Control method, device and equipment for low-carbon building energy storage converter and medium

Abstract

The invention relates to the technical field of energy storage converters, in particular to a control method, device, equipment and medium for a low-carbon building energy storage converter, and the method comprises the steps: constructing a double-ring sliding mode controller based on RMRA control and PI control, and enabling the parameters of the PI controller to be dynamically adjusted through a self-adaptive sliding law; selecting a reference model to generate an ideal output voltage signal, and adaptively controlling the MRAC through model reference to adjust parameters of a PI controller according to an error between ideal output and actual output; the current loop and the voltage loop are decoupled, coupling on the d axis and the q axis is eliminated, and independent control equations of a current controller and a voltage controller are obtained; based on a double-loop sliding mode controller and decoupled current loop and voltage loop control, the output voltage of the converter is dynamically adjusted, the output voltage is kept consistent with a reference model, and harmonic distortion is reduced. According to the method, the worst conditions such as load sudden change and nonlinear load can be responded.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage converters, and in particular to a control method, device, equipment and medium for a low-carbon building energy storage converter. Background Art

[0002] Low-carbon buildings refer to reducing the use of fossil energy, improving energy efficiency, and reducing carbon dioxide emissions throughout the entire life cycle of building materials and equipment manufacturing, construction, and building use. Low-carbon buildings have gradually become the mainstream trend in the international construction industry. The power storage inverter (Power Conversion System, PCS) can control the charging and discharging process of the battery, perform AC and DC conversion, and can directly supply power to AC loads without a power grid. Since low-carbon buildings need to make more use of clean energy such as solar energy and wind energy, energy storage inverters have become an indispensable power unit in low-carbon buildings.

[0003] The R&D and production costs of energy storage converters are high, especially when used in large-scale energy storage systems. Although there are potential economic benefits in the long run, the high initial investment makes some companies and users reluctant to invest. Due to the technical complexity of energy storage converters, maintenance and replacement costs are high, especially in areas with harsh environmental conditions, the reliability and durability of the equipment become important issues.

[0004] Energy storage inverters need to be synchronized with the voltage, frequency and phase of the power grid. Especially under unstable grid conditions, maintaining grid stability is a challenge, which may cause grid fluctuations or even the risk of black start. Energy storage inverters may generate harmonics during the conversion process, which will affect the quality of power and thus affect sensitive equipment.

[0005] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The present invention provides a control method, device, equipment and medium for a low-carbon building energy storage converter, thereby effectively solving the problems in the background technology.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a control method for a low-carbon building energy storage converter, comprising the following steps:

[0008] A dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control is constructed, in which the parameters of the PI controller are dynamically adjusted by the adaptive sliding law.

[0009] A reference model is selected to generate an ideal output voltage signal, and the parameters of the PI controller are adjusted according to the error between the ideal output and the actual output through the model reference adaptive control MRAC;

[0010] Decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations for the current controller and the voltage controller;

[0011] Based on the dual-loop sliding mode controller and the decoupled current loop and voltage loop control, the output voltage of the converter is dynamically adjusted to keep the output voltage consistent with the reference model and reduce harmonic distortion.

[0012] Furthermore, the mathematical model of the model reference adaptive control MRAC is:

[0013]

[0014] Where: I i is the inverter side current, I0 is the grid side current, V i is the inverter side voltage, V0 is the inverter output voltage, R f is the inverter side resistance, R d is the parallel resistance of the filter capacitor, L f is the inverter side filter inductor, C f For the filter capacitor.

[0015] Further, the method of controlling the MRAC by model reference adaptively according to the error between the ideal output and the actual output includes:

[0016] The mathematical model of the model reference adaptive control MRAC is subjected to Park transformation:

[0017]

[0018] Where: I idq is the inverter side current after Park transformation, I 0dq is the inverter output current after Park transformation, V idq is the inverter side voltage after Park transformation, V 0dq is the inverter output voltage after Park transformation.

[0019] Furthermore, the decoupling of the current loop and the voltage loop comprises the following steps:

[0020] Determine the state space model of the energy storage converter in the current loop and the voltage loop respectively;

[0021] Performing Laplace transformation on the state space model to obtain a decoupling matrix;

[0022] A separate controller is used to eliminate the influence of the decoupling matrix, and control equations of the current loop and the voltage loop in the d-axis and q-axis directions are obtained respectively.

