Electric power system electromagnetic transient modeling method, device and equipment based on typical element multiplexing

Abstract

The invention relates to an electromagnetic transient modeling method, device and equipment for a power system based on typical component multiplexing. The method comprises the following steps: acquiring a data file, a component model library and computing resource data; analyzing the data file to obtain analyzed data; obtaining a long-distance tie line from the network topology; taking the long-distance tie lines as candidate decoupling points, and carrying out network division on the network topology by adopting an objective function of a graph segmentation algorithm to obtain a plurality of sub-networks with low coupling degrees; each called basic typical element model is screened out from the element model library and modified according to corresponding element parameters, and electromagnetic transient simulation elements are obtained; and performing model construction according to the load data, the generator data, all the sub-networks and the electromagnetic transient simulation elements of the power devices to obtain an electromagnetic transient model of the power system. According to the method, the electromagnetic transient simulation elements are constructed through the element model library, and the network topology of the power system is subjected to sub-network division by adopting the graph segmentation algorithm, so that the modeling efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system simulation model, and particularly relates to a power system electromagnetic transient modeling method, device and equipment based on typical element reuse. BACKGROUND

[0002] The establishment of a power system electromagnetic transient simulation model is the basis for carrying out dynamic characteristic analysis of a power system. At present, the whole-process modeling process of a power system electromagnetic transient simulation model includes two links of element modeling and system modeling integration, and both links have bottlenecks in efficiency and quality.

[0003] In terms of element modeling, the existing technology mainly adopts a modeling method based on mathematical principle derivation. This method requires a modeling personnel to first deeply understand the physical characteristics and working principles of an element, then to establish accurate differential algebraic equations, and finally to realize model algorithm by manually writing C / C++ or Fortran code. The advantage of this method is that it can guarantee the mathematical rigor and physical accuracy of an element model, and provides a reliable theoretical basis for simulation calculation. However, the disadvantages of this method are also very prominent: first, the development cycle is too long, and complete modeling of a complex element may take several weeks or even months; second, the mathematical foundation and programming ability of the modeling personnel are required to be extremely high, and the modeling personnel needs to be proficient in both power system theory and numerical calculation method; third, different technical personnel developing the same type of element model often have implementation differences, resulting in poor comparability and reusability of the element model. More importantly, when the scale of the power system is expanded, this inefficient modeling method seriously restricts the advancement speed of the overall simulation work.

[0004] In terms of system modeling, the existing technology mainly relies on a manual modeling method of a graphical interface. Simulation technicians need to gradually build a system model by dragging elements and connecting lines in a graphical interface, and manually set the parameters of each element. The advantage of this existing technology is intuitive and visible, and it is convenient for construction and modification of a small-scale power system. However, the disadvantages of this existing technology become more and more obvious as the scale of the power system expands: first, the modeling efficiency is extremely low, and manual modeling of a power grid may take several weeks, and connection errors or parameter setting errors are extremely easy to occur; second, the model quality is seriously dependent on the personal experience of the technicians, and the same system model built by different technicians may have significant differences; third, there is no consideration for subsequent parallel simulation, and the network structure of the model is randomly formed without optimization design for parallel calculation, resulting in that the generated electromagnetic transient simulation model is difficult to realize load balancing in a parallel computing environment, and the performance advantages of multi-core computing hardware cannot be fully utilized.

[0005] In addition, the existing component modeling and system modeling are often disconnected, lacking effective coordination mechanism. After the component model is developed, parameter configuration and connection operation need to be repeated when the system model is integrated, which further reduces the modeling efficiency of the overall electromagnetic transient simulation model.

[0006] Therefore, there is an urgent need for a new technical solution that can improve the efficiency of component development and the quality of power system modeling, and promote the coordinated optimization of the two. SUMMARY

[0007] The present application provides a power system electromagnetic transient modeling method, device and equipment based on typical component reuse, which is used to solve the technical problem of low modeling efficiency caused by the disconnected component modeling and system modeling, lacking effective coordination mechanism.

[0008] In order to achieve the above purpose, the present application provides the following technical solution:

[0009] On the one hand, a power system electromagnetic transient modeling method based on typical component reuse is provided, comprising the following steps:

[0010] Obtain the data file and component model library of the power system, and obtain the calculation resource data of the power system simulation software;

[0011] Parse the data file to obtain parsed data, wherein the parsed data includes network topology and component parameters, load data and generator data;

[0012] Obtain long-distance tie lines from the network topology; use the network topology as the candidate decoupling point to perform network division on the network topology by using the objective function of the graph partitioning algorithm, to obtain several sub-networks with low coupling degree;

[0013] From the component model library, filter out the basic typical component model corresponding to each power device in the network topology on the power system simulation software, modify each called basic typical component model according to the corresponding component parameters, to obtain the electromagnetic transient simulation component corresponding to each power device;

[0014] According to the load data, the generator data, all the sub-networks and the electromagnetic transient simulation components of each power device, perform model construction to obtain the electromagnetic transient model of the power system;

[0015] According to the calculation resource utilization efficiency and the calculation resource communication cost of the calculation resource data, determine the objective function.

