Stability margin boundary construction method and device, storage medium and computer equipment

Abstract

According to the stability margin boundary construction method and device, the storage medium and the computer equipment provided by the invention, before the stability margin boundary is constructed, the parameter variables of the multi-converter grid-connected system are divided into the non-search variables and the search variables, and the search precision of the non-search variables and the low precision and the high precision of the search variables are determined; meanwhile, the search direction is determined through low precision; after the value of the search variable in each search direction is fixed, a stability margin index is solved based on the search precision and the low precision, and boundary points of the stability margin index are searched. In order to improve the analysis precision, a plurality of local areas can be generated in each search direction, and gradient values of the local areas are determined; wherein the local area of which the gradient value is not less than the preset threshold value needs to adopt high-precision supplementary search, so that the efficiency and the precision are balanced. Finally, inverse distance interpolation is carried out on the stability margin boundary points in all the search directions, a stability margin boundary expression is constructed, and rapid construction of the stability margin boundary under any working condition is supported.

Description

Technical Field

[0001] This application relates to the field of small-signal analysis technology, and in particular to a method, apparatus, storage medium and computer device for constructing stability margin boundaries. Background Technology

[0002] With the accelerated global energy transition, the installed capacity of new energy power generation, represented by wind power and photovoltaics, continues to climb. However, this type of high-penetration new energy power generation is characterized by significant intermittency, randomness, and output fluctuations, leading to frequent and significant fluctuations in the operating conditions of new energy grid-connected systems. As the core interface equipment for new energy grid connection, the small-signal stability of the converter is directly affected by changes in operating conditions, and its instability risk may trigger cascading failures or even system collapse. Therefore, how to quickly assess system stability online and take timely control measures has become a key challenge in ensuring the safe operation of the power grid.

[0003] Currently, the main approach to constructing small-signal stability margin boundaries is through point-by-point traversal. This involves densely selecting operating points within the parameter space, calculating their stability indices one by one, and finally fitting a stable boundary surface. However, as the scale of renewable energy systems expands, the dimensionality and accuracy requirements of the variables to be calibrated increase significantly, leading to an exponential increase in computational load. For example, when considering the coupling of multiple factors such as wind and solar power output fluctuations and grid topology changes, traditional methods require a significant amount of time to construct the boundary, making it difficult to meet the timeliness requirements of real-time evaluation and limiting their practical application in high-proportion renewable energy power systems. Summary of the Invention

[0004] The purpose of this application is to at least address one of the aforementioned technical deficiencies, particularly the technical deficiency that traditional methods in the prior art require a significant amount of time to complete boundary construction, making it difficult to meet the timeliness requirements of real-time evaluation and thus restricting their practical application in high-proportion renewable energy power systems.

[0005] This application provides a method for constructing a stability margin boundary, the method comprising:

[0006] Determine multiple parameter variables of the multi-converter grid-connected system and the domain range of each parameter variable, and extract one parameter variable from each parameter variable and mark it as a non-search variable, and mark the other parameter variables other than the non-search variable as search variables;

[0007] The search precision of the non-search variable and the low precision and high precision of the search variable are determined based on each domain interval, and multiple search directions of the search variable are determined based on the low precision.

[0008] After fixing the values ​​of the search variables in each search direction, the stability margin index of the multi-converter grid-connected system in each search direction is obtained based on the domain range of the non-search variables and the search precision, and the stability margin boundary point in each search direction is obtained based on each stability margin index.

[0009] In each search direction, multiple local regions are generated within the domain of the search variable based on the low precision, and the gradient value of each local region is determined.

[0010] Local regions with gradient values ​​not less than a preset threshold are marked as regions to be supplemented, and the search direction is supplemented using the high precision, and the stability margin boundary points of the supplemented search direction are searched in the regions to be supplemented.

[0011] By using inverse distance interpolation of the stability margin boundary points in each search direction, a stability margin boundary expression corresponding to each search direction is constructed; the stability margin boundary expression is used to quickly construct the stability margin boundary in the target search direction.

[0012] Optionally, determining the search precision of the non-search variable and the low and high precision of the search variable based on each domain interval includes:

[0013] Determine the precision coefficients of the non-search variables, the low-precision coefficients and high-precision coefficients of the search variables, and the minimum and maximum values ​​of each domain interval;

[0014] The search accuracy of the non-search variable is calculated based on the accuracy coefficient of the non-search variable and the minimum and maximum values ​​of its domain interval.

[0015] Based on the minimum and maximum values ​​of the domain interval of the search variable, the high-precision coefficient and the low-precision coefficient are calculated respectively to obtain the high-precision and low-precision of the search variable.

[0016] Optionally, the calculation method for the total number of search directions includes:

[0017]

[0018] In the formula, Indicates the total number of search directions; Indicates the number of search variables; and They represent the first The maximum and minimum values ​​of the domain interval of each search variable; Indicates the first Low precision of the search variables.

[0019] Optionally, obtaining the stability margin index of the multi-converter grid-connected system in each search direction based on the domain interval of the non-search variable and the search accuracy includes:

[0020] For each search direction, with the search precision as the step size, the non-search variables are sequentially evaluated from the minimum to the maximum value of the domain interval.

[0021] After obtaining the current variable value by taking the value of the non-search variable each time, the back ratio matrix of the current variable value is determined, and the current small signal margin index of the multi-converter grid-connected system is calculated based on the back ratio matrix.

[0022] When the current small-signal margin index is not greater than the preset system stability level or when the current variable value is the last value taken, the process of taking the value of the non-search variable is stopped, and the current small-signal margin index is taken as the final stability margin index in the search direction.

[0023] Optionally, the step of searching for the stability margin boundary point in each search direction based on various stability margin indices includes:

[0024] For each search direction, determine whether the stability margin index is not greater than the preset system stability level;

[0025] If so, the current variable value corresponding to the stability margin index is used as the critical value, and the stability margin boundary point in the search direction is generated based on the critical value.

