Power transmission and transformation project three-dimensional design checking method and system based on digital twinning

Abstract

The application provides a power transmission and transformation engineering three-dimensional design checking method and system based on digital twinning, relates to the power transmission and transformation checking technical field, and the method comprises the following steps: performing atomic-level division on the power transmission and transformation engineering to obtain a plurality of atomic-level sub-projects; performing multi-granularity engineering decomposition on the power transmission and transformation engineering to obtain H module-level sub-models and N system-level sub-models; performing atomic-level multi-dimensional checking to output atomic-level checking results; updating the power transmission and transformation engineering full-working-condition verification period according to the system-level checking results to perform multi-level dynamic checking closed loop of the power transmission and transformation engineering. The application solves the technical problems that the power transmission and transformation engineering design checking is not comprehensive, the problems cannot be accurately positioned, and the engineering operation reliability and stability are insufficient in the prior art, achieves multi-level accurate checking and dynamic optimization of the power transmission and transformation engineering model from the atomic level to the system level, and improves the technical effects of the reliability and stability of the power transmission and transformation engineering operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission and transformation verification, in particular to a power transmission and transformation engineering three-dimensional design verification method and system based on digital twinning. BACKGROUND

[0002] In the construction of power transmission and transformation engineering, the traditional design verification method has many limitations. On the one hand, two-dimensional design drawings are difficult to intuitively present complex spatial relationships and device layouts, which can easily lead to design defects being discovered only in the construction phase, resulting in increased costs and delayed construction. On the other hand, existing verification methods rely heavily on human experience and lack systematicness and precision, making it difficult to fully detect potential problems in electrical performance and device compatibility.

[0003] The prior art has the technical problem of incomplete power transmission and transformation engineering design verification, which cannot accurately locate problems, resulting in insufficient reliability and stability of the engineering operation. SUMMARY

[0004] The present application provides a power transmission and transformation engineering three-dimensional design verification method and system based on digital twinning, which is used to solve the technical problem of incomplete power transmission and transformation engineering design verification in the prior art, which cannot accurately locate problems, resulting in insufficient reliability and stability of the engineering operation.

[0005] In view of the above problems, the present application provides a power transmission and transformation engineering three-dimensional design verification method and system based on digital twinning.

[0006] In a first aspect of the present application, a power transmission and transformation engineering three-dimensional design verification method based on digital twinning is provided, which comprises:

[0007] According to the three-dimensional design model of the engineering, the power transmission and transformation engineering is divided at the atomic level to obtain a plurality of atomic-level sub-projects; a plurality of atomic-level sub-models of the plurality of atomic-level sub-projects are constructed by multi-dimensional twinning modeling mapping; the power transmission and transformation engineering is decomposed into multiple granularities, and the multi-granularity hierarchical aggregation of the plurality of atomic-level sub-models is performed according to the decomposition result, to obtain H module-level sub-models and N system-level sub-models; the atomic-level multidimensional verification of the plurality of atomic-level sub-models is performed, and the atomic-level verification result is output; if the atomic-level verification result is 1, the timing space collaborative verification of the H module-level sub-models is performed, and the module-level verification result is output; if the module-level verification result is 1, the multi-working-condition dynamic simulation verification of the N system-level sub-models is performed, and the system-level verification result is output; the full-working-condition verification period of the power transmission and transformation engineering is updated according to the system-level verification result, and the multi-level dynamic verification closed loop of the power transmission and transformation engineering is performed based on the full-working-condition verification period.

[0008] In a second aspect of the present application, a power transmission and transformation engineering three-dimensional design verification system based on digital twinning is provided, which comprises:

[0009] The project initial partitioning module is used to perform atomic-level partitioning of the power transmission and transformation project based on the 3D design model, resulting in multiple atomic-level sub-projects. The twin model construction module is used to construct multiple atomic-level sub-models for the multiple atomic-level sub-projects through multi-dimensional twin modeling mapping. The model aggregation execution module is used to perform multi-granularity engineering decomposition of the power transmission and transformation project, and to perform multi-granularity hierarchical aggregation of the multiple atomic-level sub-models based on the decomposition results, resulting in H module-level sub-models and N system-level sub-models. The twin verification execution module is used to perform atomic-level multi-dimensional... The system comprises: a degree-level verification module, which outputs atomic-level verification results; a collaborative verification execution module, which performs time-space collaborative verification on the H module-level sub-models if the atomic-level verification result is set to 1, and outputs module-level verification results; a working condition verification execution module, which performs multi-working-condition dynamic simulation verification on the N system-level sub-models if the module-level verification result is set to 1, and outputs system-level verification results; and a closed-loop verification processing module, which updates the full-working-condition verification cycle of the power transmission and transformation project according to the system-level verification results, and performs multi-level dynamic verification closed-loop of the power transmission and transformation project based on the full-working-condition verification cycle.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] Based on the 3D design model of the power transmission and transformation project, the project is divided into multiple atomic-level sub-projects. Multiple atomic-level sub-models of these sub-projects are constructed through multi-dimensional twin modeling mapping. The power transmission and transformation project is then decomposed into multi-granularity engineering components, and the multiple atomic-level sub-models are aggregated at multiple granular levels to obtain H module-level sub-models and N system-level sub-models. Atomic-level multi-dimensional verification is performed, and atomic-level verification results are output. If the atomic-level verification result is set to 1, temporal-space collaborative verification is performed, and module-level verification results are output. If the module-level verification result is set to 1, multi-condition dynamic simulation verification is performed, and system-level verification results are output. The full-condition verification cycle of the power transmission and transformation project is updated, and a multi-level dynamic verification closed loop is established. This achieves multi-level accurate verification and dynamic optimization of the power transmission and transformation project model from the atomic level to the system level, improving the technical effectiveness of the reliability and stability of the power transmission and transformation project operation. Attached Figure Description

[0012] Figure 1 A flowchart illustrating the three-dimensional design verification method for power transmission and transformation projects based on digital twins provided in this application.

[0013] Figure 2 A schematic diagram of the structure of the digital twin-based three-dimensional design verification system for power transmission and transformation projects provided in this application.

[0014] Figure labeling: Project initial partitioning module 11, twin model construction module 12, model aggregation execution module 13, twin verification execution module 14, collaborative verification execution module 15, working condition verification execution module 16, closed-loop verification processing module 17. Detailed Implementation

[0015] This application provides a three-dimensional design verification method and system for power transmission and transformation projects based on digital twins, which is used to address the technical problems of incomplete design verification and inaccurate positioning in existing power transmission and transformation projects, resulting in insufficient reliability and stability of project operation.

[0016] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0017] Example 1, as Figure 1 As shown, this application provides a three-dimensional design verification method for power transmission and transformation projects based on digital twins, the method comprising:

[0018] Step S100: Based on the three-dimensional design model of the project, the power transmission and transformation project is divided into atomic-level sub-projects.