[0023] Furthermore, the state space model of the energy storage converter in the current loop is:

[0024]

[0025] middle u di =V id -V od ,u qi =V iq -V oq is the PI controller output;

[0026] Performing Laplace transformation on the above formula yields:

[0027]

[0028] Where:

[0029]

[0030] Using D as shown below 12i (s) and D 21i (s) to eliminate G 12i (s) and G 21i Impact of (s):

[0031]

[0032] Using the decoupling matrix D 12i (s) and D 21i (s), the diagonal matrix can be derived as:

[0033]

[0034] The current control equations in the d-axis and q-axis directions are obtained as follows:

[0035]

[0036] Furthermore, the state space model of the energy storage converter in the voltage loop is:

[0037]

[0038] where u vd =I id -I od ,u vq =I iq -I oq is the PI controller output; I od and Ioq are the perturbations of the d-axis and q-axis respectively; Laplace transform is performed on the above formula:

[0039]

[0040] Where:

[0041]

[0042] Definition D 12v (s) and D 21v (s) are as follows:

[0043]

[0044] Using the decoupling matrix D 12v (s) and D 21v (s), the diagonal matrix can be derived as:

[0045]

[0046] The voltage control equations in the d-axis and q-axis directions are obtained:

[0047]

[0048] The present invention also includes a control device for a low-carbon building energy storage converter, using the above method, including:

[0049] A dual-loop sliding mode control unit is used to construct a dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control, where the parameters of the PI controller are dynamically adjusted by an adaptive sliding law;

[0050] An adaptive control unit is used to select a reference model to generate an ideal output voltage signal, and adjust the parameters of the PI controller according to the error between the ideal output and the actual output through the model reference adaptive control MRAC;

[0051] A decoupling unit is used to decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations of the current controller and the voltage controller;

[0052] The control unit is used to dynamically adjust the output voltage of the converter based on the dual-loop sliding mode controller and the decoupled current loop and voltage loop control, so as to keep the output voltage consistent with the reference model and reduce harmonic distortion.

[0053] The present invention also includes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described above is implemented.

[0054] The present invention also includes a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0055] The beneficial effects of the present invention are as follows: In order to improve the robustness of the system and reduce the total harmonic distortion, in this embodiment, the low-carbon building energy storage converter is based on a dual-loop sliding mode controller of robust model reference adaptive RMRA and PI control. In the presence of uncertainty and external interference, it is necessary to combine the adaptive controller with the sliding mode control SMC. This method combines the robustness of the variable structure with the tracking capability. At the same time, the controller has two control loops, in which the coefficients of the PI controller are adjusted by the adaptive sliding law. This method is used to adjust the output voltage of the inverter under different load conditions and uncertainties, and adapt the output to the reference model to reduce the total harmonic distortion THD. Compared with energy storage converters that use other control methods, this strategy achieves a more stable sinusoidal voltage at a lower THD. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 is a flow chart of the method in Example 1;

[0058] Figure 2 It is a structural schematic diagram of the device in Example 1;

[0059] Figure 3 This is a schematic diagram of an energy storage converter for a low-carbon building power system in Example 2;

[0060] Figure 4 is the overall structural diagram of the MRAC system in Example 2;

[0061] Figure 5 This is a control block diagram of the current loop decoupling matrix energy storage converter in Example 2;

[0062] Figure 6 This is a control block diagram of the energy storage converter of the voltage loop decoupling matrix in Example 2;

[0063] Figure 7 A schematic diagram of the structure of a computer device. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0065] Embodiment 1:

[0066] like Figure 1 As shown: A control method for a low-carbon building energy storage converter comprises the following steps:

[0067] A dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control is constructed, in which the parameters of the PI controller are dynamically adjusted by the adaptive sliding law.

[0068] A reference model is selected to generate an ideal output voltage signal, and the parameters of the PI controller are adjusted according to the error between the ideal output and the actual output through the model reference adaptive control MRAC;

[0069] Decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations for the current controller and the voltage controller;

[0070] Based on the dual-loop sliding mode controller and the decoupled current loop and voltage loop control, the output voltage of the converter is dynamically adjusted to keep the output voltage consistent with the reference model and reduce harmonic distortion.