[0026] If not, the maximum value of the non-search variable in the domain interval is taken as the critical value, and a stability margin boundary point in the search direction is generated based on the critical value.

[0027] Optionally, the step of generating multiple local regions in each search direction based on the low precision within the domain of the search variable, and determining the gradient value of each local region, includes:

[0028] For each search direction, the domain of the search variable is divided into multiple sub-intervals using the low precision method, and multiple local regions are generated based on the value range of the search variable in each sub-interval.

[0029] The search variable values ​​are arranged and combined in each local region to obtain the discrete boundary points contained in each local region; wherein the values ​​include the left boundary value and the right boundary value of the sub-region.

[0030] Gradient calculations are performed on the discrete boundary points of each local region to obtain the gradient value of each local region.

[0031] Optionally, the stability margin boundary expression includes:

[0032]

[0033] In the formula, This represents the weight value of the nth known discrete boundary point; This represents the values ​​of each search variable in the target search direction; This represents the coordinate values ​​of each search variable in the nth known discrete boundary point; N and n represent the indices of known discrete boundary points. This represents the stability margin boundary in the target search direction; This represents the critical value of the non-search variable at the nth known discrete boundary point.

[0034] This application also provides a stability margin boundary construction device, comprising:

[0035] The variable labeling module is used to determine multiple parameter variables of the multi-converter grid-connected system and the domain range of each parameter variable, and to extract one parameter variable from each parameter variable and label it as a non-search variable, and to label the other parameter variables other than the non-search variable as search variables.

[0036] The precision determination module is used to determine the search precision of the non-search variable and the low precision and high precision of the search variable based on each domain interval, and to determine multiple search directions of the search variable based on the low precision.

[0037] The boundary point search module is used to fix the value of the search variable in each search direction, and then obtain the stability margin index of the multi-converter grid-connected system in each search direction based on the domain range of the non-search variable and the search precision, and search for the stability margin boundary point in each search direction based on each stability margin index.

[0038] The gradient calculation module is used to generate multiple local regions in each search direction based on the low precision of the domain of the search variable, and to determine the gradient value of each local region.

[0039] The direction supplementation module is used to mark local regions with gradient values ​​not less than a preset threshold as regions to be supplemented, and to perform search direction supplementation using the high precision, and to search for and obtain the stability margin boundary points of the supplemented search direction in the region to be supplemented.

[0040] The expression construction module is used to construct the stability margin boundary expression for each search direction by performing inverse distance interpolation using the stability margin boundary points of each search direction; the stability margin boundary expression is used to quickly construct the stability margin boundary in the target search direction.

[0041] This application also provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the stability margin boundary construction method as described in any of the above embodiments.

[0042] This application also provides a computer device, including: one or more processors, and memory;

[0043] The memory stores computer-readable instructions, which, when executed by the one or more processors, perform the steps of the stability margin boundary construction method as described in any of the above embodiments.

[0044] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0045] The stability margin boundary construction method, apparatus, storage medium, and computer equipment provided in this application can first divide the various parameter variables of a multi-converter grid-connected system into non-search variables and search variables, and determine their domain intervals before constructing the stability margin boundary. This decomposes the complex multidimensional parameter space of the system into manageable subsets. Then, based on the domain intervals, the search precision of the non-search variables and the low and high precision of the search variables can be determined, and the search direction can be determined by the low precision to ensure the efficiency of boundary construction. Subsequently, after fixing the values ​​of the search variables in each search direction, the stability margin index can be obtained based on the domain and search precision of the non-search variables, and the boundary points can be searched. This transforms the system analysis process into a one-dimensional scanning problem of the non-search variables, significantly reducing the computational load. To improve the analysis accuracy, multiple local regions can be generated in each search direction and their gradient values ​​can be determined to quantify the sensitivity of stability to parameter changes. Among them, local regions with gradient values ​​not less than a preset threshold need to be supplemented by high precision search to balance efficiency and accuracy. Finally, by performing inverse distance interpolation on the stability margin boundary points in each search direction, the stability margin boundary expression can be constructed, which supports the rapid construction of stability margin boundaries under any operating condition. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application 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 of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A topology diagram of a multi-converter grid-connected system provided in this application embodiment;

[0048] Figure 2 A schematic diagram of a converter control strategy provided in an embodiment of this application;

[0049] Figure 3 A flowchart illustrating a stability margin boundary construction method provided in this application embodiment;

[0050] Figure 4 A schematic diagram of the structure of a small-signal stability margin index provided in an embodiment of this application;

[0051] Figure 5 A topology diagram of a stability margin boundary test system provided in this application embodiment;

[0052] Figure 6 A schematic diagram of a stability margin boundary construction device provided in this application embodiment;

[0053] Figure 7 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] Currently, the main approach to constructing small-signal stability margin boundaries is through point-by-point traversal. This involves densely selecting operating points within the parameter space, calculating their stability indices one by one, and finally fitting a stable boundary surface. However, as the scale of renewable energy systems expands, the dimensionality and accuracy requirements of the variables to be calibrated increase significantly, leading to an exponential increase in computational load. For example, when considering the coupling of multiple factors such as wind and solar power output fluctuations and grid topology changes, traditional methods require a significant amount of time to construct the boundary, making it difficult to meet the timeliness requirements of real-time evaluation and limiting their practical application in high-proportion renewable energy power systems.

[0056] Based on this, this application proposes the following technical solution, as detailed below:

[0057] In some embodiments, the stability margin boundary construction method of this application can be applied to a multi-converter grid-connected system. The mathematical model of the multi-converter grid-connected system is established in a two-phase rotating coordinate system, where the variable subscript d represents the direct axis component of the two-phase rotating coordinate system, and the variable subscript q represents the cross axis component of the two-phase rotating coordinate system.

