A method for optimizing inertia damping of a cascaded energy storage converter adapted to multi-grid conditions

Abstract

The application relates to grid-connected control technology of a converter and aims to provide a cascade energy storage converter inertia damping optimization method suitable for multiple grid conditions. The method comprises the following main steps: grid-connected system modeling, inertia parameter optimization, damping parameter optimization and parameter design under multiple grid conditions. The inertia and damping parameters are optimized through transmission characteristics and step response characteristics, the dynamic response performance and system stability of the cascade energy storage converter can be effectively improved, and the reliability of the voltage source support of the converter is ensured; through establishment of an optimization parameter library and an optimization parameter curve covering multiple grid strengths, the configuration and debugging process of the system is simplified, the complexity and time requirement of parameter adjustment are reduced, and the adaptability of the system under different grid operation conditions is effectively enhanced.

Description

Technical Field

[0001] This invention relates to the field of converter grid-connected control, and more specifically to an inertial damping optimization method for cascaded energy storage converters that adapts to multiple grid conditions. Background Technology

[0002] With the transformation of the energy structure, new energy power generation such as wind and solar power has developed rapidly. However, due to the inherent intermittency and volatility of new energy power generation, the stability of the power grid faces unprecedented challenges. To address these challenges, large-capacity energy storage technology has become an important means of ensuring grid stability. Among them, cascaded energy storage technology, due to its advantages in single-unit large capacity and direct connection to medium and high voltage, is gradually becoming the mainstream choice for large-capacity energy storage applications. Cascaded energy storage converters actively provide voltage support to the power grid by adopting voltage source control, and represent a potential solution for improving grid stability in the future.

[0003] The Short Circuit Ratio (SCR) is a crucial technical indicator in renewable energy grid-connected systems, describing the ratio of the current during a short circuit to the rated current. Specifically, it is defined as the ratio of the short-circuit current to the rated current when a short circuit occurs on the renewable energy source side. This indicator reflects the renewable energy source's response to grid short-circuit currents and its ability to withstand short-circuit conditions. Accurately understanding and mastering the SCR is of paramount importance in the design and operation of grid-connected systems. The physical meaning of the SCR lies in measuring the system's current-carrying capacity and the range of stable operating conditions. Therefore, it can be used to predict and analyze the grid's performance under different short-circuit conditions, providing theoretical support for subsequent equipment selection and system optimization design.

[0004] The multiple grid conditions described in this invention refer to actual scenarios where the power grid system operates under different short-circuit ratios. To ensure that the cascaded energy storage converter can adapt to changes in the short-circuit ratio of the power grid system and maintain continuous and stable operation, the cascaded energy storage converter needs to have the ability to adjust its operating parameters accordingly.

[0005] Currently, the commonly used voltage source control strategy is the Virtual Synchronous Machine (VSG) control strategy, which achieves grid support and stability by simulating the inertia and damping characteristics of a traditional synchronous machine. However, this technology still has shortcomings in practical applications under multiple grid conditions. Existing inertia and damping parameter design methods often fail to fully consider the specific operating conditions of the grid and the stability margin of the converter. When facing fluctuations under different grid conditions, the adaptability of existing methods is limited, which may lead to a decrease in system stability. Furthermore, existing design methods have not fully optimized the dynamic response characteristics of cascaded energy storage converters, making it difficult for the converters to achieve optimal performance in terms of response speed and accuracy; their dynamic performance still has considerable room for improvement. Although many research institutions have paid sufficient attention to these issues, no effective solutions have yet been publicly reported.

[0006] Therefore, a novel solution is needed to optimize and adjust the inertia and damping parameters of the voltage source type cascaded energy storage converter, enabling the cascaded energy storage converter to more stably support grid operation under multi-grid conditions. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide an inertial damping optimization method for cascaded energy storage converters that is adaptable to multiple power grid conditions.

[0008] To solve the above-mentioned technical problems, the solution of the present invention is:

[0009] A method for optimizing the inertial damping of cascaded energy storage converters to adapt to multiple power grid conditions is provided, comprising the following steps:

[0010] (1) Grid-connected system modeling

[0011] Based on Kirchhoff's laws and small-signal principles, a converter grid-connected system model is established, and the grid-connected system transfer function is derived as a system model for analyzing transfer characteristics and step response.

