A multi-level graph-model integration method and system for power system modeling

Abstract

The present invention discloses a multi-level graph-model integration method and system for power system modeling, which relates to the technical field of power system modeling, including multi-level decomposition of the power system, multi-level component packaging of the hierarchical subsystems, building an internal topology structure and dynamically generating interface points; adding connection identifiers, connecting multi-level components through interface points, using adaptive topology optimization to form a circuit topology diagram, and outputting a power system model; simulating the power system through the power system model and obtaining simulation data, and performing data verification by interacting with models at each level. The method of the present invention forms a circuit topology diagram and outputs a power system model by using adaptive topology optimization technology, thereby improving the efficiency of power transmission and the overall stability of the system, and enhancing the system operation efficiency; simulating and obtaining simulation data through the power system model improves the safety and predictability of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power system modeling, and in particular to a multi-level graph-model integration method and system for power system modeling. Background Art

[0002] The modeling and simulation technology of power system is one of the core technologies in the field of power engineering, involving the design, planning, operation and maintenance of the system. Since the widespread application of power systems, in order to cope with the growing power demand and complex network structure, related technologies have gone through several stages of development. Early power system models mainly focused on simple power grid analysis, such as load flow analysis and fault analysis. These models are usually calculated based on static network structures. With the development of computing technology, dynamic simulation technology has begun to be applied, allowing engineers to simulate the dynamic behavior of power grids under different operating conditions, such as voltage stability and transient response. After entering the 21st century, with the widespread access of renewable energy and the promotion of smart grid technology, power system modeling faces new challenges and demands. The development of these technologies has promoted the emergence of advanced modeling methods, such as real-time simulation and distributed simulation, as well as simulation of complex power management systems (EMS) and distribution management systems (DMS). These advanced models are able to process large-scale data and support more sophisticated power grid management decisions, including reliability analysis, asset management and optimized scheduling of power systems.

[0003] Although significant progress has been made in power system modeling technology, existing technologies still have several shortcomings, especially in terms of the ability to handle large-scale and highly complex power grids. First, existing power system modeling methods usually face challenges in dealing with large-scale integrated renewable energy and distributed resources. The access of these resources increases the dynamic complexity of the power grid, and existing static or simplified dynamic models often cannot accurately reflect this complexity. With the transformation of power grids to smart grids, higher requirements are placed on real-time modeling and simulation of power systems. Existing technologies still have limitations in real-time data processing and instant decision support, such as large delays, insufficient accuracy and lack of adaptability. In addition, multi-level system interactions and data integration are also difficult to fully achieve with existing models, which limits the application of models in comprehensive optimization and refined management of power systems. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the existing power system modeling methods have high delay, low accuracy, low reliability, and how to solve the deficiencies in real-time data processing and system interaction for modeling and simulation of multi-level power systems.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a multi-level graph-model integration method for power system modeling, comprising decomposing the power system into multiple levels, encapsulating the multi-level components of the hierarchical subsystems, building an internal topology structure and dynamically generating interface points; adding connection identifiers, connecting the multi-level components through the interface points, using adaptive topology optimization to form a circuit topology diagram, and outputting a power system model; simulating the power system through the power system model and obtaining simulation data, and performing data verification by interacting with models at each level.

[0007] As a preferred scheme of the multi-level graph-model integration method for power system modeling described in the present invention, wherein: the multi-level component packaging includes analyzing the power system, determining the function and operation mode of the power system, and decomposing the power system into multiple levels, the hierarchical content includes system level, energy production level, transmission and distribution level, control and operation level, and each level is refined into subsystems; the subsystems at the system level include the overall management system and the monitoring center; the subsystems at the energy production level include thermal power plants, nuclear power plants, wind farms, and solar power plants; the subsystems at the transmission and distribution level include high-voltage transmission networks, distribution networks, and substations; the subsystems at the control and operation level include regional dispatching centers, automatic control systems, and fault detection systems; the hierarchical subsystems are packaged with multiple levels of components, a hierarchical index tree is constructed, and subsystems are added and deleted by automatically updating the nodes in the hierarchical index tree, and each node in the hierarchical index tree It is expressed as:

[0008] ;

[0009] in, is the index of the node, is the unique identifier of the node, is the index of the node's parent node, is the index of all child nodes; adding a node is represented by:

[0010] ;

[0011] in, Represents the index of all child nodes belonging to the parent node, Represents an assignment operation. Represents an add operation, adding the index of the new node to the list of child nodes of the parent node. The index of the newly added node A collection of; deleting a node is represented by:

[0012] ;

[0013] in, Indicates a delete operation, which removes the node from the parent node's child node list. The index of the node to be deleted A collection of .

[0014] As a preferred scheme of the multi-level graphic model integration method for power system modeling described in the present invention, wherein: the construction of the internal topology structure and the dynamic generation of interface points include defining the functions of each component, including power conversion, voltage adjustment, and signal processing, determining the connection requirements between components, including voltage, current and signal compatibility, and designing components in the electrical structure including transformers, capacitors, switches, and control logic. The system dynamically generates external input ports and output ports through the internal topology, defines the interface, determines the type of interface provided by each component to the outside, and dynamically configures the interface. Based on the scalability and compatibility of the system, the interface is automatically configured through the internal topology of the component and the external connection requirements, and the interface is integrated into the automatic control system of the component. The interface is dynamically adjusted through the system status and external commands.

[0015] As a preferred solution of the multi-level graph-model integration method for power system modeling described in the present invention, wherein: the use of adaptive topology optimization to form a circuit topology diagram includes adding connection identifiers, connecting multi-level components through interface points, and the connection identifiers display the connection mode, direction and attributes between different subsystems, integrating the hierarchical index tree structure with the adaptive topology optimization algorithm, optimizing the network structure through the hierarchical relationship of nodes and the dynamic interface generation characteristics of the subsystem, and the hierarchical optimization network structure function of the circuit topology diagram It is expressed as:

[0016] ;

[0017] in, represents the position vector of the network node, represents the hierarchical connection identification matrix, represents the level index matrix, represents a matrix derived from the hierarchical index tree, n represents the total number of nodes in the network, represents the load demand between nodes i and j, which is a measure of the power demand. Represents the physical distance between nodes i and j, which directly affects the connection quality. Represents the distance decay parameter that is dynamically adjusted according to the parent-child relationship in the hierarchical index tree. When i is the parent or child of j, The value is 2, which increases the connection priority. Represents the distance attenuation parameter, which is used to adjust the effect of distance on connection strength. represents the tuning parameters for the connection quality and interface flexibility, Indicates whether there is a direct hierarchical relationship between node i and node j. When node i and node j are directly connected in the hierarchical index tree, , when node i and node j are not directly connected in the hierarchical index tree, , Indicates whether nodes i and j dynamically generate interface points through the subsystem. When the interface between nodes i and j is dynamically generated based on system requirements and conditions, , when the interface between nodes i and j is not dynamically generated based on system requirements and conditions, , Indicates whether there is a direct parent-child relationship between nodes i and j. When node i is the direct parent or child of node j, , when node i is not the direct parent or child of node j, .

[0018] The output result of the hierarchical optimization network structure function based on the circuit topology diagram is , the node level is optimized by adjusting the parameters in the level optimization network structure function.

[0019] when When the node level reaches the optimization standard, the node connections are drawn to form a circuit topology diagram.

[0020] As a preferred solution of the multi-level graph-model integration method for power system modeling described in the present invention, the output power system model includes comparing and analyzing the circuit topology diagram after node optimization with the power system structure, identifying the nodes and connections in the topology and evaluating the compatibility, checking the correct transmission and execution of data flows and control commands in the new topology, modeling all subsystems and levels, and the program automatically integrates the model into a complete power system model, combines the actual parameters of the power system, and generates a model file in CIM format.