[0016] Preferably, the element model library comprises typical element models of various power devices, a typical element model corresponding to each power device in the network topology is called from the element model library, each called typical element model is modified according to the corresponding element parameter, and an electromagnetic transient simulation element corresponding to each power device is obtained, comprising:

[0017] An external parameter interface for setting parameters is configured for each typical element model;

[0018] A typical element model corresponding to each power device in the network topology is screened from the element model library, and is recorded as a basic typical element model;

[0019] The configuration parameters of the external parameter interface of the corresponding basic typical element model are modified according to the element parameters of each power device, and an electromagnetic transient simulation element corresponding to each power device is obtained.

[0020] Preferably, the computing resource data comprises: the number of idle processors, the computing efficiency of each idle processor, the number of processors, and the communication loss between each pair of processors, and the target function is determined according to the computing resource utilization efficiency and the computing resource communication cost of the computing resource data, comprising:

[0021] A first target function maximizing the computing resource utilization efficiency is determined according to the number of idle processors and the computing efficiency of each idle processor;

[0022] A second target function minimizing the computing resource communication cost is determined according to the number of idle processors, the number of processors, and the communication loss;

[0023] The target function comprises the first target function and the second target function.

[0024] Preferably, the computing resource data comprises the number of callable message queues; the network topology is divided into sub-networks by a graph partitioning algorithm target function with the long-distance tie line as a candidate decoupling point, and a plurality of sub-networks with low coupling degrees are obtained, comprising:

[0025] The network topology is converted into a directed acyclic graph; the maximum number of sub-networks is determined according to the number of callable message queues;

[0026] With the long-distance tie line as a candidate decoupling point, the directed acyclic graph is partitioned and optimized by a graph partitioning algorithm according to the candidate decoupling point and the maximum number of sub-networks, with the minimum number of cross-sub-network lines and the balance of the number of elements in each sub-network as the partitioning target, and a plurality of sub-networks with low coupling degrees are obtained.

[0027] Preferably, the power system electromagnetic transient modeling method based on typical element reuse comprises: taking the number of the callable message queues as the maximum number of network segmentation.

[0028] Preferably, the model construction is performed according to the load data, the generator data, the electromagnetic transient simulation elements of all the sub-networks and the respective power equipment, to obtain an electromagnetic transient model of the power system, which comprises:

[0029] According to the electromagnetic transient simulation elements of each sub-network, the respective power equipment, the load data and the generator data, a sub-model corresponding to each sub-network is determined.

[0030] According to the network topology, all the sub-models are connected to obtain an electromagnetic transient model of the power system.

[0031] In another aspect, a power system electromagnetic transient modeling device based on typical element reuse is provided, which comprises a data acquisition module, a data analysis module, a network segmentation module, an element construction module and a model construction module.

[0032] The data acquisition module is configured to acquire a data file of the power system and an element model library, and acquire calculation resource data of power system simulation software.

[0033] The data analysis module is configured to analyze the data file to obtain analysis data, which comprises network topology and element parameters, load data and generator data.

[0034] The network segmentation module is configured to acquire long-distance tie lines from the network topology, and perform network segmentation on the network topology by taking the long-distance tie lines as candidate decoupling points and using an objective function of a graph segmentation algorithm, to obtain a plurality of sub-networks with low coupling degrees.

[0035] The element construction module is configured to filter out, on the power system simulation software, a basic typical element model corresponding to each power equipment in the network topology from the element model library, modify each basic typical element model according to the corresponding element parameters, and obtain electromagnetic transient simulation elements corresponding to each power equipment.

[0036] The model construction module is configured to perform model construction according to the load data, the generator data, the electromagnetic transient simulation elements of all the sub-networks and the respective power equipment, to obtain an electromagnetic transient model of the power system.

[0037] The objective function is determined according to the calculation resource utilization efficiency and the calculation resource communication cost of the calculation resource data.

[0038] Preferably, the element model library comprises typical element models of various power devices, the element construction module comprises an interface setting sub-module, a calling sub-module and an element construction sub-module;

[0039] The interface setting sub-module is configured to set an external parameter interface for setting parameters for each typical element model;

[0040] The calling sub-module is configured to screen out a typical element model corresponding to each power device in the network topology from the element model library, denoted as a basic typical element model;

[0041] The element construction sub-module is configured to modify the configuration parameters of the external parameter interface of the basic typical element model corresponding to each power device according to the element parameters of each power device, to obtain an electromagnetic transient simulation element corresponding to each power device.

[0042] Preferably, the computing resource data comprises the number of idle processors, the computing efficiency of each idle processor, the number of processors and the communication loss between each pair of processors, and the target function is determined according to the computing resource utilization efficiency and the computing resource communication cost of the computing resource data, comprising:

[0043] A first target function for maximizing the computing resource utilization efficiency is determined according to the number of idle processors and the computing efficiency of each idle processor;

[0044] A second target function for minimizing the computing resource communication cost is determined according to the number of idle processors, the number of processors and the communication loss;

[0045] The target function comprises the first target function and the second target function.

[0046] In still another aspect, a terminal device is provided, comprising a processor and a memory;

[0047] The memory is configured to store program code and transmit the program code to the processor;

[0048] The processor is configured to execute the above-mentioned power system electromagnetic transient modeling method based on typical element multiplexing according to instructions in the program code.