[0058] Indicatively, such as Figure 1 As shown, Figure 1 A topology diagram of a multi-converter grid-connected system provided in this application embodiment; Figure 2 In this text, the subscript t represents the total number of converters, and the subscript m represents the relevant variables of the m-th converter. This represents the filter inductance of the m-th converter. Let represent the filter capacitor of the m-th converter. This represents the equivalent inductance of the step-up transformer of the m-th converter. and Let represent the d-axis current component and q-axis current component injected into the external power grid at the grid connection point of the m-th converter, respectively. and These represent the d-axis and q-axis components of the converter grid connection point voltage, respectively. and These represent the d-axis and q-axis components of the total current injected into the external power grid by each converter, respectively. and These represent the d-axis and q-axis components of the grid voltage, respectively.

[0059] also, Indicates the inductance of the power grid line The impedance matrix, which is used to characterize Small signal component with voltage difference across two ends and flowing through Relationship between small-signal components of current:

[0060]

[0061] The expression can be written directly:

[0062]

[0063] In the formula, s represents the Laplace operator. Indicates the fundamental angular frequency. The value is rad / s.

[0064] Let represent the admittance matrix of the m-th converter, which characterizes the relationship between the small-signal component of the current injected into the external grid by the m-th converter and the small-signal component of the voltage at the grid connection point:

[0065]

[0066] The method for obtaining the relationship between the small-signal component of the current injected into the external power grid and the small-signal component of the voltage at the grid connection point is to linearize each link of the converter control strategy at the equilibrium point, and then eliminate the remaining variables by elimination method.

[0067] Furthermore, such as Figure 2 As shown, Figure 2 A schematic diagram of a converter control strategy provided in an embodiment of this application; Figure 2 In the text, the subscript abc indicates the values ​​of the three-phase components (A, B, and C) of the variable in the three-phase stationary coordinate system. This represents the reference value of the active power of the m-th converter. This represents the actual value of active power. This represents the reference value of reactive power for the m-th converter. This represents the actual value of reactive power. , , and Let represent the proportional-integral element in the control system of the m-th converter. Let represent the first-order inertial element in the control system of the m-th converter. This represents the output angular frequency of the phase-locked loop of the m-th converter. This represents the output phase of the m-th converter phase-locked loop, which is used for coordinate transformation between the three-phase stationary coordinate system and the two-phase rotating coordinate system, including the Parker transformation and the inverse Parker transformation.

[0068] In one embodiment, such as Figure 3 As shown, Figure 3 This is a flowchart illustrating a stability margin boundary construction method provided in an embodiment of this application. The application provides a stability margin boundary construction method, specifically including the following:

[0069] S110: Determine multiple parameter variables of the multi-converter grid-connected system and the domain range of each parameter variable, and extract one parameter variable from each parameter variable and mark it as a non-search variable, and mark the other parameter variables other than the non-search variable as search variables.

[0070] In this step, before constructing the stability margin boundary, the computer equipment can first divide the various parameter variables of the multi-converter grid-connected system into non-search variables and search variables, and determine their domain intervals, thereby decomposing the complex multidimensional parameter space of the system into manageable subsets.

[0071] Specifically, the parameter variables here refer to those affecting the line impedance matrix. and converter admittance matrix The calculation results include all variable parameters, including the voltage, current, phase, frequency, active power, and reactive power of each converter. Since each parameter variable is constrained by the converter's own capacity, the left and right boundaries of each parameter variable can be determined based on its own capacity, thus forming the domain interval.

[0072] For example, assuming a multi-converter grid-connected system has p variables, each variable is denoted as... , , ..., , Then the first p-1 variables can be... , , ..., Search variables categorized by search direction, Non-search variables are categorized as non-search directions; in this case, the search direction of the search variable can be defined as... .

[0073] Understandably, by giving the values ​​of p variables, a computer can directly determine the relative level of the system's current small-signal stability. Based on this, when constructing a stability boundary, the system's stability level is consistent across all points on the boundary; the stability level is lower on one side of the boundary than on the other; and vice versa. Given the values ​​of p-1 variables, the system's small-signal stability depends on... The value of , There exists a critical value such that the stability level of the system is exactly equal to the stability level of the intended stable boundary. At this point, given a set of... , , ..., The value of corresponds to a certain value. The critical value; constantly changing , , ..., Find the value of and find the corresponding value. Once the critical value is found, a series of discrete points on the stable boundary can be found in the p-dimensional space, and the stable boundary can be fitted based on these discrete points.

[0074] It should be noted that during the construction of stable boundaries, , , ..., The value can be modified manually, but it is related to... , , ..., The corresponding value The critical value is calculated through small-signal stability analysis; this is a variable. , , ..., With variables The essential difference lies in this. Furthermore, we introduce the concept of spatial vectors. , , ..., The continuous modification of the value is equivalent to a vector. By constantly changing direction in space, this application can transform vectors... Defined as the search direction, and based on this definition, variables can be accordingly... , , ..., Divide into search variables, that is, variables related to the search direction, and... These are classified as non-search variables, i.e., variables related to non-search directions.

[0075] S120: Determine the search precision of non-search variables and the low and high precision of search variables based on each domain interval, and determine multiple search directions for search variables based on the low precision.

[0076] In this step, after determining the non-search variables and search variables through step S110, the computer device can determine the search precision of the non-search variables and the low precision and high precision of the search variables based on the domain interval, and determine the search direction through the low precision to ensure the efficiency of boundary construction.

[0077] Understandably, the search direction needs to be constantly changed during the process of constructing a stable margin boundary, i.e., the search variable... , , ..., The value needs to be constantly changed. In the search variable... , , ..., Within the defined domain, higher precision requires traversing more search directions, but this also reduces the efficiency of constructing a stable margin boundary. To ensure that non-search variables are within the defined domain for each search direction... For the accuracy of critical boundary values, variables related to non-search directions only use one level of precision, i.e., high precision. For search variables, this application can first use a lower search precision and traverse fewer search directions to initially construct a stability margin boundary. Of course, the smoothness of the change in the constructed stability margin boundary can be examined by region to determine whether the current precision is sufficient.