[0019] Specifically, based on the functional independence of the equipment, the 3D design model of the project is initially divided, breaking down the power transmission and transformation project into multiple initial engineering devices. This step lays the foundation for subsequent precise analysis. Next, the main electrical wiring topology is extracted from the 3D design model, and the multiple initial engineering devices are treated as network nodes. Connection edges are constructed based on the main electrical wiring topology, thus completing the construction of the equipment electrical association topology. Then, a power transmission and transformation fault point is preset. Starting from this fault point, the fault propagation path is calculated in the constructed equipment electrical association topology, resulting in K key fault propagation paths. Then, based on these K key fault propagation paths, a fault impact analysis is performed on the multiple initial engineering devices. Specifically, fault evolution fitting is performed on the K key fault propagation paths to obtain multiple sets of single-path fault impact weights for the multiple initial engineering devices; an equipment-path association matrix is ​​constructed based on the initial engineering devices and key fault propagation paths, and the matrix data is filled using multiple sets of single-path fault impact weights; global weight calculation is performed in the equipment-path association matrix to obtain multiple cross-path weight features for the multiple initial engineering devices. Finally, using weight fluctuation scale and cluster quantity scale as dual-scale clustering constraints, engineering equipment is aggregated based on multiple cross-path weight features to obtain multiple engineering equipment clusters, which then serve as multiple atomic-level sub-projects. Furthermore, the electrical connection topology needs to be extracted from the engineering 3D design model, and electrical connection analysis is performed on the multiple atomic-level sub-projects based on this topology to obtain multiple atomic-level project connection identifiers. Through this series of rigorous operational procedures, the complex power transmission and transformation project is accurately divided into multiple atomic-level sub-projects.

[0020] Step S200: Construct multiple atomic-level sub-models of the multiple atomic-level sub-projects through multidimensional twin modeling mapping.

[0021] Specifically, atomic-level sub-models are constructed using multidimensional twin modeling mapping technology. From a geometric perspective, referencing the shape, size, and spatial layout of each device within the atomic-level sub-project in the engineering 3D design model, 3D modeling technology is used to accurately replicate the geometric shape of each device and their spatial relationships, ensuring a high degree of consistency between the sub-model's geometric structure and the actual atomic-level sub-project. For example, the geometric features of devices such as towers and insulators are accurately represented in the model. From an electrical perspective, based on the extracted electrical connection topology and atomic-level project connection identifiers, combined with the electrical design principles and specifications of power transmission and transformation engineering, an electrical model is constructed that accurately reflects electrical connection methods, current flow, voltage distribution, and electrical equipment performance parameters (such as resistance, inductance, and capacitance). This simulates the electrical operating characteristics of the atomic-level sub-project, providing a basis for subsequent electrical compliance and connectivity verification. From an operational perspective, historical operating data and predicted data for different operating conditions are collected from the devices in the atomic-level sub-project. The changes in operating parameters of the devices under different conditions, such as temperature, pressure, and load, are analyzed to establish a dynamic operating model. For example, by analyzing the changes in oil temperature and winding temperature of a transformer under different load conditions, its operating state can be simulated in an atomic-level sub-model to predict potential fault risks. By integrating model information from multiple dimensions such as geometry, electrical, and operation, an atomic-level sub-model corresponding one-to-one with each atomic-level sub-project is formed.

[0022] Step S300: Perform multi-granularity engineering decomposition on the power transmission and transformation project, and aggregate the multiple atomic-level sub-models at multiple granularities according to the decomposition results to obtain H module-level sub-models and N system-level sub-models.

[0023] Specifically, after completing the atomic-level sub-project division and atomic-level sub-model construction, the power transmission and transformation project undergoes multi-granularity engineering decomposition, and the atomic-level sub-models are then aggregated at multiple granular levels. First, module-level division is performed, dividing the power transmission and transformation project based on the composition of typical modular equipment, resulting in multiple initial module-level sub-projects. Then, a local association rule library is invoked, using it and multiple atomic-level sub-models as aggregation conditions. Based on the atomic-level sub-models, equipment overlap analysis is performed on the initial module-level sub-projects, completing one round of aggregation to obtain R associated module-level sub-projects. Next, multiple initial project equipment are used to traverse the association rule library, invoking equipment baseline association relationships for a second round of aggregation, resulting in H module-level sub-projects. Finally, based on these module-level sub-projects, the atomic-level sub-models are further aggregated through electrical connections, ultimately forming H module-level sub-models. At the system level, the power transmission and transformation project is divided into system-level sub-models. Based on the multi-level verification mechanism, the H module-level sub-models obtained above are integrated. During the integration process, the interaction relationship, functional synergy and role of each module-level sub-model in the whole power transmission and transformation system are comprehensively considered, so as to obtain N system-level sub-models.

[0024] Step S400: Perform atomic-level multi-dimensional verification on the multiple atomic-level sub-models and output the atomic-level verification results.

[0025] Specifically, atomic-level multi-dimensional verification encompasses hierarchically activated geometric dimension verification, electrical compliance verification, and electrical connectivity verification. Hierarchically activated geometric dimension verification, based on the geometric parameters and design specifications of equipment in the atomic-level sub-model, checks the shape, size, spatial location, and inter-device layout relationships of equipment layer by layer, from the overall structure to the details, to ensure they meet design requirements. For example, it precisely verifies geometric information such as tower height and insulator installation angles to determine consistency with design drawings, ensuring the equipment's geometry will not affect subsequent installation, operation, and maintenance. Electrical compliance verification primarily targets the electrical components in the atomic-level sub-model, meticulously verifying the selection, parameter settings, and operating characteristics of electrical equipment according to electrical design standards and specifications. For example, it checks whether the transformer capacity and voltage level meet the actual needs of the power transmission and transformation project, ensuring the selected electrical equipment meets the project's operational requirements while avoiding safety hazards caused by electrical parameter mismatches. Electrical connectivity verification focuses on the correctness and integrity of electrical connections in the atomic-level sub-model. Based on atomic-level engineering connection identifiers and electrical connection topology, it verifies whether the connections between various electrical devices conform to the design intent and whether there are any open circuits, short circuits, or other issues. For example, checking the connection points between transmission lines and equipment such as poles and transformers ensures they are secure and correct, guaranteeing stable current transmission along the designed path and preventing faults caused by electrical connectivity issues. After this series of multi-dimensional verifications, an atomic-level verification result is output, synthesizing all verification results. If the atomic-level sub-model meets design requirements in terms of geometric dimensions, electrical compliance, and electrical connectivity, the atomic-level verification result is set to 1; otherwise, if any verification fails, the atomic-level verification result is set to 0. The atomic-level verification result provides crucial information for subsequent verification steps. If the result is 1, the module-level sub-model will continue to be verified; if the result is 0, adjustments and optimizations to the atomic-level sub-engineering design corresponding to the atomic-level sub-model are necessary to ensure the design quality of the entire power transmission and transformation project.

[0026] Step S500: If the atomic-level verification result is set to 1, then perform temporal-space collaborative verification on the H module-level sub-models and output the module-level verification result.

