Method, device and equipment for dynamically analyzing frequency of network-forming type energy storage converter and medium

Abstract

The invention belongs to the technical field of power systems, and particularly discloses a method, a device and equipment for dynamically analyzing the frequency of a network construction type energy storage converter and a medium. According to the invention, quantitative conversion is carried out on the physical model parameters of the network construction type energy storage converter; according to the reference active power deviation equation, determining actual equivalent inertia data of the network construction type energy storage converter during virtual synchronous control; and determining an active power-frequency dynamic analysis strategy according to the actual equivalent inertia data, and carrying out dynamic analysis on the frequency of the network construction type energy storage converter according to the active power-frequency dynamic analysis strategy. Through the above mode, in consideration of an actual engineering application scene, that is, the actual equivalent inertia data of the network construction type energy storage converter cannot be approximated as a virtual inertia coefficient, an active-frequency dynamic analysis strategy is determined on the basis of comprehensively considering energy constraint and preceding stage control dynamics, and the frequency of the network construction type energy storage converter is dynamically analyzed; therefore, the accuracy of dynamic analysis frequency can be effectively improved.

Description

Technical Field

[0001] This application belongs to the field of power system technology, and more specifically, relates to a method, device, equipment and medium for frequency dynamic analysis of grid-type energy storage converters. Background Technology

[0002] As a core device for the stability control of new power systems, grid-connected energy storage converters have seen explosive growth in application scale in recent years, covering key areas such as wind power or photovoltaic energy storage, independent or shared energy storage power stations, weak grid areas, and isolated microgrids. Currently, the power outer loop of grid-connected energy storage converters generally adopts virtual synchronous control technology, the core of which is to introduce virtual inertia into the control system to support the grid frequency by simulating the dynamic characteristics of synchronous generators.

[0003] In practical engineering applications, dynamic frequency analysis of grid-type energy storage converters is indispensable. A prerequisite for dynamic analysis is determining the equivalent inertia data. Currently, the inertia coefficient of virtual synchronous control is directly equated to the equivalent inertia data of the grid-type energy storage converter. This only holds true under ideal conditions assuming infinite energy storage capacity and neglecting DC voltage control dynamics. In practical engineering applications, where DC voltage control parameters are not sufficiently small and the current DC capacitor is not large enough, significant errors occur. Therefore, the accuracy of the above method in dynamically analyzing the frequency of grid-type energy storage converters is relatively low. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this application is to provide a method, apparatus, equipment, and medium for dynamic frequency analysis of grid-type energy storage converters. This aims to solve the problem that existing technologies, by directly equating the inertia coefficient of virtual synchronous control with equivalent inertia data, result in low accuracy in dynamic analysis of the frequency of grid-type energy storage converters.

[0005] To achieve the above objectives, in a first aspect, this application provides a method for frequency dynamic analysis of a grid-type energy storage converter, comprising: Obtain the physical model parameters of the grid-type energy storage converter, and perform quantitative conversion on the physical model parameters to obtain the target quantitative model parameters; A reference active power deviation equation is generated based on the target quantitative model parameters and multi-dimensional DC-side control parameters; When the preset conditions are met in actual engineering application scenarios, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined according to the reference active power deviation equation and the virtual inertia coefficient. Based on the actual equivalent inertia data, an active power-frequency dynamic analysis strategy is determined, and the frequency of the grid-type energy storage converter is dynamically analyzed based on the active power-frequency dynamic analysis strategy.

[0006] In one embodiment, the step of generating a reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC-side control parameters includes: Determine the conventional DC voltage equation based on the target quantitative model parameters; The steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation during steady-state operation of the DC link are obtained based on the multi-dimensional DC-side control parameters. A deviation DC voltage equation is generated based on the conventional DC voltage equation, the steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation. A reference active power deviation equation is generated based on the deviation DC voltage equation and the deviation value of the reference DC voltage.

