A method for quantitatively evaluating transient synchronization stability of a heterogeneous converter hybrid system

Abstract

The application belongs to the technical field of new energy power generation, and specifically discloses a kind of heterogeneous converter hybrid system transient synchronous stability quantitative evaluation method, comprising: for fault duration stage and fault removal stage, respectively from the hybrid system corresponding target evaluation unit of each stage is determined, and the kinetic energy and potential energy of the target evaluation unit along the system response trajectory change are acquired;For the kinetic energy and potential energy of each stage, determine the extreme value moment when the potential energy first reaches the minimum and first reaches the maximum, based on the system state quantity corresponding to the extreme value moment, respectively construct the stability evaluation index and instability evaluation index with fixed critical value;Based on the deviation degree of the stability evaluation index and instability evaluation index relative to the fixed critical value, the transient synchronous stability of the system is quantitatively evaluated. Through the application, direct quantitative evaluation of transient synchronous stability is realized, and the stability margin and instability degree of the system are accurately described.

Description

Technical Field

[0001] This application belongs to the field of new energy power generation technology, and more specifically, relates to a quantitative evaluation method for transient synchronization stability of a heterogeneous converter hybrid system. Background Technology

[0002] With the surge in installed capacity of renewable energy, new energy sources are mainly connected to the grid via power electronic converters. Currently, converter control methods mainly include grid-following (GFL) which passively follows the grid, and grid-forming (GFM) which has the ability to construct voltage and frequency. The new power system exhibits a heterogeneous state in which the two types of converters coexist and are connected in a hybrid manner.

[0003] Because power electronic converters lack physical rotational inertia and mechanical damping, they are prone to losing lock-up in grid-connected converters or losing synchronization in grid-connected converters when large disturbances such as grid faults occur, leading to transient synchronization instability accidents that seriously endanger grid safety.

[0004] Currently, stability analysis of this hybrid system mostly employs linear small-signal analysis, which is unsuitable for scenarios with large disturbances. Existing transient synchronization stability analysis methods are primarily limited to binary qualitative discrimination, only determining stability or instability, making it difficult to quantitatively assess the transient synchronization stability of heterogeneous converter hybrid systems and thus unable to provide accurate stability margins or instability levels for power grid safety early warning. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this application aims to provide a quantitative evaluation method for the transient synchronous stability of a heterogeneous converter hybrid system. This method addresses the problem that existing transient stability analysis methods, which heavily rely on solving complex unstable equilibrium points, can only provide a binary qualitative judgment of system stability or instability, thus failing to intuitively and accurately quantify the stability margin and degree of instability of the system.

[0006] The first aspect of this application relates to a method for quantitatively evaluating the transient synchronization stability of a heterogeneous converter hybrid system. The hybrid system includes at least two types of converter units with different synchronization control characteristics. The method includes: determining target evaluation units corresponding to each stage in the hybrid system, for both the fault persistence stage and the post-fault clearing stage, and obtaining the kinetic and potential energy of the target evaluation units as they change along the system response trajectory; determining the extreme moments when the potential energy first reaches its minimum and maximum values ​​for each stage; constructing stability evaluation indices and instability evaluation indices with fixed critical values ​​based on the system state variables corresponding to the extreme moments; and quantitatively evaluating the transient synchronization stability of the system based on the degree of deviation of the stability evaluation indices and instability evaluation indices from the fixed critical values.

[0007] The above scheme identifies key converter units that dominate system stability as the target evaluation objects in stages, enabling the evaluation model to accurately capture the dynamic evolution of the entire fault process. This differentiated evaluation strategy avoids the complex calculation process caused by traditional methods that equate heterogeneous systems to a single model, and improves the pertinence and physical interpretability of transient analysis, laying the model foundation for the subsequent construction of quantitative indicators.

[0008] Furthermore, the above scheme cleverly circumvents the difficulty of analyzing critical boundaries in high-order nonlinear hybrid systems by locking onto the extreme moments when the potential energy first reaches its minimum and maximum values ​​and directly extracting the corresponding system state variables at these critical moments. Based on the state variables at these critical moments, stability and instability assessment indices with fixed critical values ​​are directly constructed, thus providing a unified and definite absolute reference benchmark for system transient stability analysis. By calculating the deviation of the assessment indices from the critical values, a direct quantitative assessment of transient synchronization stability is achieved, accurately characterizing the system's stability margin and degree of instability. This technological leap from qualitative judgment to quantitative representation intuitively reveals the true safe distance of the system from instability, providing precise data support for early warning and control of new power systems.

[0009] In some implementations, constructing stability evaluation indices and instability evaluation indices with fixed critical values ​​based on the system state variables corresponding to the extreme moments includes: constructing the stability evaluation index by the ratio of the negative of the equivalent acceleration power at the moment when the potential energy of the target evaluation unit first reaches its maximum value to the potential energy difference between the moment when the potential energy first reaches its maximum value and the moment when the potential energy first reaches its minimum value; constructing the instability evaluation index by the ratio of the kinetic energy at the moment when the potential energy of the target evaluation unit first reaches its maximum value to the kinetic energy at the moment when the potential energy first reaches its minimum value; the fixed critical value is zero.

[0010] This scheme maps complex transient dynamic processes into intuitive quantitative indicators by defining precise ratios between key state variables of the system at specific extreme moments. The stability assessment indicator uses the ratio of the negative of the equivalent acceleration power at the maximum moment to the potential energy difference, reflecting the system's deceleration and pull-back capability when energy conversion reaches its extreme, quantifying the determinism of the system's absorption of disturbance energy and maintenance of synchronization. The instability assessment indicator directly characterizes the risk of divergence across the equilibrium point due to the remaining kinetic energy that fails to dissipate at the maximum potential energy conversion point, through the proportional relationship of kinetic energy. Both indicators use zero as a natural physical boundary, eliminating the arbitrariness of artificially set thresholds and improving the universality and robustness of the assessment results.

[0011] In some implementations, the quantitative evaluation of the system's transient synchronization stability includes: if the stability evaluation index is not zero and the instability evaluation index is zero, then the hybrid system is determined to be transiently stable, and the system is judged to be in an accelerating or decelerating stable state based on the positive or negative value of the stability evaluation index; if the stability evaluation index is zero and the instability evaluation index is not zero, then the hybrid system is determined to be transiently unstable, and the system is judged to be in an accelerating or decelerating unstable state based on the positive or negative value of the instability evaluation index.

[0012] This solution can not only clearly distinguish between the stable and unstable states of the system, but also further identify the dynamic evolution direction that leads to the state. This multi-dimensional diagnostic information helps maintenance personnel to deeply understand the fault mechanism and provides refined theoretical support for formulating differentiated emergency control strategies.