[0027] Specifically, once the atomic-level verification result is set to 1, indicating that multiple atomic-level sub-projects have passed verification, a temporal-spatial collaborative verification is performed on H module-level sub-models, resulting in the output of module-level verification results. First, from a time perspective, the state changes of the power transmission and transformation project during different operating periods are simulated, such as the changes in operating parameters of each device in the module-level sub-model during peak and off-peak electricity periods, including current, voltage, and power. By analyzing the fluctuations of these parameters over time, the stability and coordination of the equipment operation in the module-level sub-model over time are checked, and whether any abnormalities due to time variations, such as equipment overload or underload operation, occur. From a spatial perspective, the layout and interaction relationships of each device in the module-level sub-model in three-dimensional space are examined. Whether the spatial distance between different devices complies with safety regulations is checked, and whether unreasonable spatial layout will lead to problems such as electromagnetic interference and poor heat dissipation. For example, whether the distance between transformers and other electrical equipment is sufficient to avoid electromagnetic induction interference to the normal operation of equipment due to excessive proximity. When performing temporal-spatial co-verification, both temporal and spatial factors are considered together. The simulation considers the comprehensive impact of spatial layout on equipment operation at different time points, as well as the feedback effect of changes in equipment operating status on the spatial environment. For example, during high-temperature periods, increased heat dissipation demands raise the question of whether the spatial layout of the equipment will affect heat dissipation, thereby impacting the equipment's uptime and performance. Through comprehensive temporal-spatial co-verification, the operating status of H module-level sub-models is evaluated, and module-level verification results are output. If all module-level sub-models perform normally in both temporal and spatial aspects and meet design requirements, the module-level verification result is set to 1; conversely, if any module-level sub-model exhibits problems in either temporal or spatial aspects, the module-level verification result is set to 0. The module-level verification result provides crucial information for determining whether to subsequently verify the system-level sub-models. If the result is set to 1, further verification of the system-level sub-models will be conducted; if the result is set to 0, adjustments and optimizations to the design of the corresponding module-level sub-models are necessary to ensure the overall design quality and operational reliability of the power transmission and transformation project.

[0028] Step S600: If the module-level verification result is set to 1, then perform multi-condition dynamic simulation verification on the N system-level sub-models and output the system-level verification result.

[0029] Specifically, power system simulation software, such as DIgSILENT and PSCAD, is used to perform multi-condition dynamic simulation verification on N system-level sub-models. First, corresponding parameters are set in the software for different operating conditions. For example, for normal operation, voltage, current, and power parameters are set according to design ratings; for overload simulation, current and power parameters are increased proportionally to test the system's performance under loads exceeding the rated capacity. For short-circuit simulation, short-circuit faults are set at specific line nodes to alter electrical connection characteristics; for lightning strike simulation, the lightning impulse module in the software injects lightning current waveforms at specific locations on towers or lines. After setting the operating parameters, the solver in the simulation software performs numerical calculations on the system-level sub-models. The solver solves the circuit equations based on the electrical parameters, topology, and set operating conditions of each device in the sub-model, simulating the dynamic changes of current and voltage throughout the power transmission and transformation system. During the simulation, the software's monitoring function collects real-time operating data of key equipment in the system-level sub-models, such as transformer oil temperature, winding temperature, active power, and reactive power; transmission line current and voltage loss; and overall system performance indicators, such as frequency stability, voltage fluctuation range, and power balance. After the simulation, the collected data is analyzed according to pre-set evaluation criteria. If the operating parameters of key equipment in all system-level sub-models are within safe ranges under various operating conditions, and the overall system performance indicators meet design specifications (e.g., voltage fluctuations within allowable ranges, frequency stability near specified values, and normal power transmission), the system-level verification result is set to 1. If any sub-model experiences abnormal conditions such as equipment parameters exceeding limits or system instability under a certain operating condition (e.g., excessively high transformer oil temperature, line overload tripping, or system voltage collapse), the system-level verification result is set to 0. Through this specific implementation method, multi-condition dynamic simulation verification of N system-level sub-models is completed, and accurate system-level verification results are output, providing strong support for reliability assessment of power transmission and transformation engineering design.

[0030] Step S700: Update the full-condition verification cycle of the power transmission and transformation project according to the system-level verification results, and perform multi-level dynamic verification closed loop of the power transmission and transformation project based on the full-condition verification cycle.

[0031] Specifically, the full-condition verification cycle of the power transmission and transformation project is updated based on the system-level verification results, and a multi-level dynamic verification closed-loop is implemented. If the system-level verification result is 1, it means that under the current design, the power transmission and transformation project has been verified through multi-condition dynamic simulation, and all system-level sub-models can operate stably and reliably, meeting the design requirements. In this case, the full-condition verification cycle is appropriately extended to reduce unnecessary verification frequency, improve work efficiency, and continuously monitor the project's operating status to ensure long-term stable operation. If the system-level verification result is 0, it indicates that there are problems in the design, and the full-condition verification cycle needs to be shortened, and the verification frequency increased. For example, if an anomaly such as equipment damage or system collapse is found in a system-level sub-model under lightning strike conditions, the cycle should be shortened to promptly identify potential problems and reduce risks. After updating the full-condition verification cycle, a multi-level dynamic verification closed loop is entered. Starting from the atomic level, the power transmission and transformation project is again divided into atomic-level sub-models based on the project's three-dimensional design model. The atomic-level sub-models are reconstructed, and the geometric dimensions, electrical compliance, and electrical connectivity of the atomic-level sub-models are checked to ensure that the design at the atomic level is accurate and error-free. Next, module-level verification is performed. The atomic-level sub-models are aggregated at multiple granular levels to obtain module-level sub-models. Then, temporal-space co-verification is executed to analyze the collaborative operation between modules. Finally, system-level verification is performed, again using multi-condition dynamic simulation to verify the system-level sub-models, simulating various operating conditions and checking the overall system performance. This process is repeated continuously to optimize the design, ensuring the accuracy, reliability, and safety of power transmission and transformation engineering design, and guaranteeing the stable operation of the power system.

[0032] In one possible implementation, step S300 further includes:

[0033] Step S310: Divide the power transmission and transformation project into modules, and dynamically aggregate the multiple atomic-level sub-models according to the association rule base and the module-level division results to obtain H module-level sub-models.

[0034] Step S320: Perform system-level partitioning on the power transmission and transformation project, and integrate the H module-level sub-models according to the multi-level verification mechanism and the system-level partitioning results to obtain N system-level sub-models.

[0035] Specifically, firstly, the power transmission and transformation project is divided into modules based on the typical modular equipment composition. For example, based on different types of equipment such as transformers, transmission lines, and switchgear, and their functions, the power transmission and transformation project is divided into multiple initial module-level sub-projects. Next, a local association rule base is invoked, which stores various relationships and constraints between equipment. Using these rules and multiple atomic-level sub-models as aggregation conditions, the initial module-level sub-projects are double-clustered. First, based on the atomic-level sub-models, equipment overlap analysis is performed on multiple initial module-level sub-projects, aggregating initial module-level sub-projects with similar equipment composition and related functions, resulting in R associated module-level sub-projects. Then, multiple initial project equipment are traversed and the local association rule base is invoked, invoking multiple equipment baseline association relationships, again aggregating the R associated module-level sub-projects, outputting H module-level sub-projects. Finally, based on these H module-level sub-projects, multiple atomic-level sub-models are further aggregated through electrical connection relationships, so that each module-level sub-model not only contains a set of related equipment but also accurately reflects the electrical connection relationships between them, thus obtaining H complete module-level sub-models. These module-level sub-models reflect the characteristics of power transmission and transformation projects from the perspective of local modules, laying the foundation for subsequent verification of the collaborative work between modules and overall performance.

[0036] Based on the module-level sub-models, system-level sub-models are constructed. When dividing a power transmission and transformation project into a system-level model, the overall function, operational logic, and interrelationships between modules are comprehensively considered. For example, based on factors such as power transmission flow and voltage level distribution, the power transmission and transformation project is divided into different system levels. Then, according to a multi-level verification mechanism encompassing verification rules and experience from the atomic level to the module level, H module-level sub-models are integrated. During the integration process, the position and role of each module-level sub-model in the system, as well as their interaction methods, are fully considered. For example, the relationships between different module-level sub-models, such as power transmission and signal transmission, are analyzed to ensure that each module-level sub-model can work collaboratively to achieve the overall function of the power transmission and transformation project. In this way, H module-level sub-models are integrated into N system-level sub-models. These system-level sub-models present the complete picture of the power transmission and transformation project at the macroscopic system level, providing a higher level of model support for comprehensively verifying the operational performance of the power transmission and transformation project under different operating conditions.

