Energy storage converter frequency response characteristic analysis method and system

Abstract

The invention belongs to the technical field of novel power system control, and particularly discloses an energy storage converter frequency response characteristic analysis method and system, and the method comprises the steps: building small signal models of different controllers in an energy storage converter containing virtual inertia control under a DC voltage time scale, constructing an amplitude-phase motion model of unbalanced power input based on the small signal model; based on the amplitude-phase motion model, extracting an equivalent inertia expression of the energy storage converter; based on the equivalent inertia expression, drawing a Bode diagram by changing controller parameters corresponding to the small signal model and operation parameters of the energy storage converter, and analyzing frequency response characteristics of the energy storage converter in different virtual inertia control modes based on amplitude-phase characteristics of the Bode diagram; wherein the amplitude of the Bode diagram is used for representing the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used for representing the inertia response speed of the energy storage converter. According to the invention, the frequency response characteristic analysis of the energy storage converter containing virtual inertia control is realized.

Description

Technical Field

[0001] The present application belongs to the field of novel power system control technology, and more specifically, relates to a method and system for analyzing frequency response characteristics of an energy storage converter. Background Art

[0002] In recent years, as the penetration rate of new energy in the power grid continues to increase, more and more new energy equipment has been connected to the power system. Unlike synchronous generators, new energy equipment cannot provide the system with spare rotation capacity to ensure the stable operation of the system, which makes the new power system lack sufficient inertia. When the power system is subject to large disturbances caused by frequent switching of loads and generators, traditional frequency regulation units cannot meet the regulation needs of the power system.

[0003] In order to improve the regulation capability of the power system, the energy storage converter with additional virtual inertia control has become an effective means to solve the low inertia of new energy sources due to its fast frequency regulation capability. In order to clarify the mechanism of its inertia action, evaluate the inertia response capability of the energy storage converter, and facilitate the optimization design of the virtual inertia control parameters of the energy storage converter, it is crucial to accurately analyze the inertia characteristics of the energy storage converter with virtual inertia control when the parameters change. The energy provided by the energy storage converter in the inertia response stage is different from the spontaneous response of the actual rotor from the inertia of the traditional unit. It is mainly affected by the control of the energy storage converter and its control parameters, so it is difficult to quantitatively characterize its inertia support capability.

[0004] At present, related research mainly evaluates the inertia support capacity of energy storage from the perspective of frequency stability of new power systems and system inertia requirements, and extracts two indicators, namely the lowest frequency point and the maximum frequency change rate, to evaluate the frequency change suppression performance of the energy storage converter. However, the ability of the energy storage converter with virtual inertia control to provide virtual inertia is not specifically quantified. There is still a lack of mature theoretical methods for analyzing the inertia response characteristics of energy storage converters with virtual inertia control and evaluating the system inertia support capacity. Summary of the invention

[0005] In view of the above-mentioned defects in the prior art, the present application provides a method and system for analyzing the frequency response characteristics of an energy storage converter, aiming to solve the problem of inertia response characteristics analysis of an energy storage converter with virtual inertia control.

[0006] In a first aspect, the present application provides a method for analyzing frequency response characteristics of an energy storage converter, comprising: The small signal model of different controllers in the energy storage converter with virtual inertia control under the DC voltage time scale is established, and the amplitude and phase motion model of unbalanced power input is constructed based on the small signal model; Based on the amplitude-phase motion model, the equivalent inertia expression of the energy storage converter is extracted; Based on the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, the Bode diagram is drawn and the frequency response characteristics of the energy storage converter under different virtual inertia control modes are analyzed based on the amplitude and phase characteristics of the Bode diagram. Among them, the amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter.

