Method and system for improving energy storage stability of super capacitor

Abstract

The invention discloses a super-capacitor energy storage stability improving method and system, and relates to the field of electric energy storage, and the method comprises the steps: collecting the state information of a super-capacitor energy storage system, and carrying out the preprocessing; constructing a dynamic mathematical model of the super-capacitor energy storage system, deducing a state equation, designing a smooth hyper-torsion algorithm controller, and constructing a sliding mode surface function and a control law to generate smooth control input; and stable operation of the super-capacitor energy storage unit is completed by dynamically adjusting the output voltage. According to the technical scheme, the smooth super-torsion algorithm controller is combined with the extended state observer, so that the problems that an existing super-capacitor energy storage control system is low in response speed, obvious in buffeting phenomenon and insufficient in system robustness under complex and changeable working conditions are solved; the effects of improving the system stability, increasing the response speed, enhancing the robustness and optimizing the energy utilization efficiency are achieved, and the system can rapidly adjust the state and dynamically compensate the voltage deviation under the condition of voltage sag or power grid fluctuation.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy storage, and in particular 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 storage and energy recovery due to their high power density, long cycle life, and fast charging and discharging capabilities. However, in practical applications, the stability of supercapacitor energy storage control systems is a key issue that directly affects 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 changeable working conditions. Summary of the invention

[0003] In view of the above-mentioned 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 changeable working conditions, and solve the problems of slow response speed, obvious jitter phenomenon and insufficient system robustness of traditional control methods, so as to realize efficient and stable operation of the supercapacitor energy storage unit under grid fluctuations or voltage sags, and ensure the system operation efficiency and safety.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for improving the stability of supercapacitor energy storage, which comprises the following steps: Collect the status information of the supercapacitor energy storage system for preprocessing; Based on the preprocessed data, a dynamic mathematical model of the supercapacitor energy storage system is constructed and the state equation is derived; The dynamic mathematical model is used to design a smooth super-torsion algorithm controller, and a sliding surface function and a control law are constructed to generate a smooth control input; The control input signal is applied to the voltage source inverter, and the stable operation of the supercapacitor energy storage unit is achieved by dynamically adjusting the output voltage.

[0006] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in the present invention, the state information includes system voltage, output current and grid voltage deviation signal.

[0007] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in the present invention, 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.

[0008] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in 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 is derived including: Continuously monitor the output voltage of the supercapacitor energy storage and the voltage source inverter, calculate the voltage sag peak percentage, evaluate the control strategy adjustment requirements, the controller decides the control signal switching, 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: , in, is the grid side voltage; is the grid side voltage reference value; When the supercapacitor energy storage dynamic voltage controller is in constant power charge and discharge mode, the state equation expression of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is: , , , in, , are the series filter resistance and inductance respectively; is the parallel filter capacitor; is the angular frequency; , is the three-phase voltage of the AC side power grid; , is the input current; is the output voltage of the supercapacitor energy storage unit, and is the switch function, The amplitude of the SVPWM control vector is limited, and the switching function amplitude constraint is, , the current switching function remains unsaturated.

[0009] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in the present invention, wherein: the use of the dynamic mathematical model to design a smooth supertorsion algorithm controller, constructing a sliding 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: , , Among them, 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, and λ is a constant.

[0010] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in the present invention, wherein: the use of the dynamic mathematical model to design a smooth supertorsion algorithm controller, constructing a sliding surface function and a control law to generate a smooth control input also includes: In view of the energy storage characteristics of supercapacitors, the sliding mode controller responds to the dynamic changes and potential nonlinear behaviors during rapid charging and discharging. The expression is: , , in, yes Derivative calculation of .

[0011] As a preferred solution of the method for improving the stability of supercapacitor energy storage described in the present invention, wherein: the use of the dynamic mathematical model to design a smooth supertorsion algorithm controller, constructing a sliding surface function and a control law to generate a smooth control input also includes: The expression of the control input u for smooth supertorsion sliding mode control is: , Among them, α and β are sliding surface coefficients to adjust the parameters of smooth supertorsion sliding mode control; The performance constraint is expressed as: , Wherein, e is the natural logarithm; k is the sign function coefficient.

[0012] Another object of the present invention is to provide a supercapacitor energy storage stability improvement system, which can achieve efficient and stable operation of the supercapacitor energy storage system through real-time control of a smooth super-torsion algorithm controller combined with an extended state observer; the system can quickly respond to complex and changeable grid conditions, and adjust the control strategy in real time to ensure that in the event of voltage sag or grid fluctuations, the load side voltage remains stable and the power supply quality of sensitive loads is not affected, thereby solving the problems of slow controller response speed, insufficient robustness and obvious jitter phenomenon in the prior art.

