Method and system for improving the energy storage stability of supercapacitors

Abstract

The present invention discloses a method and system for improving the stability of supercapacitor energy storage, which relates to the field of electrical energy storage, and includes: collecting the state information of the supercapacitor energy storage system for preprocessing; constructing a dynamic mathematical model of the supercapacitor energy storage system, deriving the state equation, designing a smooth super-twisting algorithm controller, constructing a sliding mode surface function and a control law to generate a smooth control input; and achieving the stable operation of the supercapacitor energy storage unit by dynamically adjusting the output voltage. By adopting the technical solution of combining a smooth super-twisting algorithm controller with an extended state observer, the present invention solves the problems of slow response speed, obvious chattering phenomenon and insufficient system robustness of the existing supercapacitor energy storage control system under complex and variable working conditions, achieves the effects of improving system stability, increasing response speed, enhancing robustness and optimizing energy utilization efficiency, and enables the system to quickly adjust its state and dynamically compensate for voltage deviation under voltage sags or grid fluctuations.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical energy storage, and particularly to a method and system for improving the stability of supercapacitor energy storage. Background Art

[0002] Supercapacitor energy storage systems have been widely used in the fields of power energy storage and energy recovery due to their high power density, long cycle life, and fast charge and discharge capabilities. However, in practical applications, the stability of the supercapacitor energy storage control system is a key issue, directly affecting the operating efficiency and safety of the system. Traditional control methods often have problems such as slow response speed and insufficient stability when facing complex and variable working conditions. Summary of the Invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is: how to improve the stability of the supercapacitor energy storage control system under complex and variable working conditions, solve the problems of slow response speed, obvious chattering phenomenon, and insufficient system robustness in traditional control methods, so as to achieve the efficient and stable operation of the supercapacitor energy storage unit under power grid fluctuations or voltage sags, and ensure the operating efficiency and safety of the system.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A method for improving the stability of supercapacitor energy storage, which includes the following steps:

[0006] Collect the state information of the supercapacitor energy storage system and perform preprocessing;

[0007] Based on the preprocessed data, construct a dynamic mathematical model of the supercapacitor energy storage system and deduce the state equation;

[0008] Use the dynamic mathematical model to design a smooth super-twisting algorithm controller, construct a sliding mode surface function and a control law to generate a smooth control input;

[0009] Apply the control input signal to the voltage source inverter and complete the stable operation of the supercapacitor energy storage unit by dynamically adjusting the output voltage.

[0010] As a preferred solution of a method for improving the stability of supercapacitor energy storage according to the present invention, wherein: the state information includes system voltage, output current, and grid voltage deviation signal.

[0011] As a preferred solution of a method for improving the energy storage stability of a supercapacitor according to the present invention, wherein: the preprocessing is to perform low-pass filtering on the collected state information to remove high-frequency noise interference, extract the basic signal of the signal through empirical mode decomposition method to complete the denoising process, and normalize the state information to the [0, 1] interval by linear normalization method.

[0012] As a preferred solution of a method for improving the energy storage stability of a supercapacitor according to the present invention, wherein: based on the preprocessed data, a dynamic mathematical model of the supercapacitor energy storage system is constructed, and the state equation derivation includes,

[0013] Continuously monitor the supercapacitor energy storage and the output voltage of the voltage source inverter, calculate the percentage of the voltage sag peak value, evaluate the need for control strategy adjustment, the controller makes a decision to switch the control signal, and generates a pulse width modulation signal to adjust the voltage source inverter to complete the stable compensation of the grid voltage. The expression is:

[0014] ,

[0015] Wherein, is the grid-side voltage; is the grid-side voltage reference value;

[0016] When the supercapacitor energy storage dynamic voltage controller is in the constant power charge and discharge mode, the state equation expression of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is:

[0017] ,

[0018] ,

[0019] ,

[0020] Wherein, 、 are the series filter resistance and inductance respectively; is the parallel filter capacitor; is the angular frequency; 、 are the three-phase grid voltages on the AC side; 、 are the input currents; is the output voltage of the supercapacitor energy storage unit, and are the switching functions,

[0021] The amplitude of the SVPWM control vector is limited, and the amplitude constraint of the switching function is, , and the current switching function remains unsaturated.

[0022] As a preferred embodiment of the method for improving the stability of supercapacitor energy storage according to the present invention, wherein: the design of a smooth super-twisting algorithm controller using the dynamic mathematical model, and the construction of a sliding mode surface function and a control law to generate a smooth control input includes,

[0023] Define the input and output of the dynamic voltage controller model of supercapacitor energy storage, and the expression is:

[0024] ,

[0025] ,

[0026] where x is the state variable, is the derivative of the state equation, u is the control input, y is the output, f(x) and g(x) are differentiable continuous functions, S(t,x) is the sliding surface function, and λ is a constant.