[0021] As a preferred solution of the multi-level graphic-model integration method for power system modeling described in the present invention, the acquisition of simulation data includes configuring a host computer interface to receive interactive data of models at each level of the power system, including real-time data of generator sets, real-time data of transformers, and real-time data of protection devices. The interface program checks and re-aggregates the interactive data, verifies the data integrity and format, and the aggregated data is encapsulated into a data packet based on the TCP / IP protocol and sent to a simulation server. After receiving the data packet, the simulation server interacts with the system model through the received data at each level.

[0022] As a preferred solution of the multi-level graphic-model integration method for power system modeling described in the present invention, the data verification includes that when simulation is performed, the server continuously exchanges data with the host computer interface, updates the simulation status and results, continuously monitors the simulation results, adjusts the model parameters or simulation settings in real time, and generates a simulation report based on the simulation results for reference by system engineers and decision makers to perform system optimization, fault analysis and future planning.

[0023] Another object of the present invention is to provide a multi-level graph-model integrated system for power system modeling, which can connect multi-level components through interface points by adding connection identifiers, use adaptive topology optimization to form a circuit topology diagram, and output a power system model, thereby solving the problem of low reliability in current power system modeling.

[0024] As a preferred solution of the multi-level graph-model integrated system for power system modeling described in the present invention, it includes: a system hierarchical module, a topology optimization module, and a circuit simulation module; the system hierarchical module is used to decompose the power system into multiple levels, encapsulate multi-level components of the multi-level subsystems, build an internal topological structure and dynamically generate interface points; the topology optimization module is used to add connection identifiers, connect multi-level components through interface points, use adaptive topology optimization to form a circuit topology diagram, and output a power system model; the circuit simulation module is used to simulate the power system through the power system model and obtain simulation data, and perform data verification by interacting with models at each level.

[0025] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a multi-level graphic model integration method for power system modeling.

[0026] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a multi-level graph-model integration method for power system modeling.

[0027] Beneficial effects of the present invention: The multi-level graph-model integration method for power system modeling provided by the present invention realizes effective management and simplification of the complex structure of the power system by decomposing the power system into multiple levels and encapsulating the multi-level subsystems into multiple levels of components, which not only enhances the modularity of the system, but also improves the flexibility and maintainability of the design. By building an internal topological structure and dynamically generating interface points, it supports system scalability and adaptability, allowing the power system to quickly adapt to changing operational needs and environmental changes, reducing the complexity of design and operation and maintenance, and improving the response speed and reliability of the system. By adding connection identifiers and connecting multi-level components using interface points, It achieves high customization and optimization of circuit connections, adopts adaptive topology optimization technology to form a circuit topology diagram and output a power system model, dynamically adjusts the network structure according to actual operation data and system status, improves the efficiency of power transmission and the overall stability of the system, reduces energy loss and improves system operation efficiency; simulates and obtains simulation data through the power system model, realizes comprehensive monitoring and evaluation of the operation status of the power system, and performs data verification through interaction with models at all levels, ensuring the accuracy of data and the reliability of simulation results, and improving the safety and predictability of the power system. The present invention achieves better results in terms of reliability, efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 An overall flow chart of a multi-level graph-model integration method for power system modeling provided in the first embodiment of the present invention.

[0030] Figure 2 An overall flow chart of a multi-level graph-model integration system for power system modeling provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0032] Example 1

[0033] Reference Figure 1 , as an embodiment of the present invention, provides a multi-level graph-model integration method for power system modeling, comprising:

[0034] S1: Decompose the power system into multiple levels, encapsulate the subsystems into multiple levels of components, build the internal topology and dynamically generate interface points.