[0013] In order to solve the above technical problems, the present invention provides the following technical solutions: a supercapacitor energy storage stability improvement system, comprising: 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 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 normalizes the data to a unified interval through normalization; The dynamic mathematical modeling module constructs a dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data; The controller design module uses a dynamic mathematical model to design a smooth super-torsion algorithm controller, construct a sliding surface function and a control law, and generate a smooth control input signal through a 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 adjust the voltage of the supercapacitor energy storage unit to achieve stable compensation for grid voltage fluctuations.

[0014] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for improving the stability of supercapacitor energy storage are implemented.

[0015] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for improving the stability of supercapacitor energy storage.

[0016] Beneficial effects of the invention: The invention solves the problems of slow response speed, obvious jitter phenomenon and insufficient system robustness of the existing supercapacitor energy storage control system under complex and changeable working conditions by adopting a smooth super-torsion algorithm controller combined with an extended state observer, thereby achieving the effects of improving system stability, increasing response speed, enhancing robustness and optimizing energy utilization efficiency, enabling the system to quickly adjust the state and dynamically compensate for voltage deviations in the event of voltage sag or grid fluctuations, thereby ensuring stable voltage on the load side and reliable power supply quality for sensitive loads. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 An overall flow chart of a method for improving supercapacitor energy storage stability provided in the first embodiment of the present invention.

[0019] Figure 2 A schematic diagram of a supercapacitor energy storage dynamic voltage controller in a method for improving supercapacitor energy storage stability provided in the first embodiment of the present invention.

[0020] Figure 3 A smooth supertorsion sliding mode control flow chart of a supercapacitor energy storage stability improvement method provided in the first embodiment of the present invention.

[0021] Figure 4 A diagram of phase fault voltage compensation in a method for improving supercapacitor energy storage stability provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0023] Example 1, reference Figure 1~Figure 3 According to an embodiment of the present invention, a method for improving the stability of supercapacitor energy storage is provided, comprising: like Figure 2 As shown in the figure, the supercapacitor energy storage dynamic voltage controller consists of a DC energy storage unit (supercapacitor), a voltage source inverter, a filter, a boost transformer and a control system. The control system detects a voltage drop and then generates a drive signal to drive the supercapacitor to release energy, which is converted into AC power through the voltage source inverter. The AC power is purified by the filter and then compensated to the grid by the boost transformer.

[0024] The control system continuously monitors the output voltage of the supercapacitor energy storage and the voltage source inverter, calculates the peak percentage of the voltage sag, and evaluates the need for control strategy adjustment. The controller decides the control signal switching and generates a pulse width modulation signal to accurately adjust the voltage source inverter to achieve fast and stable compensation of the grid voltage. The system combines advanced control logic and power electronics technology to effectively respond to grid voltage fluctuations through real-time monitoring and early warning to ensure stable operation of the power system, as shown in the mining and analysis of power system operation data. Compensating voltage error It can be expressed as: (1) in: is the grid side voltage; is the grid voltage reference value. The signal generation process will continue to ensure that the voltage deviation is effectively corrected.

[0025] When the supercapacitor energy storage dynamic voltage controller is in constant power charge and discharge mode, the state equation expression of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is: (2) (3) (4) in: , are the series filter resistance and inductance respectively; is the parallel filter capacitor; is the angular frequency; , is the three-phase voltage of the AC side power grid; , is the input current; Output voltage for supercapacitor energy storage unit; and is the switching function. The amplitude of the SVPWM control vector is limited, and the switching function amplitude exists: , at this time, the switching function remains unsaturated, which can ensure the operation of the system.

[0026] like Figure 3 As shown, when designing the sliding mode control strategy (SMC) of the supercapacitor energy storage system (SSTS), it is important to first clarify the sliding surface function, which is crucial to ensuring the performance of the system in the sliding mode state, and the rapid charging and discharging and energy storage characteristics of the supercapacitor must be fully considered. Determining the control law is another key. The present invention adopts a smooth super-torsion 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 copes with the nonlinearity and uncertainty of the supercapacitor energy storage system, and improves the control robustness and response speed. The present invention fully utilizes the advantages of supercapacitor energy storage through the designed sliding surface function and the smooth super-torsion sliding mode algorithm control, ensuring that the power system maintains efficient and stable operation under various disturbances.