[0012] (2) Inertial parameter optimization

[0013] The root locus diagram of the grid-connected system is plotted using the transfer function, and an equal damping line is drawn in it. The inertia coefficient corresponding to the intersection of the root locus and the equal damping line is recorded. Then, Bode plot is plotted based on the inertia coefficient and the system model in step (1), and the optimal inertia coefficient is determined based on the phase margin requirement of the grid-connected system.

[0014] (3) Damping parameter optimization

[0015] By combining the system model and the optimal inertia coefficient, step response curves under different damping coefficients are plotted; by analyzing each step response curve and combining the dynamic characteristic requirements of the converter, the maximum damping coefficient of the grid-connected system when meeting the response time and overshoot requirements is obtained, and it is taken as the optimal damping coefficient.

[0016] (4) Parameter design under multiple power grid conditions

[0017] Set the short-circuit ratio adjustment step size and determine multiple short-circuit ratio conditions that gradually increase to the maximum short-circuit ratio; then, under each short-circuit ratio condition, repeat the operation content of steps (1) to (3) to obtain the optimal inertia coefficient and optimal damping coefficient under different power grid strength conditions, and construct a control parameter library; on this basis, perform linear interpolation fitting to obtain the inertia coefficient optimization parameter curve and damping optimization parameter curve under different short-circuit ratio conditions.

[0018] This invention further provides an inertial damping optimization control method for cascaded energy storage converters adapted to multiple grid conditions. Based on the aforementioned method, it further utilizes optimized control parameters to control the cascaded energy storage converters. Specifically, it includes: during the converter's grid connection process, selecting the corresponding inertial coefficient optimization parameter curve and damping optimization parameter curve based on the real-time SCR value of the system grid; then using the control parameters corresponding to each curve to control the operation of the cascaded energy storage converters, thereby enabling the grid-connected system to maintain stability and good dynamic response under various grid conditions.

[0019] This invention also provides a high-voltage direct-connected cascaded energy storage system capable of achieving optimized control of inertial damping. The cascaded energy storage system has a three-phase star topology, with each phase consisting of a filter reactor L. f It is composed of N energy storage modules connected in series; each energy storage module has the same structure, including an H-bridge, a filter circuit, and a series battery cluster as the energy storage power source arranged in sequence; the controller module of the energy storage system includes a processor and a computer-readable storage medium, on which a computer program is stored; when the computer program is executed by the processor, it can implement the optimization method or control method as described above.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0021] (1) By optimizing the inertia and damping parameters through the transmission characteristics and step response characteristics, this invention can effectively improve the dynamic response performance and system stability of the cascaded energy storage converter, and ensure the reliability of the converter voltage source support.

[0022] (2) By establishing an optimization parameter library and optimization parameter curves covering various power grid intensities, this invention simplifies the system configuration and debugging process, reduces the complexity and time requirements of parameter tuning, and effectively enhances the system's adaptability under different power grid operating conditions. Attached Figure Description

[0023] Figure 1 This is a topology diagram of the main circuit of a cascaded energy storage converter grid-connected system.

[0024] Figure 2 This is a flowchart of the inertial damping parameter optimization process.

[0025] Figure 3 These are power step response waveforms obtained using the method of this invention under different power grid conditions. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described clearly and completely below with reference to the accompanying drawings and embodiments. It should be understood that the described embodiments are for illustrative purposes only and not for limiting the scope of the invention. Any modifications or equivalent substitutions made to this invention under the guidance of this invention, or any products similar to this invention derived by combining this invention with other features limited to the technology, all fall within the protection scope of this invention.

[0027] Part One: Implementation Scheme of the Invention

[0028] 1. First, the main circuit of the cascaded energy storage converter grid-connected system described in this invention is as follows: Figure 1 As shown, this cascaded energy storage converter adopts a three-phase star-connected H-bridge structure and has the capability for direct high-voltage connection. This structure's direct high-voltage connection capability helps achieve high efficiency and flexibility, making it suitable for large-capacity applications.

[0029] Specifically, each phase consists of a filter inductor and N energy storage modules connected in series. Each energy storage module has the same structure, including an H-bridge, a filter circuit, and a series-connected battery cluster as the energy storage power source.

[0030] 2. For example Figure 2 As shown, the inertial damping optimization method for cascaded energy storage converters adapted to multiple power grid conditions according to the present invention includes the following steps:

[0031] (1) Grid-connected system modeling

[0032] Based on Kirchhoff's laws and small-signal principles, a converter grid-connected system model is established, and the grid-connected system transfer function is derived as a system model for analyzing transfer characteristics and step response.