[0007] In one embodiment, the step of generating a reference active power deviation equation based on the deviation DC voltage equation and the deviation value of the reference DC voltage includes: The conventional reference active power equation of the virtual synchronous control converter is determined based on the target quantitative model parameters, and the first variable term of the conventional reference active power equation is obtained. The first variable term is replaced according to the deviation value of the reference DC voltage and the deviation DC voltage equation, respectively; Generate the current active power deviation equation based on the replacement results; The current active power deviation equation is adjusted based on the characteristic information of the reference DC voltage to obtain the reference active power deviation equation.

[0008] In one embodiment, the step of determining the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient when the preset conditions are met in the actual engineering application scenario includes: Obtain the current DC voltage control parameters and current DC capacitance in the actual engineering application scenario; When the current DC voltage control parameter is greater than a first value and / or the current DC capacitance is less than a second value, it is determined that the actual engineering application scenario meets the preset conditions. Obtain the conventional potential-frequency equation for a grid-type energy storage converter; The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the conventional potential-frequency equation, the reference active power deviation equation, and the virtual inertia coefficient.

[0009] In one embodiment, the step of determining the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the conventional potential-frequency equation, the reference active power deviation equation, and the virtual inertia coefficient includes: The second variable term for determining the potential frequency; The second variable term is replaced by the reference active power deviation equation and the instantaneous active power deviation respectively to obtain the current frequency deviation equation of the grid-type energy storage converter power under virtual synchronous control. The target frequency deviation equation is obtained by simplifying and deriving the current frequency deviation equation. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the target frequency deviation equation and the virtual inertia coefficient.

[0010] In one embodiment, the step of determining an active-frequency dynamic analysis strategy based on the actual equivalent inertia data, and performing dynamic frequency analysis on the grid-type energy storage converter based on the active-frequency dynamic analysis strategy, includes: Determine the active-frequency dynamic analysis strategy based on the actual equivalent inertia data; A target frequency correction curve is generated based on the active power-frequency dynamic analysis strategy. The frequency of the grid-type energy storage converter is dynamically analyzed based on the target frequency correction curve.

[0011] Secondly, this application provides a frequency dynamic analysis device for a grid-type energy storage converter, comprising: The conversion module is used to obtain the physical model parameters of the grid-type energy storage converter and to quantitatively convert the physical model parameters to obtain the target quantitative model parameters. The generation module is used to generate a reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC-side control parameters. The determination module is used to determine the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient when the preset conditions are met in the actual engineering application scenario. The analysis module is used to determine the active-frequency dynamic analysis strategy based on the actual equivalent inertia data, and to perform dynamic analysis on the frequency of the grid-type energy storage converter based on the active-frequency dynamic analysis strategy.

[0012] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation thereof.

[0013] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0014] Fifthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0015] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0016] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: (1) When performing dynamic analysis of the frequency of a grid-type energy storage converter, this application considers the actual engineering application scenario. It judges whether the preset conditions are met based on the current DC voltage control parameters and the current DC capacitor. If so, it indicates that the actual equivalent inertia data of the grid-type energy storage converter cannot be approximated as the virtual inertia coefficient. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the reference active power deviation equation and the virtual inertia coefficient, which can effectively improve the accuracy of determining the actual equivalent inertia data. Based on a comprehensive consideration of energy constraints and front-end control dynamics, an active-frequency dynamic analysis strategy is determined. Then, the frequency of the grid-type energy storage converter is dynamically analyzed according to the active-frequency dynamic analysis strategy, which can effectively improve the accuracy of dynamic frequency analysis. In addition, this application can also perform dynamic analysis of the frequency of each grid-type energy storage converter in a multi-machine system according to different branches, which is applicable to various engineering application scenarios under non-ideal conditions.

[0017] (2) In addition to performing dynamic analysis on the frequency of the grid-type energy storage converter, this application can also generate a target active power correction curve based on the active power-frequency dynamic analysis strategy, and perform dynamic analysis on the active power output of the grid-type energy storage converter based on the target active power correction curve, thereby realizing multi-dimensional dynamic analysis.