[0027] As a preferred embodiment of the method for improving the stability of supercapacitor energy storage according to the present invention, wherein: the design of a smooth super-twisting algorithm controller using the dynamic mathematical model, and the construction of a sliding mode surface function and a control law to generate a smooth control input further includes,

[0028] For the characteristics of supercapacitor energy storage, the sliding mode controller should handle the dynamic changes and potential non-linear behaviors during the fast charge and discharge process, and the expression is:

[0029] ,

[0030] ,

[0031] where, is the derivative calculation of.

[0032] As a preferred embodiment of the method for improving the stability of supercapacitor energy storage according to the present invention, wherein: the design of a smooth super-twisting algorithm controller using the dynamic mathematical model, and the construction of a sliding mode surface function and a control law to generate a smooth control input further includes,

[0033] The expression for the control input u of the smooth super-twisting sliding mode control is:

[0034] ,

[0035] where α and β are used as sliding surface coefficients to adjust the parameters of the smooth super-twisting sliding mode control;

[0036] The performance constraint condition, and the expression is:

[0037] ,

[0038] where e is the natural logarithm; k is the coefficient of the sign function.

[0039] Another object of the present invention is to provide a system for improving the energy storage stability of a supercapacitor, which can achieve the efficient and stable operation of the supercapacitor energy storage system through the real-time control of a smooth super-twisting algorithm controller combined with an extended state observer; the system can quickly respond to complex and changing grid conditions, adjust the control strategy in real time, ensure that the load-side voltage remains stable under voltage sags or grid fluctuations, and the power supply quality of sensitive loads is not affected, thereby solving the problems of slow response speed, insufficient robustness, and obvious chattering phenomenon of the controller in the prior art.

[0040] To solve the above technical problems, the present invention provides the following technical solutions: A system for improving the energy storage stability of a supercapacitor, comprising: a data acquisition and preprocessing module, a dynamic mathematical modeling module, a controller design module, and an execution and feedback module;

[0041] The data acquisition and preprocessing module collects the state information of the supercapacitor energy storage system, performs preprocessing, removes high-frequency noise interference, extracts the basic signal of the signal, and standardizes the data to a unified interval through normalization;

[0042] The dynamic mathematical modeling module constructs a dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data;

[0043] The controller design module uses the dynamic mathematical model to design a smooth super-twisting algorithm controller, constructs a sliding mode surface function and a control law, and generates a smooth control input signal through a sliding mode control strategy;

[0044] The execution and feedback module receives the control signal output by the controller, applies it to the voltage source inverter, adjusts the dynamic voltage of the supercapacitor energy storage unit, and completes the stable compensation for the grid voltage fluctuation.

[0045] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned method for improving the energy storage stability of a supercapacitor are implemented.

[0046] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for improving the energy storage stability of a supercapacitor are implemented.

[0047] Advantages of the present invention: By adopting the technical solution of a smooth super-twisting algorithm controller combined with an extended state observer, the present invention solves the problems of slow response speed, obvious chattering phenomenon, and insufficient system robustness in the existing supercapacitor energy storage control system under complex and variable working conditions, achieving the effects of improving system stability, increasing response speed, enhancing robustness, and optimizing energy utilization efficiency, enabling the system to quickly adjust its state and dynamically compensate for voltage deviation under voltage sags or grid fluctuations, thereby ensuring stable voltage on the load side and reliable power supply quality for sensitive loads. Description of the Drawings

[0048] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0049] Figure 1 It is the overall flowchart of a method for improving the stability of supercapacitor energy storage provided in the first embodiment of the present invention.

[0050] Figure 2 It is a schematic diagram of a dynamic voltage controller for supercapacitor energy storage in a method for improving the stability of supercapacitor energy storage provided in the first embodiment of the present invention.

[0051] Figure 3 It is the flowchart of smooth super-twisting sliding mode control for a method for improving the stability of supercapacitor energy storage provided in the first embodiment of the present invention.