[0037] In one possible implementation, step S500 further includes:

[0038] Step S510: Perform temporal-space co-verification on the H module-level sub-models and output the verification results of the H twin models.

[0039] Step S520: If any of the H twin model verification results is set to 0, then the module-level verification result is set to 0.

[0040] Step S530: When the module-level verification result is set to 0, locate the P module-level sub-models whose twin model verification result is set to 1.

[0041] Step S540: Perform module coverage filtering on the N system-level sub-models based on the P module-level sub-models to obtain L system-level sub-models.

[0042] Step S550: Perform multi-condition dynamic simulation verification on the L system-level sub-models and output the local verification results.

[0043] Specifically, a temporal-spatial co-validation is performed on H module-level sub-models. From a temporal perspective, the system simulates different operating phases of a power transmission and transformation project, such as peak and off-peak electricity consumption periods, monitoring the changes in operating parameters of equipment in each module-level sub-model over time, including fluctuations in indicators such as current, voltage, and power. From a spatial perspective, the system checks the rationality of the spatial layout of equipment in each module-level sub-model, identifying any issues such as electromagnetic interference or poor heat dissipation caused by improper spatial placement. By comprehensively considering both temporal and spatial factors, the operational status of each module-level sub-model is fully evaluated, ultimately outputting the validation results for H twin models.

[0044] After completing the temporal and spatial co-verification of H module-level sub-models and obtaining H twin model verification results, these results are checked one by one. Since each module-level sub-model plays an indispensable role in the entire power transmission and transformation project design system, a problem in any module can affect the overall performance and safe, stable operation of the project. If any of the H twin model verification results is 0, it means that the corresponding module-level sub-model does not meet design requirements in the temporal or spatial dimensions, such as equipment operating parameters exceeding safe ranges at specific times, or electromagnetic interference caused by equipment spatial layout. Based on this, the module-level verification result is directly set to 0, indicating that the current module-level design has defects and cannot pass the verification.

[0045] When the module-level verification result is set to 0, a comprehensive review and localization of the verification results of the H module-level sub-models' twin models is conducted. Based on pre-defined verification result storage and labeling rules, the dataset of verification results for the H twin models is traversed. In the verification results, 1 represents that the module-level sub-model performs normally in the temporal-space co-verification and meets the design requirements; 0 indicates a problem. Through a data retrieval algorithm, the module-level sub-models with a verification result of 1 are accurately identified, and their number is counted, marking these module-level sub-models with a verification result of 1 as P. These P module-level sub-models exhibit good performance in the temporal-space co-verification, providing crucial reference for subsequent verification and design optimization.

[0046] After identifying P module-level sub-models with a verification result of 1 in their twin models, a comprehensive module coverage screening is performed on N system-level sub-models based on these P well-performing module-level sub-models. Key information such as equipment, functions, and connection relationships contained in the P module-level sub-models is extracted and then compared and analyzed one by one with the N system-level sub-models. During the comparison, the focus is on whether the system-level sub-models completely cover the relevant content of the P module-level sub-models; that is, whether the system-level sub-models include all types of equipment and their corresponding connection relationships in these module-level sub-models, and whether they can achieve the corresponding functions. Only those system-level sub-models that can completely cover the key information of the P module-level sub-models are selected, ultimately resulting in L system-level sub-models. These L system-level sub-models inherit the advantages of the P module-level sub-models to a certain extent, providing more reliable objects for subsequent multi-condition dynamic simulation verification, helping to more accurately evaluate the overall performance of power transmission and transformation projects under normal local module conditions, and providing strong support for design optimization.

[0047] After selecting L system-level sub-models, local verification results are output through multi-condition dynamic simulation. Simulation software is used to simulate the operation of power transmission and transformation projects under various conditions. These conditions include normal operation under rated load, as well as abnormal fault conditions such as overload, short circuit, and lightning strikes, while also considering different environmental conditions such as high temperature, low temperature, high humidity, and strong wind. For each condition, corresponding parameters are set for the L system-level sub-models. For example, under overload conditions, parameters such as current and power are increased to simulate loads exceeding rated values; under short circuit conditions, the electrical connection topology is modified to simulate line short circuit faults; and under lightning strike conditions, lightning current waveforms are injected at specific locations. During simulation, the operating parameters of key equipment in each system-level sub-model are monitored in real time, such as transformer oil temperature, winding temperature, active power, and reactive power, as well as transmission line current and voltage losses. The overall system performance indicators, such as frequency stability, voltage fluctuation range, and power balance, are also monitored. After the simulation, the collected data is analyzed in depth according to pre-set evaluation criteria. If the operating parameters of key equipment in all L system-level sub-models remain within safe ranges under various simulated operating conditions, and the overall system performance indicators meet the design specifications (e.g., voltage fluctuations are within allowable ranges, frequency is stable near specified values, and power transmission is normal), then the local verification result is considered passed. Conversely, if any system-level sub-model exhibits abnormal conditions such as equipment parameters exceeding limits or system instability under a certain operating condition (e.g., transformer oil temperature overheating alarm, line overload tripping, system voltage collapse), the local verification result is considered failed. Through this multi-condition dynamic simulation verification process, the output local verification results can intuitively reflect the operational reliability of these system-level sub-models under different operating conditions, providing an important basis for local optimization of power transmission and transformation engineering design.

[0048] In one possible implementation, step S100 further includes:

[0049] Step S110: Based on the functional independence of the equipment, perform a preliminary division of the three-dimensional design model of the project to obtain multiple initial engineering equipment.

[0050] Step S120: Perform operational fault correlation analysis on the multiple initial engineering devices, and perform device aggregation based on the analysis results to obtain multiple engineering device clusters, and use the multiple engineering device clusters as the multiple atomic-level sub-projects.

[0051] Step S130: Extract the electrical connection topology from the three-dimensional design model of the project, and perform electrical connection analysis on the multiple atomic-level sub-projects based on the electrical connection topology to obtain multiple atomic-level project connection identifiers.

[0052] Specifically, the engineering 3D design model is initially divided based on the functional independence of the equipment. In power transmission and transformation projects, various types of equipment have different functions, such as transformers for voltage transformation and circuit breakers for controlling the opening and closing of circuits. Based on these clear functional differences, the engineering 3D design model is decomposed, separating the equipment with independent functions, thus obtaining multiple initial engineering equipment.

[0053] A fault correlation analysis was performed on multiple initial engineering devices. The main electrical wiring topology was extracted from the 3D engineering design model, and the initial engineering devices were treated as network nodes. Connection edges were constructed based on the main electrical wiring topology to complete the construction of the electrical correlation topology. Then, a transmission and transformation fault point was preset, and fault propagation paths were calculated in the electrical correlation topology starting from this fault point, resulting in K key fault propagation paths. Based on these key fault propagation paths, fault impact analysis was performed on multiple initial engineering devices. By fitting fault evolution to the fault propagation paths, multiple sets of single-path fault impact weights were obtained. Then, an equipment-path correlation matrix was constructed and filled with data, and global weights were calculated to obtain cross-path weight features. Finally, using weight fluctuation scale and cluster quantity scale as dual-scale clustering constraints, engineering devices were aggregated. Closely related devices with similar fault impacts were grouped into multiple engineering device clusters, which serve as multiple atomic-level sub-projects. This fault correlation-based aggregation method fully considers the interrelationships of devices under operational fault conditions, making the division of atomic-level sub-projects more reasonable.