[0013] In some implementations, the step of determining the target evaluation unit corresponding to each stage from the hybrid system includes: determining the target evaluation unit for each stage based on the differences in synchronization control response characteristics and stability risks of each converter unit during the fault: during the fault duration stage, the converter unit that relies on grid voltage phase tracking to achieve synchronization is determined as the target evaluation unit; during the fault clearing stage, the converter unit with active voltage frequency support capability is determined as the target evaluation unit.

[0014] During the fault duration, the grid-connected converter is highly susceptible to loss of control due to the phase-locked loop's (PLL) high sensitivity to voltage dips. Targeting it as the primary source of system instability risk directly addresses this issue. After the fault is cleared, the system's synchronous recovery depends primarily on the grid-connected converter's active voltage and frequency support capabilities. This phased, precise identification of the dominant factors in a differentiated assessment strategy avoids computational redundancy in global hybrid solutions, improving the specificity and accuracy of transient stability quantitative assessment.

[0015] In some implementations, obtaining the kinetic and potential energy trajectories of the target evaluation units includes: establishing a transient analysis model of the hybrid system; performing time-domain simulation based on the transient analysis model to extract the equivalent acceleration power and rotational speed trajectories of the target evaluation units at each stage; calculating the kinetic energy of each target evaluation unit along the system response trajectory based on the rotational speed trajectory and the equivalent inertia coefficient of the target evaluation unit; and performing an integral operation on the equivalent acceleration power trajectory to obtain the potential energy of each target evaluation unit along the system response trajectory.

[0016] This implementation method combines the advantages of time-domain simulation and the transient energy function method, ensuring both the physical authenticity of the obtained nonlinear dynamic response of the system and the efficient extraction of transient features. Differentiated solution mechanisms are adopted for different physical quantities, enabling the final calculated kinetic and potential energy data to accurately characterize the macroscopic energy exchange and conversion laws of the hybrid system under large disturbances.

[0017] In some implementations, before extracting the equivalent acceleration power of each stage target evaluation unit, the method further includes: converting the damping dissipation of each target evaluation unit into the definition of the corresponding equivalent acceleration power, so that the equivalent acceleration power simultaneously covers the active power imbalance and the damping dissipation, so as to achieve mathematical alignment between the kinetic energy extreme point and the potential energy extreme point in a non-conservative system.

[0018] This implementation method innovatively internalizes the damping effect into the definition of acceleration power, rigorously corrects the theoretical deviation of the traditional energy function method in non-conservative systems, and ensures the precise mathematical correspondence between the kinetic energy extremum and the potential energy extremum. As a result, the quantitative index based on the energy trajectory construction still maintains the calculation accuracy in actual engineering systems that take damping into account.

[0019] In some implementations, establishing the transient analysis model of the hybrid system includes: establishing equivalent swing equations for each converter unit based on the synchronous control links of each converter unit; deriving power coupling terms and voltage coupling terms between each converter unit based on the voltage network equation of the common coupling point; and combining the equivalent swing equations with the power coupling terms and voltage coupling terms to obtain a quasi-synchronous machine transient model that takes into account the interaction between converter units.

[0020] This implementation method, by introducing an electrical coupling term at a common coupling point, fully preserves the dynamic interaction path between heterogeneous converters through grid impedance, overcoming the limitation of the traditional single-machine infinite bus model that ignores the multi-machine coupling effect, and enabling the constructed model to truly reflect the complex dynamic behavior of the hybrid system under strong coupling conditions.

[0021] In some implementations, the equivalent swing equations for each converter unit are established based on the synchronization control loop of each converter unit, including: for converter units with active voltage frequency support capability, deriving their corresponding equivalent swing equations based on their active power control loop and reactive power control loop; for converter units that rely on grid voltage phase tracking to achieve synchronization, deriving their corresponding equivalent swing equations based on their phase-locked loop control equations.

[0022] This implementation method adopts a differentiated modeling path for the two types of converters with drastically different synchronization mechanisms. It equates the dynamic response of the phase-locked loop to a rotor-like motion equation, realizing the description of heterogeneous units under a unified mathematical framework and providing state variables with consistent form for the subsequent construction of the transient energy function of the overall system.

[0023] In some implementations, the method further includes: providing a safety warning for the hybrid system based on the results of the quantitative assessment; and triggering a warning signal and outputting control adjustment suggestions when the stability assessment index is lower than a preset safety margin threshold.

[0024] This implementation method directly transforms the quantitative assessment results into actionable security defense actions, establishing a closed-loop link from state awareness to risk warning. This enables dispatchers to anticipate the deterioration trend of stability margin before the system becomes unstable, thus gaining a window of time to take preventative control measures.

[0025] In some implementations, the method further includes: adjusting the control parameters or control commands of each converter unit in the hybrid system according to the control adjustment recommendations to improve the transient synchronization stability margin of the system; re-executing the quantitative evaluation method to obtain updated stability evaluation indicators and instability evaluation indicators, and dynamically adjusting the system operation strategy according to the update results.

[0026] This implementation constructs an iterative optimization mechanism of evaluation-control-re-evaluation, which enables the system operation strategy to be adaptively corrected based on real-time stability quantification feedback. This not only verifies the effectiveness of the control measures, but also ensures that the system always operates within a sufficient safety margin, significantly enhancing the resilience of the new power system to cope with uncertain disturbances.

[0027] In a second aspect, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation thereof.

[0028] Thirdly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0029] Fourthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0030] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0031] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: (1) By determining the target evaluation unit in stages and based on the system state variables corresponding to the first minimum and first maximum values ​​of potential energy, a quantitative index for stability and instability with fixed critical values ​​was constructed, solving the problem of quantitative characterization of transient stability in hybrid systems with heterogeneous converters. This method maps complex nonlinear transient processes into explicit numerical indices, making the system stability margin or instability risk calculable and comparable, providing a new quantitative tool for power system safety and stability analysis.

[0032] (2) By internalizing the damping dissipation into the definition of equivalent acceleration power, the mathematical alignment of the extreme points of kinetic and potential energy in non-conservative systems is achieved, overcoming the conservative evaluation problem caused by neglecting the damping effect in the traditional energy function method. This ensures that the quantitative indicators still maintain accurate physical meaning when considering the damping characteristics of the actual system, significantly improving the credibility and guiding value of the evaluation results in practical engineering applications.

[0033] (3) The established transient analysis model simultaneously considers the influence of each power loop of the grid-connected converter and the phase-locked loop of the grid-connected converter. It fully considers the interaction between different power generation units and the transmission network through a common coupling point. The model shows that any change in a single factor will not only change its own transient synchronization stability, but also affect the transient synchronization stability of other power generation units through coupling terms. This model is also applicable to grid-connected converter systems using other control methods and has strong versatility.