[0052] Figure 4 It is a diagram of phase fault voltage compensation in a method for improving the stability of supercapacitor energy storage provided in the third embodiment of the present invention. Detailed Embodiments

[0053] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention with reference to the accompanying drawings of the specification. Obviously, the described embodiments are some embodiments of the present invention, not all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0054] Embodiment 1, refer to Figures 1 to 3 This is an embodiment of the present invention, providing a method for improving the stability of supercapacitor energy storage, including:

[0055] As Figure 2As shown, the supercapacitor energy storage dynamic voltage controller consists of a DC energy storage unit (supercapacitor), a voltage source inverter, a filter, a step-up transformer, and a control system. The control system detects voltage sags and then generates drive signals to drive the supercapacitor to release energy, which is converted into alternating current by the voltage source inverter. The alternating current is purified by the filter and then compensated to the power grid by the step-up transformer.

[0056] The control system continuously monitors the supercapacitor energy storage and the output voltage of the voltage source inverter, calculates the peak percentage of the voltage sag, and evaluates the need to adjust the control strategy. The controller decides to switch the control signal and generates a pulse width modulation signal to precisely adjust the voltage source inverter to achieve fast and stable compensation of the power grid voltage. This system integrates advanced control logic and power electronics technology, and through real-time monitoring and early warning, effectively responds to power grid voltage fluctuations to ensure the stable operation of the power system, as demonstrated in the data mining and analysis of power system operation. The compensation voltage error can be expressed as:

[0057] (1)

[0058] where: is the voltage on the power grid side; is the reference value of the voltage on the power grid side. The generation process of this signal will continue to ensure that the voltage deviation is effectively corrected.

[0059] When the supercapacitor energy storage dynamic voltage controller is in the constant power charge and discharge mode, the state equation expression of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is:

[0060] (2)

[0061] (3)

[0062] (4)

[0063] where: and are the resistance and inductance of the series filter respectively; is the capacitance of the parallel filter; is the angular frequency; and are the three-phase voltages of the AC side power grid; and are the input currents; is the output voltage of the supercapacitor energy storage unit; and are the switching functions. The amplitude of the SVPWM control vector is limited, and the amplitude of the switching function has: , at this time, the switching function remains unsaturated, ensuring the operation of the system.

[0064] As Figure 3 shown, when designing the sliding mode control strategy (SMC) of the supercapacitor energy storage system (SSTS), it is crucial to first define the sliding surface function, which is essential for ensuring the performance of the system in the sliding mode state. The fast charge-discharge and energy storage characteristics of the supercapacitor need to be fully considered. Determining the control law is another key. The present invention uses a smooth super-twisting sliding mode algorithm to construct the control law, forcing the system state to converge to the sliding surface within a limited time. This algorithm effectively addresses the nonlinearity and uncertainty of the supercapacitor energy storage system, improving the control robustness and response speed. Through the designed sliding surface function and smooth super-twisting sliding mode algorithm control, the present invention makes full use of the advantages of supercapacitor energy storage to ensure the efficient and stable operation of the power system under various disturbances.

[0065] Define the input and output of the dynamic voltage controller model of the supercapacitor energy storage as:

[0066] (5)

[0067] where: x is the state variable; is the derivative of the state equation; u is the control input; y is the output; f(x), g(x) are differentiable continuous functions; S(t,x) is the sliding surface function, which consists of the compensated voltage error and its derivative and can be expressed as:

[0068] (6)

[0069] where λ is a constant. In the framework of the supercapacitor energy storage system (SSTS), the core of the sliding mode controller is to precisely regulate the input signal so that the system output y closely approaches zero, thereby optimizing and stabilizing the system performance. Especially in the processing of second-order sliding mode systems, the design of this controller needs to meet a series of strict conditions to ensure efficient and reliable control effects. For the characteristics of the supercapacitor energy storage system, the sliding mode controller needs to be carefully designed to handle the dynamic changes and potential nonlinear behaviors during its fast charge-discharge process. These design conditions include but are not limited to: ensuring that the controller can quickly respond to changes in the supercapacitor energy storage state, effectively suppressing the disturbances and uncertainties introduced by the energy storage elements; at the same time, the controller also needs to have sufficient robustness to maintain effective control of the output y and make it stably approach zero when the system parameters change or external disturbances occur. To meet the system requirements, the controller needs to meet the following conditions:

[0070] (7)

[0071] Taking the derivative of, we can obtain:

[0072] (8)

[0073] To ensure that the output y of the sliding mode controller can stably approach zero, the present invention expresses the control input u of the smooth super-twisting sliding mode control as follows:

[0074] (9)

[0075] Where: α and β are sliding surface coefficients, used to adjust the parameters of the smooth super-twisting sliding mode control to meet the required performance requirements; is the sign function, which can be expressed as:

[0076] (10)

[0077] Where: e is the natural logarithm; k is the sign function coefficient; the function As the value of k gradually increases, its value gets closer and closer to the sign function. When fluctuates around the 0 moment, is in a continuous state, solving the discontinuous problem of the sign function at moment and reducing the chattering of the output quantity.