[0018] In summary, this application obtains the physical model parameters of a grid-type energy storage converter and performs quantitative conversion on these parameters to obtain target quantitative model parameters. Based on the target quantitative model parameters and multi-dimensional DC-side control parameters, a reference active power deviation equation is generated. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the reference active power deviation equation. An active power-frequency dynamic analysis strategy is determined based on the actual equivalent inertia data, and the frequency of the grid-type energy storage converter is dynamically analyzed based on this strategy. By considering practical engineering application scenarios, namely that the actual equivalent inertia data of the grid-type energy storage converter cannot be approximated as a virtual inertia coefficient, an active power-frequency dynamic analysis strategy is determined based on a comprehensive consideration of energy constraints and front-end control dynamics, and the frequency of the grid-type energy storage converter is dynamically analyzed, thereby effectively improving the accuracy of the dynamic frequency analysis. Attached Figure Description

[0019] Figure 1 This is one of the flowcharts illustrating the frequency dynamic analysis method for grid-type energy storage converters provided in this application embodiment; Figure 2 This is the second flowchart illustrating the frequency dynamic analysis method for grid-type energy storage converters provided in this application embodiment; Figure 3 This is a schematic diagram of the process for constructing the equivalent swing equation of a grid-type energy storage converter according to an embodiment of this application; Figure 4 This is a topology diagram of a multi-machine grid-type energy storage converter system provided in the embodiments of this application; Figure 5 This is a schematic diagram of the module structure of the frequency dynamic analysis device for a grid-type energy storage converter provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0021] In this article, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The symbol " / " in this article indicates that the related objects are in an "or" relationship; for example, A / B means A or B.

[0022] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0023] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0024] Based on this, this application provides a method for frequency dynamic analysis of a grid-type energy storage converter, referring to... Figure 1 , Figure 1 This is one of the flowcharts illustrating the frequency dynamic analysis method for a grid-type energy storage converter provided in this application embodiment. In this embodiment, the frequency dynamic analysis method for a grid-type energy storage converter includes steps S10 to S40: Step S10: Obtain the physical model parameters of the grid-type energy storage converter, and perform quantitative conversion on the physical model parameters to obtain the target quantitative model parameters.

[0025] It should be noted that the grid-connected energy storage converter, as a core device for the stability control of new power systems, functions to simulate the physical characteristics of synchronous generators, providing voltage, frequency, and power angle stability support for grids with a high proportion of renewable energy. For grid-connected energy storage converters, virtual synchronous control technology has multiple implementation schemes and can consist of two parts: grid-connected control (active and reactive power control) and energy storage-side energy control (DC voltage control).

[0026] It should be understood that physical model parameters refer to the parameters of the physical model of the grid-type energy storage converter. This physical model includes, but is not limited to, the energy storage system, DC link, and virtual synchronization control module. After obtaining the physical model parameters of the grid-type energy storage converter, the physical model parameters can be converted into target quantitative model parameters through quantitative conversion. These target quantitative model parameters can also be called mathematical model parameters, enabling quantitative dynamic analysis. DC voltage control is essentially used to maintain the energy storage state of the DC capacitor. Conventional DC voltage is related to input power and output power.

[0027] On the one hand, the conventional DC voltage equation can be expressed as:

[0028] in, Represents the conventional DC voltage equation. Indicates input power. Indicates output power. Represents the Laplace operator. Indicates capacitance.

[0029] On the other hand, the conventional reference active power equation for a virtual synchronous control converter can be expressed as:

[0030] in, This represents the conventional reference active power equation for a virtual synchronous control converter. This represents the DC voltage proportional gain control parameter. This represents the DC voltage integral gain control parameter. This indicates the reference DC voltage.

[0031] Step S20: Generate a reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC side control parameters.

[0032] It is understandable that the multi-dimensional DC-side control parameters include, but are not limited to, the steady-state DC voltage during steady-state operation of the DC link, the active power deviation injected into the DC link, and the instantaneous active power deviation. The reference active power deviation equation refers to the active power deviation equation that combines DC voltage control with active power-phase control. In order to establish the swing equation, after obtaining the target quantitative model parameters, the reference active power deviation equation can be generated by combining the multi-dimensional DC-side control parameters.

