A method and device for predicting control of an energy storage converter and a storage medium

Abstract

The present application relates to a kind of energy storage converter prediction control method, device and storage medium.The present application is converted to α-β coordinate system under coordinate transformation by measured variable and carries out delay compensation;After obtaining the original output voltage reference value set in instruction, the error compensation reference value and the original output voltage reference value are summed to obtain the modified output voltage reference value after compensation;Based on the modified output voltage reference value, the modified full-order variable reference value is calculated and generated;The measured variable includes three-phase inductance current, three-phase capacitor voltage and three-phase output current;According to full-order variable reference value and the cost function of measurement variable prediction value calculation, and the switching state sequence that makes cost function minimum is selected as optimal switching state sequence;The first element of the optimal switching state sequence selected is applied to converter by drive circuit.The present application can effectively eliminate the output steady-state error of energy storage converter, fully consider the coupling influence of filter capacitor and filter inductor, and can effectively improve system stability.

Description

Technical Field

[0001] This invention relates to the field of energy storage converter control, and more particularly to a predictive control method, device, and storage medium for energy storage converters. Background Technology

[0002] With the increasing penetration rate of new energy sources, the dynamic characteristics and operating modes of traditional power systems have undergone profound changes. New energy sources, such as photovoltaic and wind power, inherently exhibit volatility and randomness, making it difficult for power generation and consumption curves to match in real time, resulting in an imbalance between "source and load." Energy storage systems are an effective means to mitigate the volatility of new energy sources and improve their absorption rate. Furthermore, when the main grid experiences faults, or in remote areas such as islands and deserts where the power system is difficult to cover, energy storage and its interface converter equipment can establish stable voltage and frequency, reliably supplying power to local critical loads.

[0003] Existing control strategies for grid-type energy storage converters primarily employ a proportional-resonant controller combined with active damping technology to achieve accurate output voltage tracking. Specifically, the difference between the reference and feedback values ​​of the output voltage is fed into the proportional-resonant controller, whose output is subtracted from the active damping term to obtain the voltage reference value for the grid-type energy storage converter. This reference value is then used to generate trigger signals for the power switching devices via Plus Width Modulation (PWM) to drive the converter. In recent years, predictive control methods for grid-type energy storage converters have been proposed. This method first constructs a discrete-domain mathematical model of the grid-type converter. Based on this model, it predicts the trajectory of the output voltage at future times by traversing a finite number of switching states of the converter. A cost function is designed using the sum of the squares of the differences between the output voltage reference and predicted values, and the cost function values ​​corresponding to a finite number of switching states are evaluated. The switching state that minimizes the cost function is defined as the optimal switching state and applied to the converter. This process is repeated cyclically in each switching state. For mainstream proportional resonant controllers combined with active damping control strategies, system stability must be ensured first when designing control parameters. This is typically achieved using frequency domain analysis tools (such as Bode plots and Nyquist curves) combined with stability criteria for linear systems to iteratively optimize controller parameters. The digital control system of a grid-type energy storage converter inherently contains a time delay, which causes the phase angle characteristic of the system's open-loop transfer function to decay rapidly. Furthermore, the LC filter of the grid-type energy storage converter has a gain much higher than 0 dB at the resonant frequency. Therefore, a low controller gain is necessary to ensure a reasonable gain margin in the system's open-loop transfer function and maintain system stability; excessive gain will lead to system instability. Consequently, the proportional resonant controller combined with active damping technology results in slow dynamic response and significant output voltage distortion during load surges and drops. For predictive control of grid-type energy storage converters, this method significantly improves the system's dynamic performance and reduces the degree of output voltage distortion during load surges and drops. However, this method requires high model accuracy of the controlled object and is sensitive to external uncertainties such as sampling noise and parameter drift. These factors lead to steady-state errors in the output voltage and poor power quality. Summary of the Invention

[0004] To solve the above-mentioned technical problems, or at least partially solve them, the present invention provides a predictive control method, device, and storage medium for an energy storage converter.