[0049] The power system electromagnetic transient modeling method based on typical element reuse comprises the following steps: obtaining a data file and an element model library of a power system, and obtaining computing resource data of a power system simulation software; analyzing the data file to obtain analysis data, the analysis data comprising network topology and element parameters, load data and generator data; obtaining long-distance tie lines from the network topology; using the long-distance tie lines as candidate decoupling points to perform network splitting on the network topology by using an objective function of a graph partitioning algorithm to obtain a plurality of sub-networks with low coupling degrees; on the power system simulation software, screening out basic typical element models corresponding to each power device in the network topology from the element model library, modifying each called basic typical element model according to corresponding element parameters to obtain electromagnetic transient simulation elements corresponding to each power device; and constructing a model according to the load data, the generator data, all the sub-networks and the electromagnetic transient simulation elements of each power device to obtain an electromagnetic transient model of the power system; wherein the objective function is determined according to the computing resource utilization efficiency and the computing resource communication cost of the computing resource data.

[0050] From the above technical solutions, it can be seen that the power system electromagnetic transient modeling method based on typical element reuse has the following advantages: the power system electromagnetic transient modeling method based on typical element reuse constructs electromagnetic transient simulation elements by using an element model library and divides the network topology of the power system into sub-networks by using a graph partitioning algorithm, thereby coordinating element modeling and system modeling in the construction of the electromagnetic transient model of the power system, improving the modeling efficiency, and solving the technical problem of low modeling efficiency caused by the fact that the existing element modeling and system modeling are often disconnected and lack effective coordination mechanisms.

[0051] The power system electromagnetic transient modeling device based on typical element reuse automatically reads standard data files by using a data acquisition module, a data analysis module, a network partitioning module, an element construction module and a model construction module, thereby avoiding tedious and error-prone manual modeling; and the intelligent network partitioning algorithm (such as a graph partitioning algorithm) ensures the generation of the electromagnetic transient model of the power system, realizes automatic and intelligent construction of the electromagnetic transient model, and improves the modeling efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction will be given below to the drawings needed to be used in the embodiments or the prior art descriptions. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative labor.

[0053] Figure 1 The power system electromagnetic transient modeling method based on typical element reuse described in the embodiments of the present application has the step flowchart shown in the figure.

[0054] Figure 2 A schematic diagram of a power system electromagnetic transient modeling device based on typical element multiplexing according to an embodiment of the present application;

[0055] Figure 3 A schematic diagram of a terminal device according to an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to make the purposes, characteristics and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the embodiments described below are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0057] In the description of the embodiments of the present application, the terms "first", "second" are used only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise explicitly specified and limited.

[0058] In the embodiments of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection", "fixing" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0059] Patent terms of the present application:

[0060] The definition of balancing the number of elements in a subnet is to ensure that the number of hosts or devices in each subnet is evenly distributed when dividing the subnet, so as to avoid excessive or insufficient resources in some subnets, thereby optimizing network performance and address utilization.

[0061] Power system simulation refers to simulating the operation state of the power system through mathematical models and computer technology, which is used for analyzing device characteristics, optimizing operation strategies and verifying safety and stability. Its core functions include electromechanical transient simulation, electromagnetic transient simulation and digital-analog hybrid simulation, and are applied to power grid planning and design, fault analysis, new energy access verification and dispatcher training fields.

[0062] This application provides a method, apparatus, and equipment for electromagnetic transient modeling of power systems based on the reuse of typical components. It solves the technical problem that the existing component modeling and system modeling stages are often separated, lack an effective coordination mechanism, and have low modeling efficiency.

[0063] Example 1:

[0064] Figure 1 This is a flowchart illustrating the steps of the electromagnetic transient modeling method for power systems based on the reuse of typical components described in this application.

[0065] like Figure 1 As shown in the figure, this application provides a method for electromagnetic transient modeling of power systems based on the reuse of typical components, including the following steps:

[0066] S1. Obtain the data files and component model library of the power system, as well as the computational resource data of the power system simulation software.

[0067] It should be noted that during the construction of the electromagnetic transient model of the power system, step S1 is used to obtain the data files and component model library of the power system required for constructing the electromagnetic transient model of the power system, as well as the computational resource data of the power system simulation software.

[0068] For example, a power system data file can be understood as acquiring power grid operation data from systems such as the Energy Management System (EMS), Distribution Management System (DMS), Wide Area Measurement System (WAMS), Production Management System (PMS), Grid Dispatch and Control System (SCADA), Fault Management System, and Image Monitoring System, and then converting the power grid operation data to obtain a data file that can be directly read by widely used power system analysis software such as BPA and PSASP.

[0069] For example, a power system component model library can include existing mature typical component models of various power equipment (such as converters, wind turbines, controllers, transformers, transmission lines, switchgear, etc.). Typical component models include "doubly fed wind turbine model," "MMC converter model," "π-type transmission line model," "adder," and "multiplier," etc., which are encapsulated as typical component models and stored in the component model library. Each typical component model has completed the conversion from mathematical principles to stability calculation code. This power system electromagnetic transient modeling method based on typical component reuse can reduce repetitive modeling work and improve modeling efficiency through typical component models. For example, by adjusting the parameters of typical component models in power system simulation software (such as PSCAD), different capacity power equipment can be quickly adapted.

