A method, system, device and medium for designing a network-constructed SVG control boundary parameter

Abstract

The present application relates to the technical field of new energy power grid, and more particularly to a grid-forming SVG control boundary parameter design method, system, device and medium, comprising: based on small signal analysis method, the harmonic state space model of grid-forming SVG is established;Based on eigenvalue analysis method, the key control parameters of the harmonic state space model are analyzed, and the stable operation condition of the key control parameters of the grid-forming SVG is obtained;Based on the stable operation condition, combined with the grid-forming dynamic support requirement, the boundary constraint frame and parameter design method of the control parameters of the grid-forming SVG are determined;The stability boundary of the key control parameters is quantitatively described by establishing the harmonic state space model of the grid-forming SVG, and on this basis, the control parameter design method under the constraint of grid-forming support performance and stability domain is realized, thereby providing theoretical basis and technical support for the engineering application of the grid-forming SVG in the new energy power system.

Description

Technical Field

[0001] This invention relates to the field of new energy power grid technology, and in particular to a method, system, device and medium for designing control boundary parameters of grid-type SVG. Background Technology

[0002] As the penetration rate of new energy power generation equipment in power systems continues to increase, the equivalent inertia and damping level of power systems have significantly decreased. Against this backdrop, grid-based control technology, due to its voltage source characteristics and designable dynamic support capabilities, is gradually becoming an important means of improving grid stability in new power systems. However, the impact of grid-based control structure and parameter configuration on system dynamic stability is complex, especially under multi-frequency disturbances, where equipment may exhibit significant periodic time-varying characteristics and harmonic coupling effects, thus increasing the difficulty of stability analysis and control design.

[0003] Grid-type static var generators (SVGs), as a typical type of grid-type power electronic equipment, have numerous control parameters that are coupled with each other. When the control parameters are not configured properly, grid-type SVGs may introduce low-damping modes, even leading to a deterioration in system stability. Existing stability analysis methods are mostly based on linear time-invariant models or equivalent impedance models, which have limited ability to characterize the dynamic behavior of grid-type SVGs under multi-harmonic coupling conditions. They also struggle to reveal the quantitative relationship between control parameter variations and system stability boundaries, resulting in the control parameter tuning process relying heavily on engineering experience.

[0004] Furthermore, in scenarios involving weak power grids or high proportions of renewable energy integration, the control parameters of grid-connected SVG not only need to meet the basic requirements of system stability but also need to consider grid support performance and dynamic response characteristics. Due to the lack of a clear quantitative description of the stability boundary of grid-connected SVG control parameters, existing parameter design methods struggle to achieve an effective trade-off between grid support capability and stability margin, making it difficult to guarantee the rationality and robustness of parameter selection.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the present invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The technical problem to be solved by this invention is to provide a method, system, device and medium for designing control boundary parameters of grid-type SVG. By establishing a harmonic state-space model of grid-type SVG, the stability boundary of key control parameters is quantitatively characterized. On this basis, a method for designing control parameters under the constraints of grid support performance and stability domain is realized, thereby providing theoretical basis and technical support for the engineering application of grid-type SVG in new energy power systems.

[0007] To achieve the above objectives, the technical solution adopted by this invention is: a method for designing control boundary parameters of a mesh-based SVG, comprising the following steps: Based on the small signal analysis method, a harmonic state-space model of a network-type SVG is established; Based on eigenvalue analysis, the key control parameters of the harmonic state-space model are analyzed to obtain the stable operating conditions of the key control parameters of the network-type SVG. Based on the stable operating conditions and the requirements for dynamic support of the network structure, the boundary constraint frame and parameter design method for the control parameters of the network-type SVG are determined.

[0008] Furthermore, the harmonic state-space model is established considering the cascaded H-bridge topology, DC voltage synchronization loop, reactive voltage loop, and virtual impedance inner loop.

[0009] Furthermore, the establishment of the harmonic state-space model of the network-type SVG includes the following steps: Based on the grid-connected SVG star-cascaded H-bridge topology, a harmonic state-space model is established, which includes the three-phase grid-connected side voltage and current, the DC side voltage of each link, and the three-phase modulation signal power circuit. Based on the grid-type SVG power control structure, a harmonic state-space model including reactive voltage control loop and inner loop control quantity is established. Based on the grid-type SVG DC voltage synchronization control mechanism, a harmonic state-space model describing the phase relationship between DC voltage disturbance and output voltage is established.

[0010] Furthermore, based on coordinate transformation relationships, the power circuit harmonic state-space model in the dq coordinate system and the power control harmonic state-space model in the ABC three-phase coordinate system are combined to establish a unified HSS model for the network-type SVG. The expression is: ; In the formula, , These are the state variable vector and input vector variables of the unified HSS model for the network-type SVG; , These are the state coefficient matrix and input coefficient matrix of the network-type SVG unified HSS model, respectively.

[0011] Furthermore, the key control parameters of the network-type SVG include the DC voltage droop coefficient. reactive voltage inertia coefficient Virtual resistance and virtual inductance .

[0012] Furthermore, the analysis of key control parameters of the harmonic state-space model based on eigenvalue analysis includes the following steps: For the state coefficient matrix Eigenvalues ​​are solved to construct the system characteristic equations and obtain the eigenvalue distribution of the network-type SVG under different control parameter conditions. Analyze the variation law of the real part of the eigenvalues ​​to determine the stability criterion of the small signal of the system. When the real part of all eigenvalues ​​is less than zero, the system is determined to be in a stable operating state.