[0071] In order to improve the robustness of the system and reduce the total harmonic distortion, in this embodiment, the low-carbon building energy storage converter is based on a dual-loop sliding mode controller of the robust model reference adaptive (RMRA) PI control (Proportional-Integral Control). In the presence of uncertainty and external interference, it is necessary to combine the adaptive controller with the sliding mode control (SMC). This method combines the robustness of the variable structure with the tracking capability. At the same time, the controller has two control loops, in which the coefficients of the PI controller are adjusted by the adaptive sliding law. This method is used to adjust the output voltage of the inverter under different load conditions and uncertainties, and adapt the output to the reference model to reduce the total harmonic distortion (THD). Compared with energy storage converters that use other control methods, this strategy achieves a more stable sinusoidal voltage at a lower THD.

[0072] This embodiment can help respond to the worst cases such as load mutation, nonlinear load, etc., and at the same time has good low THD voltage regulation performance under load mutation and uncertainty conditions.

[0073] In this embodiment, the mathematical model of the model reference adaptive control MRAC is:

[0074]

[0075] Where: I i is the inverter side current, I0 is the grid side current, V i is the inverter side voltage, V0 is the inverter output voltage, R f is the inverter side resistance, R d is the parallel resistance of the filter capacitor, L f is the inverter side filter inductor, C f For the filter capacitor.

[0076] Among them, the MRAC is controlled by model reference adaptively according to the error between the ideal output and the actual output, including:

[0077] Perform Park transformation on the mathematical model of model reference adaptive control MRAC:

[0078]

[0079] Where: I idq is the inverter side current after Park transformation, I 0dq is the inverter output current after Park transformation, V idq is the inverter side voltage after Park transformation, V 0dq is the inverter output voltage after Park transformation.

[0080] As a preferred embodiment of the above, decoupling the current loop and the voltage loop includes the following steps:

[0081] Determine the state space model of the energy storage converter in the current loop and the voltage loop respectively;

[0082] Perform Laplace transform on the state space model to obtain the decoupling matrix;

[0083] Separate controllers are used to eliminate the influence of the decoupling matrix, and the control equations of the current loop and the voltage loop in the d-axis and q-axis directions are obtained respectively.

[0084] The state space model of the energy storage converter in the current loop is:

[0085]

[0086] middleu di =V id -V od ,u qi =V iq -Voq is the PI controller output;

[0087] Performing Laplace transformation on the above formula yields:

[0088]

[0089] Where:

[0090]

[0091] Using D as shown below 12i (s) and D 21i (s) to eliminate G 12i (s) and G 21i Impact of (s):

[0092]

[0093] Using the decoupling matrix D 12i (s) and D 21i (s), the diagonal matrix can be derived as:

[0094]

[0095] The current control equations in the d-axis and q-axis directions are obtained as follows:

[0096]

[0097] The state space model of the energy storage converter in the voltage loop is:

[0098]

[0099] where u vd =I id -I od ,u vq =I iq -I oq is the PI controller output; I od and I oq are the perturbations of the d-axis and q-axis respectively; Laplace transform is performed on the above formula:

[0100]

[0101] Where:

[0102]

[0103] Definition D 12v (s) and D 21v (s) are as follows:

[0104]

[0105] Using the decoupling matrix D 12v (s) and D 21v (s), the diagonal matrix can be derived as:

[0106]

[0107] The voltage control equations in the d-axis and q-axis directions are obtained:

[0108]

[0109] like Figure 2 As shown, this embodiment also includes a control device for a low-carbon building energy storage converter, using the above method, including:

[0110] A dual-loop sliding mode control unit is used to construct a dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control, where the parameters of the PI controller are dynamically adjusted by an adaptive sliding law;

[0111] An adaptive control unit is used to select a reference model to generate an ideal output voltage signal, and adjust the parameters of the PI controller according to the error between the ideal output and the actual output through the model reference adaptive control MRAC;

[0112] A decoupling unit is used to decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations of the current controller and the voltage controller;

[0113] The control unit is used to dynamically adjust the output voltage of the converter based on a dual-loop sliding mode controller and decoupled current loop and voltage loop control, so as to keep the output voltage consistent with a reference model and reduce harmonic distortion.