[0033] Further, step S20 includes: determining the conventional DC voltage equation based on the target quantitative model parameters; obtaining the steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation during steady-state operation of the DC link based on the multi-dimensional DC-side control parameters; generating a deviation DC voltage equation based on the conventional DC voltage equation, the steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation; and generating a reference active power deviation equation based on the deviation DC voltage equation and the deviation value of the reference DC voltage.

[0034] It should be understood that after determining the conventional DC voltage equation, a deviated DC voltage equation can be generated by combining the steady-state DC voltage during steady-state operation of the DC link, the active power deviation injected into the DC link, and the instantaneous active power deviation. Compared to linearizing the conventional DC voltage equation, this deviated DC voltage equation can be expressed as:

[0035] Where Δ represents the deviation from the corresponding variable, The equation representing the deviation DC voltage is as follows: This represents the steady-state DC voltage during steady-state operation of the DC link. This indicates the active power deviation injected into the DC link. This indicates the instantaneous active power deviation.

[0036] Further, the step of generating the reference active power deviation equation based on the deviation DC voltage equation and the deviation value of the reference DC voltage includes: determining the conventional reference active power equation of the virtual synchronous control converter based on the target quantitative model parameters, and obtaining the first variable term of the conventional reference active power equation; replacing the first variable term according to the deviation value of the reference DC voltage and the deviation DC voltage equation respectively; generating the current active power deviation equation based on the replacement result; and adjusting the current active power deviation equation according to the characteristic information of the reference DC voltage to obtain the reference active power deviation equation.

[0037] It is understandable that the conventional reference active power equation refers to the active power equation determined by the virtual synchronous control converter with typical DC voltage control as a reference. The dynamic characteristics of DC-side energy can be reflected in the DC voltage control. The first variable term refers to the variable term in the conventional reference active power equation that can be replaced to generate the current active power deviation equation. This first variable term can be the reference DC voltage. and conventional DC voltage equation At this point, the first variable term can be replaced according to the deviation value of the reference DC voltage and the deviation DC voltage equation, that is, the reference DC voltage... Replace with the deviation value of the reference DC voltage, conventional DC voltage equation Replacing it with the biased DC voltage equation is equivalent to linearizing the conventional reference active power equation. The resulting current active power bias equation can then be expressed as:

[0038] in, The equation representing the current active power deviation is as follows: The equation representing the deviation DC voltage is as follows: This indicates the deviation value of the reference DC voltage.

[0039] It should be noted that, in order to establish the swing equation, after obtaining the deviation DC voltage equation, the deviation DC voltage equation can be substituted into the current active power deviation equation. The substituted current active power deviation equation can then be expressed as:

[0040] It is understandable that the reference DC voltage is determined to be constant based on the characteristic information of the reference DC voltage, i.e., the deviation value of the reference DC voltage. =0. At this point, we can further derive the current active power deviation equation after substituting the value. The active power deviation equation can be specifically expressed as:

[0041] Step S30: When the preset conditions are met in the actual engineering application scenario, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined according to the reference active power deviation equation and the virtual inertia coefficient.

[0042] It should be understood that the actual engineering application scenario refers to the engineering application scenario of the grid-type energy storage converter at the current moment. When the actual engineering application scenario meets the preset conditions, it indicates that the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is significantly different from the virtual inertia coefficient. The virtual inertia coefficient cannot be directly approximated to the actual equivalent inertia data. Instead, it is necessary to comprehensively determine the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient. This actual equivalent inertia data is related to the virtual inertia coefficient, DC voltage control parameters, and DC capacitor.

[0043] Step S40: Determine the active power-frequency dynamic analysis strategy based on the actual equivalent inertia data, and perform dynamic analysis on the frequency of the grid-type energy storage converter based on the active power-frequency dynamic analysis strategy.