[0013] Furthermore, obtaining the stable operating conditions for the key control parameters of the network-type SVG includes the following steps: Single parameter variation analysis was performed on the key control parameters of the network-type SVG. When analyzing any key control parameter, keep the other key control parameters at their rated design values ​​and continuously adjust or incrementally scan the target key control parameter. Under each parameter value, the state coefficient matrix is ​​recalculated based on the unified harmonic state-space model. The eigenvalues ​​are obtained, and the evolution trajectory of the real part of the eigenvalues ​​as a function of the parameter is obtained. Determine the stability boundary range of each key control parameter and establish the stability interval of each parameter. Based on the single-parameter stability interval, the feasible region constraint of the key control parameters is constructed and determined as the stable operating condition.

[0014] Furthermore, the step of constructing feasible region constraints for key control parameters based on the single-parameter stability interval and determining them as the stable operating conditions includes the following steps: A multi-parameter coupled stability domain is constructed, and eigenvalue joint analysis is performed under the condition that multiple key control parameters change simultaneously. The stable and feasible region formed by combining all parameters that satisfy the small-signal stability criterion in the multi-dimensional parameter space is defined as the multi-parameter coupling stability domain of the network-type SVG; Extracting the boundary surface of the stability domain provides feasible domain constraints for the collaborative optimization design of key control parameters.

[0015] Furthermore, based on the droop characteristic constraints of the control parameters of the mesh-type SVG, the boundary constraint box of the control parameters of the mesh-type SVG is determined, including the following steps: Determine the DC voltage droop factor The proportional relationship between DC-side voltage deviation and output voltage amplitude, and the reactive voltage inertia coefficient. The dynamic adjustment relationship between reactive power changes and AC side voltage amplitude changes; Establish a droop control function expression that includes voltage deviation, reactive power disturbance and corresponding regulation output, and construct a mathematical model of droop characteristics; Based on the grid operation specifications and dynamic voltage support capability requirements, the slope range and adjustment sensitivity range of the curve corresponding to the droop characteristic mathematical model are limited to obtain a set of parameter constraints that meet the voltage support performance requirements. The set of drooping characteristic constraints is mapped to the multi-parameter coupled stability domain to determine the boundary constraint box of the dual-constraint integrated design of key control parameters.

[0016] Furthermore, the dynamic support requirements for the network structure are determined through the small-signal transfer function of the network-type SVG, including the following steps: Based on the small-signal transfer function of the network SVG, and according to the preset dynamic support performance index, the range of the real part of the closed-loop poles and the damping ratio is limited to determine the control parameter constraint region that meets the dynamic performance requirements. The control parameter constraint region is determined to be a performance boundary condition independent of the harmonic state space stability domain.

[0017] Furthermore, the parameter design method for determining the control parameters of the network-type SVG is based on the construction of a multi-parameter coupled stability domain combined with the control parameter constraint region to perform dual-constraint comprehensive parameter design.

[0018] Furthermore, the dual-constraint synthesis parameter design includes the following steps: An intersection operation is performed on the multi-parameter coupled stability domain and the network control performance constraint region to determine the control parameter design region that simultaneously satisfies the requirements of stability, droop characteristics and dynamic performance. The final network SVG control parameters are then determined within the control parameter design region.

[0019] This invention also provides a network-based SVG control boundary parameter design system, comprising: The model building unit is used to establish a harmonic state-space model of a network-type SVG based on the small-signal analysis method. The stability domain analysis unit is used to analyze the key control parameters of the harmonic state space model based on the eigenvalue analysis method, and obtain the stable operating conditions of the key control parameters of the network-type SVG. The constraint analysis and parameter design unit is used to determine the boundary constraint frame and parameter design method of the control parameters of the network-type SVG based on the stable operating conditions and the requirements of the network dynamic support.

[0020] The present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the mesh-type SVG control boundary parameter design method as described above.

[0021] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the network-type SVG control boundary parameter design method as described above.

[0022] The beneficial effects of this invention are as follows: Based on the harmonic state-space model and the dual-path analysis method of network control requirements, this invention realizes the quantitative expression of the stability boundary of key control parameters of network-type SVG, and can systematically reveal the coupling influence relationship between DC voltage droop coefficient, reactive voltage inertia coefficient and virtual impedance parameter; under the dual constraints of stability domain and network control performance, the invention completes parameter collaborative design, avoids the stability uncertainty problem caused by traditional empirical tuning methods, improves the stable operation capability, voltage support capability and dynamic response performance of network-type SVG, and has good engineering application value. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the method for designing control boundary parameters for a mesh-type SVG in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the mesh-type SVG control boundary parameter design system in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the mesh-type SVG star-cascaded H-bridge topology in an embodiment of the present invention; Figure 4 This is a control block diagram of a mesh-type SVG in an embodiment of the present invention; Figure 5 This is a block diagram of the harmonic state-space model of the mesh-type SVG in an embodiment of the present invention; Figure 6 The voltage and current characteristic curves of the network-type SVG harmonic state-space model in this embodiment of the invention are shown. Figure 7 This is a complete curve showing the variation of the characteristic value of the DC voltage droop coefficient of the grid-type SVG in this embodiment of the invention; Figure 8 This is a near-imaginary axis curve showing the variation of the characteristic value of the DC voltage droop coefficient of the grid-type SVG in this embodiment of the invention; Figure 9 The above is the frequency response curve of the mesh-type SVG in an embodiment of the present invention; Figure 10 This is the average DC-side voltage curve of a single-chain SVG in a case embodiment of the present invention; Figure 11 This is a verification diagram of the reactive power droop characteristics and dynamic characteristics of the SVG network in the embodiment of the present invention; Figure 12 This is a three-dimensional diagram of the stability domain of key parameters for network construction in an embodiment of the present invention. Figure 13 This is a planar diagram showing the design range of key parameters for network construction in an embodiment of the present invention. Figure 14 This is a schematic diagram of the structure of a computer electronic device in an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0026] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0028] like Figures 1 to 14 The illustrated method for designing control boundary parameters for a mesh-based SVG includes the following steps: Based on the small signal analysis method, a harmonic state-space model of a network-type SVG is established; Based on eigenvalue analysis, the key control parameters of the harmonic state-space model are analyzed to obtain the stable operating conditions of the key control parameters of the network-type SVG. Based on stable operating conditions and the requirements for dynamic support of the network structure, the boundary constraint frame and parameter design method for the control parameters of the network-type SVG are determined.