[0034] (4) The evaluation results revealed the dynamic interaction patterns between heterogeneous converters through the common coupling point. The larger virtual inertia and damping coefficient of the grid-type converter can alleviate voltage and frequency fluctuations at the common coupling point, effectively improving the stability of the grid-connected converter. During a fault, the grid-connected converter can reasonably increase the reactive current injection, which can reduce the acceleration kinetic energy of the grid-type converter through voltage drop coupling and improve its transient stability. Furthermore, the key factors dominating stability throughout the fault process were accurately captured through a differentiated evaluation strategy. Based on the quantitative results and control recommendations output by this evaluation method, the parameter coordination optimization of grid-type and grid-connected converters can be effectively guided. By enhancing the positive interaction between equipment, the overall transient synchronous stability level of the system can be improved, thus enhancing the security and defense capabilities of the new power system. Attached Figure Description

[0035] Figure 1This is a flowchart illustrating the transient synchronization stability quantification evaluation method for heterogeneous converter hybrid systems provided in this application embodiment.

[0036] Figure 2 This is the heterogeneous converter hybrid system topology provided in the embodiments of this application.

[0037] Figure 3 These are schematic diagrams of the control loops used in the various converters provided in the embodiments of this application; wherein, (a) is a schematic diagram of the active and reactive power loop control of a grid-type converter using virtual synchronous generator control; and (b) is a schematic diagram of the phase-locked loop and current loop of a grid-connected converter using PQ control based on phase-locked loop.

[0038] Figure 4 yes Figure 2 Voltage vector relationship diagram for the corresponding hybrid system.

[0039] Figure 5 yes Figure 2 Equivalent circuit diagram of the corresponding hybrid system.

[0040] Figure 6 yes Figure 2 Transient analysis model for corresponding hybrid systems.

[0041] Figure 7 This describes the changes and transformations of kinetic and potential energy along the fault trajectory during the duration of a fault in the grid-type converter in this embodiment of the application.

[0042] Figure 8 This describes the change in potential energy when the system is able to maintain transient synchronization and stability in the embodiments of this application.

[0043] Figure 9 This describes the change in potential energy when the system cannot maintain transient synchronization and stability in this embodiment of the application.

[0044] Figure 10 The heterogeneous converter hybrid system provided in this application embodiment has stability evaluation index and instability evaluation index that vary with... J GFM and D GFM Variational surface.

[0045] Figure 11 The heterogeneous converter hybrid system provided in this application embodiment has stability evaluation index and instability evaluation index that vary with... K q and X g Variational surface.

[0046] Figure 12 The heterogeneous converter hybrid system provided in this application embodiment has stability evaluation index and instability evaluation index that vary with...I 2d and I 2q Variational surface.

[0047] Figure 13 The heterogeneous converter hybrid system provided in this application embodiment has stability evaluation index and instability evaluation index that vary with output current phase angle. c Change curve.

[0048] Figure 14 The heterogeneous converter hybrid system provided in this application embodiment has stability evaluation index and instability evaluation index that vary with... U gf and P ref1 Variational surface.

[0049] Figures 15(a)-15(f) This application provides a heterogeneous converter hybrid system, which, when control parameters, line parameters, and control commands change, shows the transient response changes in the difference between the output frequency and the grid frequency of the grid-connected converter and the grid-connected converter, as well as the power angle. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0051] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. In this application, the symbol " / " indicates that the related objects are in an "or" relationship, for example, A / B means A or B.

[0052] In this application, the terms "first" and "second," etc., are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0053] In this application, the term "electrical connection" can refer to a direct circuit connection or a signal transmission via a communication protocol.

[0054] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0055] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0056] The following is in conjunction with the appendix Figure 1-1 5. This application provides a description of the quantitative evaluation method for transient synchronization stability of heterogeneous converter hybrid systems. For example... Figure 1 As shown, this embodiment provides a method for quantitatively evaluating the transient synchronization stability of a heterogeneous converter hybrid system. This method is applied to hybrid systems containing at least two types of converter units with different synchronization control characteristics. Here, a heterogeneous converter hybrid system refers to a collection of power electronic devices operating in parallel at the same common coupling point, containing at least two types of converters with distinctly different synchronization mechanisms. For example, such as... Figure 2 In the typical topology shown, the system simultaneously includes a grid-connected converter controlled by a virtual synchronous generator and a grid-following converter controlled by a phase-locked loop (PLL). The grid-connected converter exhibits voltage source characteristics, actively establishing voltage and frequency references to the grid; while the grid-following converter exhibits current source characteristics, passively tracking the grid phase to achieve synchronization via a PLL. This heterogeneous hybrid structure results in significant differences in the dynamic response time scale and instability modes of the two types of equipment when the system experiences large disturbances, making traditional single-model analysis methods difficult to apply. This embodiment aims to solve the challenge of quantitative stability assessment of this complex system through a targeted evaluation process. The method provided in this embodiment includes steps 110-130.

[0057] Step 110: For the fault persistence stage and the fault clearing stage, determine the target evaluation unit corresponding to each stage from the hybrid system, and obtain the kinetic and potential energy of the target evaluation unit along the system response trajectory.

[0058] Specifically, the fault duration phase refers to the time interval from the occurrence of a grid fault to the time when the protection device operates to clear the fault; the post-fault clearance phase refers to the time interval from the time the fault is cleared until the system returns to steady state or instability is confirmed. This division is not simply a time segmentation, but is based on the differences in the dominant stability factors of heterogeneous systems at different times. During the fault duration, due to the voltage drop in the grid, grid-following converters that rely on voltage phase tracking are very prone to becoming the weak link in system stability due to phase-locked loop loss. Therefore, the target evaluation unit in this phase is usually locked to grid-following converters. After the fault is cleared, the system enters the voltage and frequency reconstruction process. The virtual rotor dynamics of grid-connected converters with active support capabilities determine whether the system can be resynchronized. Therefore, the target evaluation unit in this phase switches to grid-connected converters.

[0059] After identifying the target evaluation unit, time-domain simulation is performed using a constructed transient analysis model to extract the rotational speed trajectory and equivalent acceleration power trajectory of the corresponding unit. Subsequently, the kinetic energy is directly calculated based on the rotational speed trajectory and the equivalent inertia coefficient of the target evaluation unit, and the potential energy is obtained by integrating the equivalent acceleration power trajectory. This accurately obtains the kinetic and potential energy changes of each target evaluation unit along the system response trajectory. This phased and differentiated energy state acquisition method ensures that the evaluation object always focuses on the core contradiction that restricts the stability of the system in the current period.