[0044] It is understandable that the active-frequency dynamic analysis strategy refers to the dynamic analysis strategy determined by comprehensively considering energy constraints and front-end control dynamics. After determining the active-frequency dynamic analysis strategy based on the actual equivalent inertia data, dynamic analysis can be performed on the frequency of the grid-type energy storage converter, as well as on the active power output of the grid-type energy storage converter.

[0045] Further, step S40 includes: determining an active-frequency dynamic analysis strategy based on the actual equivalent inertia data; generating a target frequency correction curve based on the active-frequency dynamic analysis strategy; and performing dynamic analysis on the frequency of the grid-type energy storage converter based on the target frequency correction curve.

[0046] It should be understood that the target frequency correction curve refers to the correction curve that can dynamically analyze the frequency of the grid-type energy storage converter. This target frequency correction curve is different from the traditional frequency curve. For example, in the traditional frequency curve, the lowest point of the system frequency is monotonically related to the virtual inertia coefficient, while in the target frequency correction curve in this embodiment, the lowest point of the system frequency is not monotonically related to the virtual inertia coefficient.

[0047] It should also be emphasized that, for the active power-frequency dynamic analysis strategy, in addition to generating the target frequency correction curve as mentioned above, a target active power correction curve can also be generated. At this time, the active power output of the grid-type energy storage converter can be dynamically analyzed based on the target active power correction curve.

[0048] This embodiment acquires the physical model parameters of the grid-type energy storage converter and performs quantitative conversion on these parameters to obtain target quantitative model parameters. A reference active power deviation equation is generated based on the target quantitative model parameters and multi-dimensional DC-side control parameters. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the reference active power deviation equation. An active power-frequency dynamic analysis strategy is determined based on the actual equivalent inertia data, and the frequency of the grid-type energy storage converter is dynamically analyzed based on this strategy. By considering practical engineering applications—that is, the actual equivalent inertia data of the grid-type energy storage converter cannot be approximated as a virtual inertia coefficient—an active power-frequency dynamic analysis strategy is determined based on a comprehensive consideration of energy constraints and front-end control dynamics, and the frequency of the grid-type energy storage converter is dynamically analyzed, thereby effectively improving the accuracy of the dynamic frequency analysis.

[0049] In one specific implementation, this application provides steps for determining the actual equivalent inertia data of a grid-type energy storage converter under virtual synchronous control. Please refer to... Figure 2 , Figure 2 This is the second flowchart illustrating the frequency dynamic analysis method for grid-type energy storage converters provided in this application embodiment. Step S30 includes steps S301 to S304: Step S301: Obtain the current DC voltage control parameters and current DC capacitance under the actual engineering application scenario.

[0050] It should be noted that in order to effectively improve the accuracy of determining the actual equivalent inertia data of the grid-type energy storage converter during virtual synchronous control, it is necessary to consider the actual engineering application scenario. That is, the actual equivalent inertia data of the grid-type energy storage converter cannot be directly approximated as the virtual inertia coefficient. Current DC voltage control parameters include, but are not limited to, DC voltage proportional gain control parameters, etc.

[0051] Step S302: When the current DC voltage control parameter is greater than the first value and / or the current DC capacitance is less than the second value, it is determined that the actual engineering application scenario meets the preset conditions.

[0052] Understandably, after obtaining the current DC voltage control parameters and current DC capacitance in the actual engineering application scenario, the current DC voltage control parameters are compared with the first value and the current DC capacitance is compared with the second value. When the current DC voltage control parameter is greater than the first value, it indicates that the current DC voltage control parameter is not small enough. When the current DC capacitance is less than the second value, it indicates that the current DC capacitance is not large enough. At this time, it is determined that the actual engineering application scenario meets the preset condition, that is, the actual equivalent inertia data of the grid-type energy storage converter cannot be directly approximated as the virtual inertia coefficient.

[0053] Step S303: Obtain the conventional potential-frequency equation of the grid-type energy storage converter.

[0054] Step S304: Determine the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the conventional potential frequency equation, the reference active power deviation equation, and the virtual inertia coefficient.