[0114] Embodiment 2:

[0115] This embodiment includes an energy storage converter for a low-carbon building power system, which uses a dual-loop sliding mode controller based on robust model reference adaptive (RMRA) PI control. Its topology is as follows: Figure 3 shown.

[0116] In the presence of uncertainties and external disturbances, it is necessary to combine an adaptive controller with SMC. Sliding mode control is a robust control technique that has the characteristics of robustness to parameter changes and insensitivity to disturbances. This method combines the robustness of variable structure with tracking capabilities. Therefore, this method can help respond to worst-case scenarios such as sudden load changes, nonlinear loads, etc.

[0117] like Figure 4The overall structure of the MRAC system shown consists of four main components, namely the controlled object, reference model, controller and adaptive mechanism. The reference model is selected to generate the ideal output, and the PI controller parameters are adjusted by the error between the actual signal and the reference signal.

[0118] (1) Mathematical model of MRAC system

[0119]

[0120] Where: I i is the inverter side current, I0 is the grid side current, V i is the inverter side voltage, V0 is the inverter output voltage, R f is the inverter side resistance, R d is the parallel resistance of the filter capacitor, L f is the inverter side filter inductor, C f For the filter capacitor.

[0121] Apply Park transformation to the above formula:

[0122]

[0123] Where: I idq is the inverter side current after Park transformation, I 0dq Side current, V idq is the inverter side voltage after Park transformation, V 0dq is the inverter output voltage after Park transformation.

[0124] (2) Current loop control

[0125] In order to achieve fast dynamic response, the state space variables are decoupled as follows. Each control loop is decoupled, and the state space model of the energy storage converter in the current loop is:

[0126]

[0127] where u di =V id -V od ,u qi =V iq -V oq is the output of the PI controller.

[0128] Performing Laplace transformation on the above formula yields:

[0129]

[0130] Where:

[0131]

[0132] Because there is coupling between the input and output of the d-axis and q-axis, a separate controller is required to eliminate G 12i (s) and G 21i (s) is affected. Using D as shown in the following formula 12i (s) and D 21i (s):

[0133]

[0134] Its structure is as Figure 5 shown.

[0135] Using the decoupling matrix D 12i (s) and D 21i (s), the diagonal matrix can be derived as:

[0136]

[0137] Therefore, the equations of the current control loop in the d-axis and q-axis directions are:

[0138]

[0139] (3) Voltage loop control

[0140] The state space model of the energy storage converter in the voltage loop is:

[0141]

[0142] where u vd =I id -I od ,u vq =I iq -I oq is the PI controller output; I od and I oq are the disturbances of the d-axis and q-axis respectively. The Laplace transform of the above equation can be expressed as:

[0143]

[0144] Where:

[0145]

[0146] Similarly, in order to eliminate the coupling between input and output in the voltage loop, define D 12v (s) and D 21v (s) are as follows:

[0147]

[0148] Its structure is as Figure 6 shown.

[0149] Using the decoupling matrix D 12v (s) and D 21v (s), the diagonal matrix can be derived as:

[0150]

[0151]

[0152] This results in the voltage control loop equations for the d-axis and q-axis directions:

[0153]

[0154] The beneficial effects of this embodiment are as follows: for the inverter of the low-carbon building power system, a dual-loop strategy sliding mode controller based on RMRA-PI is proposed. In the presence of uncertainty, load mutation and nonlinear load, the controller well realizes the voltage regulation control of the low-carbon building power system. At the same time, compared with the traditional dual PI control scheme, the controller provides a more stable sinusoidal voltage for the low-carbon building power system at a lower THD.

[0155] Combines the robustness of variable structure with tracking capability. Therefore, this method can help respond to the worst case scenarios such as sudden load changes, nonlinear loads, etc. Since both the current and voltage control loops are cross-coupled, decoupling is performed between the d-axis and q-axis loops. This control method can provide voltage regulation with fast dynamic response, small steady-state error, and low total harmonic distortion (THD) in the presence of sudden load changes and filter output uncertainty.

[0156] See also Figure 7 A computer device 400 provided in an embodiment of the present application includes: a processor 410 and a memory 420, wherein the memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, the above method is executed.