[0005] In a first aspect, the present invention provides a predictive control method for an energy storage converter, comprising: The measured variables are transformed to [coordinate transformation value]. α - βIn the coordinate system, delay compensation is performed; after obtaining the original output voltage reference value set in the instruction, the error compensation reference value is summed with the original output voltage reference value to obtain the compensated corrected output voltage reference value; based on the corrected output voltage reference value, the corrected full-order variable reference value is calculated and generated; the measured variables include three-phase inductor current, three-phase capacitor voltage, and three-phase output current; all switching states of the two-level three-phase bridge power circuit in the converter are traversed, the predicted values ​​of the measured variables are calculated, and the cost function of each switching state is calculated according to the full-order variable reference value and the predicted values ​​of the measured variables, and the switching state sequence that minimizes the cost function is selected as the optimal switching state sequence; the first element of the selected optimal switching state sequence is applied to the converter through the drive circuit.

[0006] Furthermore, after obtaining the original output voltage reference value set in the instruction, the process of summing the error compensation reference value with the original output voltage reference value to obtain the compensated corrected output voltage reference value includes: obtaining the original output voltage reference value set in the instruction and the actual output voltage value and subtracting them to obtain an error signal; inputting the error signal to the proportional multi-resonant controller to calculate the compensation reference value; and summing the compensation reference value with the original output voltage reference value to obtain the compensated corrected output voltage reference value.

[0007] Furthermore, the frequency domain expression of the proportional multiresonator controller is: , in, This is the proportionality coefficient. ( ) represents the coefficients of each harmonic resonance term. .

[0008] Furthermore, the measured variables are transformed to coordinates... α - β The coordinate transformation formulas involved in the coordinate system are as follows: , , and For measurement variables.

[0009] Furthermore, the calculation of the corrected full-order variable reference value based on the corrected output voltage reference value includes: compensating for the delay introduced by digital control, and calculating the corrected output voltage reference value in... and Full-order reference values ​​at time points: , , in, The electrical angle rotated in one sampling period. Sampling time; According to Kirchhoff's current law, the inductor current is calculated using a full-order reference value that corrects the output voltage reference value. and Full-order reference values ​​at time points: , , in, This is the capacitance value of the filter capacitor. and Let be the load current. Typically, the load current change is negligible within a single sampling period, therefore the following equation holds: and .

[0010] Furthermore, the measured variables are transformed to coordinates... α - β The coordinate transformation formula used in the coordinate system is: .

[0011] Furthermore, to switch to α - β The calculation method for delay compensation of measured variables in the coordinate system is as follows: , in, , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; For system matrix, For the input matrix and Let each be a perturbation matrix, and their respective forms are as follows: , , ,in, This is the inductance value of the filter inductor. This is the capacitance value of the filter capacitor. The resistance value is the one connected in series with the filter inductor. Sampling time.

[0012] Furthermore, the expression for the cost function is as follows: , in, Let cost function be , This serves as a reference value for all-order variables. Indicates The weight matrix is ​​a quadratic form. Indicates The weight matrix is ​​a quadratic form. The penalty term for overcurrent: , This is the upper limit of the current. To calculate the voltage of the filter capacitor and the current of the filter inductor and Predicted value at time: , .

[0013] Secondly, the present invention provides a predictive control device for an energy storage converter, comprising: at least one processing unit, a storage unit, a first current acquisition unit, a second current acquisition unit, a voltage acquisition unit, and a bus unit, wherein the bus unit is connected to the processing unit, the storage unit, the first current acquisition unit, the second current acquisition unit, and the voltage acquisition unit, the storage unit stores at least one instruction, and the processing unit executes the instruction to implement the predictive control method for the energy storage converter.