[0078] In regions where changes are relatively gradual, the current accuracy can be determined to be sufficient; in regions where changes are relatively drastic, the current accuracy can be determined to be insufficient. Therefore, the number of search directions in such regions can be increased in the future, thereby improving the efficiency of constructing stability margin boundaries while ensuring construction accuracy.

[0079] S130: After fixing the values ​​of the search variables in each search direction, the stability margin index of the multi-converter grid-connected system in each search direction is obtained based on the domain range and search accuracy of the non-search variables, and the stability margin boundary point in each search direction is obtained based on each stability margin index.

[0080] In this step, after determining the search directions of the search variables in step S120, the computer device can first fix the values ​​of the search variables in each search direction, and then calculate the stability margin index and search the boundary points based on the domain and search accuracy of the non-search variables, transforming the system analysis process into a one-dimensional scanning problem of the non-search variables, which greatly reduces the amount of computation.

[0081] Understandably, computer equipment can fix the values ​​of search variables for each search direction, locking the search space along a specific path. Then, based on the domain of non-search variables and the corresponding search precision, it calculates the stability margin index and searches for boundary points point by point. In this way, the originally complex stability margin problem involving multi-variable coupling is transformed into a one-dimensional scanning task of non-search variables in a given direction. The search process is greatly simplified, eliminating the need for a full traversal in high-dimensional space, thus significantly improving the speed of boundary construction.

[0082] S140: In each search direction, generate multiple local regions in the domain of the search variable with low precision, and determine the gradient value of each local region.

[0083] In this step, after obtaining the stability margin boundary points for each search direction through step S130, the computer device can also generate multiple local regions in the (p-1)-dimensional space in each search direction based on low precision within the domain of the search variable, and determine the gradient value of each local region, thereby quantifying the sensitivity of stability to parameter changes.

[0084] Understandably, in each search direction, the computer device can generate multiple local regions within the domain of the search variables with low precision. By uniformly or adaptively dividing these local regions, each region can represent a local characteristic range in the search direction. Subsequently, the computer device determines the corresponding gradient value based on the local change of the stability margin index with parameter variation within each local region. Based on the distribution characteristics of the gradient value, the computer device can identify local regions that significantly affect stability, thereby automatically adjusting the search strategy during boundary construction, reducing redundant computation in flat regions and enhancing resolution in sensitive regions, thus improving overall search efficiency and the accuracy of stability margin boundary construction.

[0085] S150: Mark the local region with gradient value not less than the preset threshold as the region to be supplemented, and use high precision to supplement the search direction, and search for the stability margin boundary point of the supplemented search direction in the region to be supplemented.

[0086] In this step, after determining the gradient value of each local region through step S140, the computer device can mark the local region with a gradient value not less than a preset threshold as the region to be supplemented, and use high precision to supplement the search direction, and search for the stable margin boundary point of the supplemented search direction in the region to be supplemented, thereby balancing the efficiency and accuracy of stable margin boundary construction.

[0087] Understandably, when the gradient value of a local region is not less than a preset threshold, it indicates that the region is experiencing drastic changes and the current precision is insufficient. Therefore, it can be marked as a region to be supplemented, and high precision can be used in these local regions to increase the number of search directions and search for the stability margin boundary points of these search directions, thereby improving the accuracy of the stability margin boundary construction in these regions. On the other hand, when the gradient value of a local region is not less than the preset threshold, it indicates that the region is experiencing relatively gentle changes and the current precision is sufficient. Therefore, it is not necessary to use high precision for redundant calculations, thereby improving the overall search efficiency.

[0088] For example, a computer device can record the maximum gradient value in each local region as... Iterate through each local region, where the gradient value is less than 0.7. No precision adjustment is needed in local regions, especially for gradients greater than or equal to 0.7. For local regions, it is necessary to change the search precision of the search variables to high precision, and supplement the search direction and corresponding stability margin boundary points in the corresponding local regions.

[0089] S160: By using the stability margin boundary points of each search direction to perform inverse distance interpolation, the stability margin boundary expression corresponding to each search direction is constructed; the stability margin boundary expression is used to quickly construct the stability margin boundary in the target search direction.

[0090] In this step, after performing a high-precision search on the rapidly changing local area through step S150, the computer device can perform inverse distance interpolation on the stability margin boundary points in each search direction, thereby constructing a stability margin boundary expression. This expression can support the rapid construction of stability margin boundaries under any operating condition.

[0091] Understandably, by weighted fitting of the spatial distribution characteristics of boundary points at different locations, this application can generate a stability margin boundary expression describing the stability margin variation trend of a multi-converter grid-connected system in a multi-dimensional parameter space. Using this expression, in the corresponding search direction, this application can directly and quickly deduce the corresponding stability margin boundary position from any given discrete points of the stability margin boundary without needing to perform a large-scale numerical search again, thus achieving rapid construction of the stability margin boundary.

[0092] In the above embodiments, before constructing the stability margin boundary, the various parameter variables of the multi-converter grid-connected system can be divided into non-search variables and search variables, and their domain intervals can be determined. This decomposes the complex multidimensional parameter space of the system into manageable subsets. Then, based on the domain intervals, the search precision of the non-search variables and the low and high precision of the search variables can be determined, and the search direction can be determined by the low precision to ensure the efficiency of boundary construction. Subsequently, after fixing the values ​​of the search variables in each search direction, the stability margin index can be obtained based on the domain and search precision of the non-search variables, and the boundary points can be searched. This transforms the system analysis process into a one-dimensional scanning problem of the non-search variables, significantly reducing the amount of computation. To improve the analysis accuracy, multiple local regions can be generated in each search direction and their gradient values ​​can be determined to quantify the sensitivity of stability to parameter changes. Among them, local regions with gradient values ​​not less than a preset threshold need to be supplemented with high precision search to balance efficiency and accuracy. Finally, by performing inverse distance interpolation on the stability margin boundary points in each search direction, the stability margin boundary expression can be constructed, which supports the rapid construction of the stability margin boundary under any operating condition.