[0070] For example, the computational resource data of power system simulation software can be obtained through a communication interface to determine the current usage of the computational resource queue: PRC={COMPU1, COMPU2, COMPU1={core1, core2...}, core1={type=a, spare=yes, comtime=b...}. This includes information such as the size of the computational resources, their idle status, available queues, and communication attributes. In this example, PRC represents the set of currently available computational resources, COMPU represents the processor, core represents the idle cores of the processor, type represents the type of idle cores, spare indicates whether the resource is idle, and comtime represents the set of idle time periods, with the numbers representing the quantity. This electromagnetic transient modeling method for power systems based on the reuse of typical components can avoid the problem of insufficient computational resources during the construction of electromagnetic transient models of power systems by utilizing the computational resource data of power system simulation software, thus supporting real-time simulation of large-scale power systems.

[0071] This can be understood as follows: Data files for the power system can be directly downloaded from the IEEE 30-node system, including standardized grid topology, power equipment parameters, and grid operation data. Component model libraries for the power system can also be obtained using pre-built component model libraries from open-source power system simulation tools (such as OpenModelica and GridLAB-D), for example, by downloading open-source component models (such as transformers, transmission lines, and IGBTs) from platforms like GitHub and ResearchGate. Computational resource data for power system simulation software can be automatically distributed by the simulation software (such as PSASP and BPA), and the information can be received directly from the software.

[0072] S2. Parse the data file to obtain parsed data, which includes network topology and component parameters, load data, and generator data.

[0073] It should be noted that step S2 involves parsing the data file obtained in step S1 to obtain the analytical data required to construct the electromagnetic transient model of the power system. This analytical data includes power system volume attribute data, power system modeling characteristic data, network topology, component parameters, load data, and generator data, providing data for constructing the power system electromagnetic transient model. In this embodiment, component parameters include physical parameters and operating parameters. For example, for typical generator components, operating parameters include rated power, rated voltage, inertia time constant, and transient reactance. For the control loop, operating parameters can be the proportional, integral, and derivative coefficients of a PID controller.

[0074] In this embodiment of the application, the power system volume attribute data can be represented as SYS={MAV, WIND, SUN, R, L, SUM...}, where SYS contains a set of various power devices. Each set of power devices contains specific parameter settings, quantities, and connection relationships of the power devices. For example, MAV={mav1, mav2, mav3...}, mav={type=a, freq=b, Tmav=c, combine(from(sign1, sign2...), to{signa, signb...})...}. In this example, SYS represents the system component set, MAV is the generator set, WIND is the wind turbine unit set, SUN is the photovoltaic unit set, R is the resistor set, L is the inductor set, SUM is the adder set, mav is the generator, type is the generator type (e.g., doubly-fed induction generator a), freq is the frequency setting (e.g., frequency b), Tmav is the rated capacity (e.g., rated capacity c), combine is the connection relationship, from is the source signal, and to is the target transmission signal. In MAV and combine, the numbers represent quantities.

[0075] In this embodiment, the power system modeling feature data can be understood as obtaining the power system's scale characteristics, natural decoupling points, and strongly correlated module information set by analyzing SYS data: CHA={NUM, DEC, STC...}, NUM={comp1=a, comp2=b, comp3=c...}, DEC={comp1=a, comp2=b, comp3=c...}, STC={com-comp2, comp3-comp4-comp5...}. In the example, CHA represents the system attribute set, and NUM is the quantity set. comp1=a means that there are a total of a components comp1, comp2=b means that there are b total of b components comp2, comp3=c means that there are c total of c components comp3, DEC represents the set of naturally decoupled components, and STC represents the set of component connection relationships.

[0076] This can be understood as follows: power system modeling feature data is obtained from all data files of the power system, such as BPA, and parsed to obtain the desired series of data sets, such as scale features, natural decoupling point sets, and strongly correlated module sets, corresponding to the sets shown. Among them, in the component connection relationship set, corresponding component connection lines, i.e., branches, are generated based on the signal transmission relationships between components and line connection relationships. The intersection of a branch and a component is a node.

[0077] S3. Obtain long-distance links from the network topology; using these long-distance links as candidate decoupling points, employ a graph partitioning algorithm with the objective function to divide the network topology into several sub-networks with low coupling. Determine the objective function based on the computational resource utilization efficiency and communication cost of the computational resource data.

[0078] It should be noted that step S3 can be based on the network topology obtained in step S2, where long-distance tie lines are first determined as candidate decoupling points for network topology segmentation, or as the segmentation boundary of the network. In this embodiment, during the network topology segmentation process, cross-regional critical links in the network topology are identified using candidate decoupling points, or optimal subnet partitioning is generated using long-distance tie lines as initial constraints. The objective function of the graph segmentation algorithm is used to achieve network decoupling, generating a low-coupling subnet cluster. Alternatively, a topology feature-driven hierarchical segmentation method can be used, with long-distance connections as boundary constraints, to construct a loosely coupled network partitioning architecture. Specifically, combining the available computing resource data (such as the number of CPU cores and memory) of the power system simulation software, long-distance tie lines are used as the main candidate decoupling points. A graph segmentation algorithm (such as Metis) is employed, with the optimization objectives of minimizing the number of connections (i.e., communication volume) between subnets and balancing the computational load of each subnet, to automatically calculate and select the optimal set of subnetting lines (such as containing several low-coupling subnets).

[0079] For example, in the process of dividing the network topology into subnets, graph segmentation algorithms such as deep learning, edge detection, and region segmentation can be used with the objective function as the objective to divide the network topology into several subnets of similar size and low coupling, which reduces the difficulty of constructing electromagnetic transient models of force systems and improves the efficiency of model construction.