[0029] This invention, based on a harmonic state-space model and a dual-path analysis method for network control requirements, achieves a quantitative expression of the stability boundary of key control parameters for network-type SVG. It can systematically reveal the coupling influence relationship between DC voltage droop coefficient, reactive voltage inertia coefficient, and virtual impedance parameters. Under the dual constraints of stability domain and network control performance, it completes parameter collaborative design, avoiding the stability uncertainty problem caused by traditional empirical tuning methods, and improving the stable operation capability, voltage support capability, and dynamic response performance of network-type SVG, thus having good engineering application value.

[0030] Based on the above embodiments, a harmonic state-space model is established considering the cascaded H-bridge topology, DC voltage synchronization loop, reactive voltage loop, and virtual impedance inner loop.

[0031] The power circuit and control block diagram of the grid-type SVG based on DC voltage synchronous control are as follows: Figure 3 , Figure 4 As shown, the SVG establishes a connection between the DC-side capacitor voltage Vdc and the grid frequency through DC voltage synchronization control, achieving phase angle synchronization. Compared with grid-connected SVGs, this synchronization method functionally replaces the phase-locked loop and global voltage equalization loop, and simplifies the control structure. Reactive power droop control dynamically adjusts the voltage amplitude at the grid connection point through the voltage droop coefficient Kut, thereby controlling the reactive power output of the SVG. The virtual impedances Rv and Lv can be approximately equivalent to series inductance before the filter, limiting the current output of the SVG and providing damping for the converter, enabling stable operation of the grid-connected SVG in multiple scenarios. The phase-to-phase voltage equalization control loop performs voltage equalization control on the average value of the three-phase DC-side voltages.

[0032] Based on the above embodiments, a harmonic state-space model of a network-type SVG is established, including the following steps: Based on the grid-connected SVG star-cascaded H-bridge topology, a harmonic state-space model is established, which includes the three-phase grid-connected side voltage and current, the DC side voltage of each link, and the three-phase modulation signal power circuit. Based on the grid-type SVG power control structure, a harmonic state-space model including reactive voltage control loop and inner loop control quantity is established. Based on the grid-type SVG DC voltage synchronization control mechanism, a harmonic state-space model describing the phase relationship between DC voltage disturbance and output voltage is established.

[0033] Specifically, small-signal analysis is performed on the SVG-averaged model of the star-cascaded H-bridge topology, and the modeling principle of HSS is as follows: (1) In the formula, 0 in the subscript represents the initial state of the state variable, and ∆ represents the small signal change of the corresponding variable. , , These are vector forms of the changes in grid connection point voltage, input current, and modulation signal, respectively. for Vector form of phase DC voltage change; It is a 7th order identity matrix; for ; The rated angular frequency of the power grid; This indicates a Toplitz transformation of the steady-state signal.

[0034] definition , These are the state variable vector and input variable vector of the SVG main circuit, respectively, and their column vectors are respectively... (2) (3) Rearranging formula (1) into the form of a harmonic state-space model, we have: (4) In the formula , These are the 42nd order state coefficient matrix and input coefficient matrix of the SVG main circuit section, respectively. The specific matrices are as follows: (5) (6) In the formula, E represents a 7th-order identity matrix, and "0" in the matrix indicates a 7th-order zero matrix. The correlation coefficient matrix... , , and They are respectively , , and .

[0035] Grid-based SVG power control primarily relies on reactive power droop control to obtain a reference level for reactive power control and grid-connected voltage amplitude regulation. Ultimately, the inner loop generates a modulation signal. The time-domain expression of the power control stage is as follows: (7) in , , , The vector forms of the d-axis and q-axis components of the grid-connected voltage and the output voltage, respectively. , The vector forms of the d-axis and q-axis components of the PWM modulation signal change. and These are reactive power reference and voltage amplitude reference, respectively. This refers to the change in output voltage of the reactive voltage loop. and These are virtual resistance and virtual inductance, respectively.

[0036] Define the state variable vector and input vector variables as follows: (8) in , , This refers to the state variable vector, input vector vector, and output variable vector of the SVG power control section; specifically, it can be set as follows: It is a 7×1 order vector. It is a 42×1 order vector. It is a 14×1 order vector.

[0037] The HSS model of the SVG power control part of formula (8) is as follows: (9) , , , The state coefficient matrix, input coefficient matrix, output coefficient matrix, and correlation coefficient matrix of the SVG power control section are organized into the following specific matrices: (10) In the formula, the correlation coefficient matrix , , , , and They are respectively , , , , and .

[0038] The harmonic state-space model of the power circuit is derived in a three-phase coordinate system, therefore, coordinate transformation is needed to link the two. According to Figure 4 The block diagram of DC voltage synchronization control, and the steady-state time-domain small-signal expression for the phase angle are as follows: (11) In the formula The gain of the DC loop control circuit; , , These are the average values ​​of the DC-side voltages of all three-phase submodules; This represents the change in phase angle.