[0054] The electrical connection topology is extracted from the 3D engineering design model. This topology details the electrical connection methods and paths between various devices. Based on this topology, electrical connection analysis is performed on multiple atomic-level sub-projects. Through analysis, the electrical connection relationships between each atomic-level sub-project and other sub-projects are determined, including the start and end points of the connections and the connection types. This ultimately yields multiple atomic-level project connection identifiers. These identifiers provide crucial foundational data for subsequent construction of atomic-level sub-models and electrical verification, ensuring that the electrical connection characteristics of the power transmission and transformation project are accurately reflected in the digital model, thereby guaranteeing the accuracy and reliability of the entire verification process.

[0055] In one possible implementation, step S120 further includes:

[0056] Step S121: Extract the electrical main wiring topology from the three-dimensional design model of the project.

[0057] Step S122: Treat the multiple initial engineering devices as multiple network nodes, and construct the connection edges of the multiple network nodes according to the electrical main wiring topology to complete the construction of the device electrical association topology.

[0058] Step S123: Preset the power transmission and transformation fault point, and calculate the fault propagation path in the electrical association topology of the equipment, starting from the power transmission and transformation fault point, to obtain K key fault propagation paths.

[0059] Step S124: Based on the K key fault propagation paths, perform fault impact analysis on the multiple initial engineering equipment, and aggregate the engineering equipment according to the analysis results to obtain the multiple engineering equipment cluster.

[0060] Specifically, the main electrical wiring topology is extracted from the 3D engineering design model. As the core architecture of electrical connections in power transmission and transformation engineering, the main electrical wiring topology clearly presents the connection relationships between various major electrical devices, such as the electrical connection methods and power transmission paths between transformers, circuit breakers, busbars, and other equipment. This information is an important foundation for subsequent analysis.

[0061] Multiple initial engineering devices are treated as network nodes, and connection edges are constructed based on the previously extracted electrical main wiring topology. In this way, the various independent initial engineering devices are electrically interconnected, forming a complete device electrical interconnection topology. This topology not only visually demonstrates the electrical connections between devices but also provides a clear path and structural framework for subsequent fault propagation analysis.

[0062] To identify K critical fault propagation paths, a depth-first search (DFS) algorithm combined with electrical characteristic analysis is employed. First, based on common fault types and key areas of concern in power transmission and transformation projects, fault points are selected within the electrical interconnection topology. Then, the DFS begins from these fault points. During the search, at each network node (i.e., the node corresponding to the initial engineering equipment), the flow and distribution of fault current at that node are analyzed based on the electrical connection topology information, Ohm's law, Kirchhoff's current law, and voltage law. For example, for nodes connecting multiple branch lines, the current distribution ratio of the fault on different branches is calculated based on parameters such as the resistance and reactance of each line. When reaching the next node along a connection edge, the electrical characteristic analysis is repeated to determine whether the fault will continue to propagate along that path. If equipment on a path cannot operate normally due to excessive fault current or abnormal voltage (judged based on the equipment's rated parameters and fault tolerance), this path is marked as a potential fault propagation path. After the DFS has traversed the entire electrical interconnection topology, all marked potential paths are organized and filtered. Based on the severity of fault propagation (such as the magnitude of the fault current and the importance of the affected equipment), K representative paths with a significant impact on the entire power transmission and transformation system are selected as critical fault propagation paths. These critical fault propagation paths will provide important basis for subsequent fault impact analysis and equipment aggregation of the initial engineering equipment.

[0063] For K key fault propagation paths, fault evolution fitting is performed. By studying the propagation patterns of faults along each path and combining electrical principles and equipment characteristics, multiple sets of single-path fault impact weights for several initial engineering devices are calculated. For example, based on factors such as the impact of fault current on equipment along different paths, equipment tolerance, and the probability of fault occurrence, the impact weight of each device under a single fault propagation path is determined. A device-path association matrix is ​​constructed based on multiple initial engineering devices and the K key fault propagation paths. The calculated multiple sets of single-path fault impact weights are then filled into the matrix, ensuring that each element accurately reflects the degree of impact of the corresponding device under a specific fault propagation path. Then, a global weight calculation is performed on the device-path association matrix, comprehensively considering the impact weights of each device under different paths, resulting in multiple cross-path weight features for multiple initial engineering devices. These features comprehensively demonstrate the overall impact of each device in the entire fault scenario. Finally, the weight fluctuation scale and cluster quantity scale are used as dual-scale clustering constraints. The weight fluctuation scale measures the changes in the degree of impact of equipment under different fault propagation paths, while the cluster quantity scale determines a reasonable range of cluster quantities based on actual engineering needs and experience. Based on multiple cross-path weight features, a clustering algorithm is used to aggregate the initial engineering equipment. During the clustering process, equipment with similar weight features and similar degrees of impact from faults are grouped together, ultimately forming multiple engineering equipment clusters.

[0064] In one possible implementation, step S124 further includes:

[0065] Step S1241: Perform fault evolution fitting on the K key fault propagation paths to obtain multiple sets of single-path fault influence weights for the multiple initial engineering equipment.

[0066] Step S1242: Construct a device-path association matrix based on the multiple initial engineering devices and K key fault propagation paths, and fill the data of the device-path association matrix according to the multiple sets of single-path fault influence weights.

[0067] Step S1243: Perform global weight calculation on the device-path association matrix to obtain multiple cross-path weight features of multiple initial engineering devices.

[0068] Step S1244: Using the weight fluctuation scale and cluster quantity scale as dual-scale clustering constraints, the engineering equipment is aggregated based on the multiple cross-path weight features to obtain the multiple engineering equipment clusters.

[0069] Specifically, for the K key fault propagation paths already identified, mathematical modeling and fitting techniques are used to fit the fault evolution. Based on circuit principles, equipment characteristics, and past power transmission and transformation fault data, the propagation process of the fault along each path is simulated, and the impact of the fault on each initial engineering device at different times is analyzed. This yields multiple sets of single-path fault impact weights for multiple initial engineering devices. These weights reflect the severity of the fault impact on each device under a single fault propagation path.

[0070] A two-dimensional device-path association matrix is ​​constructed based on multiple initial engineering devices and K critical fault propagation paths. The rows of the matrix represent the initial engineering devices, and the columns represent different critical fault propagation paths. Then, the multiple sets of single-path fault impact weights obtained in the previous step are filled into the corresponding positions in the matrix to complete the data filling. In this way, each element in the matrix accurately records the fault impact weight of a specific device under a specific fault propagation path, providing a data foundation for subsequent comprehensive analysis.

[0071] Global weights are calculated for the device-path association matrix populated with data. By comprehensively considering the weight of each device under different fault propagation paths, a weighted average method is used to calculate multiple cross-path weight features for each initial engineering device. These features are no longer limited to the influence of a single path, but rather reflect the overall impact characteristics of the device in the entire fault scenario.