[0027] The input and output of the supercapacitor energy storage dynamic voltage controller model are defined as: (5) Among them: 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 compensation voltage error and its derivative, and can be expressed as: (6) Among them, λ is a constant. In the framework of supercapacitor energy storage system (SSTS), the core of the sliding mode controller is to optimize and stabilize the system performance by precisely controlling the input signal so that the system output y is closely approached to zero. Especially in the processing of second-order sliding mode systems, the design of the controller must meet a series of strict conditions to ensure efficient and reliable control effects. In view of the characteristics of supercapacitor energy storage systems, sliding mode controllers need to be carefully designed to cope with dynamic changes and potential nonlinear behaviors during rapid charging and discharging. These design conditions include but are not limited to: ensuring that the controller can quickly respond to changes in the energy storage state of the supercapacitor and effectively suppress disturbances and uncertainties introduced by the energy storage elements; at the same time, the controller must also have sufficient robustness to maintain effective control of the output y when the system parameters change or face external interference, so that it can stably approach zero. To meet system requirements, the controller must meet the following conditions: (7) Taking the derivative of , we can get: (8) In order 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 supertorque sliding mode control as follows: (9) Among them: α and β are sliding surface coefficients used to adjust the parameters of smooth supertorsional sliding mode control to achieve the required performance requirements; is a symbolic function, which can be expressed as: (10) Where: e is the natural logarithm; k is the coefficient of the sign function; function As the value of k increases, its value becomes closer and closer to the sign function. When fluctuating around time 0, In a continuous state, solving the symbolic function in The discontinuity problem at the moment reduces the jitter of the output.

[0028] Embodiment 2 is an embodiment of the present invention, which provides a supercapacitor energy storage stability improvement system, including: a data acquisition and preprocessing module, a dynamic mathematical modeling module, a controller design module, and an execution and feedback module.

[0029] 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 normalizes the data to a unified interval through normalization; The dynamic mathematical modeling module constructs a dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data; The controller design module uses a dynamic mathematical model to design a smooth super-torsion algorithm controller, construct a sliding surface function and a control law, and generate a smooth control input signal through a 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 adjust the voltage of the supercapacitor energy storage unit to achieve stable compensation for grid voltage fluctuations.

[0030] If the 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, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0031] 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 conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "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 conjunction with such instruction execution systems, devices or apparatuses.

[0032] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a 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, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0033] 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, 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, 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.

[0034] Example 3, reference Figure 4 This is another embodiment of the present invention. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. This embodiment experiments the existing traditional method and the method of this embodiment respectively.

[0035] in accordance with Figure 4 A simulation model of a supercapacitor energy storage dynamic voltage controller is built to simulate and verify the proposed optimization control. When the system voltage is normal, the bypass switch connected in parallel with the voltage source inverter is in a closed state. When a voltage change is detected, the bypass switch is disconnected and the dynamic voltage controller is put into operation to achieve control of voltage sag. The simulation system parameters used in the present invention are shown in Table 1. Table 1 lists in detail 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.

[0036] Table 1 Simulation system parameters , When the monitoring system detects an abnormal voltage condition, the dynamic voltage restorer will start and operate immediately. At this time, the control strategy based on the extended state observer-super spiral sliding mode control (ESO-SSTSMC) will be activated to achieve effective compensation for voltage fluctuations. Figure 4As shown in the figure, the voltage waveform changes when the grid voltage sags under different voltage fluctuations are shown in detail. The voltage waveform on the grid side when the voltage sag occurs, the voltage waveform on the load side connected to the sensitive load when the voltage sag occurs, and the compensation voltage waveform injected by the supercapacitor energy storage dynamic voltage controller device are depicted.

[0037] pass Figure 4 From the waveform data in Figure 1, we can see the compensation effect of the supercapacitor energy storage dynamic voltage controller when voltage sag occurs, thereby ensuring the normal operation of sensitive loads and avoiding equipment damage or data loss caused by voltage fluctuations. Figure 4 Several key points can be found by looking at the waveform data in Figure 1. First, the voltage waveform on the grid side shows a significant drop during the voltage sag, which may cause unstable power supply to the grid and have an adverse effect on the equipment connected to the grid. However, due to the timely intervention of the supercapacitor energy storage dynamic voltage controller, the voltage waveform on the load side can be kept relatively stable, and the fluctuation amplitude is greatly reduced.