[0080] S4. In the power system simulation software, select the basic typical component models corresponding to each power device in the network topology from the component model library, modify each basic typical component model according to the corresponding component parameters, and obtain the electromagnetic transient simulation components corresponding to each of the power devices.

[0081] It should be noted that step S4 can select the basic typical component models corresponding to each power equipment analyzed in step S2 from the component model library. By modifying the parameters of each basic typical component model according to the corresponding component parameters, the electromagnetic transient simulation component of the corresponding power system can be obtained, which greatly improves the efficiency of component modeling. This electromagnetic transient modeling method for power systems based on the reuse of typical components liberates component technology from cumbersome mathematical derivation and code writing through the parameterized reuse of typical component models, realizing the rapid construction and verification of electromagnetic transient simulation component models and shortening the research and development cycle.

[0082] Understandably, in the process of constructing electromagnetic transient simulation elements for power equipment, step S1 determines the basic typical component model of the power equipment that needs to be constructed. Then, the parameters of the power equipment are extracted from the analytical data in step S2. Based on these parameters, the parameters of the basic typical component model are modified to obtain the electromagnetic transient simulation element for the power equipment. For example, firstly, based on the network topology analysis results, a basic typical component model compatible with the actual power equipment type, voltage level, and connection relationship is automatically matched from a pre-built standardized component model library. Subsequently, through parameter mapping, the nameplate data, test parameters, and operating constraints of the actual power equipment are converted into simulation model parameters. The parameters of the basic typical component model are then modified to modify the simulation model parameters, completing the parameterization correction of the basic typical component model. Finally, an electromagnetic transient simulation element for power equipment that conforms to the IEC 61970 standard and has electromagnetic transient simulation capabilities is generated.

[0083] S5. Based on the load data, generator data, all sub-networks and electromagnetic transient simulation elements of each power device, a model is constructed to obtain the electromagnetic transient model of the power system.

[0084] It should be noted that step S5 automatically models the power system's component distribution (e.g., network topology) and system sub-networks (e.g., sub-networks) using SYS (e.g., load data, generator data, etc.). Component arrangement is required to avoid overlap, and component connections should have minimal intersections. In this embodiment, load data, generator parameters, and electromagnetic transient simulation components (e.g., generators, lines) for each sub-network are all imported into the power system simulation software. Then, they are assembled according to the actual power grid connection method, the parameters are checked for accuracy, and finally, the electromagnetic transient model of the entire power system is generated.

[0085] This can be understood as follows: In constructing an electromagnetic transient model of a power system, the first step is to integrate load dynamic characteristic data, generator electromechanical-electromagnetic coupling parameters (such as generator data), and sub-network topology information. Then, through a hierarchical modeling strategy, the electromagnetic transient simulation components of each sub-network are aggregated according to their electrical connection relationships to construct a refined electromagnetic transient model that includes distributed power sources, dynamic loads, and power equipment. Finally, the model is encapsulated according to the IEC 61970-301 standard to ensure that it meets the accuracy requirements for real-time simulation and stability analysis.

[0086] In this embodiment, the electromagnetic transient modeling method for power systems based on the reuse of typical components avoids tedious and error-prone manual modeling by automatically reading standard data files; the intelligent network splitting algorithm (as shown in the figure segmentation algorithm) ensures that the generated electromagnetic transient model of the power system has good parallelism, creating conditions for simulation acceleration from the source and realizing the automatic and intelligent construction of the electromagnetic transient model.

[0087] It should be noted that the electromagnetic transient modeling method for power systems based on the reuse of typical components obtains a typical component model library, which ensures the correctness and reliability of the basic typical component model; it reduces human error in the automated construction of electromagnetic transient models, while intelligent network subdivision improves the scientific nature and simulation efficiency of electromagnetic transient models.

[0088] This application provides a method for electromagnetic transient modeling of power systems based on the reuse of typical components. The method includes acquiring power system data files and a component model library, as well as acquiring computational resource data from power system simulation software. The data files are parsed to obtain parsed data, which includes network topology and component parameters, load data, and generator data. Long-distance tie lines are obtained from the network topology. Using these long-distance tie lines as candidate decoupling points, the network topology is divided into several low-coupling sub-networks using a graph partitioning algorithm with an objective function. In the power system simulation software, basic typical component models corresponding to each power device in the network topology are selected from the component model library. Each basic typical component model is modified according to its corresponding component parameters to obtain electromagnetic transient simulation components for each power device. A model is constructed based on the load data, generator data, all sub-networks, and the electromagnetic transient simulation components for each power device to obtain the electromagnetic transient model of the power system. The objective function is determined based on the computational resource utilization efficiency and computational resource communication cost of the computational resource data. This electromagnetic transient modeling method for power systems based on the reuse of typical components constructs electromagnetic transient simulation components through a component model library and uses a graph partitioning algorithm to divide the network topology of the power system into sub-networks. In the construction of the electromagnetic transient model of the power system, component modeling and system modeling are coordinated to improve modeling efficiency. This solves the technical problem that the existing component modeling and system modeling are often separated, lack an effective coordination mechanism, and have low modeling efficiency.