[0072] The weight fluctuation scale and cluster size scale are used as dual-scale clustering constraints. The weight fluctuation scale measures the change in weight of equipment under different fault propagation paths, reflecting the stability of equipment affected by faults. The cluster size scale is a reasonable range of cluster sizes pre-defined based on actual engineering needs, experience, and equipment characteristics. Based on these constraints, the K-Means clustering algorithm is used to aggregate the initial engineering equipment according to multiple cross-path weight features. The algorithm groups equipment with similar cross-path weight features together. After multiple iterations and optimizations, multiple engineering equipment clusters are finally obtained.

[0073] In one possible implementation, step S310 further includes:

[0074] Step S311: Based on the typical modular equipment configuration, the power transmission and transformation project is divided into modules to obtain multiple initial module-level sub-projects.

[0075] Step S312: Locally call the association rule library, and use the local call association rule library and multiple atomic-level sub-models as aggregation conditions to drive the dual clustering of the multiple initial module-level sub-projects to obtain H module-level sub-projects.

[0076] Step S313: Based on the H module-level sub-projects, the multiple atomic-level sub-models are aggregated through electrical connections to obtain the H module-level sub-models.

[0077] Specifically, power transmission and transformation projects are divided into modules based on the typical modular equipment composition. These projects include various equipment such as transformers, transmission lines, and switchgear. Based on the similarities in function, structure, and role of these devices within the project, the project is initially broken down. For example, the transformer responsible for voltage transformation and its related auxiliary equipment are classified as one initial module, while the transmission lines used for power transmission, along with their associated towers and insulators, are grouped into another initial module. This approach yields multiple initial module-level sub-projects.

[0078] Next, a local association rule base is invoked. This rule base stores a large amount of information about the relationships between devices, covering electrical connection requirements, functional coordination rules, and spatial layout constraints. The locally invoked association rule base and multiple atomic-level sub-models are used as aggregation conditions to drive multiple initial module-level sub-projects through dual clustering. First, based on multiple atomic-level sub-models, device overlap analysis is performed on multiple initial module-level sub-projects. Initial module-level sub-projects containing similar devices or with close functional relationships are aggregated in the first round, resulting in R associated module-level sub-projects. Then, multiple initial project devices are used to traverse the locally invoked association rule base, invoking multiple device baseline association relationships. Based on these relationships, the R associated module-level sub-projects are aggregated in the second round, ultimately resulting in H module-level sub-projects. This dual clustering process fully utilizes the information from the association rule base and atomic-level sub-models, making the division of module-level sub-projects more scientific and reasonable, and strengthening the relationships between devices within modules.

[0079] Based on the resulting H module-level sub-projects, multiple atomic-level sub-models are further aggregated through electrical connections. For each module-level sub-project, the electrical connection relationships between the devices represented by its internal atomic-level sub-models are analyzed in detail. Based on the electrical connection topology and electrical parameters, interconnected and closely related atomic-level sub-models are integrated together. For example, for a module-level sub-project containing a transformer and its connected transmission line, the atomic-level sub-models representing the transformer and transmission line are merged and associated according to their actual electrical connection methods. This ensures that the module-level sub-models accurately reflect the electrical characteristics and operating logic of the modules in the power transmission and transformation project, ultimately resulting in H complete module-level sub-models. These module-level sub-models not only contain the corresponding set of equipment but also accurately reflect the electrical connection relationships between the equipment, providing effective model support for subsequent module-level verification and analysis of power transmission and transformation projects.

[0080] In one possible implementation, step S312 further includes:

[0081] Step S3121: Perform device overlap analysis on the multiple initial module-level sub-projects based on the multiple atomic-level sub-models, and aggregate the multiple initial module-level sub-projects in one round according to the analysis results to obtain R related module-level sub-projects.

[0082] Step S3122: Use the multiple initial engineering devices to traverse the local call association rule library and call the multiple device baseline association relationships.

[0083] Step S3123: Based on the multiple device reference association relationships, aggregate the R associated module-level sub-projects in a second round and output the H module-level sub-projects.

[0084] Specifically, based on multiple atomic-level sub-models, equipment overlap analysis is conducted on multiple initial module-level sub-projects. Each atomic-level sub-model represents a specific basic equipment or equipment combination in a power transmission and transformation project. By comparing the atomic-level sub-models contained in each initial module-level sub-project, the degree of equipment overlap and functional similarity between them are determined. For example, if two initial module-level sub-projects both contain atomic-level sub-models representing a certain type of switching equipment and both involve circuit opening and closing control in function, then they have a high degree of overlap in terms of equipment and function. Based on the results of this overlap analysis, initial module-level sub-projects with similar equipment and functions are aggregated in one round, merging closely related parts together to obtain R related module-level sub-projects. This step initially integrates similar modules, reduces redundancy between modules, and makes the module structure clearer.

[0085] The algorithm employs multiple initial engineering devices to traverse a locally invoked association rule base. This rule base stores a large number of pre-defined device baseline associations, covering various aspects such as electrical connection specifications, operational logic relationships, and spatial layout requirements between devices. Each initial engineering device serves as the starting point for the search, retrieving various related associations within the association rule base. For example, for a transformer device, the association rule base can find its standard electrical connection methods with other devices such as circuit breakers and surge arresters, as well as the rules for its collaborative operation with these devices during operation. By traversing this system, multiple device baseline associations are obtained, providing crucial information for subsequent module aggregation.

[0086] Based on the acquired equipment baseline relationships, a second round of aggregation is performed on R related module-level sub-projects. These relationships are applied to the R related module-level sub-projects to check whether the sub-projects meet these relationship requirements. For example, based on electrical connection relationships, module-level sub-projects whose electrical connection tightness was not fully considered in the first round of aggregation are further integrated to ensure that the electrical connections between the sub-projects comply with specifications. According to operational logic relationships, module-level sub-projects that are functionally complementary and operate collaboratively are merged together. After this round of aggregation, H module-level sub-projects are finally output. These module-level sub-projects are more reasonable and complete in terms of equipment composition, functional implementation, and interrelationships, laying a solid foundation for the subsequent construction of a complete module-level sub-model.

[0087] In one possible implementation, step S400 further includes:

[0088] Step S410: The atomic-level multi-dimensional verification includes hierarchically activated geometric dimension verification, electrical compliance verification, and electrical connectivity verification.

[0089] Specifically, atomic-level multi-dimensional verification comprehensively ensures the accuracy and reliability of atomic-level sub-models through hierarchically activated geometric dimension verification, electrical compliance verification, and electrical connectivity verification. Hierarchically activated geometric dimension verification examines the spatial location, size, and distances between devices in the atomic-level sub-model from a spatial layout perspective. Based on the design specifications of power transmission and transformation projects and actual site conditions, 3D modeling is used to ensure that the spatial layout of equipment is reasonable and meets requirements for installation, maintenance, and safe distances. For example, it checks whether the distance between transformers and surrounding equipment complies with regulations for preventing electromagnetic interference and facilitating maintenance, avoiding equipment malfunctions or safety hazards caused by unreasonable spatial layout.

[0090] Electrical compliance verification begins by comparing the rated voltage of each device in the atomic-level sub-model with the system's maximum operating voltage to ensure that the rated voltage of the devices meets the system's operational requirements and can still operate safely and stably even when the system voltage fluctuates by 1.1 times. Secondly, the short-circuit current withstand capability and calculated short-circuit current of the devices are evaluated to ensure that the devices can withstand an impact of at least 1.2 times the calculated short-circuit current in the event of a short-circuit fault, preventing damage due to excessive short-circuit current. Through electrical parameter comparison and standard verification, the atomic-level sub-model is ensured to meet relevant specifications and actual engineering requirements in terms of electrical performance.