[0014] Thirdly, the present invention provides a storage medium for implementing a predictive control method for an energy storage converter. The storage medium stores a computer program, which, when executed by a processor connected to the energy storage converter via a drive circuit, implements the predictive control method for the energy storage converter.

[0015] The technical solutions provided in the embodiments of the present invention have the following advantages compared with the prior art: Traditional predictive control relies heavily on the accuracy of the controlled object's model and suffers from poor parameter robustness, leading to steady-state errors in the output voltage. This, in turn, results in poor power quality for grid-connected energy storage converters and a decline in power supply quality to the load. This invention addresses this issue by generating a compensation reference value using a proportional-multiplexer controller based on the error signal between the original and actual output voltage reference values. The compensation reference value is then summed with the original output voltage reference value to obtain a corrected output voltage reference value. This effectively eliminates the steady-state error of the energy storage converter's output, improves system power supply quality, and demonstrates significant engineering practical value.

[0016] For energy storage converters constructed with LC filters, traditional predictive control only includes the output voltage error term in the cost function, neglecting the operating state of the inductor current. This can easily lead to oscillations of the LC filter at its inherent resonant frequency, and even system instability. Furthermore, ignoring the inductor current's operating state can easily cause overcurrent during the dynamic adjustment process of the energy storage converter, potentially causing power switching devices to exceed their current stress and fail. This invention includes both the filter capacitor voltage and the filter inductor current in the cost function, fully considering their influence and effectively improving system stability. In addition, a penalty term for the upper current bound is introduced into the cost function, enabling protection based on the cost function to be executed even during overcurrent, achieving rapid overcurrent protection for the converter and improving system reliability. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of an energy storage converter provided in an embodiment of the present invention; Figure 2 A flowchart of a predictive control method for an energy storage converter provided in an embodiment of the present invention; Figure 3 This is a flowchart illustrating how, after obtaining the original output voltage reference value set in the instruction, the error compensation reference value is summed with the original output voltage reference value to obtain the compensated corrected output voltage reference value, as provided in an embodiment of the present invention. Figure 4 A flowchart for calculating and generating corrected full-order variable reference values ​​based on corrected output voltage reference values, provided for embodiments of the present invention; Figure 5 A schematic diagram of a predictive control device for an energy storage converter provided in an embodiment of the present invention; Figure 6 A schematic diagram of a predictive control system for an energy storage converter provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of a corrected output voltage reference value generation module in a predictive control system for an energy storage converter, provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0022] The power topology diagram of the energy storage converter is as follows: Figure 1 As shown, it mainly consists of an AC-side LC filter, a two-level three-phase bridge power circuit, and a DC-side bus capacitor C. dc Composition. The AC-side LC filter primarily filters out high-frequency harmonics generated during power electronic switching, obtaining a smooth sinusoidal output voltage. The three-phase output terminals of the filter are connected to the load to supply power. A two-level three-phase bridge power circuit performs high-frequency chopping on the DC bus, generating appropriate high-frequency square wave pulse signals at the midpoints A, B, and C of the bridge arms. The DC bus capacitor is typically connected to an energy storage unit (e.g., a battery E). dc The parallel connection filters out the high-frequency ripple superimposed on the DC bus, thus constructing a relatively stable and smooth DC bus voltage.

[0023] Example 1 See Figure 2 As shown, an embodiment of the present invention provides a predictive control method for an energy storage converter, comprising: S100, transforming the measured variables through coordinate transformation In a coordinate system, the measured variables include: three-phase filter inductor current. Three-phase filter capacitor voltage and three-phase output current Among them, the three-phase natural coordinate system to The coordinate system transformation formula is: .

[0024] S200, for conversion to Time delay compensation for measurement variables in the coordinate system: , in, , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; For system matrix, For the input matrix and Let each be a perturbation matrix, and their respective forms are as follows: , , ,in, This is the inductance value of the filter inductor. This is the capacitance value of the filter capacitor. The resistance value is the one connected in series with the filter inductor. Sampling time.