[0089] In one embodiment of this application, the component model library includes typical component models of various power devices. Typical component models corresponding to each power device in the network topology are called from the component model library. Each called typical component model is modified according to its corresponding component parameters to obtain the electromagnetic transient simulation components corresponding to each power device, including:

[0090] Configure an external parameter interface for setting parameters for each typical component model;

[0091] Select typical component models corresponding to each power device in the network topology from the component model library and record them as basic typical component models;

[0092] The configuration parameters of the external parameter interface of the corresponding basic typical component model are modified according to the component parameters of each power device to obtain the electromagnetic transient simulation component corresponding to each power device.

[0093] It's important to note that when creating a new electromagnetic transient simulation component, it's unnecessary to write code from scratch. Instead, one first searches for a typical component model with similar or identical functionality in the component model library. Then, by calling this typical component model and modifying the configuration parameter values ​​in its standardized external parameter interface, an electromagnetic transient simulation component instance that meets specific requirements can be quickly generated. This power system electromagnetic transient modeling method based on the reuse of typical components greatly improves modeling efficiency by transforming the development work of components in the power system from "writing algorithm code" to "configuring parameters."

[0094] For example, in constructing electromagnetic transient simulation components, typical component models are encapsulated using a reuse mode. The core code of the typical component model is encapsulated, while standardized external parameter interfaces for variable parameters are provided for direct reuse when constructing new components. By analyzing the function of the target component (such as power equipment), the system automatically parses the minimum component sequence, adhering to the principle of maximizing the reuse rate of typical components and minimizing the workload of new code development. By calling the reuse encapsulation mode of reusable components (such as typical component models) and modifying configuration parameters, reused modules (such as electromagnetic transient simulation components) are constructed. New functions are then written based on the differentiated requirements of the target component. Alternatively, the universality of new functions can be assessed for reuse mode encapsulation, or the entire target component can be encapsulated using a reuse mode to facilitate development.

[0095] In the embodiments of this application, the power system electromagnetic transient modeling method based on the reuse of typical components designs a standardized external parameter interface for typical component models, and achieves rapid construction of new electromagnetic transient simulation components by modifying the configuration parameters of the interface.

[0096] In one embodiment of this application, the computing resource data includes: the number of idle processors, the computing efficiency of each idle processor, the number of processors, and the communication loss between any two processors. Based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data, the objective function is determined as follows:

[0097] Based on the number of idle processors and the computational efficiency of each idle processor, determine the first objective function to maximize the utilization efficiency of computing resources;

[0098] Based on the number of idle processors, the number of processors, and communication losses, determine the second objective function that minimizes the communication cost of computing resources;

[0099] The objective function includes a first objective function and a second objective function.

[0100] It should be noted that the objective function is constructed with power system load (load data) balancing as the goal, combined with available computing resource data, component connection relationships, etc., for automatic modeling. In this embodiment, mathematical optimization ideas can be used for modeling, and the objective function can be set to maximize computing resource utilization efficiency, minimize computing resource communication costs, etc. For example, the following mathematical model can be constructed: the expression of the first objective function is: max sum(n, Rn); the expression of the second objective function is: min sum((n, m), Cnm); where n is the number of idle processors, Rn is the computing efficiency of the processors; Cnm is the communication loss between any two processors, and m is the number of processors. In mathematical solvers such as GUROBI and GAMS, automatic network division can be performed based on the objective function with constraints such as component connection relationships, total computing resource constraints, decoupling constraints of candidate decoupling points, and non-decoupling constraints of strongly associated modules.

[0101] In one embodiment of this application, the computing resource data includes the number of callable message queues; the network topology is divided into several low-coupling sub-networks using a graph segmentation algorithm with long-distance connection lines as candidate decoupling points as the objective function, including:

[0102] Transform the network topology to obtain a directed acyclic graph; determine the maximum number of subnets based on the number of callable message queues;

[0103] Using long-distance connecting lines as candidate decoupling points, and based on the candidate decoupling points and the maximum number of subnets, a graph segmentation algorithm is used to optimize the segmentation of the directed acyclic graph with the goal of minimizing the number of lines across subnets and balancing the number of components in each subnet, resulting in several subnets with low coupling.

[0104] Specifically, based on the electromagnetic transient simulation elements of each sub-network and each power device, load data, and generator data, a sub-model corresponding to each sub-network is determined;

[0105] By connecting all sub-models according to the network topology, the electromagnetic transient model of the power system is obtained.

[0106] It should be noted that the number of callable message queues is used as the maximum number of subnets. Based on the parsed data obtained in step S2, the power system network topology can first be transformed into a directed acyclic graph. Long-distance lines can be naturally decoupled and disconnected first. Then, combined with the number of callable message queues in the computational resource data of the power system simulation software, the maximum number of subnets can be obtained. Based on this, graph partitioning is performed, with the partitioning optimization aiming to minimize the number of lines across subnets and balance the number of components in each subnet. The entire network is automatically divided into several subnets of similar size and low coupling, laying the foundation for subsequent efficient parallel simulation.

[0107] For example, in dividing the network topology into subnetworks, a network topology with loops is transformed into a unidirectional acyclic graph to avoid tasks getting stuck. The maximum number of subnetworks is determined based on the number of messages the system can process. Long-distance lines across regions are selected as cutting points to reduce the dependence of the subnetworks after division. Intelligent splitting algorithms balance the size of the subnetworks while minimizing the number of lines cut, ultimately resulting in several small, highly independent networks.