[0091] Electrical connectivity verification focuses on the electrical connections between devices in the atomic-level sub-model. Using electrical topology analysis tools, each line connection, electrical node, and loop between devices is checked to ensure that all electrical connections meet design requirements and that there are no open circuits, short circuits, or connection errors. For example, it checks whether the connection between transmission lines and substation equipment is correct, ensuring that current flows smoothly along the expected path, making the entire atomic-level sub-model an electrically complete and reliable system. Through these three dimensions of verification, the atomic-level sub-model is comprehensively checked from different aspects, providing a solid guarantee for the reliability and stability of power transmission and transformation projects.

[0092] Example 2, based on the same inventive concept as the digital twin-based three-dimensional design verification method for power transmission and transformation projects in the previous examples, such as... Figure 2 As shown, this application provides a three-dimensional design verification system for power transmission and transformation projects based on digital twins, wherein the system includes:

[0093] The initial engineering division module 11 is used to divide the power transmission and transformation project into multiple atomic-level sub-projects based on the three-dimensional design model of the project.

[0094] The twin model construction module 12 is used to construct multiple atomic-level sub-models of the multiple atomic-level sub-projects through multidimensional twin modeling mapping.

[0095] The model aggregation execution module 13 is used to perform multi-granularity engineering decomposition on the power transmission and transformation project, and to perform multi-granularity hierarchical aggregation of the multiple atomic-level sub-models based on the decomposition results, to obtain H module-level sub-models and N system-level sub-models.

[0096] The twin verification execution module 14 is used to perform atomic-level multi-dimensional verification on the multiple atomic-level sub-models and output atomic-level verification results.

[0097] The collaborative verification execution module 15 is used to perform temporal-space collaborative verification on the H module-level sub-models if the atomic-level verification result is set to 1, and output the module-level verification result.

[0098] The operating condition verification execution module 16 is used to perform multi-operating condition dynamic simulation verification on the N system-level sub-models if the module-level verification result is set to 1, and output the system-level verification result.

[0099] The closed-loop verification processing module 17 is used to update the full-condition verification cycle of the power transmission and transformation project according to the system-level verification results, and to perform multi-level dynamic verification closed-loop of the power transmission and transformation project based on the full-condition verification cycle.

[0100] Furthermore, the system is also used to implement the following functions:

[0101] The power transmission and transformation project is divided into modules, and the multiple atomic-level sub-models are dynamically aggregated according to the association rule base and the module-level division results to obtain H module-level sub-models; the power transmission and transformation project is divided into systems, and the H module-level sub-models are integrated according to the multi-level verification mechanism and the system-level division results to obtain N system-level sub-models.

[0102] Furthermore, the system is also used to implement the following functions:

[0103] Perform temporal-space co-verification on the H module-level sub-models and output H twin model verification results; if any of the H twin model verification results is set to 0, then the module-level verification result is set to 0; if the module-level verification result is set to 0, locate the P module-level sub-models whose twin model verification results are set to 1; perform module coverage filtering on the N system-level sub-models based on the P module-level sub-models to obtain L system-level sub-models; perform multi-condition dynamic simulation verification on the L system-level sub-models and output local verification results.

[0104] Furthermore, the system is also used to implement the following functions:

[0105] The engineering 3D design model is initially divided based on the functional independence of the equipment to obtain multiple initial engineering equipment; operational fault correlation analysis is performed on the multiple initial engineering equipment, and equipment aggregation is performed based on the analysis results to obtain multiple engineering equipment clusters, which are then used as multiple atomic-level sub-projects; electrical connection topology is extracted from the engineering 3D design model, and electrical connection analysis is performed on the multiple atomic-level sub-projects based on the electrical connection topology to obtain multiple atomic-level engineering connection identifiers.

[0106] Furthermore, the system is also used to implement the following functions:

[0107] The electrical main wiring topology is extracted from the three-dimensional design model of the project; the multiple initial engineering devices are used as multiple network nodes, and the connection edges of the multiple network nodes are constructed according to the electrical main wiring topology to complete the construction of the electrical association topology of the equipment; a power transmission and transformation fault point is preset, and the fault propagation path is calculated in the electrical association topology of the equipment starting from the power transmission and transformation fault point to obtain K key fault propagation paths; based on the K key fault propagation paths, the fault impact analysis is performed on the multiple initial engineering devices, and the engineering devices are aggregated according to the analysis results to obtain the multiple engineering devices cluster.

[0108] Furthermore, the system is also used to implement the following functions:

[0109] Fault evolution fitting is performed on the K key fault propagation paths to obtain multiple sets of single-path fault impact weights for the multiple initial engineering devices; an equipment-path association matrix is ​​constructed based on the multiple initial engineering devices and the K key fault propagation paths, and the data of the equipment-path association matrix is ​​filled according to the multiple sets of single-path fault impact weights; global weight calculation is performed on the equipment-path association matrix to obtain multiple cross-path weight features for the multiple initial engineering devices; the weight fluctuation scale and cluster quantity scale are used as dual-scale clustering constraints, and the engineering devices are aggregated according to the multiple cross-path weight features to obtain the multiple engineering device clusters.

[0110] Furthermore, the system is also used to implement the following functions:

[0111] The power transmission and transformation project is divided into modules based on the typical modular equipment configuration, resulting in multiple initial module-level sub-projects. A local association rule library is invoked, and the local invocation of the association rule library and multiple atomic-level sub-models are used as aggregation conditions to drive the dual clustering of the multiple initial module-level sub-projects, resulting in H module-level sub-projects. Based on the H module-level sub-projects, the multiple atomic-level sub-models are aggregated through electrical connections to obtain the H module-level sub-models.

[0112] Furthermore, the system is also used to implement the following functions:

[0113] Based on the multiple atomic-level sub-models, device overlap analysis is performed on the multiple initial module-level sub-projects. Based on the analysis results, the multiple initial module-level sub-projects are aggregated in one round to obtain R related module-level sub-projects. The multiple initial project devices are used to traverse the local call association rule library and call multiple device benchmark association relationships. Based on the multiple device benchmark association relationships, the R related module-level sub-projects are aggregated in a second round to output the H module-level sub-projects.

[0114] Furthermore, the system is also used to implement the following functions:

[0115] The atomic-level multi-dimensional verification includes hierarchically activated geometric dimension verification, electrical compliance verification, and electrical connectivity verification.

[0116] In summary, any of the methods or steps described above can be stored as computer instructions or programs in various types of computer memory, and the computer instructions or programs can be recognized by various types of computer processors to implement any of the above methods or steps.

[0117] Based on the above specific embodiments of the present invention, any improvements and modifications made to the present invention by those skilled in the art without departing from the principle of the present invention shall fall within the patent protection scope of the present invention.