[0025] S300: After obtaining the original output voltage reference value set in the instruction, the error compensation reference value is summed with the original output voltage reference value to obtain the compensated corrected output voltage reference value. Specifically, the error signal is obtained by subtracting the original output voltage reference value from the actual output voltage value after delay compensation, and the proportional multiresonant controller generates the error compensation reference value based on the error signal.

[0026] In the specific implementation process, please refer to Figure 3 As shown, step S300 includes: S301, retrieve the original output voltage reference value set in the command. and the actual output voltage value after delay compensation .

[0027] S302, the original output voltage reference value Compared with the actual output voltage value after delay compensation The difference is used to obtain the error signal. .

[0028] S303 will send the error signal The input is fed into the proportional multiresonant controller to calculate the compensation reference value. Specifically, referring to the figure, the frequency domain expression of the proportional multiresonator controller is: , in, This is the proportionality coefficient. ( ) represents the coefficients of each harmonic resonance term. For damping bandwidth, The fundamental frequency is the ratio of the fundamental frequency to the resonant frequency. The proportional and fundamental resonant components can eliminate the steady-state error at the fundamental frequency. The resonant terms of other lower harmonics of the multi-resonant compensator can effectively eliminate the harmonic components generated by the nonlinear load, such as the 3rd, 5th, 7th, 9th and 11th harmonic components.

[0029] S304, Compensation Reference Value Compared with the original output voltage reference value Summing yields the corrected output voltage reference value after compensation: .

[0030] Traditional predictive control systems, lacking voltage compensators, directly transmit the given reference voltage to the predictive controller without correction. However, because predictive controllers themselves require high model accuracy and are sensitive to external uncertainties such as sampling noise and parameter drift, applying an uncorrected reference voltage cannot avoid noise and drift interference, leading to steady-state errors in the output voltage. This application eliminates the problems of steady-state output voltage errors and poor power quality caused by parameter drift and noise disturbances through closed-loop feedback.

[0031] S400, calculates and generates corrected full-order variable reference values ​​based on corrected output voltage reference values; In the specific implementation process, please refer to Figure 4 As shown, S400 includes: S401, which compensates for the delay introduced by digital control and calculates and corrects the output voltage reference value. and The full-order reference value at time t is: , , in, The electrical angle rotated in one sampling period. Sampling time.

[0032] S202, according to Kirchhoff's current law, the inductor current is calculated using the full-order reference value of the corrected output voltage reference value. and Full-order reference values ​​at time: , , in, This is the capacitance value of the filter capacitor. and Let be the load current. Typically, the load current change is negligible within a single sampling period, therefore the following equation holds: and .

[0033] S500 iterates through all switching states of the two-level three-phase bridge power circuit in the converter and calculates the filter capacitor voltage and filter inductor current based on the corresponding switching states. and Predicted values ​​at time 3. The prediction equations for the filter capacitor voltage and filter inductor current are: , .

[0034] S600 calculates the cost function based on the reference values ​​of the full-order variables and the predicted values ​​of the measured variables. The optimal switch-state sequence is selected by choosing the switch-state sequence that minimizes the cost function. Cost function The expression is as follows: , in, Let cost function be , This serves as a reference value for all-order variables. For the predicted values ​​of the measurement variables as described in S500; Indicates The weight matrix is ​​a quadratic form. Indicates The weight matrix is ​​a quadratic form. The penalty term for overcurrent: , This is the upper limit of the current. When the current exceeds the upper limit, the cost function will always be infinite, and the minimum cost function will not be selected, thus preventing overcurrent protection from being implemented to protect the energy storage converter.

[0035] S700, the first element of the optimal switch state sequence selected in S600, i.e. The drive signal is applied to the converter via the drive circuit. The converter receives the drive signal from the drive circuit to control the power switching devices.

[0036] Repeat the above steps when the next sampling time arrives.