[0007] In a second aspect, the present application also provides a system for analyzing frequency response characteristics of an energy storage converter, comprising: Modeling module, used to establish small signal models of different controllers in energy storage converters with virtual inertia control at the DC voltage time scale, and to build amplitude and phase motion models of unbalanced power input based on the small signal model; Equivalent inertia extraction module, used to extract the equivalent inertia expression of the energy storage converter based on the amplitude-phase motion model; An analysis module is used to draw a Bode diagram based on an equivalent inertia expression by changing controller parameters corresponding to the small signal model and operating parameters of the energy storage converter, and to analyze the frequency response characteristics of the energy storage converter under different virtual inertia control modes based on the amplitude and phase characteristics of the Bode diagram; Among them, the amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter.

[0008] In a third aspect, the present application also provides an electronic device, comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0009] In a fourth aspect, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0010] In a fifth aspect, the present application further provides a computer program product, which, when executed on a processor, enables the processor to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0011] The present application provides a method and system for analyzing the frequency response characteristics of an energy storage converter. By establishing a small signal model of different controllers in an energy storage converter with virtual inertia control at a DC voltage time scale, an amplitude-phase motion model of unbalanced power input is constructed. The amplitude-phase motion model has a clear physical process and good scalability, that is, when the inertia control strategy is changed, only the modeling of the inertia part needs to be modified. Based on the amplitude-phase motion model, an equivalent inertia expression of the energy storage converter with virtual inertia control is extracted. By using the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, a Bode diagram is obtained as the basis for analyzing the inertia characteristics of the energy storage converter with virtual inertia control. The method is suitable for analyzing the inertia characteristics of the energy storage converter with virtual inertia control under different virtual inertia control modes. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 It is a flow chart of a method for analyzing frequency response characteristics of an energy storage converter provided in an embodiment of the present application; Figure 2 It is a small signal model of an energy storage converter with virtual inertia control provided in an embodiment of the present application; Figure 3 It is a comparison diagram of active output obtained by the amplitude-phase motion model provided in the embodiment of the present application and the real model; Figure 4 is a comparison diagram of the system frequency obtained by the amplitude-phase motion model provided in the embodiment of the present application and the real model; Figure 5 is a schematic diagram of a process for extracting equivalent inertia based on a synchronous machine model provided in an embodiment of the present application; Figure 6 It is a schematic diagram of a process of extracting equivalent inertia based on an amplitude-phase motion model provided in an embodiment of the present application; Figure 7 is the inertia coefficient under the different virtual inertia control droop coefficients provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics; Figure 8 is the equivalent inertia under different virtual inertia control droop coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig. 9 is the inertia coefficient under different virtual inertia control time constants provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics; Fig.10 is the equivalent inertia under different virtual inertia control time constants provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.11 is the inertia coefficient under different DC voltage control proportional coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.12 is the equivalent inertia under different DC voltage control proportional coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.13 It is the inertia coefficient of the energy storage converter controlled by virtual inertia under different DC voltage control differential coefficients provided in the embodiment of the present application. Schematic diagram of the amplitude-phase characteristics; Fig.14 is the equivalent inertia under different DC voltage control differential coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.15 is the inertia coefficient under different PLL controller bandwidths provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics; Fig.16 is the equivalent inertia under different PLL controller bandwidths provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.17 is the inertia coefficient under different damping ratios of the phase-locked loop controller provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.18 is the equivalent inertia under different damping ratios of the phase-locked loop controller provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics; Fig.19 It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different virtual inertia control droop coefficients provided in an embodiment of the present application when the grid frequency is disturbed; Fig. 20 It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different virtual inertia control time constants provided in an embodiment of the present application when the grid frequency is disturbed; Fig.21 It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different DC voltage controller proportional coefficients provided in an embodiment of the present application when the grid frequency is disturbed; Fig. 22It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different DC voltage controller integral coefficients provided in an embodiment of the present application when the grid frequency is disturbed; Fig.23 It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different phase-locked loop controller bandwidths provided in an embodiment of the present application when the grid frequency is disturbed; Fig.24 It is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different phase-locked loop controller damping ratios provided in an embodiment of the present application when the grid frequency is disturbed; Fig.25 It is a structural schematic diagram of a frequency response characteristic analysis system of an energy storage converter provided in an embodiment of the present application; Fig.26 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0015] Figure 1 is a flow chart of a method for analyzing frequency response characteristics of an energy storage converter provided in an embodiment of the present application, such as Figure 1 As shown, the method includes at least the following steps: S101, establishing a small signal model of different controllers in an energy storage converter with virtual inertia control at a DC voltage time scale, and constructing an amplitude-phase motion model of unbalanced power input based on the small signal model; S102. Extracting an equivalent inertia expression of the energy storage converter based on the amplitude-phase motion model; S103. Based on the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, a Bode diagram is drawn and the frequency response characteristics of the energy storage converter under different virtual inertia control modes are analyzed based on the amplitude and phase characteristics of the Bode diagram.