[0093] In one embodiment, step S120, which involves determining the search precision of non-search variables and the low and high precision of search variables based on each domain interval, may include:

[0094] S121: Determine the precision coefficients of the non-search variables, the low-precision coefficients and high-precision coefficients of the search variables, and the minimum and maximum values ​​of each domain interval.

[0095] S122: The search accuracy of non-search variables is calculated based on the accuracy coefficients of non-search variables and the minimum and maximum values ​​of their domain intervals.

[0096] S123: Based on the minimum and maximum values ​​of the domain interval of the search variable, calculate the high-precision coefficient and the low-precision coefficient respectively to obtain the high-precision and low-precision values ​​of the search variable.

[0097] In this embodiment, when determining the precision of a variable, the computer device can first determine the precision coefficients of the non-search variable, the low-precision coefficients and high-precision coefficients of the search variable, as well as the minimum and maximum values ​​of each domain interval. For the non-search variable, the computer device can calculate the search precision of the non-search variable based on its precision coefficients and the minimum and maximum values ​​of its domain interval; while for the search variable, the computer device can calculate the high-precision coefficients and low-precision coefficients respectively based on the minimum and maximum values ​​of its domain interval to obtain the high precision and low precision of the search variable.

[0098] Specifically, this application can include non-search variables The domain interval is denoted as Non-search variables Its precision coefficient is 0.01, therefore its search accuracy is... It can be calculated using the following formula:

[0099]

[0100] Similarly, search variables The domain interval is denoted as Search variables Its low-precision coefficient is 0.05, and its high-precision coefficient is 0.01, therefore its search accuracy is low. and high search accuracy The calculation expressions can be as follows:

[0101]

[0102]

[0103] In one embodiment, the calculation of the total number of search directions in step S120 includes:

[0104]

[0105] In the formula, Indicates the total number of search directions; Indicates the number of search variables; and They represent the first The maximum and minimum values ​​of the domain interval of each search variable; Indicates the first Low precision of the search variables.

[0106] Understandably, when determining the search direction, the computer device can discretize each search variable within its domain with a low precision step size, obtaining the number of intervals for that search variable. These interval numbers corresponding to different search variables are multiplied together. Since the number of discrete points corresponding to the number of discretized intervals of each variable is 1 more than the number of intervals, 1 is added to the multiplication result. The final result is the total number of search directions after discretization of the entire search space.

[0107] In one embodiment, the process of obtaining the stability margin index of the multi-converter grid-connected system in each search direction based on the domain range and search accuracy of the non-search variables in step S130 may include:

[0108] S131: For each search direction, with the search precision as the step size, take values ​​for the non-search variables sequentially from the minimum to the maximum value of the domain interval.

[0109] S132: After obtaining the current variable value by taking the value of the non-search variable each time, determine the back ratio matrix of the current variable value, and calculate the current small signal margin index of the multi-converter grid-connected system based on the back ratio matrix.

[0110] S133: When the current small-signal margin index is not greater than the preset system stability level or when the current variable value is the last value taken, stop the value taking process of the non-search variable and take the current small-signal margin index as the final stability margin index in this search direction.

[0111] In this embodiment, for each search direction, the computer device can sequentially take values ​​for the non-search variables, from the minimum to the maximum value within the domain interval, using the search precision of the non-search variables as the step size. After each value is taken, the computer device can use that value as the current variable value and determine the backpropagation matrix of the current variable value. Then, based on the backpropagation matrix, it calculates the current small-signal margin index of the multi-converter grid-connected system. During this process, if the calculated current small-signal margin index is not greater than the preset system stability level or if the current variable value is the last taken value, the computer device can stop the non-search variable value taking process, and use the current small-signal margin index as the final stability margin index for that search direction.

[0112] Specifically, for each search direction When all parameter values ​​are fixed, the small-signal stability level of a multi-converter grid-connected system is constant. Based on the admittance matrix of each converter and the impedance matrix of the grid line inductance, the system's hysteresis ratio matrix L can be obtained. The expression for L is as follows:

[0113]

[0114] According to the generalized Nyquist stability criterion, computer equipment can analyze the small-signal stability of a system using the back-ratio matrix L. For example... Figure 4 As shown, Figure 4 A schematic diagram of the structure of a small-signal stability margin index provided in an embodiment of this application; Figure 4 Based on the Nyquist curve obtained by plotting the eigenvalues ​​of the back-ratio matrix L, and referring to the definition of gain margin, this application can calculate the system's stability margin index h (unit: dB) using the following formula:

[0115]

[0116] In one embodiment, the process of searching for the stability margin boundary point in each search direction based on each stability margin index in step S130 may include:

[0117] S134: For each search direction, determine whether the stability margin index is not greater than the preset system stability level.

[0118] S135: If so, the current variable value corresponding to the stability margin index is used as the critical value, and the stability margin boundary point in the search direction is generated based on the critical value.

[0119] S136: If not, then the maximum value of the non-search variable in the domain interval is taken as the critical value, and the stability margin boundary point in the search direction is generated based on the critical value.

[0120] In this embodiment, for each search direction, if its stability margin index is greater than the preset system stability level, the current variable value corresponding to the stability margin index can be used as the critical value; otherwise, the maximum value of the non-search variable in the domain interval can be used as the critical value. Then, stability margin boundary points for each search direction can be generated based on the critical values ​​of each search direction.

[0121] For example, suppose the stability level of the small-signal stability margin boundary required for a multi-converter grid-connected system is [value missing]. If the stability margin index of the search direction is at this time Then the computer equipment can identify the non-search variable corresponding to the stability margin index. The value of is denoted as the critical value. ;like Continue to increase to The system can still be maintained Then the critical value in the search direction The value is set as This gives us the search direction. Stability margin boundary points .

