy storage converter control method includes: Collect grid information and grid phase; Obtaining an error value e and an error change rate ec of a current inner loop according to the grid information and the grid phase; The current inner loop adopts variable universe fuzzy linear active disturbance rejection control, performs fuzzy processing on the error value e and the error change rate ec, and outputs a modulation signal.

2. The energy storage converter control method according to claim 1, characterized in that: The current inner loop adopts variable universe fuzzy linear active disturbance rejection control to adjust the error value e and the error change rate ec and output a modulation signal, including: Using the error value e and the error change rate ec as input signals of a variable universe fuzzy controller; Acquire an input scaling factor according to the input signal and output scaling factor ; Receive the input scaling factor , the output scaling factor and the input signal, performing fuzzy domain processing on the input signal according to fuzzy rules to dynamically adjust the output parameters of the variable domain fuzzy controller and ; According to the output parameters and The modulated signal is obtained.

3. The energy storage converter control method according to claim 2, characterized in that: The fuzzy domain processing uses NB, NM, NS, ZO, PS, PM, PB7 fuzzy subsets to process the output parameters of the variable domain fuzzy controller. and Perform fuzzy domain calculations.

4. The energy storage converter control method according to claim 3, characterized in that: include: The variable universe fuzzy controller selects triangular membership functions to describe fuzzy sets.

5. The energy storage converter control method according to claim 2, characterized in that: The input scaling factor ; The output scaling factor ; in, represents the accuracy of the control system, and (0, 1), k represents the sensitivity of the control system, represents the domain value of the error value e, Represents the domain value of the error change rate ec.

6. The energy storage converter control method according to claim 1, characterized in that: The collecting of grid information and grid phase includes: Collect the three-phase voltage value of the AC side of the energy storage converter and three-phase current values ; Tracking and locking the grid phase via a phase-locked loop; The grid information includes: the three-phase voltage value and the three-phase current values .

7. The energy storage converter control method according to claim 6, characterized in that: The step of obtaining an error value e and an error change rate ec of a current inner loop according to the grid information and the grid phase includes: Obtaining active power P and reactive power Q according to the grid information and the grid phase; Set the active power reference value The active power error value is obtained by subtracting the active power P from the active power P, and the reactive power reference value is obtained. Subtracting the reactive power Q from the reactive power to obtain a reactive power error value; The active power error value and the reactive power error value are calculated by the power outer loop PI controller to obtain the active current reference value. and reactive current reference value ; The active current reference value and active current The active current error value is obtained by subtracting the reactive current reference value. and reactive current Make the difference to obtain the reactive current error value; The error value e and the error change rate ec are obtained according to the active current error value and the reactive current error value.

8. The energy storage converter control method according to claim 6, characterized in that: The phase-locked loop adopts a second-order generalized integrator.

9. A variable universe fuzzy linear active disturbance rejection based energy storage converter control system, characterized in that: The energy storage converter control system is used to implement the energy storage converter control method based on variable universe fuzzy linear active disturbance rejection according to any one of claims 1 to 8, and the energy storage converter control system includes: A data acquisition module, wherein the data acquisition module is used to collect power grid information and power grid phase; A processing module, configured to obtain an error value e and an error change rate ec of a current inner loop according to the grid information and the grid phase; A control module is used for the current inner loop to adopt variable universe fuzzy linear active disturbance rejection control, perform fuzzy processing on the error value e and the error change rate ec, and output a modulation signal.

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