[0078] Embodiment 2 is an embodiment of the present invention, which provides a system for improving the stability of supercapacitor energy storage, including: a data acquisition and preprocessing module, a dynamic mathematical modeling module, a controller design module, and an execution and feedback module.

[0079] The data acquisition and preprocessing module collects the state information of the supercapacitor energy storage system, performs preprocessing, removes high-frequency noise interference, extracts the basic signal of the signal, and standardizes the data to a unified interval through normalization;

[0080] The dynamic mathematical modeling module constructs the dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data;

[0081] The controller design module uses the dynamic mathematical model to design a smooth super-twisting algorithm controller, constructs a sliding mode surface function and a control law, and generates a smooth control input signal through a sliding mode control strategy;

[0082] The execution and feedback module receives the control signal output by the controller, applies it to the voltage source inverter, dynamically adjusts the voltage of the supercapacitor energy storage unit, and completes the stable compensation for the grid voltage fluctuation.

[0083] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0084] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device.

[0085] More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memories), fiber optic devices, and portable compact disc read-only memories (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or otherwise processing it as necessary, and then storing it in a computer memory.

[0086] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple 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, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0087] Embodiment 3, referring to Figure 4 is another embodiment of the present invention. To verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. In this embodiment, experiments are respectively carried out on the existing traditional method and the method of this embodiment.

[0088] According to Figure 4 Build a simulation model of a supercapacitor energy storage dynamic voltage controller to simulate and verify the proposed optimized control. When the system voltage is normal, the bypass switch connected in parallel with the voltage source inverter is in the closed state. When a voltage change is detected, the bypass switch disconnects and the dynamic voltage controller is put into operation to achieve the control of voltage sags. The simulation system parameters adopted in the present invention are shown in Table 1. Table 1 details the main parameters of the simulation system, including the rated voltage, capacity, internal resistance, etc. of the supercapacitor, as well as the key parameter settings of the controller.

[0089] Table 1 Simulation System Parameter Table

[0090] ,

[0091] When the monitoring system detects an abnormal voltage situation, the dynamic voltage restorer will be immediately started and put into operation. At this time, the control strategy based on extended state observer - super-twisting sliding mode control (ESO - SSTSMC) will be activated to achieve effective compensation for voltage fluctuations. As Figure 4 shown, the figure details the voltage waveform changes when a voltage sag occurs in the power grid under different voltage fluctuation conditions. It depicts the voltage waveform on the power grid side when a voltage sag occurs, the voltage waveform on the load side connected to the sensitive load when a voltage sag occurs, and the compensation voltage waveform injected by the supercapacitor energy storage dynamic voltage controller device.

[0092] Through Figure 4 the waveform data in, the compensation effect of the supercapacitor energy storage dynamic voltage controller when a voltage sag occurs is observed, so as to ensure the normal operation of the sensitive load and avoid equipment damage or data loss caused by voltage fluctuations. Further analysis Figure 4From the waveform data, several key points can be found. First, the voltage waveform on the grid side shows a significant drop during the voltage sag, which may lead to unstable power supply from the grid and have an adverse impact on the devices connected to the grid. However, due to the timely intervention of the dynamic voltage controller with supercapacitor energy storage, the voltage waveform on the load side is maintained relatively stable, and the fluctuation amplitude is greatly reduced.

[0093] The compensated voltage waveform injected by the dynamic voltage controller with supercapacitor energy storage shows the compensated voltage injected by the dynamic voltage controller with supercapacitor energy storage to counteract the voltage drop on the grid side. The amplitude and phase of the compensated voltage are precisely calculated to ensure that the voltage on the load side can be restored to near the normal voltage level. In this way, the dynamic voltage controller with supercapacitor energy storage effectively reduces the impact of voltage sag on sensitive loads. With different situations of voltage fluctuations, the compensation strategy of the dynamic voltage controller with supercapacitor energy storage will also be adjusted. In the case of a relatively mild voltage sag, the compensated voltage injected by the dynamic voltage controller with supercapacitor energy storage is relatively small; while in the case of a more severe voltage sag, the dynamic voltage controller with supercapacitor energy storage will increase the amplitude of the compensated voltage to ensure the stability of the voltage on the load side.