[0016] The method for analyzing the frequency response characteristics of an energy storage converter provided in an embodiment of the present application establishes a small signal model of different controllers in an energy storage converter with virtual inertia control at a DC voltage time scale, and constructs an amplitude-phase motion model of unbalanced power input. The amplitude-phase motion model has a clear physical process and good scalability, that is, when the inertia control strategy is changed, only the modeling of the inertia part needs to be modified; based on the amplitude-phase motion model, an equivalent inertia expression of the energy storage converter with virtual inertia control is extracted, and by using the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, a Bode diagram is obtained as a basis for analyzing the inertia characteristics of the energy storage converter with virtual inertia control, and the method is suitable for analyzing the inertia characteristics of the energy storage converter with virtual inertia control under different virtual inertia control modes.

[0017] The following is an example of a three-machine nine-node circuit to illustrate the technical solution provided by the embodiment of the present application. The circuit is composed of two synchronous machines and an energy storage converter, wherein the energy storage converter is composed of 200 500kW sub-converters; the benchmark parameters of the energy storage converter with virtual inertia control are shown in Table 1.

[0018] Table 1

[0019] For S101, a small signal model of different controllers in the energy storage converter with virtual inertia control at the DC voltage time scale is established, and an amplitude and phase motion model of unbalanced power input is constructed based on the small signal model.

[0020] Specifically, as a key device connecting the energy storage system and the power grid, the performance of the energy storage converter directly affects the stability and reliability of the power system. At the DC voltage time scale (usually 0.1s), the dynamic response characteristics of the energy storage converter play an important role in the frequency regulation and voltage support of the power system. Establishing a small signal model of different controllers in the energy storage converter with virtual inertia control at the DC voltage time scale will help to deeply understand the dynamic behavior of the energy storage converter.

[0021] Energy storage converters usually consist of a main circuit and a control circuit, and the control circuit is responsible for implementing various control strategies. Figure 2 is a small signal model of an energy storage converter with virtual inertia control provided in an embodiment of the present application, such as Figure 2As shown, a small signal model of an energy storage converter with virtual inertia control at a DC voltage time scale is established, including establishing small signal models of a virtual inertia controller, a DC voltage controller, an energy storage controller, and a phase-locked loop controller. By using the controller parameters and operating parameters of the energy storage converter with virtual inertia control and combining the structure of the energy storage converter with virtual inertia control, a small signal model of an energy storage converter with virtual inertia control at a DC voltage time scale is established.

[0022] The amplitude-phase motion model uses the change of internal potential under unbalanced power drive to describe the characteristics of the equipment and reflects the operating nature of the AC power system. In the power system, the dynamic process of the internal potential phase and amplitude of the equipment has an important impact on the stability and performance of the system. By structurally splitting the energy storage converter with virtual inertia control, the modeling of the small signal model of each controller is realized. The controllers interact with each other through electrical connections. Based on the small signal models of each controller and the interaction between each controller, the amplitude-phase motion model of the energy storage converter with virtual inertia control with unbalanced power input is established. The amplitude-phase motion model has a clear physical process and good scalability, that is, when changing the inertia control strategy, only the modeling of the inertia part needs to be modified.