[0055] It should be noted that the required internal potential of a grid-type energy storage converter can be directly generated through pulse width modulation or indirectly generated through dual-loop voltage control. After obtaining the conventional potential-frequency equation of the grid-type energy storage converter, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control can be determined by combining the reference active power deviation equation and the virtual inertia coefficient. Obviously, in addition to the virtual inertia coefficient, the parameters for determining the actual equivalent inertia data also include the conventional potential-frequency equation and the reference active power deviation equation, which means that in actual engineering application scenarios where the current DC voltage control parameter is greater than the first value and / or the current DC capacitor is less than the second value, the actual equivalent inertia data of the grid-type energy storage converter cannot be directly approximated by the virtual inertia coefficient.

[0056] Further, step S304 includes: determining the second variable term of the conventional potential frequency equation; replacing the second variable term according to the reference active power deviation equation and the instantaneous active power deviation to obtain the current frequency deviation equation of the grid-type energy storage converter power under virtual synchronization control; simplifying and deriving the current frequency deviation equation to obtain the target frequency deviation equation; and determining the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronization control according to the target frequency deviation equation and the virtual inertia coefficient.

[0057] It should be understood that the second variable term refers to the variable term in the conventional potential-frequency equation that can be substituted to generate the current frequency deviation equation of the grid-type energy storage converter power under virtual synchronous control. This second variable term includes, but is not limited to, the conventional reference active power. and conventional actual active power At this point, the second variable term can be replaced according to the reference active power deviation equation and the instantaneous active power deviation, respectively. Specifically, the conventional reference active power is replaced by the reference active power deviation equation, and the conventional actual active power is replaced by the instantaneous active power deviation. This is equivalent to linearizing the conventional potential-frequency equation. The current frequency deviation equation of the grid-type energy storage converter power under virtual synchronous control can then be expressed as:

[0058] in, This represents the conventional potential-frequency equation for obtaining a grid-type energy storage converter. This represents the virtual inertia coefficient.

[0059] Furthermore, the current frequency deviation equation can be simplified and derived to obtain the target frequency deviation equation, specifically:

[0060] Furthermore, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control can be determined based on the target frequency deviation equation and the virtual inertia coefficient, specifically:

[0061] Understandable, This represents the conventional potential-frequency equation for obtaining a grid-type energy storage converter. This represents the actual equivalent inertia data of a grid-type energy storage converter during virtual synchronous control. This represents the DC voltage proportional gain control parameter. This represents the DC voltage integral gain control parameter. Represents the Laplace operator. Indicates capacitance. This represents the steady-state DC voltage during steady-state operation of the DC link. This represents the virtual inertia coefficient.

[0062] It should be noted that, as shown in the above formula, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is a transfer function that is related to the virtual inertia coefficient, DC voltage proportional gain control parameters, DC voltage integral gain control parameters, and capacitor, and is not a simple algebraic value. Therefore, the equivalent swing equation of the grid-type energy storage converter can be expressed as follows: Figure 3 As shown, where, This represents the actual equivalent inertia data of a grid-type energy storage converter during virtual synchronous control. This represents the damping control parameters.

[0063] Furthermore, based on the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control, the active-frequency dynamic characteristics can be expressed as follows:

[0064] It should be understood that an active power-frequency dynamic analysis strategy can be determined based on the aforementioned dynamic characteristics, and the frequency of the grid-type energy storage converter can be dynamically analyzed based on this strategy. Additionally, refer to... Figure 4 , Figure 4 The topology diagram for a multi-machine grid-connected energy storage converter system is as follows: A multi-machine grid-connected energy storage converter system includes multiple grid-connected energy storage converters, which can be numbered as Grid-connected Energy Storage Converter 1, Grid-connected Energy Storage Converter 2, ..., Grid-connected Energy Storage Converter m. Dynamic analysis of the frequency of each grid-connected energy storage converter is then performed according to different branches. The phase angle output by the multi-machine grid-connected energy storage converter system to the grid is... .