[0039] By rearranging formula (11), the harmonic state-space model of the network-type SVG synchronization element can be derived as follows: (12) In the formula . , The state coefficient matrix and input coefficient matrix of the SVG synchronous control section are organized into the following specific matrices: (13) Based on the above embodiments, the coordinate transformation relationship between the harmonic state-space model vectors of the power circuit, main power control, and synchronization control is clarified, and a system is established. Figure 5 The flowchart shown illustrates the vector derivation process. Based on coordinate transformation relationships, it combines the power circuit harmonic state-space model in the dq coordinate system and the power control harmonic state-space model in the ABC three-phase coordinate system to establish a unified HSS model for the network-type SVG. The expression is: (14); In the formula, , These are the state variable vector and input vector variables of the unified HSS model for the network-type SVG; , These are the state coefficient matrix and input coefficient matrix of the network-type SVG unified HSS model, respectively.

[0040] In the formula (15) in, for Transform the Toplitz matrix, for Transform the Toplitz matrix, for The Topplitz transform matrix of the extra component caused by the phase angle small signal; for The left half of the matrix, for The right half of the matrix; for The left 14 columns of the matrix form a submatrix. for The middle 14 columns of the matrix form a submatrix. for The right 14 columns of the matrix form a submatrix. for The left 14 columns of the matrix form a submatrix; It is a zero matrix; It is a 21×7 matrix formed by the Toplitz expansion of the three-phase current steady-state vectors.

[0041] Based on the above embodiments, the key control parameters of the network-type SVG include the DC voltage droop coefficient. reactive voltage inertia coefficient Virtual resistance and virtual inductance .

[0042] Based on the above embodiments, the key control parameters of the harmonic state-space model are analyzed using eigenvalue analysis, including the following steps: For the state coefficient matrix Eigenvalues ​​are solved to construct the system characteristic equations and obtain the eigenvalue distribution of the network-type SVG under different control parameter conditions. Analyze the variation law of the real part of the eigenvalues ​​to determine the stability criterion of the small signal of the system. When the real part of all eigenvalues ​​is less than zero, the system is determined to be in a stable operating state.

[0043] Based on the above embodiments, the stable operating conditions of key control parameters of the network-type SVG are obtained, including the following steps: Single parameter variation analysis was performed on the key control parameters of the network-type SVG. When analyzing any key control parameter, keep the other key control parameters at their rated design values ​​and continuously adjust or incrementally scan the target key control parameter. Under each parameter value, the state coefficient matrix is ​​recalculated based on the unified harmonic state-space model. The eigenvalues ​​are obtained, and the evolution trajectory of the real part of the eigenvalues ​​as a function of the parameter is obtained. Determine the stability boundary range of each key control parameter and establish the stability interval of each parameter. Based on the single-parameter stability interval, feasible region constraints for key control parameters are constructed and determined as stable operating conditions.

[0044] Specifically, the eigenvalues ​​of the Asvg matrix of the unified harmonic state-space small-signal model based on the cascaded H-bridge network-type SVG can be used to analyze the impact of power circuit parameters (such as DC-side capacitors and filter parameters) and control loop parameters (such as network control parameters and virtual impedance parameters) on system stability. The focus is on network control strategies based on DC voltage synchronization, with stability analysis conducted around DC voltage droop parameters, reactive voltage control loop inertia coefficients, and virtual impedance inner loop control parameters.

[0045] In the stability analysis process, the single parameter variation analysis method is first adopted. Under the condition of keeping other parameters unchanged, the eigenvalues ​​of the DC voltage droop coefficient, the reactive voltage control loop inertia coefficient, and the virtual impedance inner loop control parameters are calculated respectively. The migration trajectory of the real part of the eigenvalue with the parameter variation is tracked to determine the stability critical boundary and safe operating range of each key parameter.

[0046] To further consider the dynamic coupling effect between control parameters, multi-parameter joint analysis is carried out. A mapping relationship between parameter combinations and eigenvalue distribution is constructed in the multi-dimensional parameter space to form a multi-parameter coupled stability region that satisfies the condition that the real part of all eigenvalues ​​is less than zero.

[0047] Based on the above embodiments, feasible region constraints for key control parameters are constructed based on the single-parameter stability interval and determined as stable operating conditions, including the following steps: A multi-parameter coupled stability domain is constructed, and eigenvalue joint analysis is performed under the condition that multiple key control parameters change simultaneously. The stable and feasible region formed by combining all parameters that satisfy the small-signal stability criterion in the multi-dimensional parameter space is defined as the multi-parameter coupling stability domain of the network-type SVG; Extracting the boundary surface of the stability domain provides feasible domain constraints for the collaborative optimization design of key control parameters.

[0048] Based on the above embodiments, the boundary constraint box of the control parameters of the mesh-type SVG is determined based on the droop characteristic constraint of the control parameters, including the following steps: Determine the DC voltage droop factor The proportional relationship between DC-side voltage deviation and output voltage amplitude, and the reactive voltage inertia coefficient. The dynamic adjustment relationship between reactive power changes and AC side voltage amplitude changes; Establish a droop control function expression that includes voltage deviation, reactive power disturbance and corresponding regulation output, and construct a mathematical model of droop characteristics; Based on the grid operation specifications and dynamic voltage support capability requirements, the slope range and adjustment sensitivity range of the curve corresponding to the droop characteristic mathematical model are limited to obtain a set of parameter constraints that meet the voltage support performance requirements. By mapping the drooping characteristic constraint set to the multi-parameter coupled stability domain, the boundary constraint box of the dual-constraint integrated design of key control parameters is determined.