[0023] Figure 3 is a comparison diagram of active output obtained by the amplitude-phase motion model provided in the embodiment of the present application and the real model, Figure 4 : is a system frequency comparison diagram obtained by the amplitude-phase motion model provided in the embodiment of the present application and the real model. Taking the energy storage converter with virtual inertia control connected to the three-machine nine-node power grid as an example, the simulation accuracy of the amplitude-phase motion model of the energy storage converter with virtual inertia control provided in the embodiment of the present application is verified. Assuming that 10% active load is connected to the power grid at t = 60s, as shown in FIG. Figure 3 and Figure 4 As shown, the comparative responses of the amplitude-phase motion model and the real model are provided respectively. It can be seen that the amplitude-phase motion model provided in the embodiment of the present application can accurately reflect the active output of the energy storage converter with virtual inertia control and the system frequency dynamics, and can be used to study inertia problems.

[0024] For S102, the equivalent inertia expression of the energy storage converter is extracted based on the amplitude-phase motion model.

[0025] Figure 5 is a schematic diagram of a process for extracting equivalent inertia based on a synchronous machine model provided in an embodiment of the present application, Figure 6 is a schematic diagram of the process of extracting equivalent inertia based on the amplitude-phase motion model provided in the embodiment of the present application, which is similar to Figure 5 The process of extracting equivalent inertia using a synchronous machine model is shown. In the embodiment of the present application, the equivalent inertia is extracted using an amplitude-phase motion model of an energy storage converter with virtual inertia control. Figure 6As shown in the figure, the equivalent inertia expression of the energy storage converter with virtual inertia control is extracted, which satisfies:

[0026] in, represents the equivalent inertia expression, , , and They represent the inertia coefficients extracted from the amplitude and phase motion models, respectively. These inertia coefficients are related to the multi-loop control parameters and the operating parameters of the energy storage converter. Specifically: Related to the inherent characteristics of the energy storage converter, it meets the following requirements:

[0027] in, represents the rated angular velocity of the grid frequency, represents the power factor, represents the Laplace operator.

[0028] Related to the control parameters of the virtual inertia controller, it satisfies:

[0029] in, K 0 means virtual inertia control droop coefficient, T K Indicates the virtual inertia control time constant.

[0030] Related to the control parameters of the DC voltage controller and the energy storage controller, it satisfies:

[0031] in, C Indicates the DC capacitance value, U dc0 Indicates the DC bus voltage. X f Indicates the size of the filter inductor. k pu represents the DC voltage control proportional coefficient, k iu represents the DC voltage control differential coefficient, K D represents the energy storage coefficient, E 0 represents the steady-state value of the output voltage of the energy storage converter.

[0032] Related to the control parameters of the phase-locked loop controller, it satisfies:

[0033] in, k ppll represents the phase-locked loop control proportional coefficient, k ipll represents the phase-locked loop control differential coefficient, ω n represents the oscillation frequency of the second-order system, ξ Represents the damping ratio.

[0034] For a phase-locked loop controller, the bandwidth of the phase-locked loop satisfies:

[0035] in, Indicates the angular frequency corresponding to the phase-locked loop bandwidth angle.

[0036] For S103, based on the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, the Bode diagram is drawn and the frequency response characteristics of the energy storage converter under different virtual inertia control modes are analyzed based on the amplitude and phase characteristics of the Bode diagram.

[0037] Specifically, the amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter with virtual inertia control, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter with virtual inertia control. The higher the amplitude of the Bode diagram, the greater the active power of the energy storage converter, and the smaller the phase distance 0, the shorter the time it takes for the energy storage converter output power to reach its peak.

[0038] By changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, the Bode diagram of the energy storage converter with virtual inertia control is obtained. Then, the frequency response characteristics of the energy storage converter under different virtual inertia control modes are analyzed using the amplitude and phase characteristics of the Bode diagram.