[0033] The parameters used in system modeling include grid parameters, converter parameters, and control parameters. Among them, grid parameters include short-circuit ratio, grid voltage, and grid angular frequency; converter parameters include rated power and rated output voltage; and control parameters include inertia coefficient and damping coefficient.

[0034] The transfer function is as follows:

[0035]

[0036] Where G(s) is the transfer function; V0 is the rated output voltage of the converter; V g ω is the grid voltage; SCR is the short-circuit ratio; P0 is the converter rated power; J is the inertia coefficient; ω0 is the grid voltage angular frequency; s is the Laplace operator; D is the damping coefficient.

[0037] (2) Inertial parameter optimization

[0038] The root locus diagram of the grid-connected system is plotted using the transfer function, and an isodamped line is drawn within it. The inertia coefficients corresponding to the intersections of the root locus and the isodamped line are recorded. Then, a Bode plot is plotted based on these inertia coefficients and the system model, and the optimal inertia coefficient is determined based on the phase margin requirements of the grid-connected system. Specifically, this includes:

[0039] First, set the initial damping coefficient D1, and use the transfer function constructed in step (1) to draw the root locus diagram; draw an isodamped line with a specific damping ratio in the root locus diagram, and record the inertia coefficient corresponding to the intersection of the root locus and the isodamped line, denoted as J1; then, draw the Bode diagram according to the inertia coefficient J1 and the system model, and check whether J1 meets the phase margin condition according to the phase margin requirement of the grid-connected system; if the phase margin meets the requirement, then confirm J1 as the optimal inertia coefficient Jx; if the phase margin does not meet the requirement, then gradually reduce the value of the inertia coefficient by 5% until the requirement is met, and take the inertia coefficient J2 at this time as the optimal inertia coefficient Jx.

[0040] (3) Damping parameter optimization

[0041] First, set the damping adjustment step size D0, and gradually increase the damping coefficient from the minimum damping coefficient D1 to the maximum damping coefficient D2. Combining the system model constructed in step (1) and the optimal inertia coefficient Jx in step (2), plot the step response curve for each damping parameter. Then, by analyzing each step response curve and combining it with the dynamic characteristic requirements of the system, obtain the maximum damping coefficient of the grid-connected system when the response time and overshoot requirements are met, and take it as the optimal damping coefficient Dx.

[0042] (4) Parameter design under multiple power grid conditions

[0043] Power grid conditions can be classified into three levels based on the short-circuit ratio (SCR): strong grid (SCR>3), weak grid (3≥SCR>1.5), and extremely weak grid (1.5≥SCR). To accommodate different grid strengths, parameter design is performed using the following methods:

[0044] First, set the short-circuit ratio adjustment step size S0, so that the SCR gradually increases from 1 to the maximum short-circuit ratio SCR. max Determine multiple short-circuit ratio conditions; then, under each short-circuit ratio condition, repeat the operation of steps (1) to (3) to obtain the optimal inertia coefficient and optimal damping coefficient under different power grid strength conditions, and construct a control parameter library; on this basis, perform linear interpolation fitting to obtain the inertia coefficient optimization parameter curve and damping optimization parameter curve under different short-circuit ratio conditions.

[0045] 3. After obtaining the above-mentioned inertia coefficient optimization parameter curves and damping optimization parameter curves, they can be further used to implement an inertial damping optimization control method for cascaded energy storage converters adapted to multi-grid conditions. Specifically, based on the previous optimization method, the optimized control parameters are further used to control the cascaded energy storage converters; including:

[0046] During the grid connection process of the converter, the corresponding inertia coefficient optimization parameter curve and damping optimization parameter curve are selected according to the real-time SCR value of the system grid. Then, the operation of the cascaded energy storage converter is controlled by the control parameters corresponding to each curve, so that the grid-connected system can maintain stability and good dynamic response under various grid conditions.

[0047] This invention employs a virtual synchronous machine control strategy as a voltage source control method. By simulating the inertia and damping characteristics of a traditional synchronous machine, the virtual synchronous machine control strategy can significantly improve the dynamic response capability and stability of the grid-connected system, effectively supporting the frequency and voltage regulation of the power grid, and is particularly suitable for the operational requirements under different grid strengths.

[0048] 4. In the high-voltage direct-connected cascaded energy storage system of the present invention, its controller module includes a processor and a computer-readable storage medium, on which a computer program is stored; when the computer program is executed by the processor, it can implement the optimization method or control method as described above.