[0037] Example 2 See Figure 5As shown, this embodiment of the invention provides a predictive control device for an energy storage converter, comprising: at least one processing unit, a storage unit, a first current acquisition unit, a second current acquisition unit, a voltage acquisition unit, and a bus unit. The bus unit is connected to the processing unit, the storage unit, the first current acquisition unit, the second current acquisition unit, and the voltage acquisition unit. The storage unit stores at least one instruction, and the processing unit executes the instruction to implement the predictive control method for the energy storage converter. In specific implementation, the first current acquisition unit acquires three-phase inductor current, the second current acquisition unit acquires three-phase output current, and the voltage acquisition unit acquires three-phase capacitor voltage. The predictive control device for the energy storage converter is connected to a drive circuit via the control bus of the bus unit. The drive circuit is connected to the power switching devices of the two-level three-phase bridge power circuit of the converter. The drive circuit uses optocouplers for signal isolation.

[0038] Example 3 This invention provides a storage medium for implementing a predictive control method for an energy storage converter. The storage medium stores a computer program, which, when executed by a processor connected to the energy storage converter via a drive circuit, implements the predictive control method for the energy storage converter.

[0039] Example 4 See Figure 6 and Figure 7 As shown, this embodiment of the invention provides a predictive control system for an energy storage converter, including: a corrected output voltage reference value generation module. This module obtains the original output voltage reference value set in the instruction, and then sums the error compensation reference value with the original output voltage reference value to obtain the compensated corrected output voltage reference value. Specifically, see [link to relevant documentation]. Figure 7 As shown, the corrected output voltage reference value generation module includes a proportional-multiplexer controller. The proportional-multiplexer controller calculates the compensation reference value based on the error signal. The frequency domain expression of the proportional-multiplexer controller is: .

[0040] Coordinate transformation and compensation module, the coordinate transformation and compensation module is used to transform the measured variables to In the coordinate system, time delay compensation is performed. Three-phase natural coordinate system to... The coordinate system transformation formula is: .

[0041] To convert to Time delay compensation for measurement variables in the coordinate system: , in, , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; For system matrix, For the input matrix and Let each be a perturbation matrix, and their respective forms are as follows: ， , ,in, This is the inductance value of the filter inductor. This is the capacitance value of the filter capacitor. The resistance value is the one connected in series with the filter inductor. Sampling time.

[0042] The predictive control module includes a full-order variable reference value generation unit, a drive signal generation unit, and a state variable prediction unit.

[0043] A full-order variable reference value generation unit is connected to a corrected output voltage reference value generation module. This unit compensates for the delay introduced by digital control and uses the corrected output voltage reference value to calculate the corrected output voltage reference value at... and At time t, using the full-order reference value and Kirchhoff's current law, the inductor current is calculated using the full-order reference value of the corrected output voltage reference value. and Full-order reference value at any given time; The state variable prediction unit is connected to the coordinate transformation and compensation module. The state variable prediction unit predicts the measured variables based on the coordinate transformation and compensation module. and The measurement variable at time.

[0044] The drive signal generation unit is connected to the full-order variable reference value generation unit and the state variable prediction unit. It uses the provided full-order variable reference value and the measured variable prediction value to calculate the cost function of all switching states, and selects the switching state sequence that minimizes the cost function as the optimal switching state sequence. The first element of the selected optimal switching state sequence is applied to the converter through the drive circuit.

[0045] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0046] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0047] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0048] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A predictive control method for an energy storage converter, characterized in that, include: The measured variables are transformed to [coordinate transformation value]. α - β The coordinate system is used and delay compensation is performed; the measured variables include three-phase inductor current, three-phase capacitor voltage and three-phase output current; after obtaining the original output voltage reference value set in the instruction, the error compensation reference value is summed with the original output voltage reference value to obtain the compensated corrected output voltage reference value; The corrected full-order variable reference value is calculated and generated based on the corrected output voltage reference value; Iterate through all switching states of the two-level three-phase bridge power circuit in the converter, calculate the predicted values ​​of the measured variables, and calculate the cost function for each switching state based on the reference values ​​of the full-order variables and the predicted values ​​of the measured variables. Select the switching state sequence that minimizes the cost function as the optimal switching state sequence. Apply the first element of the selected optimal switching state sequence to the converter through the drive circuit.