[0049] Specifically, the parameter range defined based on the droop relationship constraint includes the DC voltage droop coefficient. and reactive voltage droop coefficient .

[0050] The DC voltage droop factor approximates the droop characteristic of DC-side voltage with respect to grid frequency; that is, a 1% change in grid frequency results in approximately a K% change in DC-side voltage. The relationship is expressed as follows: (16); In the formula DC side voltage The power grid frequency; The voltage droop factor determines the correction relationship between the voltage at point PCC and the reactive power given, and the relationship expression is: (17); In the formula This is the rated reactive power output. This represents the maximum amplitude of the grid voltage.

[0051] DC voltage synchronization control is similar to droop control commonly used in grid-connected converters. The DC voltage droop coefficient approximately simulates the droop characteristics of the DC-side voltage and the grid frequency; that is, a 1% change in grid frequency results in approximately a K% change in DC-side voltage. Ordinary SVGs have limited DC-side energy storage; if the K value is small, the system recovery time will be prolonged. Conversely, if the K value is too large, it will lead to significant DC-side voltage fluctuations; excessively low frequencies will cause system saturation, while excessively high frequencies will exceed the DC-side withstand voltage. Grid standards require that the frequency deviation of the power system during normal operation should not exceed ±0.2 Hz, and for isolated grids, the frequency deviation is allowed to not exceed ±0.5 Hz. Simultaneously, the sum of the DC-side voltages of a single link in the SVG should not be less than the amplitude of the single-phase voltage connected to the grid under normal operating conditions. For a typical SVG connected to 35 kV, 36 modules are selected on the DC side, with a rated DC-side voltage of 1000 V per module. Taking this scenario as an example, the DC-side voltage of a single link can drop to the phase voltage amplitude at its lowest, considering a 1.2 times DC-side voltage margin.

[0052] (18) In the formula, This represents the change in DC-side voltage. This refers to the change in power grid frequency. This is the lowest permissible voltage limit on the DC side; This is the DC-side reference voltage; The minimum operating frequency allowed by the power grid; The rated operating frequency of the power grid.

[0053] The reactive power droop control loop mainly involves the voltage droop coefficient Kut and the reactive power inertia coefficient Kq. The voltage droop coefficient determines the correction relationship between the PCC point voltage and the reactive power setpoint. It is typically designed so that a 10% change in the PCC point voltage amplitude corresponds to a 100% change in reactive power output. In per-unit calculations, if the rated single-phase voltage amplitude and rated single-phase current amplitude are selected as per-unit coefficients, the rated reactive power calculation result is 1.5. Combining the reactive power-voltage regulation quantitative relationship, the corresponding mathematical expression is: (19); Based on the above embodiments, the dynamic support requirements for network construction are determined through the small-signal transfer function of the network-type SVG, including the following steps: Based on the small-signal transfer function of the network SVG, and according to the preset dynamic support performance index, the range of the real part of the closed-loop poles and the damping ratio is limited to determine the control parameter constraint region that meets the dynamic performance requirements. The control parameter constraint region is determined to be a performance boundary condition independent of the harmonic state space stability domain.

[0054] Specifically, reactive voltage droop inertia coefficient The main factor determining the response speed of SVG reactive power compensation is the establishment of a small-signal reactive voltage model for grid-type SVG. The relevant expressions are: (20); In the formula This is the actual reactive small signal. For small-signal AC side voltage; This refers to the phase voltage amplitude of the power grid. It is the sum of the grid-side inductance and reactance and the grid impedance.

[0055] Equation (20) shows that the reactive power loop is a typical first-order element with a time constant. This time constant reflects the inertia of the grid-type SVG simulated excitation system. The "Grid Operation Standard" stipulates that the response time of grid voltage regulation should be significantly shorter than the system frequency regulation time, the response time of SVG participating in grid voltage regulation should be within 0.2 seconds, and the cutoff frequency of the reactive power loop should be less than 10 Hz. From this, the constraints on the reactive power voltage inertia coefficient can be obtained: (twenty one) Based on the constructed multi-parameter coupled stability domain, a parameter design method is formed under the dual constraints of stability domain and dynamic performance.

[0056] Based on the above embodiments, the parameter design method for determining the control parameters of the network-type SVG is based on the construction of a multi-parameter coupled stability domain combined with the control parameter constraint region to perform dual-constraint comprehensive parameter design.

[0057] Based on the above embodiments, the dual-constraint synthesis parameter design includes the following steps: The intersection operation of the multi-parameter coupled stability domain and the network control performance constraint region is performed to determine the control parameter design region that simultaneously satisfies the requirements of stability, droop characteristics and dynamic performance. The final network SVG control parameters are then determined within the control parameter design region.

[0058] Specifically, firstly, based on the eigenvalue analysis of the harmonic state-space model, a multi-parameter stability region satisfying the small-signal stability criterion is obtained, clarifying the stable operating boundary of the control parameters; secondly, based on the small-signal closed-loop transfer function of the network control, a mapping relationship between dynamic performance indicators and control parameters is established, obtaining a dynamic performance constraint region that meets the requirements of response speed and voltage support capability; finally, the intersection operation of the stability region and the dynamic performance constraint region is performed to obtain a comprehensive feasible parameter region that simultaneously meets the requirements of stability and dynamic support, and within this region, the collaborative optimization design of the DC voltage droop coefficient, reactive voltage inertia coefficient, and virtual impedance parameters is completed, realizing the quantitative and systematic tuning of the network-type SVG control parameters.