[0065] This embodiment obtains the current DC voltage control parameters and current DC capacitance under actual engineering application scenarios; when the current DC voltage control parameters are greater than a first value and / or the current DC capacitance is less than a second value, it is determined that the actual engineering application scenario meets preset conditions; the conventional potential-frequency equation of the grid-type energy storage converter is obtained; based on the conventional potential-frequency equation, the reference active power deviation equation, and the virtual inertia coefficient, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined. Through the above method, the comparison results between the current DC voltage control parameters and the first value, and between the current DC capacitance and the second value, determine whether the actual engineering application scenario meets preset conditions. If the preset conditions are met, it indicates that the actual equivalent inertia data of the grid-type energy storage converter cannot be directly approximated by the virtual inertia coefficient. In this case, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined by combining the reference active power deviation equation and the virtual inertia coefficient, thereby effectively improving the accuracy of determining the actual equivalent inertia data.

[0066] The frequency dynamic analysis device for a grid-type energy storage converter provided in this application is described below. The frequency dynamic analysis device described below corresponds to the frequency dynamic analysis method described above. Please refer to... Figure 5 , Figure 5 This is a schematic diagram of the module structure of the frequency dynamic analysis device for a grid-type energy storage converter provided in this application embodiment, including: The conversion module T10 is used to obtain the physical model parameters of the grid-type energy storage converter and to quantitatively convert the physical model parameters to obtain the target quantitative model parameters.

[0067] The generation module T20 is used to generate a reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC side control parameters.

[0068] The determination module T30 is used to determine the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient when the preset conditions are met in the actual engineering application scenario.

[0069] The analysis module T40 is used to determine the active-frequency dynamic analysis strategy based on the actual equivalent inertia data, and to perform dynamic analysis on the frequency of the grid-type energy storage converter based on the active-frequency dynamic analysis strategy.

[0070] This embodiment acquires the physical model parameters of the grid-type energy storage converter and performs quantitative conversion on these parameters to obtain target quantitative model parameters. A reference active power deviation equation is generated based on the target quantitative model parameters and multi-dimensional DC-side control parameters. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the reference active power deviation equation. An active power-frequency dynamic analysis strategy is determined based on the actual equivalent inertia data, and the frequency of the grid-type energy storage converter is dynamically analyzed based on this strategy. By considering practical engineering applications—that is, the actual equivalent inertia data of the grid-type energy storage converter cannot be approximated as a virtual inertia coefficient—an active power-frequency dynamic analysis strategy is determined based on a comprehensive consideration of energy constraints and front-end control dynamics, and the frequency of the grid-type energy storage converter is dynamically analyzed, thereby effectively improving the accuracy of the dynamic frequency analysis.

[0071] It is understood that the detailed functional implementation of each of the above modules can be found in the description of the aforementioned method embodiments, and will not be repeated here.

[0072] It should be understood that the above-described device is used to execute the methods in the above embodiments. The implementation principle and technical effect of the corresponding program modules in the device are similar to those described in the above methods. The working process of the device can be referred to the corresponding process in the above methods, and will not be repeated here.

[0073] Based on the methods in the above embodiments, this application provides an electronic device, please refer to... Figure 6 , Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application.

[0074] It should be noted that the system may include: a processor 10, a communications interface 20, a memory 30, and a communication bus 40. The processor 10, communications interface 20, and memory 30 communicate with each other via the communication bus 40. The processor 10 can invoke logical instructions stored in the memory 30 to execute the methods described in the above embodiments.

[0075] Furthermore, the logical instructions in the aforementioned memory 30 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the 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 to cause 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 the various embodiments of this application.

[0076] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0077] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0078] It is understood that the processor in the embodiments of this application can be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, field-programmable gate arrays, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0079] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor.

[0080] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. Those skilled in the art will readily understand that the above descriptions are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for dynamic frequency analysis of a grid-type energy storage converter, characterized in that, include: Obtain the physical model parameters of the grid-type energy storage converter, and perform quantitative conversion on the physical model parameters to obtain the target quantitative model parameters; A reference active power deviation equation is generated based on the target quantitative model parameters and multi-dimensional DC-side control parameters; When the preset conditions are met in actual engineering application scenarios, the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined according to the reference active power deviation equation and the virtual inertia coefficient. Based on the actual equivalent inertia data, an active power-frequency dynamic analysis strategy is determined, and the frequency of the grid-type energy storage converter is dynamically analyzed based on the active power-frequency dynamic analysis strategy.