[0108] In this embodiment, the power system electromagnetic transient modeling method based on the reuse of typical components identifies system scale and long-distance interconnects by automatically parsing data files in formats such as BPA, and intelligently selects sub-networks with the goal of load balancing and minimizing connections, in conjunction with computational resource data.

[0109] Example 2:

[0110] Figure 2 This is a schematic diagram of the framework of the electromagnetic transient modeling device for power systems based on the reuse of typical components described in the embodiments of this application.

[0111] like Figure 2 As shown, this application provides a power system electromagnetic transient modeling device based on the reuse of typical components, including a data acquisition module 10, a data parsing module 20, a network segmentation module 30, a component construction module 40, and a model construction module 50;

[0112] The data acquisition module 10 is used to acquire data files and component model libraries of the power system, as well as computing resource data of the power system simulation software;

[0113] Data parsing module 20 is used to parse data files to obtain parsed data, which includes network topology and component parameters, load data and generator data;

[0114] The network segmentation module 30 is used to obtain long-distance connection lines from the network topology; using the long-distance connection lines as candidate decoupling points, the objective function of the graph segmentation algorithm is used to segment the network topology into several sub-networks with low coupling.

[0115] The component construction module 40 is used to select basic typical component models corresponding to each power device in the network topology from the component model library in the power system simulation software, and modify each basic typical component model according to the corresponding component parameters to obtain the electromagnetic transient simulation components corresponding to each power device.

[0116] The model building module 50 is used to build a model based on load data, generator data, all sub-networks and electromagnetic transient simulation elements of each power device, so as to obtain the electromagnetic transient model of the power system.

[0117] The objective function is determined based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data.

[0118] It should be noted that the content of the modules in the device of Embodiment 2 has already been described in the steps of the method of Embodiment 1, and the content of the modules of the power system electromagnetic transient modeling device based on the reuse of typical components will not be described again in this embodiment. In this embodiment, the power system electromagnetic transient modeling device based on the reuse of typical components automatically reads standard data files through the data acquisition module, data parsing module, network segmentation module, component construction module, and model construction module, avoiding tedious and error-prone manual modeling; the intelligent network segmentation algorithm (as shown in the figure segmentation algorithm) ensures the generation of the electromagnetic transient model of the power system, realizes the automatic and intelligent construction of the electromagnetic transient model, and improves the modeling efficiency.

[0119] In this embodiment of the application, the component model library includes typical component models of various power equipment, and the component construction module 40 includes an interface setting submodule, a calling submodule, and a component construction submodule;

[0120] The interface settings submodule is used to configure an external parameter interface for setting parameters for each typical component model;

[0121] The submodule is called to filter out typical component models corresponding to each power device in the network topology from the component model library, and these are recorded as basic typical component models.

[0122] The component construction submodule is used to modify the configuration parameters of the external parameter interface of the corresponding basic typical component model according to the component parameters of each power device, so as to obtain the electromagnetic transient simulation component corresponding to each power device.

[0123] In this embodiment, the computing resource data includes: the number of idle processors, the computing efficiency of each idle processor, the number of processors, and the communication loss between any two processors. Based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data, the objective function is determined as follows:

[0124] Based on the number of idle processors and the computational efficiency of each idle processor, determine the first objective function to maximize the utilization efficiency of computing resources;

[0125] Based on the number of idle processors, the number of processors, and communication losses, determine the second objective function that minimizes the communication cost of computing resources;

[0126] The objective function includes a first objective function and a second objective function.

[0127] Example 3:

[0128] Figure 3 This is a schematic diagram of the terminal device described in an embodiment of this application.

[0129] like Figure 3 As shown, this application provides a terminal device, including a processor and a memory;

[0130] Memory is used to store program code and transfer the program code to the processor;

[0131] The processor is used to execute the above-described electromagnetic transient modeling method for power systems based on the reuse of typical components, according to the instructions in the program code.

[0132] It should be noted that the processor is used to execute the steps in the above-described embodiment of a power system electromagnetic transient modeling method based on typical component reuse, according to the instructions in the program code. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described system / device embodiments.

[0133] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0134] Terminal devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. Terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that this does not constitute a limitation on the terminal device, which may include more or fewer components than illustrated, or combinations of certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0135] The processor 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, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0136] Memory can be an internal storage unit of a terminal device, such as a hard drive or RAM. Memory can also be an external storage device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal and external storage units. Memory is used to store computer programs and other programs and data required by the terminal device. Memory can also be used to temporarily store data that has been output or will be output.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0138] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0139] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0140] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0141] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part 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 the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0142] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for electromagnetic transient modeling of power systems based on the reuse of typical components, characterized in that, Includes the following steps: Acquire data files and component model libraries of the power system, as well as computational resource data for power system simulation software; The data file is parsed to obtain parsed data, which includes network topology and component parameters, load data, and generator data. Obtain long-distance connection lines from the network topology; Using the long-distance connection line as a candidate decoupling point, the network topology is divided into several sub-networks with low coupling by employing the objective function of a graph partitioning algorithm. In the power system simulation software, basic typical component models corresponding to each power device in the network topology are selected from the component model library. Each basic typical component model is modified according to the corresponding component parameters to obtain the electromagnetic transient simulation components corresponding to each power device. Based on the load data, the generator data, all the sub-networks and the electromagnetic transient simulation elements of each power device, a model is constructed to obtain the electromagnetic transient model of the power system; The objective function is determined based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data.