2. The predictive control method for energy storage converters according to claim 1, characterized in that, After obtaining the original output voltage reference value set in the instruction, the error compensation reference value is summed with the original output voltage reference value to obtain the compensated corrected output voltage reference value. This includes: obtaining the original output voltage reference value set in the instruction and the actual output voltage value after delay compensation and subtracting them to obtain the error signal; inputting the error signal into the proportional multi-resonant controller to calculate the compensation reference value; and summing the compensation reference value with the original output voltage reference value to obtain the compensated corrected output voltage reference value.

3. The predictive control method for energy storage converters according to claim 2, characterized in that, The frequency domain expression of the proportional multiresonator controller is: ， in, This is the proportionality coefficient. ( ) represents the coefficients of each harmonic resonance term. .

4. The predictive control method for energy storage converters according to claim 1, characterized in that, The measured variables are transformed to [coordinate range]. α - β The coordinate transformation formulas involved in the coordinate system are as follows: , , and For measurement variables.

5. The predictive control method for energy storage converters according to claim 1, characterized in that, The calculation of the corrected full-order variable reference value based on the corrected output voltage reference value includes: compensating for the delay introduced by digital control, and calculating the corrected output voltage reference value in... and Full-order reference values ​​at time points: ， ， in, The electrical angle rotated in one sampling period. Sampling time; According to Kirchhoff's current law, the inductor current is calculated using a full-order reference value that corrects the output voltage reference value. and Full-order reference values ​​at time points: ， ， in, This is the capacitance value of the filter capacitor. and Let the load current be the load current. Typically, the load current change is negligible within a single sampling period; therefore, the following equation holds: and .

6. The predictive control method for energy storage converters according to claim 1, characterized in that, The measured variables are transformed to [coordinate transformation value]. α - β The coordinate transformation formula used in the coordinate system is: .

7. The predictive control method for energy storage converters according to claim 1, characterized in that, Switch to α - β The calculation method for delay compensation of measured variables in the coordinate system is as follows: ， in, , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; , and They are respectively Shaft measurement variables, Axis input variables and Shaft load disturbance; For system matrix, For the input matrix and Let each be a perturbation matrix, and their respective forms are as follows: , , ,in, The inductance value of the filter inductor. This is the capacitance value of the filter capacitor. The resistance value is the one connected in series with the filter inductor. Sampling time.

8. The predictive control method for energy storage converters according to claim 1, characterized in that, The expression for the cost function is as follows: ， in, Let cost function be , This serves as a reference value for all-order variables. Indicated by The weight matrix is ​​a quadratic form. Indicated by The weight matrix is ​​a quadratic form. The penalty term for overcurrent: ， This is the upper limit of the current. To calculate the voltage of the filter capacitor and the current of the filter inductor and Predicted value at time: ， 。 9. A predictive control device for an energy storage converter, characterized in that, include: The device includes at least one processing unit, a storage unit, a first current acquisition unit, a second current acquisition unit, a voltage acquisition unit, and a bus unit. The bus unit is connected to the processing unit, the storage unit, the first current acquisition unit, the second current acquisition unit, and the voltage acquisition unit. The storage unit stores at least one instruction, and the processing unit executes the instruction to implement the predictive control method for the energy storage converter as described in any one of claims 1-8.

10. A storage medium for implementing a predictive control method for an energy storage converter, the storage medium storing a computer program, characterized in that, When the computer program is executed by a processor connected to the energy storage converter via a drive circuit, it implements the predictive control method for the energy storage converter as described in any one of claims 1-8.

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