[0060] Step 120: For the kinetic and potential energy at each stage, determine the extreme moments when the potential energy first reaches its minimum and maximum values. Based on the system state variables corresponding to the extreme moments, construct stability evaluation index and instability evaluation index with fixed critical values ​​respectively.

[0061] Specifically, during a transient process, the system's energy continuously evolves and transforms between kinetic and potential energy. For example... Figures 7 to 9 As shown, regardless of whether the operating conditions are stable or unstable, the moments when the potential energy first reaches its minimum and maximum values ​​are the physical extreme points that play a decisive role in this dynamic transformation law. This embodiment abandons fuzzy tracking of complex change ranges and instead locks onto these two specific extreme moments, directly extracting the corresponding key system state quantities, such as the equivalent acceleration power at the maximum moment, the kinetic energy at a specific moment, and the potential energy difference between the two. This is because at these two critical nodes, the system's deceleration and pull-back ability when energy transformation reaches its extreme, and the risk of divergence due to undissipated residual kinetic energy at the maximum potential energy transformation point, are most concentrated and significant.

[0062] The stability and instability assessment indices directly constructed from the state quantities at these specific extreme moments both have fixed critical values. These fixed critical values ​​refer to natural numerical boundaries determined by physical laws and unaffected by operating conditions or human experience; in this embodiment, they are preferably zero.

[0063] Step 130: Based on the degree of deviation of the stability assessment index and the instability assessment index from the fixed critical value, the transient synchronous stability of the system is quantitatively assessed.

[0064] Specifically, the quantitative assessment process transforms the abstract stability problem into concrete numerical metrics. By calculating the magnitude and direction of the deviations of two indicators from the zero critical value, it is possible to directly determine whether the system is currently in a stable or unstable state, and further identify whether the system is in a specific evolutionary pattern of accelerating stability, decelerating stability, accelerating instability, or decelerating instability. For example, when the stability assessment indicator is significantly greater than zero and the instability assessment indicator is zero, it indicates that the system has sufficient stability margin and is in the process of accelerating synchronization recovery; conversely, if the stability assessment indicator is zero and the instability assessment indicator is significantly greater than zero, it indicates that the system has crossed the stability boundary and is accelerating out of sync. This quantitative mechanism based on the degree of deviation not only provides binary stability / instability conclusions but also provides continuous spectrum information on the depth of stability or the level of instability risk, providing a refined decision-making basis for subsequent safety early warning and control strategy formulation.

[0065] Based on the above embodiments, a method for quantitatively evaluating the transient synchronization stability of a heterogeneous converter hybrid system is provided, comprising the following steps: Step S1: Establish a transient analysis model for the hybrid system. Specifically, this includes: establishing equivalent swing equations for each converter unit based on its synchronization control loop. For converter units with active voltage frequency support capabilities, derive their corresponding equivalent swing equations based on their active power control and reactive power control loops; for converter units that rely on grid voltage phase tracking for synchronization, derive their corresponding equivalent swing equations based on their phase-locked loop control equations.

[0066] Subsequently, based on the voltage network equation of the common coupling point, the power coupling terms and voltage coupling terms between each converter unit are derived; by combining the equivalent swing equation with the power coupling terms and voltage coupling terms, a synchronous-like transient model considering the interaction between converter units is obtained.

[0067] Specifically, such as Figure 2 The diagram shows a typical topology of a heterogeneous converter hybrid system, including grid-connected converters, grid-connected converters, and an infinite grid. The output of the grid-connected converter, after passing through an LC filter and line impedance, is connected to the same Point of Common Coupling (PCC) bus as the output of the grid-connected converter, after passing through a filter inductor and line impedance. The bus at the PCC is then connected to the infinite grid via line impedance. Since the lines in a distributed generation system are primarily inductive, i.e. R << XTherefore, the line resistance is ignored in this application to simplify the analysis. (See figure) U GFM and I 1 represents the output voltage and output current vectors of the grid-type converter, respectively. L f1 , C f and L 1 represents the output-side filter inductance, filter capacitor, and line inductance of the grid-type converter, respectively. U GFL and I 2 represents the output voltage and output current vectors of the grid-connected converter, respectively. L f2 and L 2 represents the output-side filter inductance and line inductance of the grid-type converter, respectively; U PCC and U g These represent the phase voltage vectors at the point of common coupling and the infinite power grid, respectively. L g This represents the line inductance on the power grid side.

[0068] Figure 3 This embodiment presents the specific control loops used by each converter. The grid-connected converter employs virtual synchronous generator technology, drawing inspiration from the operation of traditional synchronous generators. Synchronization with the power grid is achieved by simulating its rotor motion equations and excitation regulation system. The control loop of the grid-connected converter consists of a power control outer loop and a dual inner loop for voltage and current control. Since the bandwidth of its voltage and current loops is much larger than that of its power outer loop, it can be assumed that the actual output values ​​can quickly track the given values. Therefore, the influence of the voltage and current loops is usually ignored when analyzing its transient stability. Its transient synchronous stability characteristics are mainly determined by the power outer loop, which includes... Figure 3 (a) There are two links: active power control loop and reactive power control loop.

[0069] The grid-connected converter adopts PQ control based on a phase-locked loop (PLL), and its control structure mainly includes... Figure 3 (b) The circuit consists of a phase-locked loop (PLL) and a current loop. Under normal grid operating conditions, the current control loop is switched to position 0, and the current reference value is provided by the power control loop. When the grid voltage drops, the grid-connected converter enters the low-voltage ride-through phase, and the switch is switched to position 1. A single current loop control mode is used to rapidly inject reactive current according to grid guidelines. By rationally designing the current loop control parameters, its control bandwidth can be made much larger than that of the PLL. Therefore, when analyzing the transient synchronization stability of the grid-connected converter, the dynamics of the current loop can be ignored. I 2d =I 2dref , I 2q = I 2qref Externally, it can be considered as having an output current of I 2∠ c The current source.

[0070] Figure 4 The voltage vector relationship of the hybrid system in this example is given, with the grid voltage as the phase reference value. The angle difference between the grid-connected converter and the grid-coupled converter relative to the common reference frame is their respective power angle. δ 1. δ 2.

[0071] like Figure 5 As shown, since the external characteristics of a grid-type converter exhibit that of a voltage source, while those of a parallel-type converter exhibit that of a current source, a parallel system of two heterogeneous converters can be equivalently represented as a parallel circuit of voltage and current sources. An infinite power grid is modeled using a voltage source plus line impedance. Based on the superposition theorem, the output voltage of the parallel-type converter can be derived. U GFL The expression:

[0072] in, X t =j( ω 2 +ω n ) L t , L t = L 1 / / L g + L 2; X g = ω n L g Equivalent grid reactance; X 1= ω n L 1 represents the output line reactance of the grid-type converter.