[0049] Part Two: A Specific Application Example

[0050] In this example, the circuit topology and control model of the converter grid-connected system are constructed in the PLECS simulation software to verify the specific feasibility and corresponding technical effects of the present invention.

[0051] Figure 1The main circuit topology diagram of the cascaded energy storage converter grid-connected system for this invention adopts a three-phase star-cascaded H-bridge structure. In this example, each phase consists of a filter inductor and 40 energy storage modules connected in series. Each energy storage module has the same structure, including an H-bridge, a filter circuit, and a series-connected battery cluster (composed of 300 cells connected in series, each cell with a rated voltage of 3.2V and a rated capacity of 280Ah) arranged sequentially as the energy storage power source. The operating conditions are set as follows: grid voltage 20.2kV, grid frequency 50Hz, and rated power of the cascaded energy storage converter 10MVA.

[0052] In this example, the control parameter design conditions are set as follows: system phase margin condition is phase margin not less than 20 degrees, damping adjustment step size D0 is 1, initial damping coefficient D1 is 1, maximum damping coefficient D2 is 200, response time requirement is not greater than 500ms, overshoot requirement is not higher than 5%, short-circuit ratio adjustment step size S0 is 0.25, and maximum short-circuit ratio SCRmax is 4.

[0053] Figure 2 This is a flowchart of the inertial damping parameter optimization process of the present invention, and its specific implementation steps are as follows:

[0054] (1) Grid-connected system modeling

[0055] Based on the set grid parameters and cascaded energy storage converter parameters, an overall transfer function model of the grid-connected system is established as a system model for analyzing transfer characteristics and step response.

[0056] By deriving from Kirchhoff's laws and the small-signal modeling method, the transfer function G(s) of the grid-connected system is obtained as follows:

[0057]

[0058] Where G(s) is the transfer function; V0 is the rated output voltage of the converter; V g ω is the grid voltage; SCR is the short-circuit ratio; P0 is the converter rated power; J is the inertia coefficient; ω0 is the grid voltage angular frequency; s is the Laplace operator; D is the damping coefficient.

[0059] (2) Inertial parameter optimization

[0060] Plot the root locus and Bode plot using the transfer function and the initial damping coefficient D1.

[0061] First, determine the inertia coefficient J1 when the damping ratio is 0.707 using the root locus plot. Then, optimize the inertia coefficient based on the phase margin requirement. If J1 satisfies the condition that the phase margin is not less than 20 degrees, the preferred inertia coefficient Jx = J1 is selected; if not, the inertia coefficient is gradually reduced by 5% until the requirement is met. Record the inertia coefficient at this point as J2, and set Jx = J2.

[0062] (3) Damping parameter optimization

[0063] Based on the optimal inertia coefficient Jx, and by setting the damping adjustment step size D0 = 1, the damping coefficient D is gradually increased from 0 to the maximum damping coefficient D2 = 200. Using the optimal inertia coefficient as the basis of the system model, step response curves are plotted for each damping parameter. Considering the dynamic characteristics of the grid-connected system, the maximum damping coefficient that satisfies the converter response time and overshoot requirements is obtained by analyzing each step response curve, and this maximum damping coefficient is taken as the optimal damping coefficient Dx.

[0064] (4) Parameter design under multiple power grid conditions

[0065] The SCR is gradually increased from 1 to the maximum short-circuit ratio SCR using S0 as the step size. max Under each SCR condition, the above optimization steps are repeated to construct a library of inertial and damping control parameters under different grid strength conditions, and the optimized parameter curves are obtained by linear interpolation fitting.

[0066] (5) Control under multiple power grid conditions

[0067] Based on the current SCR value of the power grid, select the corresponding inertia coefficient optimization parameter curve and damping optimization parameter curve; then use the control parameters corresponding to each curve as a voltage source control strategy for virtual synchronous machine control to ensure the stability and dynamic response of the converter under various power grid conditions.

[0068] Figure 3 The power step response waveforms of the method of this invention under different grid strength conditions are shown. The results show that the system can achieve stable operation under different grid operating conditions (SCR = 1.3 and 3.3) and has good dynamic response.