2. The method as described in claim 1, characterized in that, The step of generating the reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC-side control parameters includes: Determine the conventional DC voltage equation based on the target quantitative model parameters; The steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation during steady-state operation of the DC link are obtained based on the multi-dimensional DC-side control parameters. A deviation DC voltage equation is generated based on the conventional DC voltage equation, the steady-state DC voltage, the active power deviation injected into the DC link, and the instantaneous active power deviation. A reference active power deviation equation is generated based on the deviation DC voltage equation and the deviation value of the reference DC voltage.

3. The method as described in claim 2, characterized in that, The step of generating the reference active power deviation equation based on the deviation DC voltage equation and the deviation value of the reference DC voltage includes: The conventional reference active power equation of the virtual synchronous control converter is determined based on the target quantitative model parameters, and the first variable term of the conventional reference active power equation is obtained. The first variable term is replaced according to the deviation value of the reference DC voltage and the deviation DC voltage equation, respectively; Generate the current active power deviation equation based on the replacement results; The current active power deviation equation is adjusted based on the characteristic information of the reference DC voltage to obtain the reference active power deviation equation.

4. The method as described in claim 1, characterized in that, The step of determining the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient when the preset conditions are met in actual engineering application scenarios includes: Obtain the current DC voltage control parameters and current DC capacitance in the actual engineering application scenario; When the current DC voltage control parameter is greater than a first value and / or the current DC capacitance is less than a second value, it is determined that the actual engineering application scenario meets the preset conditions. Obtain the conventional potential-frequency equation for a grid-type energy storage converter; The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the conventional potential-frequency equation, the reference active power deviation equation, and the virtual inertia coefficient.

5. The method as described in claim 4, characterized in that, The step of determining the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the conventional potential-frequency equation, the reference active power deviation equation, and the virtual inertia coefficient includes: The second variable term for determining the potential frequency; The second variable term is replaced by the reference active power deviation equation and the instantaneous active power deviation respectively to obtain the current frequency deviation equation of the grid-type energy storage converter power under virtual synchronous control. The target frequency deviation equation is obtained by simplifying and deriving the current frequency deviation equation. The actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control is determined based on the target frequency deviation equation and the virtual inertia coefficient.

6. The method according to any one of claims 1 to 5, characterized in that, The step of determining the active power-frequency dynamic analysis strategy based on the actual equivalent inertia data, and performing dynamic frequency analysis on the grid-type energy storage converter based on the active power-frequency dynamic analysis strategy, includes: Determine the active-frequency dynamic analysis strategy based on the actual equivalent inertia data; A target frequency correction curve is generated based on the active power-frequency dynamic analysis strategy. The frequency of the grid-type energy storage converter is dynamically analyzed based on the target frequency correction curve.

7. A frequency dynamic analysis device for a grid-type energy storage converter, characterized in that, include: The conversion module is used to obtain the physical model parameters of the grid-type energy storage converter and to quantitatively convert the physical model parameters to obtain the target quantitative model parameters. The generation module is used to generate a reference active power deviation equation based on the target quantitative model parameters and multi-dimensional DC-side control parameters. The determination module is used to determine the actual equivalent inertia data of the grid-type energy storage converter under virtual synchronous control based on the reference active power deviation equation and the virtual inertia coefficient when the preset conditions are met in the actual engineering application scenario. The analysis module is used to determine the active-frequency dynamic analysis strategy based on the actual equivalent inertia data, and to perform dynamic analysis on the frequency of the grid-type energy storage converter based on the active-frequency dynamic analysis strategy.

8. An electronic device, characterized in that, include: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, it causes the processor to perform the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, When the computer program product is run on a processor, the processor causes the processor to perform the method as described in any one of claims 1-6.

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