[0073] exist dq In the GFL coordinate system, combined with the voltage vector relationship, the output voltage of the grid converter can be further obtained. U GFL of q Axial components U GFL_q The specific expression is:

[0074] according to Figure 3 The schematic diagram of a phase-locked loop (PLL) and the control equations can be written as follows:

[0075] Will U GFL_q Substituting the expression into the control equations of the phase-locked loop, we obtain the swing equations, which are similar to those of a synchronous machine to those of a grid converter:

[0076] The relevant equivalent parameters are:

[0077] In the formula J GFL To match the equivalent inertia coefficient of the grid converter, and P GFL This is the equivalent active power reference value and equivalent output power of the grid-type converter. D GFL1 and D GFL2 To determine the self-damping coefficient and cross-damping coefficient of the grid-type converter, K p , K i These are the proportional and integral coefficients of the phase-locked loop. I 2d , I 2q To reference the output current of the grid-connected converter at its output phase dq Components in coordinate system δ 1 δ 2 represents the power angle of the grid-connected converter and the grid-following converter, respectively. ω 2 represents the deviation between the output angular frequency and the rated angular frequency of the grid-type converter.

[0078] For grid-type converters, according to Figure 5 Draw the equivalent circuit diagram and write the voltage network equations for the parallel system:

[0079] The expressions for the voltage at point PCC and the output current of the grid-type converter can be obtained as follows:

[0080]

[0081] Then, based on the basic power calculation formula, the output power of the grid-type converter is obtained as follows:

[0082]

[0083]

[0084] in accordance with Figure 3 (a) is a schematic diagram of the virtual synchronous control power outer loop. The swing equation of the grid-type converter is similar to that of a synchronous machine:

[0085] in, J GFM and D GFM For the virtual inertia coefficient and virtual damping coefficient of the active power loop, U g This represents the effective value of the phase voltage of the power grid. P ref1 The active power reference value given to the grid-type converter. ω 1 represents the deviation between the output angular frequency and the rated angular frequency of the grid-type converter.

[0086] The equivalent active power reference value of the grid-type converter The terminal voltage can be written as:

[0087]

[0088] In the formula,

[0089] in, K q This is the reactive power-voltage droop factor.

[0090] Combining the transient equations of grid-connected and grid-connected converters, the transient analysis model of a hybrid system of two heterogeneous converters is obtained as follows: Figure 6 As shown, the parallel connection of the two machines will generate interactive power and voltage coupling terms, which will affect the transient synchronization stability of the two machines.

[0091] Step S2 involves determining the target evaluation unit for each stage of the fault persistence phase and the post-fault clearance phase from the hybrid system, and obtaining the kinetic and potential energy of the target evaluation unit as it changes along the system response trajectory. Specifically, this includes determining the target evaluation unit for each stage based on the differences in synchronization control response characteristics and stability risks of each converter unit during the fault: during the fault persistence phase, converter units that rely on grid voltage phase tracking for synchronization are identified as target evaluation units; during the post-fault clearance phase, converter units with active voltage frequency support capabilities are identified as target evaluation units.

[0092] Then, time-domain simulation is performed based on the transient analysis model. The damping dissipation of each target evaluation unit is converted into the definition of the corresponding equivalent acceleration power, so that the equivalent acceleration power simultaneously covers the active power imbalance and damping dissipation, thereby achieving mathematical alignment between the kinetic energy extremum and the potential energy extremum in the non-conservative system. The equivalent acceleration power and rotational speed trajectory of the corresponding target evaluation unit at each stage are extracted; based on the rotational speed trajectory and the equivalent inertia coefficient of the target evaluation unit, the kinetic energy of each target evaluation unit along the system response trajectory is calculated; the equivalent acceleration power trajectory is integrated to obtain the potential energy of each target evaluation unit along the system response trajectory.

[0093] Specifically, based on known equivalent swing equations, transient stability analysis of multi-machine power systems often employs an inertial center coordinate system to eliminate the influence of overall system frequency drift, focusing on the relative power angle motion between units. However, this application uses a synchronous rotating coordinate system based on an infinite grid voltage vector, focusing on whether each generating unit in the grid-connected system can maintain synchronization with the main grid. Furthermore, based on the different control characteristics of grid-connected and grid-connected converters, differentiated time evaluation windows are adopted: for the stability or instability of the system during the fault duration, the response results of the grid-connected converter are mainly extracted for solution; for the stability or instability of the system after the fault is cleared, the response results of the grid-connected converter are mainly extracted for solution.

[0094] Step S3: For the kinetic and potential energy at each stage, determine the extreme moments when the potential energy first reaches its minimum and maximum. Based on the system state variables corresponding to the extreme moments, construct stability and instability evaluation indices with fixed critical values. Specifically, this includes: constructing a stability evaluation index by the ratio of the negative of the equivalent acceleration power at the moment the target evaluation unit's potential energy first reaches its maximum to the potential energy difference between the moments when the potential energy first reaches its maximum and minimum; constructing an instability evaluation index by the ratio of the kinetic energy at the moment the target evaluation unit's potential energy first reaches its maximum to the kinetic energy at the moment the potential energy first reaches its minimum; the fixed critical value is zero.

[0095] Specifically, stability assessment indicators (denoted as...) SIn mathematics, the potential energy difference (P0) is defined as the ratio of the negative of the equivalent acceleration power of the target evaluation unit at the moment when the potential energy first reaches its maximum value to the potential energy difference between the moments when the potential energy first reaches its maximum value and the moments when it first reaches its minimum value. Physically, the negative of the equivalent acceleration power at the maximum value is essentially equivalent to the slope of the potential energy versus power angle curve at that moment. Since this slope tends to zero when the system approaches the unstable equilibrium point (UEP) and the potential energy minimum point (stable operating point), examining only the numerator will not reveal the true stable state of the system. Therefore, this embodiment introduces the potential energy difference as the denominator to distinguish between these two distinct physical conditions: when the system trajectory approaches the unstable equilibrium point (UEP), the potential energy difference value within this specific interval is larger, thus making the ratio... S A significant decrease and approach to zero accurately reflects the critical state where the system is about to become unstable; conversely, when the system trajectory converges and approaches the potential energy minimum point due to damping dissipation and other effects, the corresponding potential energy difference approaches zero, making the ratio... S Increase. Therefore. S Through this mathematical construction, the indicator accurately distinguishes the system's operating state and quantifies the true safety margin of the system's distance from the Unstable Limit Point (UEP).