[0039] Specifically, the equivalent inertia is the inertia coefficient , , and The cumulative multiplication of the combined effect, therefore different controller parameters and energy storage converter operating parameters have different effects on the inertia coefficient , , and The impact is reflected in the equivalent inertia of the energy storage converter with virtual inertia control. In the embodiment of the present application, each inertia coefficient is split and analyzed. By analyzing the expression of a single inertia coefficient, the controller parameters and the energy storage converter operating parameters are changed respectively, and the Bode diagram is obtained for the equivalent inertia and the inertia coefficient respectively. The frequency response characteristics of the energy storage converter under different virtual inertia control modes can be analyzed by combining the amplitude and phase characteristics of the Bode diagram.

[0040] For the inertia coefficient , the Bode diagram reflects the inherent coefficients in the energy storage converter with virtual inertia control: the rated angular velocity of the grid frequency and power factor . Change the controller parameters to the inertia coefficient No impact.

[0041] For the inertia coefficient , by changing the virtual inertia control droop coefficient and virtual inertia control time constant of the virtual inertia controller, the inertia coefficient is obtained and equivalent inertia Bode diagram; select the oscillation frequency under the DC voltage time scale, analyze the amplitude and phase characteristics of the Bode diagram under different control parameters, and obtain the controller parameters that affect the inertia response of the energy storage converter.

[0042] Figure 7 is the inertia coefficient under the different virtual inertia control droop coefficients provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics, Figure 8 is the equivalent inertia under different virtual inertia control droop coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics, Fig. 9 is the inertia coefficient under different virtual inertia control time constants provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics, Fig.10 is the equivalent inertia under different virtual inertia control time constants provided in the embodiment of the present application The amplitude-phase characteristics diagram of Figures 7 to 10 As shown in the figure, it can be seen from the amplitude characteristics that the virtual inertia controls the droop coefficient K 0 The larger the value, the greater the virtual inertia control time constant. T K The smaller it is, the stronger the inertia response of the energy storage converter is; from the phase characteristics, it can be seen that the virtual inertia controls the droop coefficient K 0 has little effect on the inertia response speed of the energy storage converter, while the virtual inertia control time constant T K The smaller it is, the faster the inertia response speed is.

[0043] That is, the virtual inertia controls the droop coefficient K0 is positively correlated with the inertia response of the energy storage converter; virtual inertia control time constant T K It is negatively correlated with the inertia response and inertia response speed of the energy storage converter.

[0044] For the inertia coefficient By changing the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller K D , get the inertia coefficient and equivalent inertia Bode diagram; select the oscillation frequency under the DC voltage time scale, analyze the amplitude and phase characteristics of the Bode diagram under different control parameters, and obtain the controller parameters that affect the inertia response of the energy storage converter.

[0045] Fig.11 is the inertia coefficient under different DC voltage control proportional coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics, Fig.12 is the equivalent inertia under different DC voltage control proportional coefficients provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics, Fig.13 It is the inertia coefficient of the energy storage converter controlled by virtual inertia under different DC voltage control differential coefficients provided in the embodiment of the present application. Schematic diagram of the amplitude-phase characteristics, Fig.14 is the equivalent inertia under different DC voltage control differential coefficients provided in the embodiment of the present application The amplitude-phase characteristics diagram of Figures 11 to 14 As shown in the figure, it can be seen from the amplitude-phase characteristics that the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller K D There is almost no influence on the inertia response of the energy storage converter, that is, the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller have nothing to do with the inertia response of the energy storage converter.

[0046] For the inertia coefficient , by changing the bandwidth of the phase-locked loop controller (the bandwidth is related to the damping ratio) and the damping ratio ξ , get the inertia coefficient and equivalent inertia Bode diagram; select the oscillation frequency under the DC voltage time scale, analyze the amplitude and phase characteristics of the Bode diagram under different control parameters, and obtain the controller parameters that affect the inertia response of the energy storage converter.