2. The electromagnetic transient modeling method for power systems based on the reuse of typical components according to claim 1, characterized in that, The component model library includes typical component models of various power devices. Typical component models corresponding to each power device in the network topology are called from the component model library. Each called typical component model is modified according to its corresponding component parameters to obtain the electromagnetic transient simulation components corresponding to each power device, including: Configure an external parameter interface for setting parameters for each of the typical component models; Typical component models corresponding to each power device in the network topology are selected from the component model library and recorded as basic typical component models. The configuration parameters of the external parameter interface of the corresponding basic typical component model are modified according to the component parameters of each power device to obtain the electromagnetic transient simulation component corresponding to each power device.

3. The electromagnetic transient modeling method for power systems based on the reuse of typical components according to claim 1, characterized in that, The computing resource data includes: the number of idle processors, the computing efficiency of each idle processor, the total number of processors, and the communication overhead between any two processors. Based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data, the objective function is determined as follows: Based on the number of idle processors and the computing efficiency of each idle processor, a first objective function for maximizing computing resource utilization efficiency is determined; Based on the number of idle processors, the number of processors, and the communication loss, a second objective function is determined to minimize the communication cost of computing resources. The objective function includes a first objective function and a second objective function.

4. The electromagnetic transient modeling method for power systems based on the reuse of typical components according to claim 1, characterized in that, The computing resource data includes the number of callable message queues; Using the long-distance connection lines as candidate decoupling points, the network topology is divided into several low-coupling sub-networks using the objective function of a graph partitioning algorithm, including: The network topology is transformed to obtain a directed acyclic graph; the maximum number of subnets is determined based on the number of callable message queues. Using the long-distance connection line as a candidate decoupling point, and based on the candidate decoupling point and the maximum number of subnets, a graph segmentation algorithm is used to segment and optimize the directed acyclic graph with the goal of minimizing the number of lines across subnets and balancing the number of components in each subnet, resulting in several subnets with low coupling.

5. The electromagnetic transient modeling method for power systems based on the reuse of typical components according to claim 4, characterized in that, include: The number of callable message queues is used as the maximum number of subnets.

6. The electromagnetic transient modeling method for power systems based on the reuse of typical components according to claim 4, characterized in that, Based on the load data, the generator data, all the sub-networks, and the electromagnetic transient simulation elements of each power device, a model is constructed to obtain the electromagnetic transient model of the power system, including: Based on each sub-network, the electromagnetic transient simulation element of each power device, the load data, and the generator data, determine the sub-model corresponding to each sub-network; By connecting all the sub-models according to the network topology, an electromagnetic transient model of the power system is obtained.

7. A power system electromagnetic transient modeling device based on the reuse of typical components, characterized in that, include: Data acquisition module, data parsing module, network segmentation module, component construction module, and model construction module; The data acquisition module is used to acquire data files and component model libraries of the power system, as well as computing resource data of the power system simulation software. The data parsing module is used to parse the data file to obtain parsed data, which includes network topology and component parameters, load data and generator data; The network segmentation module is used to obtain long-distance connection lines from the network topology; and to segment the network topology using the long-distance connection lines as candidate decoupling points and the objective function of the graph segmentation algorithm to obtain several sub-networks with low coupling. The component construction module is used to select basic typical component models corresponding to each power device in the network topology from the component model library on the power system simulation software, and modify each basic typical component model according to the corresponding component parameters to obtain the electromagnetic transient simulation components corresponding to each power device. The model building module is used to build a model based on the load data, the generator data, all the sub-networks and the electromagnetic transient simulation elements of each power device, so as to obtain an electromagnetic transient model of the power system. The objective function is determined based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data.

8. The electromagnetic transient modeling device for power systems based on the reuse of typical components according to claim 7, characterized in that, The component model library includes typical component models of various power equipment, and the component construction module includes an interface setting submodule, a calling submodule, and a component construction submodule. The interface setting submodule is used to configure an external parameter interface for setting parameters for each of the typical component models; The calling submodule is used to filter out typical component models corresponding to each power device in the network topology from the component model library, and denoted as the basic typical component model. The component construction submodule is used to modify the configuration parameters of the external parameter interface of the corresponding basic typical component model according to the component parameters of each power device, so as to obtain the electromagnetic transient simulation component corresponding to each power device.

9. The electromagnetic transient modeling device for power systems based on the reuse of typical components according to claim 7, characterized in that, The computing resource data includes: the number of idle processors, the computing efficiency of each idle processor, the total number of processors, and the communication overhead between any two processors. Based on the computing resource utilization efficiency and computing resource communication cost of the computing resource data, the objective function is determined as follows: Based on the number of idle processors and the computing efficiency of each idle processor, a first objective function for maximizing computing resource utilization efficiency is determined; Based on the number of idle processors, the number of processors, and the communication loss, a second objective function is determined to minimize the communication cost of computing resources. The objective function includes a first objective function and a second objective function.

10. A terminal device, characterized in that, Including the processor and memory; The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the electromagnetic transient modeling method for power systems based on the reuse of typical components as described in any one of claims 1-6, according to the instructions in the program code.

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