[0122] In one embodiment, step S140, which involves generating multiple local regions in each search direction based on low precision within the domain of the search variable and determining the gradient value of each local region, may include:

[0123] S141: For each search direction, the domain of the search variable is divided into multiple sub-intervals using low precision, and multiple local regions are generated based on the value range of the search variable in each sub-interval.

[0124] S142: Arrange and combine the values ​​of the search variable in each local region to obtain the discrete boundary points contained in each local region; wherein, the values ​​include the left boundary value and the right boundary value of the sub-region.

[0125] S143: Perform gradient calculations on the discrete boundary points of each local region to obtain the gradient value of each local region.

[0126] In this embodiment, for each search direction, the computer device can divide the domain of the search variable into multiple sub-regions with low precision, and generate multiple local regions based on the value range of the search variable in each sub-region; then, the value results of the search variable can be arranged and combined in each local region to obtain the discrete boundary points contained in each local region; wherein, the value results include the left boundary value and the right boundary value of the sub-region; finally, the computer device can perform gradient calculation on the discrete boundary points of each local region to obtain the gradient value of each local region.

[0127] Specifically, search variables Domain interval Due to its low precision Divided into Sub-intervals, . Domain interval The The number of subintervals can be represented as For (p-1) search variables, when a sub-interval is selected for the value of each variable, a local region can be enclosed in (p-1)-dimensional space. The total number T of local regions can be calculated based on the number of sub-intervals of the search variables, as shown in the following formula:

[0128]

[0129] Accordingly, each search variable within a certain local region takes a value within a sub-interval, either the left boundary value or the right boundary value of the sub-interval. Based on permutations and combinations, the number of discrete boundary points contained within the local region is... , represented as .

[0130] In one embodiment, the stability margin boundary expression in step S160 may include:

[0131]

[0132] In the formula, This represents the weight value of the nth known discrete boundary point; This represents the values ​​of each search variable in the target search direction; This represents the coordinate values ​​of each search variable in the nth known discrete boundary point; N and n represent the indices of known discrete boundary points. This represents the stability margin boundary in the target search direction; This represents the critical value of the non-search variable at the nth known discrete boundary point.

[0133] In this embodiment, the stability margin boundary points within the local region It can be represented as The function, i.e. Given any search direction within a local area. In this search direction, let the stability margin index Critical parameter values That is, the stability margin boundary can be based on existing local conditions. The discrete points of the stability margin boundary are obtained by inverse distance interpolation.

[0134] Indicatively, such as Figure 5 As shown, Figure 5 A topology diagram of a stability margin boundary test system provided in this application embodiment; Figure 5 A test system with four converters connected to an infinite power grid via inductive lines was used for simulation verification. The relevant parameter values ​​of the test system are shown in the table below:

[0135]

[0136] The reactive power reference value for each converter is taken as 0.25 pu. The active power reference values ​​for the 2nd, 3rd, and 4th converters are... , and Set as a variable parameter of the system. When the active power reference value of the first converter... The table below compares the computation time of the point-by-point traversal method and the method proposed in this application when fitting the boundary of the h=0.3dB margin index, with the values ​​set to 0.1pu, 0.2pu, and 0.3pu respectively:

[0137]

[0138] As can be seen from the table above, compared with the traditional point-by-point traversal method, the method of this application greatly improves the computational efficiency.

[0139] The stability margin boundary construction apparatus provided in the embodiments of this application is described below. The stability margin boundary construction apparatus described below and the stability margin boundary construction method described above can be referred to in correspondence.

[0140] In one embodiment, such as Figure 6 As shown, Figure 6 This application provides a structural schematic diagram of a stability margin boundary construction device according to an embodiment of the present application. The present application also provides a stability margin boundary construction device, including a variable marking module 210, an accuracy determination module 220, a boundary point search module 230, a gradient calculation module 240, a direction supplementation module 250, and an expression construction module 260, specifically comprising the following:

[0141] The variable labeling module 210 is used to determine multiple parameter variables of the multi-converter grid-connected system and the domain range of each parameter variable, and to extract one parameter variable from each parameter variable and label it as a non-search variable, and to label the other parameter variables other than the non-search variable as search variables.

[0142] The precision determination module 220 is used to determine the search precision of the non-search variable and the low precision and high precision of the search variable based on each domain interval, and to determine multiple search directions of the search variable based on the low precision.

[0143] Boundary point search module 230 is used to fix the value of the search variable in each search direction, obtain the stability margin index of the multi-converter grid-connected system in each search direction based on the domain range of the non-search variable and the search precision, and search for the stability margin boundary point in each search direction based on each stability margin index.

[0144] The gradient calculation module 240 is used to generate multiple local regions in each search direction according to the low precision of the domain range of the search variable, and to determine the gradient value of each local region.

[0145] The direction supplementation module 250 is used to mark local areas with gradient values ​​not less than a preset threshold as areas to be supplemented, and to perform search direction supplementation using the high precision, and to search for and obtain stable margin boundary points of the supplemented search direction in the areas to be supplemented.

[0146] The expression construction module 260 is used to construct a stability margin boundary expression for each search direction by performing inverse distance difference calculations on the stability margin boundary points of each search direction; the stability margin boundary expression is used to quickly construct the stability margin boundary in the target search direction.