Claims

1. A method for optimizing the inertial damping of cascaded energy storage converters to adapt to multiple power grid conditions, characterized in that, Includes the following steps: (1) Grid-connected system modeling Based on Kirchhoff's laws and small-signal principles, a converter grid-connected system model is established, and the grid-connected system transfer function is derived as a system model for analyzing transfer characteristics and step response. (2) Inertial parameter optimization The root locus diagram of the grid-connected system is plotted using the transfer function, and an equal damping line is drawn in it. The inertia coefficient corresponding to the intersection of the root locus and the equal damping line is recorded. Then, Bode plot is plotted based on the inertia coefficient and the system model in step (1), and the optimal inertia coefficient is determined based on the phase margin requirement of the grid-connected system. (3) Damping parameter optimization By combining the system model and the optimal inertia coefficient, step response curves under different damping coefficients are plotted; by analyzing each step response curve and combining the dynamic characteristic requirements of the converter, the maximum damping coefficient of the grid-connected system when meeting the response time and overshoot requirements is obtained, and it is taken as the optimal damping coefficient. (4) Parameter design under multiple power grid conditions Set the short-circuit ratio adjustment step size and determine multiple short-circuit ratio conditions that gradually increase to the maximum short-circuit ratio; then, under each short-circuit ratio condition, repeat the operation content of steps (1) to (3) to obtain the optimal inertia coefficient and optimal damping coefficient under different power grid strength conditions, and construct a control parameter library; on this basis, perform linear interpolation fitting to obtain the inertia coefficient optimization parameter curve and damping optimization parameter curve under different short-circuit ratio conditions.

2. The method according to claim 1, characterized in that, In step (1), the parameters used in system modeling include grid parameters, converter parameters, and control parameters; among which, grid parameters include short-circuit ratio, grid voltage, and grid angular frequency; converter parameters include rated power and rated output voltage; and control parameters include inertia coefficient and damping coefficient.

3. The method according to claim 1, characterized in that, The transfer function mentioned in step (1) is as follows: Where G(s) is the transfer function; V0 is the rated output voltage of the converter; V g ω is the grid voltage; SCR is the short-circuit ratio; P0 is the converter rated power; J is the inertia coefficient; ω0 is the grid voltage angular frequency; s is the Laplace operator; D is the damping coefficient.

4. The method according to claim 1, characterized in that, Step (2) specifically includes: First, set the initial damping coefficient D1, and use the transfer function of the grid-connected system to draw the root locus diagram; draw an isodamped line with a specific damping ratio in the root locus diagram, and record the inertia coefficient corresponding to the intersection of the root locus and the isodamped line, denoted as J1; Then, Bode plots are drawn based on the inertia coefficient J1 and the system model, and J1 is checked to see if it meets the phase margin requirements of the grid-connected system. If the phase margin meets the requirements, J1 is confirmed as the optimal inertia coefficient. If the phase margin does not meet the requirements, the value of the inertia coefficient is gradually reduced by 5% until the requirements are met, and the inertia coefficient J2 at this time is taken as the optimal inertia coefficient.

5. The method according to claim 1, characterized in that, When plotting the step response curve in step (3), first set the damping adjustment step size and gradually increase the damping coefficient from the minimum damping coefficient to the maximum damping coefficient. Based on the system model and the optimal inertia coefficient, the step response curves for each damping parameter are plotted.

6. The method according to claim 1, characterized in that, The cascaded energy storage converter adopts a star-type cascaded H-bridge structure and has the capability of direct high-voltage connection.

7. A method for optimized inertial damping control of cascaded energy storage converters adaptable to multiple power grid conditions, characterized in that, Based on the method described in any one of claims 1 to 6, the cascaded energy storage converter is further controlled using optimized control parameters; specifically including: During the grid connection process of the converter, the corresponding inertia coefficient optimization parameter curve and damping optimization parameter curve are selected according to the real-time SCR value of the system grid. Then, the operation of the cascaded energy storage converter is controlled by the control parameters corresponding to each curve, so that the grid-connected system can maintain stability and good dynamic response under various grid conditions.

8. The method according to claim 7, characterized in that, This control method employs a virtual synchronous machine control strategy as a voltage source control, possessing the ability to simulate the inertia and damping characteristics of a traditional synchronous machine.

9. A high-voltage direct-connected cascaded energy storage system capable of achieving optimized control of inertial damping, characterized in that, The cascaded energy storage system has a three-phase star topology, with each phase consisting of a filter reactor L. f It consists of N energy storage modules connected in series; each energy storage module has the same structure, including an H-bridge, a filter circuit, and a series battery cluster as the energy storage power source arranged in sequence. The controller module of the energy storage system includes a processor and a computer-readable storage medium, on which a computer program is stored; when the computer program is executed by the processor, it can implement the optimization method or control method as described in any one of claims 1 to 8.

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