[0096] Instability assessment indicators (denoted as) U The potential energy (Penergy) is defined as the ratio of the kinetic energy of the target evaluation unit at the moment when the potential energy first reaches its maximum value to the kinetic energy at the moment when the potential energy first reaches its minimum value. Here, the moment when the potential energy first reaches its minimum value usually corresponds to a significant state of kinetic energy accumulation after a fault, representing the large disturbance impact energy the system has withstood; while the moment when the potential energy first reaches its maximum value is the key critical node for determining whether the system can maintain transient synchronization. At this maximum value, if the system's kinetic energy is still not zero (i.e., the numerator is greater than zero), it means that the maximum kinetic energy injected into the system during the fault cannot be completely absorbed and converted by the potential energy barrier, and the system has excess residual kinetic energy. Under the continuous drive of this residual kinetic energy, the system's operating point will inevitably cross the unstable equilibrium point, diverging in the direction of continuously increasing work angle, ultimately leading to system loss of synchronization. Therefore, U The indicator directly quantifies the absolute risk and degree of instability that leads to system divergence by using the ratio of residual kinetic energy at extreme moments.

[0097] In this embodiment, S and U The fixed critical values ​​are all set to zero. Choosing zero as the critical value is not based on empirical judgment, but rather stems from the physical laws of energy conservation and transient dynamics: when the system is exactly at the transient stability boundary, the kinetic energy generated by the disturbance is completely converted into potential energy when the potential energy first reaches its maximum value (i.e., the system reaches the unstable equilibrium point UEP). At this point, the remaining kinetic energy of the system must be zero, making the instability assessment index... UIt is strictly equal to zero; at the same time, at this unstable equilibrium point, the slope of the potential energy change with the work angle (i.e., the equivalent accelerating power) tends to zero, and the potential energy difference within a specific interval reaches its maximum, making the stability assessment index... S It will inevitably approach zero. This fixed critical value design based on physical essence eliminates the subjectivity and uncertainty of evaluation caused by relying on manually tuned thresholds in traditional methods, so that the index value itself has the absolute physical benchmark significance of judging whether the system can maintain transient synchronization.

[0098] During the fault duration, the transient synchronization stability of the parallel system mainly depends on the grid-connected converter. Figure 7 The changes and transformations of kinetic and potential energy along the fault trajectory during the fault duration are presented. If the instant of the fault occurrence is taken as the potential energy reference point, the total energy of the grid converter remains constant along the fault trajectory after the system's last operation, equal to the energy possessed by the system at the instant of the fault occurrence. Furthermore, regardless of whether the system is stable or unstable, kinetic and potential energy undergo mutual transformation, with the maximum potential energy point corresponding to the minimum kinetic energy point. The main difference between the energy trajectories under stable and unstable conditions lies in whether the system's kinetic energy is zero when the potential energy function first reaches its maximum value.

[0099] For systems that remain stable during a fault, the kinetic and potential energy curves of the grid converter show a convergent trend. The potential energy reaches its maximum value at... t b2 At the instant the fault occurs, all the kinetic energy injected into the system has been converted into the system's potential energy. During the process of the potential energy changing from its minimum to its maximum value, the energy conversion situation corresponds to... Figure 8 The solid line segment on the middle curve, on this segment V PE - δ The slope of the curve is never zero. To further distinguish whether the work angle is closer to the potential energy minimum point or closer to the unstable equilibrium point UEP, and at the same time... V PE2 ( t b2 , t a2 )= V PE2 ( t b2 )– V PE2 ( t a2 As a stability assessment indicator S When the denominator is... δ b The closer δ a hour, V PE2 ( tb2 , t a2 The smaller the value, the more stable the evaluation index. S The larger; and when δ b near δ UEP At that time, stability assessment indicators S Decrease and approach 0.

[0100] Based on the above analysis of the trajectory energy characteristics, the stability evaluation index of the system during the fault duration is constructed as follows:

[0101] in, t a2 To track the moment when the potential energy of the grid converter first reaches its minimum value, t b2 The moment when the potential energy first reaches its maximum value. V PE2 ( δ 2) The potential energy of the grid-connected converter, P a2 Defined as the equivalent acceleration power of a grid-type converter.

[0102] Among them, the accelerated power of the grid converter P a2 With potential energy V PE2 The specific expression is:

[0103]

[0104] For systems that cannot remain stable during a fault, both the kinetic and potential energy curves exhibit divergence, with the potential energy maxima reaching their maximum points. t b2 The corresponding kinetic energy at the point is still not zero, meaning that the maximum injected kinetic energy after the fault cannot be fully converted into potential energy. Under the influence of kinetic energy, the operating point will continue to move in the direction of increasing power angle beyond the unstable equilibrium point, eventually leading to system instability. During the process of potential energy changing from its minimum to its maximum value, the energy conversion situation corresponds to... Figure 9 The solid line segment on the curve represents the kinetic energy value, which reflects the degree of instability of the system. An instability assessment index is defined. U The kinetic energy possessed when the potential energy first reaches its maximum value. V KE2 ( t b2 The kinetic energy possessed when the potential energy first reaches its minimum value. V KE2 ( ta2 The ratio of ) is expressed as follows:

[0105] in, J GFL To match the equivalent inertia coefficient of the grid converter, ω 2 represents the deviation between the output angular frequency and the rated angular frequency of the grid-connected converter, i.e. ω 2= ω GFL – ω n , V KE2 ( t () represents the kinetic energy of the grid-connected converter as it changes over time.

[0106] Among them, the kinetic energy of the grid converter V KE2 The specific expression is:

[0107] Quantitative evaluation indicators of transient synchronization stability or instability in a heterogeneous converter two-unit parallel system after fault clearance S , U The results were calculated from the transient response of the grid-type converter:

[0108]

[0109] in, J GFM The equivalent inertia coefficient of the grid-type converter. ω 1 represents the deviation between the output angular frequency and the rated angular frequency of the grid-type converter, i.e. ω 1= ω GFM – ω n , t a1 This is the moment when the potential energy of the grid-type converter first reaches its minimum value. t b1 The moment when the potential energy first reaches its maximum value. V PE1 ( δ 1) The potential energy of the grid-type converter. V KE1 ( t ) represents the time-varying kinetic energy of a grid-type converter. P a1 Defined as the equivalent accelerating power of a grid-type converter.

[0110] Among them, the grid-type converter accelerates power P a1 Potential energy V PE1 and kinetic energy V KE1 The specific expression is:

[0111]

[0112]

[0113] Step S4: Based on the deviations of the stability evaluation index and the instability evaluation index from the fixed critical value, the transient synchronization stability of the system is quantitatively evaluated. Specifically, this includes: if the stability evaluation index is not zero and the instability evaluation index is zero, the hybrid system is determined to be transiently stable, and the system is judged to be in an accelerating or decelerating stable state based on the positive or negative value of the stability evaluation index; if the stability evaluation index is zero and the instability evaluation index is not zero, the hybrid system is determined to be transiently unstable, and the system is judged to be in an accelerating or decelerating unstable state based on the positive or negative value of the instability evaluation index.