[0147] In the above embodiments, before constructing the stability margin boundary, the various parameter variables of the multi-converter grid-connected system can be divided into non-search variables and search variables, and their domain intervals can be determined. This decomposes the complex multidimensional parameter space of the system into manageable subsets. Then, based on the domain intervals, the search precision of the non-search variables and the low and high precision of the search variables can be determined, and the search direction can be determined by the low precision to ensure the efficiency of boundary construction. Subsequently, after fixing the values ​​of the search variables in each search direction, the stability margin index can be obtained based on the domain and search precision of the non-search variables, and the boundary points can be searched. This transforms the system analysis process into a one-dimensional scanning problem of the non-search variables, significantly reducing the amount of computation. To improve the analysis accuracy, multiple local regions can be generated in each search direction and their gradient values ​​can be determined to quantify the sensitivity of stability to parameter changes. Among them, local regions with gradient values ​​not less than a preset threshold need to be supplemented with high precision search to balance efficiency and accuracy. Finally, by performing inverse distance interpolation on the stability margin boundary points in each search direction, the stability margin boundary expression can be constructed, which supports the rapid construction of the stability margin boundary under any operating condition.

[0148] In one embodiment, the accuracy determination module 220 may include:

[0149] The coefficient determination submodule is used to determine the precision coefficients of non-search variables, the low-precision coefficients and high-precision coefficients of search variables, as well as the minimum and maximum values ​​of each domain interval.

[0150] The first calculation submodule is used to calculate the search precision of the non-search variable based on the precision coefficient of the non-search variable and the minimum and maximum values ​​of its domain interval.

[0151] The second calculation submodule is used to calculate the high-precision coefficient and the low-precision coefficient based on the minimum and maximum values ​​of the domain interval of the search variable, respectively, to obtain the high-precision and low-precision values ​​of the search variable.

[0152] In one embodiment, the calculation method for the total number of search directions in the accuracy determination module 220 may include:

[0153]

[0154] In the formula, Indicates the total number of search directions; Indicates the number of search variables; and They represent the first The maximum and minimum values ​​of the domain interval of each search variable; Indicates the first Low precision of the search variables.

[0155] In one embodiment, the boundary point search module 230 may include:

[0156] The variable retrieval submodule is used to retrieve values ​​for non-search variables sequentially from the minimum to the maximum value of the domain interval for each search direction, with the search precision as the step size.

[0157] The index calculation submodule is used to determine the back ratio matrix of the current variable value after each value is obtained from the non-search variable, and to calculate the current small signal margin index of the multi-converter grid-connected system based on the back ratio matrix.

[0158] The indicator determination submodule is used to stop the value taking process of non-search variables when the current small signal margin indicator is not greater than the preset system stability level or when the current variable value is the last value taken, and to take the current small signal margin indicator as the final stability margin indicator in the search direction.

[0159] In one embodiment, the boundary point search module 230 may further include:

[0160] The indicator judgment submodule is used to determine whether the stability margin indicator is not greater than the preset system stability level for each search direction.

[0161] The first boundary point determination submodule is used to, if so, take the current variable value corresponding to the stability margin index as the critical value, and generate the stability margin boundary point in the search direction based on the critical value.

[0162] The second boundary point determination submodule is used to, if not, take the maximum value of the non-search variable in the domain interval as the critical value, and generate the stability margin boundary point in the search direction based on the critical value.

[0163] In one embodiment, the gradient calculation module 240 may include:

[0164] The region generation submodule is used to divide the domain of the search variable into multiple sub-regions with low precision for each search direction, and generate multiple local regions based on the value range of the search variable in each sub-region.

[0165] The value combination submodule is used to arrange and combine the value results of the search variable in each local region to obtain the discrete boundary points contained in each local region; wherein, the value results include the left boundary value and the right boundary value of the subregion.

[0166] The gradient calculation submodule is used to calculate the gradient of discrete boundary points in each local region to obtain the gradient value of each local region.

[0167] In one embodiment, the stability margin boundary expression in the expression construction module 260 may include:

[0168]

[0169] In the formula, This represents the weight value of the nth known discrete boundary point; This represents the values ​​of each search variable in the target search direction; This represents the coordinate values ​​of each search variable in the nth known discrete boundary point; N and n represent the indices of known discrete boundary points. This represents the stability margin boundary in the target search direction; This represents the critical value of the non-search variable at the nth known discrete boundary point.

[0170] In one embodiment, this application also provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the stability margin boundary construction method as described in any of the above embodiments.

[0171] In one embodiment, this application also provides a computer device storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the stability margin boundary construction method as described in any of the above embodiments.

[0172] Indicatively, such as Figure 7 As shown, Figure 7 This is a schematic diagram of the internal structure of a computer device 300 provided in an embodiment of this application. The computer device 300 can be provided as a server. (Refer to...) Figure 7 The computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by memory 301 for storing instructions, such as application programs, that can be executed by the processing component 302. The application programs stored in memory 301 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 302 is configured to execute instructions to perform the stability margin boundary construction method of any of the above embodiments.

[0173] The computer device 300 may also include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate on an operating system stored in memory 301, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0174] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0175] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0176] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0177] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for constructing stability margin boundaries, characterized in that, The method comprises: determining a plurality of parameter variables of a multi-inverter grid-connected system and a definition domain interval of each parameter variable, and extracting a parameter variable from each parameter variable as a non-search variable, and marking other parameter variables outside the non-search variable as search variables; determining a search precision of the non-search variable and a low precision and a high precision of the search variables based on the definition domain intervals, and determining a plurality of search directions of the search variables based on the low precision; after fixing the value of the search variable in each search direction, determining a stability margin index of the multi-inverter grid-connected system in each search direction based on the definition domain interval of the non-search variable and the search precision, and searching for a stability margin boundary point in each search direction based on each stability margin index; in each search direction, generating a plurality of local regions in the definition domain interval of the search variable according to the low precision, and determining a gradient value of each local region; marking a local region with a gradient value not less than a preset threshold as a region to be supplemented, supplementing the search direction by using the high precision, and searching for a stability margin boundary point of the supplemented search direction in the region to be supplemented; performing inverse distance interpolation by using the stability margin boundary points of each search direction to construct a stability margin boundary expression corresponding to each search direction; the stability margin boundary expression is used for quickly constructing a stability margin boundary in a target search direction.