Claims

1. A power transmission and transformation project three-dimensional design checking method based on digital twinning, characterized in that, The method comprises: According to the three-dimensional design model of the project, the power transmission and transformation project is divided at the atomic level to obtain a plurality of atomic level sub-projects; A plurality of atomic level sub-models of the plurality of atomic level sub-projects are constructed by multi-dimensional twin modeling mapping; The power transmission and transformation project is subjected to multi-granularity engineering decomposition, and multi-granularity hierarchical aggregation of the plurality of atomic level sub-models is performed according to the decomposition result to obtain H module level sub-models and N system level sub-models; The atomic level multi-dimensional verification of the plurality of atomic level sub-models is performed, and the atomic level verification result is output; If the atomic level verification result is 1, the timing space collaborative verification of the H module level sub-models is performed, and the module level verification result is output; If the module level verification result is 1, the N system level sub-models are subjected to multi-working condition dynamic simulation verification, and the system level verification result is output; According to the system level verification result, the full working condition verification period of the power transmission and transformation project is updated, and multi-level dynamic verification closed loop of the power transmission and transformation project is performed based on the full working condition verification period; According to the three-dimensional design model of the project, the power transmission and transformation project is divided at the atomic level to obtain a plurality of atomic level sub-projects, and the method comprises: The preliminary division of the three-dimensional design model of the project is performed based on the functional independence of the equipment to obtain a plurality of initial engineering equipment; The running fault correlation analysis of the plurality of initial engineering equipment is performed, and the equipment aggregation is performed according to the analysis result to obtain a plurality of engineering equipment clusters, and the plurality of engineering equipment clusters are taken as the plurality of atomic level sub-projects; The electrical connection topology is extracted from the three-dimensional design model of the project, and the electrical connection analysis of the plurality of atomic level sub-projects is performed according to the electrical connection topology to obtain a plurality of atomic level engineering connection identifiers.

2. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 1, wherein, The power transmission and transformation project is subjected to multi-granularity engineering decomposition, and multi-granularity hierarchical aggregation of the plurality of atomic level sub-models is performed according to the decomposition result to obtain H module level sub-models and N system level sub-models, and the method comprises: The power transmission and transformation project is subjected to module level division, and the plurality of atomic level sub-models are dynamically aggregated according to the correlation rule library and the module level division result to obtain H module level sub-models; The power transmission and transformation project is subjected to system level division, and the H module level sub-models are integrated according to the multi-level verification mechanism and the system level division result to obtain N system level sub-models.

3. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 1, wherein, The method further comprises: The timing space collaborative verification of the H module level sub-models is performed, and H twin model verification results are output; If any result in the H twin model verification results is 0, the module level verification result is 0; In the case that the module level verification result is 0, the P module level sub-models with the twin model verification result of 1 are located; According to the P module level sub-models, the N system level sub-models are subjected to module coverage screening to obtain L system level sub-models; The L system level sub-models are subjected to multi-working condition dynamic simulation verification, and the local verification result is output.

4. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 1, wherein, The running fault correlation analysis of the plurality of initial engineering equipment is performed, and the equipment aggregation is performed according to the analysis result to obtain a plurality of engineering equipment clusters, and the plurality of engineering equipment clusters are taken as the plurality of atomic level sub-projects, and the method comprises: extracting an electrical main wiring topology from the engineering three-dimensional design model; taking the plurality of initial engineering devices as a plurality of network nodes, and constructing connection edges of the plurality of network nodes according to the electrical main wiring topology, to complete construction of a device electrical correlation topology; presetting a power transmission and transformation fault point, and taking the power transmission and transformation fault point as a starting point to calculate a fault conduction path in the device electrical correlation topology, to obtain K key fault conduction paths; performing fault impact analysis on the plurality of initial engineering devices according to the K key fault conduction paths, and performing engineering device aggregation according to an analysis result, to obtain a plurality of engineering device clusters.

5. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 4, characterized in that, performing fault impact analysis on the plurality of initial engineering devices according to the K key fault conduction paths, and performing engineering device aggregation according to an analysis result, to obtain a plurality of engineering device clusters, the method comprising: performing fault evolution fitting on the K key fault conduction paths, to obtain a plurality of sets of single-path fault impact weights of the plurality of initial engineering devices; constructing a device-path correlation matrix based on the plurality of initial engineering devices and the K key fault conduction paths, and performing data filling of the device-path correlation matrix according to the plurality of sets of single-path fault impact weights; performing global weight calculation in the device-path correlation matrix, to obtain a plurality of cross-path weight features of the plurality of initial engineering devices; taking weight fluctuation scale and cluster quantity scale as double-scale clustering constraints, and performing engineering device aggregation according to the plurality of cross-path weight features, to obtain the plurality of engineering device clusters.

6. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 1, wherein, performing module-level division on the power transmission and transformation project, and dynamically aggregating a plurality of atomic-level sub-models according to an association rule base and a module-level division result, to obtain H module-level sub-models, the method comprising: performing module-level division on the power transmission and transformation project based on typical module device composition, to obtain a plurality of initial module-level sub-projects; locally calling an association rule base, and taking the locally called association rule base and the plurality of atomic-level sub-models as aggregation conditions, to drive double clustering of the plurality of initial module-level sub-projects, to obtain the H module-level sub-models; performing electrical connection aggregation on the plurality of atomic-level sub-models according to the H module-level sub-models, to obtain the H module-level sub-models.

7. The power transmission project three-dimensional design checking method based on digital twinning according to claim 6, characterized in that, locally calling an association rule base, and taking the locally called association rule base and the plurality of atomic-level sub-models as aggregation conditions, to drive double clustering of the plurality of initial module-level sub-projects, to obtain the H module-level sub-models, the method comprising: performing device overlap analysis on the plurality of initial module-level sub-projects according to the plurality of atomic-level sub-models, and performing one-round aggregation of the plurality of initial module-level sub-projects according to an analysis result, to obtain R associated module-level sub-projects; traversing the locally called association rule base using the plurality of initial engineering devices, to call a plurality of device benchmark association relationships; performing two-round aggregation of the R associated module-level sub-projects according to the plurality of device benchmark association relationships, to output the H module-level sub-models.

8. The power transmission and transformation project three-dimensional design checking method based on digital twinning according to claim 1, wherein, The atomic-level multi-dimensional verification comprises hierarchical activated geometric dimension verification, electrical compliance verification, and electrical connectivity verification.

9. A power transmission and transformation project three-dimensional design checking system based on digital twinning, characterized in that, The system is used to implement the digital-twin-based power transmission and transformation project three-dimensional design verification method according to any one of claims 1-8, and the system comprises: an engineering initial division module configured to perform atomic-level division on the power transmission and transformation project according to a three-dimensional design model of the project to obtain a plurality of atomic-level sub-projects; a twin model construction module configured to construct a plurality of atomic-level sub-models of the plurality of atomic-level sub-projects through multi-dimensional twin modeling mapping; a model aggregation execution module configured to perform multi-granularity project decomposition on the power transmission and transformation project, and perform multi-granularity hierarchical aggregation of the plurality of atomic-level sub-models according to a decomposition result to obtain H module-level sub-models and N system-level sub-models; a twin verification execution module configured to perform atomic-level multi-dimensional verification on the plurality of atomic-level sub-models, and output an atomic-level verification result; a collaborative verification execution module configured to perform timing space collaborative verification on the H module-level sub-models if the atomic-level verification result is 1, and output a module-level verification result; a working condition verification execution module configured to perform multi-working condition dynamic simulation verification on the N system-level sub-models if the module-level verification result is 1, and output a system-level verification result; a closed-loop verification processing module configured to update a full-working condition verification cycle of the power transmission and transformation project according to the system-level verification result, and perform multi-hierarchical dynamic verification closed loop of the power transmission and transformation project based on the full-working condition verification cycle.

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