[0047] Fig.15 is the inertia coefficient under different PLL controller bandwidths provided in the embodiments of the present application Schematic diagram of the amplitude-phase characteristics, Fig.16is the equivalent inertia under different PLL controller bandwidths provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics, Fig.17 is the inertia coefficient under different damping ratios of the phase-locked loop controller provided in the embodiment of the present application Schematic diagram of the amplitude-phase characteristics, Fig.18 is the equivalent inertia under different damping ratios of the phase-locked loop controller provided in the embodiment of the present application The amplitude-phase characteristics diagram of Figures 15 to 18 As shown, it can be seen from the amplitude-phase characteristics that the bandwidth and damping ratio of the phase-locked loop controller have almost no effect on the inertia response of the energy storage converter, that is, the bandwidth and damping ratio of the phase-locked loop controller have nothing to do with the inertia response of the energy storage converter.

[0048] Fig.19 is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different virtual inertia control droop coefficients provided in an embodiment of the present application when the grid frequency is disturbed, Fig. 20 is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different virtual inertia control time constants provided in an embodiment of the present application when the grid frequency is disturbed, Fig.21 is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different DC voltage controller proportional coefficients provided in an embodiment of the present application when the grid frequency is disturbed, Fig. 22 is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different DC voltage controller integral coefficients provided in an embodiment of the present application when the grid frequency is disturbed, Fig.23 is a schematic diagram of changes in active output and system frequency of an energy storage converter with virtual inertia control under different phase-locked loop controller bandwidths provided in an embodiment of the present application when the grid frequency is disturbed, Fig.24 : is a schematic diagram of the change of active output and system frequency of the energy storage converter with virtual inertia control under different phase-locked loop controller damping ratios provided in the embodiment of the present application when the grid frequency is disturbed, such as Figures 19 to 24 It shows that when different control parameters change, the active output and system frequency of the energy storage converter with virtual inertia control change when the grid frequency is disturbed, and the frequency response characteristic analysis method of the energy storage converter provided in the embodiment of the present application is further verified.

[0049] The energy storage converter frequency response characteristic analysis system provided in the present application is described below. The energy storage converter frequency response characteristic analysis system described below and the energy storage converter frequency response characteristic analysis method described above can be referenced to each other.

[0050] Fig.25: is a structural schematic diagram of a frequency response characteristic analysis system for an energy storage converter provided in an embodiment of the present application. As shown in FIG. 1 , the system at least includes: Modeling module 2501, used to establish small signal models of different controllers in energy storage converter with virtual inertia control at DC voltage time scale, and build amplitude and phase motion model of unbalanced power input based on small signal model; An equivalent inertia extraction module 2502 is used to extract an equivalent inertia expression of the energy storage converter based on an amplitude-phase motion model; The analysis module 2503 is used to draw a Bode diagram based on an equivalent inertia expression by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, and analyze the frequency response characteristics of the energy storage converter under different virtual inertia control modes based on the amplitude and phase characteristics of the Bode diagram; Among them, the amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter.

[0051] In some embodiments, an energy storage converter with virtual inertia control includes a virtual inertia controller, a DC voltage controller, an energy storage controller, and a phase-locked loop controller.

[0052] In some embodiments, the equivalent inertia expression of the energy storage converter satisfies:

[0053] in, represents the equivalent inertia of the energy storage converter, , , and denote the inertia coefficients extracted from the amplitude and phase motion models, respectively; in, Related to the inherent characteristics of the energy storage converter, it meets the following requirements:

[0054] in, represents the rated angular velocity of the grid frequency, represents the power factor, represents the Laplace operator; Related to the control parameters of the virtual inertia controller, it satisfies:

[0055] in, K 0 means virtual inertia control droop coefficient, T K Indicates the virtual inertia control time constant; Related to the control parameters of the DC voltage controller and the energy storage controller, it satisfies:

[0056] in, C Indicates the DC capacitance value, U dc0 Indicates the DC bus voltage. X f Indicates the size of the filter inductor. k pu represents the DC voltage control proportional coefficient, k iu represents the DC voltage control differential coefficient, K D represents the energy storage coefficient, E 0 represents the steady-state value of the output voltage of the energy storage converter; Related to the control parameters of the phase-locked loop controller, it satisfies:

[0057] in, k ppll represents the phase-locked loop control proportional coefficient, k ipll represents the phase-locked loop control differential coefficient, ω n represents the oscillation frequency of the second-order system, ξ Represents the damping ratio.

[0058] In some embodiments, the inertia coefficient Related to the inherent characteristics of the energy storage converter, changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter has an impact on the inertia coefficient No impact.

[0059] In some embodiments, the analysis module 2503 is specifically used to: The inertia coefficient is obtained by changing the virtual inertia control droop coefficient and virtual inertia control time constant of the virtual inertia controller. and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia From the Bode plot, it is determined that the virtual inertia control droop coefficient is positively correlated with the inertia response of the energy storage converter, and the virtual inertia control time constant is negatively correlated with the inertia response and inertia response speed of the energy storage converter.

[0060] In some embodiments, the analysis module 2503 is specifically used to: By changing the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller, the inertia coefficient is obtained and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia The Bode diagram of the DC voltage controller and the energy storage coefficient of the energy storage controller are determined to be independent of the inertia response of the energy storage converter.

[0061] In some embodiments, the analysis module 2503 is specifically used to: By changing the bandwidth and damping ratio of the phase-locked loop controller, the inertia coefficient is obtained and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia The Bode plot of shows that the bandwidth and damping ratio of the PLL controller are independent of the inertia response of the energy storage converter.

[0062] It can be understood that the detailed functional implementation of each of the above-mentioned units / modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0063] It should be understood that the above-mentioned system is used to execute the methods in the above-mentioned embodiments. The implementation principles and technical effects of the corresponding program modules in the system are similar to those described in the above-mentioned methods. The working process of the system can refer to the corresponding process in the above-mentioned method and will not be repeated here.

[0064] Based on the method in the above embodiment, an embodiment of the present application provides an electronic device. The device may include: at least one memory for storing programs and at least one processor for executing the programs stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the above embodiment.

[0065] Fig.26 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Fig.26 As shown, the electronic device may include: a processor (Processor) 2601, a communication interface (Communications Interface) 2602, a memory (Memory) 2603 and a communication bus 2604, wherein the processor 2601, the communication interface 2602, and the memory 2603 communicate with each other through the communication bus 2604. The processor 2601 can call the software instructions in the memory 2603 to execute the method described in the above embodiment.

[0066] In addition, the logic instructions in the above-mentioned memory 2603 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present application.

[0067] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0068] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0069] It is understandable that the processor in the embodiment of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0070] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0071] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0072] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0073] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for analyzing frequency response characteristics of an energy storage converter, characterized in that: include: Establish a small signal model of different controllers in an energy storage converter with virtual inertia control at a DC voltage time scale, and construct an amplitude-phase motion model of unbalanced power input based on the small signal model; Based on the amplitude-phase motion model, extracting an equivalent inertia expression of the energy storage converter; Based on the equivalent inertia expression, by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter, a Bode diagram is drawn and the frequency response characteristics of the energy storage converter under different virtual inertia control modes are analyzed based on the amplitude and phase characteristics of the Bode diagram; The amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter.

2. The method for analyzing the frequency response characteristics of an energy storage converter according to claim 1, characterized in that: The energy storage converter with virtual inertia control comprises a virtual inertia controller, a DC voltage controller, an energy storage controller and a phase-locked loop controller.