[0059] like Figure 2 As shown, the present invention also provides a control boundary parameter design system for a network-type SVG, comprising: The model building unit is used to establish a harmonic state-space model of a network-type SVG based on the small-signal analysis method. The stability domain analysis unit is used to analyze the key control parameters of the harmonic state-space model based on the eigenvalue analysis method, and obtain the stable operating conditions of the key control parameters of the network-type SVG. The constraint analysis and parameter design unit is used to determine the boundary constraint frame and parameter design method of the control parameters of the network-type SVG based on stable operating conditions and the requirements of network dynamic support.

[0060] This system establishes a unified harmonic state-space model for a grid-type SVG, performs small-signal linearization on the system, and forms a state-space expression. By solving the eigenvalues ​​of the state coefficient matrix, a small-signal stability criterion is constructed. Further, single-parameter and multi-parameter coupling analyses are conducted to quantify the stability boundaries of the DC voltage droop coefficient, reactive voltage inertia coefficient, and virtual impedance parameters, forming a multi-parameter coupled stability domain. A mathematical model of grid-type control droop is established to clarify the functional relationship between voltage and power regulation and determine the parameter range that meets voltage support requirements. Simultaneously, a small-signal closed-loop transfer function model is constructed to derive the mapping relationship between system poles and control parameters, forming a dynamic performance constraint region that meets damping ratio and dynamic response time requirements. Through comprehensive analysis of the stability domain and the control performance constraint region, a comprehensive feasible region that meets stability, droop characteristics, and dynamic performance requirements is determined through parameter set intersection operations. Within this region, the optimal selection of control parameters is completed, achieving collaborative design and boundary quantification of key parameters for the grid-type SVG. This avoids the stability uncertainty problems caused by traditional empirical tuning methods and improves the stable operation capability, voltage support capability, and dynamic response performance of the grid-type SVG.

[0061] This embodiment provides a method for quantizing control boundaries and designing parameters of a meshed SVG based on a harmonic state-space model, and performs parameter design and verification for a 10Mvar meshed SVG.

[0062] Table 1 shows the relevant parameters for mesh-type SVG.

[0063] Table 1

[0064] 1. Derivation of the harmonic state-space model of the network-type SVG; The unified HSS model for mesh-based SVG is represented as follows: (twenty two) Considering the parameters in Table 1, the voltage and current characteristic curves of a 10Mvar grid-connected SVG can be plotted. Based on the Matlab / Simulink simulation model, a small voltage signal is injected at the measurement point, and the small current signal at the corresponding frequency at the grid connection point is measured. Frequency sweep verification is performed, and the voltage and current characteristic curves of the unified HSS model of the 10Mvar grid-connected SVG are shown below. Figure 6 As shown. Aggregated impedance and analysis of integrated network-type SVG wind field; Eigenvalue analysis was performed on the DC voltage droop coefficient, based on... Figure 7From the complete root locus curve, it can be observed that the eigenvalues ​​of matrix A can be divided into two categories: one type consists of eigenvalues ​​far from the imaginary axis, which are less affected by control parameters and have a very weak impact on stability, and their influence can be ignored; the other type consists of eigenvalues ​​close to the imaginary axis, which are susceptible to the influence of control parameters, causing the eigenvalue curve to extend into the positive half-plane and leading to system instability. Figure 8 Provide a magnified view of the eigenvalue locus for this type of feature root. From Figure 8 As can be seen, the stability of mesh-type SVG is mainly affected by the root locus defined by the frame lines. As the value continues to rise, the eigenvalue maintains a rightward shift. When the value is greater than 12.8, the real part of the eigenvalue is greater than 0, at which point the system becomes unstable. In summary, in... Stability constraint boundary conditions can be satisfied within the range of <12.8.

[0065] 2. SVG network construction control function; Corresponding changes in the average DC-side voltage of the submodule The droop characteristic is essentially based on AC-side frequency information to achieve the SVG inertial response. This example simulates and verifies the dynamic response characteristics of the grid-type SVG under a grid frequency drop of 0.5 Hz. The response waveform is shown below. Figure 9 and Figure 10 As shown in the figure. The simulation results show that the frequency response of the SVG has a linear relationship with the average value of the DC side voltage of the SVG. When the grid frequency decreases by 1%, the DC side voltage decreases by 10%, which is consistent with the DC voltage droop coefficient, and the grid-type SVG operates stably.

[0066] Voltage droop coefficient =15 indicates that a 10% change in the voltage amplitude at the PCC point corresponds to a 100% change in reactive power output. Figure 11 The paper presents the response curve of the grid-type SVG under the scenario of a 10% drop in grid voltage. As shown in the figure, after the grid voltage drops, the SVG completes the reactive power output response within 0.15s, and the reactive power output doubles. The relevant parameter design meets the requirements of the "Grid Operation Standard" for dynamic reactive power response, further verifying the effectiveness of the reactive power-voltage droop control characteristics.