[0157] The embodiment of the present application further provides a storage medium 430 on which a computer program is stored. When the computer program is run by the processor 410, the above method is executed.

[0158] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0159] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0160] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0161] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0162] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0163] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0164] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0165] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0166] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A control method for a low-carbon building energy storage converter, characterized in that: The steps include: A dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control is constructed, in which the parameters of the PI controller are dynamically adjusted by the adaptive sliding law. A reference model is selected to generate an ideal output voltage signal, and the parameters of the PI controller are adjusted according to the error between the ideal output and the actual output through the model reference adaptive control MRAC; Decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations for the current controller and the voltage controller; Based on the dual-loop sliding mode controller and the decoupled current loop and voltage loop control, the output voltage of the converter is dynamically adjusted to keep the output voltage consistent with the reference model and reduce harmonic distortion.

2. The control method for a low-carbon building energy storage converter according to claim 1, characterized in that: The mathematical model of the model reference adaptive control MRAC is: Where: I i is the inverter side current, I0 is the grid side current, V i is the inverter side voltage, V0 is the inverter output voltage, R f is the inverter side resistance, R d is the parallel resistance of the filter capacitor, L f is the inverter side filter inductor, C f For the filter capacitor.

3. The control method for a low-carbon building energy storage converter according to claim 2, characterized in that: The method of controlling the MRAC by model reference adaptively according to the error between the ideal output and the actual output includes: The mathematical model of the model reference adaptive control MRAC is subjected to Park transformation: Where: I idq is the inverter side current after Park transformation, I 0dq is the inverter output current after Park transformation, V idq is the inverter side voltage after Park transformation, V 0dq is the inverter output voltage after Park transformation.

4. The control method for a low-carbon building energy storage converter according to claim 2, characterized in that: The decoupling of the current loop and the voltage loop comprises the following steps: Determine the state space model of the energy storage converter in the current loop and the voltage loop respectively; Performing Laplace transformation on the state space model to obtain a decoupling matrix; A separate controller is used to eliminate the influence of the decoupling matrix, and control equations of the current loop and the voltage loop in the d-axis and q-axis directions are obtained respectively.

5. The control method for a low-carbon building energy storage converter according to claim 4, characterized in that: The state space model of the energy storage converter in the current loop is: middleu di =V id -V od ,u qi =V iq -V oq is the PI controller output; Performing Laplace transformation on the above equation yields: Where: Using D as shown below 12i (s) and D 21i (s) to eliminate G 12i (s) and G 21i Impact of (s): Using the decoupling matrix D 12i (s) and D 21i (s), the diagonal matrix can be derived as: The current control equations in the d-axis and q-axis directions are obtained as follows:

6. The control method for a low-carbon building energy storage converter according to claim 4, characterized in that: The state space model of the energy storage converter in the voltage loop is: where u vd =I id -I od ,u vq =I iq -I oq is the PI controller output; I od and I oq are the perturbations of the d-axis and q-axis respectively; Perform Laplace transform on the above formula: Where: Definition D 12v (s) and D 21v (s) are as follows: Using the decoupling matrix D 12v (s) and D 21v (s), the diagonal matrix can be derived as: The voltage control equations in the d-axis and q-axis directions are obtained:

7. A control device for a low-carbon building energy storage converter, characterized in that: Use of the method according to any one of claims 1 to 6, comprising: A dual-loop sliding mode control unit is used to construct a dual-loop sliding mode controller based on robust model reference adaptive RMRA control and proportional integral PI control, where the parameters of the PI controller are dynamically adjusted by the adaptive sliding law; An adaptive control unit is used to select a reference model to generate an ideal output voltage signal, and adjust the parameters of the PI controller according to the error between the ideal output and the actual output through the model reference adaptive control MRAC; A decoupling unit is used to decouple the current loop and the voltage loop, eliminate the coupling on the d-axis and the q-axis, and obtain independent control equations of the current controller and the voltage controller; The control unit is used to dynamically adjust the output voltage of the converter based on the dual-loop sliding mode controller and the decoupled current loop and voltage loop control, so as to keep the output voltage consistent with the reference model and reduce harmonic distortion.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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