[0114] Specifically, for a given transient process, at the point of maximum potential energy, the system either has zero kinetic energy (stable) or non-zero kinetic energy (instable). These two states are mathematically strictly complementary and mutually exclusive; there is no fuzzy intermediate state that is both stable and unstable. When a system is determined to be transiently stable (…),… S ≠0 and U When =0), further according to S Positive / negative distinction dynamic mode: S >0 indicates that the system exhibits an accelerated regression trend during the recovery process, i.e., accelerated stabilization; S A value less than 0 indicates that the system, while able to remain stable, has undergone a deceleration adjustment process, i.e., deceleration stability. Similarly, when it is determined to be transient instability ( S =0 and U When ≠0, U >0 indicates that the system crosses the stability boundary with positive residual kinetic energy, which is an accelerated instability and carries an extremely high risk. U A value less than 0 indicates that the system is unstable during reverse motion, which is a type of deceleration instability. This refined state identification mechanism not only provides a clear conclusion on stability / instability but also reveals the directional characteristics of the system's evolution.

[0115] Step S5: Based on the results of the quantitative assessment, a safety warning is issued for the hybrid system; when the stability assessment index is lower than the preset safety margin threshold, a warning signal is triggered and a control adjustment suggestion is output.

[0116] Specifically, the preset safety margin threshold here is an engineering safety boundary parameter distinct from the aforementioned fixed critical value (zero). The fixed critical value of zero only indicates whether the system is physically at the boundary between stability and instability. However, in actual power grid operation, the system must maintain sufficient stability reserves to cope with unknown secondary disturbances or model errors. Therefore, the preset safety margin threshold is usually set to a positive number greater than zero (e.g., 0.1 or 0.2, the specific value can be adjusted according to power grid dispatching regulations or historical operating experience). Its physical meaning is the minimum energy buffer distance allowed for the system to move away from the critical instability state. When the stability assessment index is calculated in real time... S Although the value is greater than zero (i.e., physically stable), if it falls below the preset safety margin threshold, it indicates that the system may cross the stability boundary at any time due to minor additional disturbances. In this case, the system will automatically trigger a warning signal. The form of this warning signal can be flexibly set according to the actual situation. Simultaneously, the system will also output control adjustment suggestions. These suggestions can be specific operational guidelines generated based on the current system state and parameter sensitivity analysis.

[0117] Step S6: According to the control adjustment suggestions, adjust the control parameters or control commands of each converter unit in the hybrid system to improve the transient synchronization stability margin of the system; re-execute the quantitative evaluation method to obtain the updated stability evaluation index and instability evaluation index, and dynamically adjust the system operation strategy according to the update results.

[0118] Specifically, this step establishes a complete closed-loop feedback mechanism of evaluation-regulation-re-evaluation. Adjusting the control parameters or control commands of each converter unit in a hybrid system refers to making online modifications or issuing commands to the underlying controllers of grid-connected or interconnected converters, based on the aforementioned recommendations. For example, for grid-connected converters, their active power reference value can be adjusted. P ref1 Virtual inertia coefficient Virtual damping coefficient or reactive power droop coefficient For grid-connected converters, the phase-locked loop control parameters can be adjusted, or the reactive current injection reference command during low-voltage ride-through can be adjusted. These parameter changes directly affect the system's transient energy function, thereby altering the kinetic and potential energy conversion patterns along the system's response trajectory.

[0119] However, due to the strong nonlinearity and parameter coupling characteristics of heterogeneous hybrid systems, the effects of a single parameter adjustment are often difficult to predict accurately and may cause stability issues in other modes. Therefore, after parameter adjustment, the quantitative evaluation method is re-executed, and the stability evaluation index is recalculated using the updated system model or measured data. S Instability assessment indicators UBased on the new evaluation results, the next round of iterative optimization or switching to a backup control scheme is initiated. This dynamic adjustment mechanism ensures that the system operation strategy always adapts and evolves in accordance with real-time operating conditions, avoiding the problem of insufficient adaptability that may occur in fixed parameter control under complex and changing environments, and truly realizing intelligent closed-loop control based on quantitative perception.

[0120] Based on the above embodiments, in order to further illustrate the evaluation effect of the transient synchronization stability quantitative evaluation method of the heterogeneous converter hybrid system proposed in this application, a specific implementation method will be described below.

[0121] This implementation takes a grid-connected system with one grid-connected converter and one grid-connected converter as an example for simulation study. The system parameters are shown in Table 1. t The grid voltage drops at 3s, and recovers to 1p.u. after the fault lasts for a period of time. The simulated system experiences a transient voltage drop disturbance.

[0122] Table 1

[0123] Using the proposed stability or instability discrimination index, Figure 10 , Figure 11 , Figure 12 and Figure 13 It gives the situation when the grid voltage drops to U g When the virtual inertia coefficient of the grid-type converter is 0.2 pu for 0.3 seconds and then recovers to 1.0 pu, the virtual inertia coefficient is quantitatively analyzed. J GFM Virtual damping coefficient D GFM Reactive power-voltage droop coefficient K q and grid-side line impedance X g Results on the influence of transient synchronization stability on parallel systems; Figure 14 It gives the situation when the grid voltage drops to U g When the voltage drops from 0.2 pu for 0.5 seconds to 1.0 pu, the degree of voltage drop in the power grid is quantitatively analyzed. U gf and the active power reference value of grid-type converters P ref1 Results on the influence of transient synchronization stability on parallel systems.

[0124] In the simulation, the fault conditions and parameter settings for each scenario in the embodiment are as follows: Scenario 1: Set the grid voltage amplitude of the system at 3 seconds. Ug The device dropped to 0.2 PU and recovered after 0.3 seconds. J GFM = At time 4, different damping coefficients D GFM The simulation results of the two-machine parallel system are shown in Figure 15(a).

[0125] Scenario II: Set the grid voltage amplitude of the system at 3 seconds U g The device dropped to 0.2 PU and recovered after 0.3 seconds. D GFM = At 15:00, different virtual inertia coefficients J GFM The simulation results of the two-machine parallel system are shown in Figure 15(b).

[0126] Scenario III: Set the grid voltage amplitude of the system at 3 seconds U g The device dropped to 0.2 PU and recovered after 0.3 seconds. J GFM = 4, D GFM = At 10 o'clock, different droop coefficients K q The simulation results of the two-machine parallel system are shown in Figure 15(c).