[0067] Based on the dual constraints of stability region and grid-based control, taking key grid-based control as an example, the DC voltage droop coefficient K and the reactive voltage control loop inertia coefficient are... All parameters significantly affect the eigenvalue trajectories of the HSS model's state matrix and jointly determine the stable operating characteristics of the network-based SVG. When any one parameter changes, the feasible value range constraints of the other parameter may change. Therefore, it is necessary to consider all factors comprehensively. and Based on the interaction, the stable operating domain of the SVG network construction control parameters is determined. Keeping other parameters constant, and considering the droop characteristics and dynamic response characteristics, the control boundaries and stability domains of the key network construction control parameters are plotted as follows: Figure 12 and Figure 13 As shown, the x and y axes represent the network control parameters, respectively. and The z-axis represents the real part value of the largest eigenvalue of the ASVG of the HSS model under the change of the set of network control parameters. When the value is greater than 0, it means that the eigenvalue falls into the right half plane under this set of parameters, and the system is unstable. The intersection of this three-dimensional plane and the z=0 plane is the control boundary, and the area below the z=0 plane is the stability region. Figure 11 The value in the figure represents the stability region of the key parameters of the 3D mesh, and the region below the z=0 plane is the stability region. Figure 13 As shown in the diagram, the purple area represents the stability region considering the network parameters K and Kq of the 10Mvar cascaded H-bridge SVG. It can be seen that... and The two parameters are mutually restrictive; when one parameter increases, the stable range of the other parameter will continuously shrink. Combining droop characteristics and response speed, the parameter value range is defined, and the rated parameter... =10 and =20 is reasonable.

[0068] like Figure 14 As shown, the present invention also provides a computer device 400, including a processor 410, a memory 420, and a computer program stored in the memory 420 and executable on the processor 410. When the processor 410 executes the program, it implements the above-mentioned steps of the control boundary parameter design method for the network-type SVG, including: establishing a harmonic state-space model of the network-type SVG based on the small-signal analysis method; analyzing the key control parameters of the harmonic state-space model based on the eigenvalue analysis method to obtain the stable operating conditions of the key control parameters of the network-type SVG; and determining the boundary constraint frame and parameter design method of the control parameters of the network-type SVG based on the stable operating conditions and in combination with the network dynamic support requirements.

[0069] The present invention also provides a computer-readable storage medium 430, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the above-described method for designing control boundary parameters of a network-type SVG, including: establishing a harmonic state-space model of a network-type SVG based on a small-signal analysis method; analyzing the key control parameters of the harmonic state-space model based on eigenvalue analysis to obtain stable operating conditions for the key control parameters of the network-type SVG; and determining the boundary constraint frame and parameter design method for the control parameters of the network-type SVG based on the stable operating conditions and in conjunction with the dynamic support requirements of the network.

[0070] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. "A plurality of" means two or more, unless otherwise explicitly specified.

[0071] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0072] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0073] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0075] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0076] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0077] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for designing control boundary parameters for a mesh-based SVG, characterized in that, Includes the following steps: Based on the small signal analysis method, a harmonic state-space model of a network-type SVG is established; Based on eigenvalue analysis, the key control parameters of the harmonic state-space model are analyzed to obtain the stable operating conditions of the key control parameters of the network-type SVG. Based on the stable operating conditions and combined with the dynamic support requirements of the network structure, the boundary constraint box and parameter design method of the control parameters of the network-type SVG are determined. The parameter design method includes: Based on the eigenvalue analysis of the harmonic state-space model, a multi-parameter stability domain that satisfies the small-signal stability criterion is obtained, and the stable operating boundary of the control parameters is clarified. Based on the small-signal closed-loop transfer function of the network control, a mapping relationship between dynamic performance indicators and control parameters is established to obtain the dynamic performance constraint region that meets the requirements of response speed and voltage support capability. By performing an intersection operation on the stable region and the dynamic performance constraint region, a comprehensive feasible parameter region that simultaneously satisfies the requirements of stability and dynamic support is obtained. Within this region, the coordinated optimization design of the DC voltage droop coefficient, reactive voltage inertia coefficient, and virtual impedance parameters is completed, thereby realizing the quantitative and systematic tuning of the control parameters of the grid-type SVG.

2. The method for designing control boundary parameters of a mesh-type SVG according to claim 1, characterized in that, The harmonic state-space model is established considering the cascaded H-bridge topology, DC voltage synchronization loop, reactive voltage loop, and virtual impedance inner loop.

3. The method for designing control boundary parameters of a mesh-type SVG according to claim 2, characterized in that, The establishment of the harmonic state-space model of the network-type SVG includes the following steps: Based on the grid-connected SVG star-cascaded H-bridge topology, a harmonic state-space model is established, which includes the three-phase grid-connected side voltage and current, the DC side voltage of each link, and the three-phase modulation signal power circuit. Based on the grid-type SVG power control structure, a harmonic state-space model including reactive voltage control loop and inner loop control quantity is established. Based on the grid-type SVG DC voltage synchronization control mechanism, a harmonic state-space model describing the relationship between DC voltage disturbance and output voltage phase is established.

4. The method for designing control boundary parameters of a mesh-type SVG according to claim 3, characterized in that, The establishment of the harmonic state-space model of the network-type SVG also includes the following steps: Based on coordinate transformation relationships, the power circuit harmonic state-space model in the dq coordinate system and the power control harmonic state-space model in the ABC three-phase coordinate system are combined to establish a unified HSS model for the network-type SVG. The expression is: ； In the formula, , These are the state variable vector and input vector variables of the unified HSS model for the network-type SVG; , These are the state coefficient matrix and input coefficient matrix of the network-type SVG unified HSS model, respectively.

5. The method for designing control boundary parameters of a mesh-type SVG according to claim 1, characterized in that, The key control parameters of the network-type SVG include the DC voltage droop coefficient. reactive voltage inertia coefficient Virtual resistance and virtual inductance .

6. The method for designing control boundary parameters of a mesh-type SVG according to claim 5, characterized in that, The analysis of key control parameters of the harmonic state-space model based on eigenvalue analysis includes the following steps: For the state coefficient matrix Eigenvalues ​​are solved to construct the system characteristic equations and obtain the eigenvalue distribution of the network-type SVG under different control parameter conditions. Analyze the variation law of the real part of the eigenvalues ​​to determine the stability criterion of the small signal of the system. When the real part of all eigenvalues ​​is less than zero, the system is determined to be in a stable operating state.