2. The stable margin boundary construction method according to claim 1, characterized by, The method comprises: determining a plurality of parameter variables of a multi-inverter grid-connected system and a definition domain interval of each parameter variable, and extracting a parameter variable from each parameter variable as a non-search variable, and marking other parameter variables outside the non-search variable as search variables; determining a search precision of the non-search variable and a low precision and a high precision of the search variables based on the definition domain intervals, and determining a plurality of search directions of the search variables based on the low precision; after fixing the value of the search variable in each search direction, determining a stability margin index of the multi-inverter grid-connected system in each search direction based on the definition domain interval of the non-search variable and the search precision, and searching for a stability margin boundary point in each search direction based on each stability margin index; 3. The stable margin boundary construction method of claim 1, wherein, in each search direction, generating a plurality of local regions in the definition domain interval of the search variable according to the low precision, and determining a gradient value of each local region; wherein, denotes the total number of search directions; denotes the number of search variables; and denote the maximum and minimum value of the domain interval of the th search variable, respectively; denotes the low accuracy of the th search variable.

4. The stable margin boundary construction method of claim 1, wherein, marking a local region with a gradient value not less than a preset threshold as a region to be supplemented, supplementing the search direction by using the high precision, and searching for a stability margin boundary point of the supplemented search direction in the region to be supplemented; performing inverse distance interpolation by using the stability margin boundary points of each search direction to construct a stability margin boundary expression corresponding to each search direction; the stability margin boundary expression is used for quickly constructing a stability margin boundary in a target search direction. The method comprises: determining a plurality of parameter variables of a multi-inverter grid-connected system and a definition domain interval of each parameter variable, and extracting a parameter variable from each parameter variable as a non-search variable, and marking other parameter variables outside the non-search variable as search variables; 5. The stable margin boundary construction method according to claim 4, characterized by, determining a search precision of the non-search variable and a low precision and a high precision of the search variables based on the definition domain intervals, and determining a plurality of search directions of the search variables based on the low precision; after fixing the value of the search variable in each search direction, determining a stability margin index of the multi-inverter grid-connected system in each search direction based on the definition domain interval of the non-search variable and the search precision, and searching for a stability margin boundary point in each search direction based on each stability margin index; in each search direction, generating a plurality of local regions in the definition domain interval of the search variable according to the low precision, and determining a gradient value of each local region; marking a local region with a gradient value not less than a preset threshold as a region to be supplemented, supplementing the search direction by using the high precision, and searching for a stability margin boundary point of the supplemented search direction in the region to be supplemented; performing inverse distance interpolation by using the stability margin boundary points of each search direction to construct a stability margin boundary expression corresponding to each search direction; the stability margin boundary expression is used for quickly constructing a stability margin boundary in a target search direction. For each search direction, it is judged whether the stability margin index is not greater than the preset system stability level; If yes, a current variable value corresponding to the stability margin index is taken as a critical value, and a stability margin boundary point in the search direction is generated according to the critical value; If no, a maximum value of the non-search variable in the domain interval is taken as the critical value, and the stability margin boundary point in the search direction is generated according to the critical value.

6. The stable margin boundary construction method of claim 1, wherein, In each search direction, a plurality of local regions are generated in the domain interval of the search variable according to the low precision, and a gradient value of each local region is determined, including: For each search direction, the domain interval of the search variable is divided into a plurality of sub-intervals by using the low precision, and a plurality of local regions are generated based on the value interval of the search variable in each sub-region; In each local region, the value result of the search variable is arranged and combined to obtain discrete boundary points contained in each local region; wherein the value result includes the left boundary value and the right boundary value of the sub-region; The gradient values of each local region are obtained by respectively performing gradient calculation on the discrete boundary points of each local region.

7. The stable margin boundary construction method of claim 1, wherein, The stability margin boundary expression includes: wherein, represents the weight value of the nth known discrete boundary point; represents the value of each search variable in the target search direction; represents the coordinate value of each search variable in the nth known discrete boundary point; N and n represent the index of the known discrete boundary point; represents the stable margin boundary in the target search direction; represents the critical value of the non-search variable in the nth known discrete boundary point.

8. A stable margin boundary construction device characterized by comprising: including: A variable marking module is configured to determine a plurality of parameter variables of a multi-inverter grid-connected system and a domain interval of each parameter variable, and extract one parameter variable from each parameter variable as a non-search variable, and mark other parameter variables except the non-search variable as search variables; An accuracy determination module is configured to determine the search accuracy of the non-search variable and the low precision and high precision of the search variable based on each domain interval, and determine a plurality of search directions of the search variable based on the low precision; A boundary point search module is configured to, after fixing the value of the search variable in each search direction, obtain the stability margin index of the multi-inverter grid-connected system in each search direction based on the domain interval of the non-search variable and the search accuracy, and search for the stability margin boundary point in each search direction based on each stability margin index; A gradient calculation module is configured to, in each search direction, generate a plurality of local regions in the domain interval of the search variable according to the low precision, and determine the gradient value of each local region; A direction supplement module is configured to mark a local region with a gradient value not less than a preset threshold as a to-be-supplemented region, supplement the search direction by using the high precision, and search for the stability margin boundary point of the supplemented search direction in the to-be-supplemented region; An expression construction module is configured to perform inverse distance interpolation by using the stability margin boundary points of each search direction to construct the stability margin boundary expression corresponding to each search direction; the stability margin boundary expression is used to quickly construct the stability margin boundary in a target search direction.

9. A storage medium characterized by: The storage medium stores computer readable instructions, and the computer readable instructions are executed by one or more processors to perform the steps of the stability margin boundary construction method according to any one of claims 1 to 7.

10. A computer device, comprising: including: one or more processors, and a memory; The memory stores computer readable instructions which, when executed by the one or more processors, perform the steps of the method for constructing a stability margin boundary as claimed in any one of claims 1 to 7.

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