[0127] Scenario IV: Set the grid voltage amplitude of the system at 3 seconds. U g The device dropped to 0.2 PU and recovered after 0.3 seconds. K q =0.005, J GFM = 4, D GFM = At 10 o'clock, different line impedances X g The simulation results of the two-machine parallel system are shown in Figure 15(d).

[0128] Scenario V: Set the grid voltage amplitude of the system at 3 seconds. U g The device dropped to 0.2 PU and recovered after 0.5 seconds. K q =0.001, J GFM = 4, DGFM = At 10:00, different current injection phase angles occurred during the fault. c The simulation results of the two-machine parallel system are shown in Figure 15(e).

[0129] Scenario VI: Set the grid voltage amplitude of the system at 3 seconds. U g The device dropped to 0.2 PU and recovered after 0.5 seconds. K q =0.001, J GFM = 4, D GFM = At 10:00, active power reference values ​​for converters of different grid types during the fault period. P ref1 The simulation results of the two-machine parallel system are shown in Figure 15(f).

[0130] Figures 15(a)-15(f) The dynamic interaction between the two converters was revealed. The larger virtual inertia and damping coefficient of the grid-type converter can alleviate voltage and frequency fluctuations at the common coupling point, effectively improving the stability of the grid-connected converter. During fault periods, the grid-connected converter can appropriately increase the reactive current injection, reducing the acceleration kinetic energy of the grid-type converter through voltage drop coupling, thus improving its transient stability. The variation patterns of output frequency and power angle of the grid-type and grid-connected converters shown in the figure are consistent with the results of analysis using the proposed stability / instability discrimination index, indicating that the proposed quantitative stability evaluation index is correct and effective.

[0131] Based on the methods in the above embodiments, this application provides an electronic device that may include a processor, a communications interface, a memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor may invoke logical instructions stored in the memory to execute the methods in the above embodiments.

[0132] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0133] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0134] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0135] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0136] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0137] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0138] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0139] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for quantitatively evaluating the transient synchronization stability of a heterogeneous converter hybrid system, characterized in that, The hybrid system comprises at least two converter units with different synchronous control characteristics, and the method includes: For the fault persistence phase and the fault clearing phase, the target evaluation unit corresponding to each phase is determined from the hybrid system, and the kinetic and potential energy of the target evaluation unit along the system response trajectory is obtained. For the kinetic and potential energy at each stage, the extreme moments when the potential energy first reaches its minimum and maximum are determined. Based on the system state variables corresponding to the extreme moments, stability evaluation index and instability evaluation index with fixed critical values ​​are constructed respectively. The transient synchronous stability of the system is quantitatively evaluated based on the degree of deviation of the stability evaluation index and the instability evaluation index from the fixed critical value.

2. The method according to claim 1, characterized in that, Based on the system state variables corresponding to the extreme moments, stability evaluation indices and instability evaluation indices with fixed critical values ​​are constructed, including: The stability evaluation index is constructed by taking the negative of the equivalent acceleration power at the moment when the potential energy of the target evaluation unit first reaches its maximum value as the ratio of the potential energy difference between the moment when the potential energy first reaches its maximum value and the moment when it first reaches its minimum value. The instability assessment index is constructed by the ratio of the kinetic energy at the moment when the potential energy of the target assessment unit first reaches its maximum value to the kinetic energy at the moment when the potential energy first reaches its minimum value. The fixed critical value is zero.

3. The method according to claim 2, characterized in that, The quantitative evaluation of the system's transient synchronization stability includes: If the stability evaluation index is not zero and the instability evaluation index is zero, then the hybrid system is determined to be transiently stable, and the system is judged to be in an accelerating or decelerating stable state based on the positive or negative value of the stability evaluation index. If the stability assessment index is zero and the instability assessment index is not zero, the hybrid system is determined to be transiently unstable, and the system is judged to be in an accelerating or decelerating instability state based on the positive or negative value of the instability assessment index.

4. The method according to claim 1, characterized in that, The step of determining the target evaluation unit corresponding to each stage from the hybrid system includes: Based on the differences in synchronization control response characteristics and stability risks of each converter unit during the fault, the target evaluation units for each stage are determined: during the fault duration stage, converter units that rely on grid voltage phase tracking to achieve synchronization are identified as target evaluation units; during the post-fault clearance stage, converter units with active voltage and frequency support capabilities are identified as target evaluation units.

5. The method according to claim 1, characterized in that, The acquisition of the kinetic and potential energy of the target evaluation unit along the system response trajectory includes: Establish a transient analysis model for the hybrid system; Based on the transient analysis model, time-domain simulation is performed to extract the equivalent acceleration power and rotational speed trajectory of the target evaluation unit at each stage; Based on the rotational speed trajectory and the equivalent inertia coefficient of the target evaluation unit, the kinetic energy of each target evaluation unit along the system response trajectory is calculated. By integrating the equivalent acceleration power trajectory, the potential energy of each target evaluation unit along the system response trajectory is obtained.

6. The method according to claim 5, characterized in that, Before extracting the equivalent acceleration power of the target evaluation unit corresponding to each stage, the following is also included: The damping dissipation of each target evaluation unit is converted into the definition of the corresponding equivalent acceleration power, so that the equivalent acceleration power simultaneously covers the active power imbalance and damping dissipation, so as to achieve mathematical alignment of the kinetic energy extreme point and the potential energy extreme point in the non-conservative system.

7. The method according to claim 5, characterized in that, The establishment of the transient analysis model for the hybrid system includes: Based on the synchronous control loop of each converter unit, the equivalent swing equation of each converter unit is established respectively. Derivation of power coupling and voltage coupling terms between converter units based on voltage network equations at common coupling points; By combining the equivalent swing equation with the power coupling term and the voltage coupling term, a synchronous-like transient model that takes into account the interaction between converter units is obtained.

8. The method according to claim 7, characterized in that, The equivalent swing equations for each converter unit are established based on the synchronous control loop of each converter unit, including: For converter units with active voltage and frequency support capabilities, the corresponding equivalent swing equations are derived based on their active power control and reactive power control links. For converter units that rely on grid voltage phase tracking for synchronization, the corresponding equivalent swing equation is derived based on their phase-locked loop control equation.

9. The method according to any one of claims 1 to 8, characterized in that, Also includes: Based on the results of the quantitative assessment, a safety warning is issued for the hybrid system. When the stability assessment index is lower than the preset safety margin threshold, an early warning signal is triggered and control adjustment suggestions are output.

10. The method according to claim 9, characterized in that, Also includes: Based on the control and adjustment recommendations, adjust the control parameters or control commands of each converter unit in the hybrid system to improve the system's transient synchronization stability margin. The quantitative evaluation method is re-executed to obtain updated stability and instability evaluation indicators, and the system operation strategy is dynamically adjusted based on the update results.

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