7. The method for designing control boundary parameters of a mesh-type SVG according to claim 6, characterized in that, The stable operating conditions for obtaining the key control parameters of the network-type SVG include the following steps: Single parameter variation analysis was performed on the key control parameters of the network-type SVG. When analyzing any key control parameter, keep the other key control parameters at their rated design values ​​and continuously adjust or incrementally scan the target key control parameter. Under each parameter value, the state coefficient matrix is ​​recalculated based on the unified harmonic state-space model. The eigenvalues ​​are obtained, and the evolution trajectory of the real part of the eigenvalues ​​as a function of the parameter is obtained. Determine the stability boundary range of each key control parameter and establish the stability interval of each parameter. Based on the single-parameter stability interval, the feasible region constraint of the key control parameters is constructed and determined as the stable operating condition.

8. The method for designing control boundary parameters of a mesh-type SVG according to claim 7, characterized in that, The process of constructing feasible region constraints for key control parameters based on the single-parameter stability interval, and determining them as the stable operating conditions, includes the following steps: A multi-parameter coupled stability domain is constructed, and eigenvalue joint analysis is performed under the condition that multiple key control parameters change simultaneously. The stable and feasible region formed by combining all parameters that satisfy the small-signal stability criterion in the multi-dimensional parameter space is defined as the multi-parameter coupling stability domain of the network-type SVG; Extracting the boundary surface of the stability domain provides feasible domain constraints for the collaborative optimization design of key control parameters.

9. The method for designing control boundary parameters of a mesh-type SVG according to claim 8, characterized in that, Based on the droop characteristic constraint of the control parameters of the mesh-type SVG, the boundary constraint box of the control parameters of the mesh-type SVG is determined, including the following steps: Determine the DC voltage droop factor The proportional relationship between DC-side voltage deviation and output voltage amplitude, and the reactive voltage inertia coefficient. The dynamic adjustment relationship between reactive power changes and AC side voltage amplitude changes; Establish a droop control function expression that includes voltage deviation, reactive power disturbance and corresponding regulation output, and construct a mathematical model of droop characteristics; Based on the grid operation specifications and dynamic voltage support capability requirements, the slope range and adjustment sensitivity range of the curve corresponding to the droop characteristic mathematical model are limited to obtain a set of parameter constraints that meet the voltage support performance requirements. The set of parameter constraints that satisfy the voltage support performance is mapped to the multi-parameter coupled stability domain to determine the boundary constraint box of the dual-constraint integrated design of key control parameters.

10. The method for designing control boundary parameters of a mesh-based SVG according to claim 9, characterized in that, The dynamic support requirements for the network structure are determined through the small-signal transfer function of the network-type SVG, including the following steps: Based on the small-signal transfer function of the network SVG, and according to the preset dynamic support performance index, the range of the real part of the closed-loop poles and the damping ratio is limited to determine the control parameter constraint region that meets the dynamic performance requirements. The control parameter constraint region is determined to be a performance boundary condition independent of the harmonic state space stability domain; The harmonic state-space stability domain is specifically a multi-parameter stability domain that satisfies the small-signal stability criterion, obtained based on the eigenvalue analysis of the harmonic state-space model.

11. The method for designing control boundary parameters of a mesh-based SVG according to claim 10, characterized in that, The parameter design method for determining the control parameters of the network-type SVG is based on the construction of a multi-parameter coupled stability domain combined with the control parameter constraint region to perform dual-constraint comprehensive parameter design.

12. The method for designing control boundary parameters of a mesh-based SVG according to claim 11, characterized in that, The dual-constraint synthesis parameter design includes the following steps: The intersection operation of the multi-parameter coupled stability domain and the network control performance constraint region is performed to determine the control parameter design region that simultaneously satisfies the requirements of stability, droop characteristics and dynamic performance, and the final network SVG control parameters are determined within the control parameter design region. The network control performance constraint region is specifically a dynamic performance constraint region that meets the requirements of response speed and voltage support capability, obtained by establishing a mapping relationship between dynamic performance indicators and control parameters based on the small-signal closed-loop transfer function of network control.

13. A network-based SVG control boundary parameter design system, characterized in that, include: The model building unit is used to establish a harmonic state-space model of a network-type SVG based on the small-signal analysis method. The stability domain analysis unit is used to analyze the key control parameters of the harmonic state space model based on the eigenvalue analysis method, and obtain the stable operating conditions of the key control parameters of the network-type SVG. The constraint analysis and parameter design unit is used to determine the boundary constraint box and parameter design method of the control parameters of the network-type SVG based on the stable operating conditions and the requirements of the network dynamic support. The parameter design method includes: Based on the eigenvalue analysis of the harmonic state-space model, a multi-parameter stability domain that satisfies the small-signal stability criterion is obtained, and the stable operating boundary of the control parameters is clarified. Based on the small-signal closed-loop transfer function of the network control, a mapping relationship between dynamic performance indicators and control parameters is established to obtain the dynamic performance constraint region that meets the requirements of response speed and voltage support capability. By performing an intersection operation on the stable region and the dynamic performance constraint region, a comprehensive feasible parameter region that simultaneously satisfies the requirements of stability and dynamic support is obtained. Within this region, the coordinated optimization design of the DC voltage droop coefficient, reactive voltage inertia coefficient, and virtual impedance parameters is completed, thereby realizing the quantitative and systematic tuning of the control parameters of the grid-type SVG.

14. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the mesh-type SVG control boundary parameter design method as described in any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the network-type SVG control boundary parameter design method as described in any one of claims 1 to 12.

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