[0094] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for improving the energy storage stability of supercapacitors, characterized in that, It includes: Collect the state information of the supercapacitor energy storage system and perform preprocessing; Based on the preprocessed data, construct the dynamic mathematical model of the supercapacitor energy storage system and derive the state equation; Use the dynamic mathematical model to design a smooth super-twisting algorithm controller, construct a sliding mode surface function and a control law to generate a smooth control input; Apply the control input signal to the voltage source inverter and complete the stable operation of the supercapacitor energy storage unit by dynamically adjusting the output voltage; The step of using the dynamic mathematical model to design a smooth super-twisting algorithm controller, constructing a sliding mode surface function and a control law to generate a smooth control input further includes: The expression of the control input u for the smooth super-twisting sliding mode control is: Where α and β are used as sliding surface coefficients to adjust the parameters of the smooth super-twisting sliding mode control, and S(t,x) is the sliding surface function; Performance constraint conditions, the expression is: Where e is the natural logarithm; k is the coefficient of the sign function.

2. The method for improving the energy storage stability of a supercapacitor according to claim 1, characterized in that: The state information includes the system voltage, output current and grid voltage deviation signal.

3. The method for improving the energy storage stability of a supercapacitor according to claim 2, characterized in that: The preprocessing is to perform low-pass filtering on the collected state information to remove high-frequency noise interference, extract the basic signal of the signal through the empirical mode decomposition method to complete the denoising process, and use the linear normalization method to standardize the state information to the [0,1] interval.

4. The method for improving the energy storage stability of a supercapacitor according to claim 3, characterized in that: The step of constructing the dynamic mathematical model of the supercapacitor energy storage system and deriving the state equation based on the preprocessed data includes: Continuously monitor the output voltage of the supercapacitor energy storage and the voltage source inverter, calculate the percentage of the voltage sag peak value, evaluate the need for control strategy adjustment, switch the controller decision control signal, and generate a pulse width modulation signal to adjust the voltage source inverter to complete the stable compensation of the grid voltage. The expression is: Among them, V c is the grid-side voltage; is the grid-side voltage reference value; When the supercapacitor energy storage dynamic voltage controller is in the constant power charge and discharge mode, the expression of the state equation of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is: where r and L are the resistance and inductance of the series filter respectively; C is the capacitance of the parallel filter; ω is the angular frequency; v d , v q are the three-phase voltages of the AC-side power grid; i d , i q are the input currents; V dc is the output voltage of the supercapacitor energy storage unit, and δ d and δ q are the switching functions; The amplitude of the SVPWM control vector is limited, and the amplitude constraint of the switching function is that the current switching function remains unsaturated.

5. The method for improving the energy storage stability of a supercapacitor according to claim 4, wherein: The step of using the dynamic mathematical model to design a smooth super-twisting algorithm controller, constructing a sliding mode surface function and a control law to generate a smooth control input includes: Define the input and output of the supercapacitor energy storage dynamic voltage controller model, the expression is: where x is the state variable, is the derivative of the state equation, u is the control input, y is the output, f(x) and g(x) are differentiable continuous functions, S(t, x) is the sliding surface function, and λ is a constant.

6. The method for improving the energy storage stability of a supercapacitor according to claim 5, characterized in that: The step of using the dynamic mathematical model to design a smooth super-twisting algorithm controller, constructing a sliding mode surface function and a control law to generate a smooth control input further includes: For the characteristics of the supercapacitor energy storage, the sliding mode controller should handle the dynamic changes and potential non-linear behaviors during the fast charge and discharge process. The expression is: Among them, is the derivative calculation of S(t, x).

7. A system adopting a method for improving the energy storage stability of a super capacitor as described in any one of claims 1 to 6, characterized in that: It includes a data acquisition and preprocessing module, a dynamic mathematical modeling module, a controller design module, and an execution and feedback module; The data acquisition and preprocessing module is to collect the state information of the supercapacitor energy storage system, perform preprocessing, remove high-frequency noise interference, extract the basic signal of the signal, and standardize the data to a unified interval through normalization; The dynamic mathematical modeling module is to construct the dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data; The controller design module is to use the dynamic mathematical model to design a smooth super-twisting algorithm controller, construct a sliding mode surface function and a control law, and generate a smooth control input signal through the sliding mode control strategy; The execution and feedback module receives the control signal output by the controller and applies it to the voltage source inverter to dynamically regulate the voltage of the supercapacitor energy storage unit, thereby completing the stable compensation for the grid voltage fluctuation.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of a method for improving the stability of supercapacitor energy storage according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of a method for improving the stability of supercapacitor energy storage according to any one of claims 1 to 6.

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