3. The method for analyzing the frequency response characteristics of an energy storage converter according to claim 2, characterized in that: The equivalent inertia expression of the energy storage converter satisfies: in, represents the equivalent inertia of the energy storage converter, , , and denote respectively the inertia coefficients extracted from the amplitude and phase motion model; in, Related to the inherent characteristics of the energy storage converter, it satisfies: in, represents the rated angular velocity of the grid frequency, represents the power factor, represents the Laplace operator; Related to the control parameters of the virtual inertia controller, it satisfies: in, K 0 means virtual inertia control droop coefficient, T K Indicates the virtual inertia control time constant; Related to the control parameters of the DC voltage controller and the energy storage controller, satisfying: in, C Indicates the DC capacitance value, U dc0 Indicates the DC bus voltage. X f Indicates the size of the filter inductor. k pu represents the DC voltage control proportional coefficient, k iu represents the DC voltage control differential coefficient, K D represents the energy storage coefficient, E 0 represents the steady-state value of the output voltage of the energy storage converter; Related to the control parameters of the phase-locked loop controller, satisfying: in, k ppll represents the phase-locked loop control proportional coefficient, k ipll represents the phase-locked loop control differential coefficient, ω n represents the oscillation frequency of the second-order system, ξ Represents the damping ratio.

4. The method for analyzing the frequency response characteristics of an energy storage converter according to claim 3, characterized in that: Inertia coefficient Related to the inherent characteristics of the energy storage converter, changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter has an effect on the inertia coefficient No impact.

5. The method for analyzing frequency response characteristics of an energy storage converter according to claim 3, characterized in that: The analyzing the frequency response characteristics of the energy storage converter under different virtual inertia control modes includes: The inertia coefficient is obtained by changing the virtual inertia control droop coefficient and the virtual inertia control time constant of the virtual inertia controller. and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia The Bode diagram is used to determine that: the virtual inertia control droop coefficient is positively correlated with the inertia response of the energy storage converter, and the virtual inertia control time constant is negatively correlated with both the inertia response and the inertia response speed of the energy storage converter.

6. The method for analyzing the frequency response characteristics of an energy storage converter according to claim 3, characterized in that: The analyzing the frequency response characteristics of the energy storage converter under different virtual inertia control modes includes: By changing the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller, the inertia coefficient is obtained. and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia The Bode diagram of the embodiment of the present invention determines that the PI coefficient of the DC voltage controller and the energy storage coefficient of the energy storage controller are independent of the inertia response of the energy storage converter.

7. The method for analyzing frequency response characteristics of an energy storage converter according to claim 3, characterized in that: The analyzing the frequency response characteristics of the energy storage converter under different virtual inertia control modes includes: By changing the bandwidth and damping ratio of the phase-locked loop controller, the inertia coefficient is obtained and equivalent inertia Bode diagram; Based on the inertia coefficient and equivalent inertia The Bode plot of FIG. 4 shows that the bandwidth and damping ratio of the phase-locked loop controller are independent of the inertia response of the energy storage converter.

8. A frequency response characteristic analysis system for an energy storage converter, characterized in that: include: A modeling module, used to establish a small signal model of different controllers in an energy storage converter with virtual inertia control at a DC voltage time scale, and to construct an amplitude-phase motion model of unbalanced power input based on the small signal model; An equivalent inertia extraction module, used to extract an equivalent inertia expression of the energy storage converter based on the amplitude-phase motion model; An analysis module, for drawing a Bode diagram based on the equivalent inertia expression and analyzing the frequency response characteristics of the energy storage converter under different virtual inertia control modes based on the amplitude-phase characteristics of the Bode diagram by changing the controller parameters corresponding to the small signal model and the operating parameters of the energy storage converter; The amplitude of the Bode diagram is used to characterize the equivalent inertia time constant of the energy storage converter, and the phase of the Bode diagram is used to characterize the inertia response speed of the energy storage converter.

9. An electronic device / image signal generator / network device / transmitter / terminal / base station / industrial computer, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program runs on a processor, the processor is caused to execute the method according to any one of claims 1 to 7.

Images