[0038] The compensation voltage waveform injected by the supercapacitor energy storage dynamic voltage controller shows the compensation voltage injected by the supercapacitor energy storage dynamic voltage controller to offset the voltage drop on the grid side. The amplitude and phase of the compensation voltage are accurately calculated to ensure that the voltage on the load side can be restored to a level close to the normal voltage. In this way, the supercapacitor energy storage dynamic voltage controller effectively reduces the impact of voltage sag on sensitive loads. With different voltage fluctuations, the compensation strategy of the supercapacitor energy storage dynamic voltage controller will also be adjusted. When the voltage sag is relatively mild, the compensation voltage injected by the supercapacitor energy storage dynamic voltage controller is relatively small; when the voltage sag is more severe, the supercapacitor energy storage dynamic voltage controller will increase the amplitude of the compensation voltage to ensure the stability of the voltage on the load side.

[0039] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for improving the stability of supercapacitor energy storage, characterized in that: include: Collect the status information of the supercapacitor energy storage system for preprocessing; Based on the preprocessed data, a dynamic mathematical model of the supercapacitor energy storage system is constructed and the state equation is derived; The dynamic mathematical model is used to design a smooth super-torsion algorithm controller, and a sliding surface function and a control law are constructed to generate a smooth control input; The control input signal is applied to the voltage source inverter, and the stable operation of the supercapacitor energy storage unit is achieved by dynamically adjusting the output voltage.

2. A method for improving supercapacitor energy storage stability as claimed in claim 1, characterized in that: The state information includes system voltage, output current and grid voltage deviation signal.

3. A method for improving supercapacitor energy storage stability as claimed in 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. A method for improving supercapacitor energy storage stability as claimed in claim 3, characterized in that: Based on the preprocessed data, a dynamic mathematical model of the supercapacitor energy storage system is constructed, and the state equation is derived, including: Continuously monitor the output voltage of the supercapacitor energy storage and the voltage source inverter, calculate the voltage sag peak percentage, evaluate the control strategy adjustment requirements, the controller decides the control signal switching, 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: ， in, is the grid side voltage; is the grid side voltage reference value; When the supercapacitor energy storage dynamic voltage controller is in constant power charge and discharge mode, the state equation expression of the supercapacitor energy storage dynamic voltage controller in the dq coordinate system is: ， ， ， in, , are the series filter resistance and inductance respectively; is the parallel filter capacitor; is the angular frequency; , is the three-phase voltage of the AC side power grid; , is the input current; is the output voltage of the supercapacitor energy storage unit, and is the switch function; The amplitude of the SVPWM control vector is limited, and the switching function amplitude constraint is, , the current switching function remains unsaturated.

5. A method for improving supercapacitor energy storage stability as claimed in claim 4, characterized in that: The design of a smooth super-torsion algorithm controller using the dynamic mathematical model, constructing a sliding 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: ， ， Among them, x is the state variable, is the derivative of the state equation, u is the control input, y is the output, , is a differentiable continuous function, is the sliding surface function, and λ is a constant.

6. A method for improving supercapacitor energy storage stability as claimed in claim 5, characterized in that: The design of a smooth super-torsion algorithm controller using the dynamic mathematical model, constructing a sliding surface function and a control law to generate a smooth control input also includes: In view of the energy storage characteristics of supercapacitors, the sliding mode controller responds to the dynamic changes and potential nonlinear behaviors during rapid charging and discharging. The expression is: ， ， in, yes Derivative calculation of .

7. A method for improving supercapacitor energy storage stability as claimed in claim 6, characterized in that: The design of a smooth super-torsion algorithm controller using the dynamic mathematical model, constructing a sliding surface function and a control law to generate a smooth control input also includes: The expression of the control input u for smooth supertorsion sliding mode control is: ， Among them, α and β are sliding surface coefficients to adjust the parameters of smooth supertorsion sliding mode control; The performance constraint is expressed as: ， Wherein, e is the natural logarithm; k is the sign function coefficient.

8. A system using a method for improving the stability of supercapacitor energy storage as claimed in any one of claims 1 to 7, characterized in that: It includes data acquisition and preprocessing module, dynamic mathematical modeling module, controller design module, execution and feedback module; 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 normalizes the data to a unified interval through normalization; The dynamic mathematical modeling module constructs a dynamic mathematical model of the supercapacitor energy storage system based on the preprocessed data; The controller design module uses a dynamic mathematical model to design a smooth super-torsion algorithm controller, construct a sliding surface function and a control law, and generate a smooth control input signal through a 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 adjust the voltage of the supercapacitor energy storage unit to achieve stable compensation for grid voltage fluctuations.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a method for improving the stability of supercapacitor energy storage according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for improving the stability of supercapacitor energy storage according to any one of claims 1 to 7 are implemented.

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