[0035] Furthermore, the multi-level component packaging includes analyzing the power system, determining the functions and operation modes of the power system, and decomposing the power system into multiple levels, including system level, energy production level, transmission and distribution level, control and operation level, and breaking down each level into subsystems; the subsystems at the system level include the overall management system and the monitoring center; the subsystems at the energy production level include thermal power plants, nuclear power plants, wind farms, and solar power plants; the subsystems at the transmission and distribution level include high-voltage transmission networks, distribution networks, and substations; the subsystems at the control and operation level include regional dispatching centers, automated control systems, and fault detection systems; the subsystems at the hierarchical level are packaged in multiple levels, a hierarchical index tree is constructed, and subsystems are added and deleted by automatically updating the nodes in the hierarchical index tree. Each node in the hierarchical index tree It is expressed as:

[0036] ;

[0037] in, is the index of the node, is the unique identifier of the node, is the index of the node's parent node, is the index of all child nodes; adding a node is represented by:

[0038] ;

[0039] in, Represents the index of all child nodes belonging to the parent node, Represents an assignment operation. Represents an add operation, adding the index of the new node to the list of child nodes of the parent node. The index of the newly added node A collection of; deleting a node is represented by:

[0040] ;

[0041] in, Indicates a delete operation, which removes the node from the parent node's child node list. The index of the node to be deleted A collection of .

[0042] It should be noted that building the internal topology and dynamically generating interface points includes defining the functions of each component, including power conversion, voltage adjustment, and signal processing, determining the connection requirements between components, including voltage, current, and signal compatibility, and designing components in the electrical structure, including transformers, capacitors, switches, and control logic. The system dynamically generates external input ports and output ports through the internal topology, defines the interface, determines the type of interface provided by each component to the outside, and dynamically configures the interface. Based on the scalability and compatibility of the system, the interface is automatically configured through the internal topology of the component and the external connection requirements, and the interface is integrated into the component's automation control system. The interface is dynamically adjusted through the system status and external commands.

[0043] It should also be noted that by defining multiple levels such as system level, energy production level, transmission and distribution level, and control and operation level, each level is further refined into specific subsystems. For example, the energy production level includes different types of power plants. This decomposition allows each level to focus on its core functions, improving management efficiency and response speed. In this process, the nodes of each level are given unique identifiers, making management in the hierarchical index tree (such as adding or deleting nodes) very intuitive and systematic. By defining the functions of each component in the internal topology structure and dynamically generating input and output ports, the present invention allows the system to adjust the connection mode as needed during operation, thereby improving the adaptability of the system. For example, when the system state or external command changes, the interface can be automatically reconfigured to ensure that the power system can continue to operate stably. The introduction of multi-level component packaging and dynamic interface generation technology not only makes the structure of the power system more reasonable, but also improves the system's ability to respond quickly to environmental changes, which is very valuable in improving the reliability and efficiency of power supply, especially in the face of high load demand or system-level failures.

[0044] S2: Add connection identifiers, connect multi-level components through interface points, use adaptive topology optimization to form a circuit topology diagram, and output the power system model.

[0045] Furthermore, the circuit topology diagram formed by adaptive topology optimization includes adding connection identifiers, connecting multi-level components through interface points, and the connection identifiers show the connection mode, direction and attributes between different subsystems. The hierarchical index tree structure is integrated with the adaptive topology optimization algorithm, and the network structure is optimized through the hierarchical relationship of nodes and the dynamic interface generation characteristics of subsystems. The hierarchical optimization network structure function of the circuit topology diagram It is expressed as:

[0046] ;

[0047] in, Represents the location vector of a network node. The key is to consider the physical distance between nodes, which is crucial to optimizing the quality of network connections. Represents the hierarchical connection identification matrix, indicating whether there is a direct hierarchical relationship between nodes, which is the basis for understanding and implementing hierarchical control. Represents a hierarchical index matrix, which is used to dynamically express the interface generation between nodes and enhance the system's adaptive capabilities. represents a matrix derived from the hierarchical index tree, n represents the total number of nodes in the network, represents the load demand between nodes i and j, which is a measure of the power demand. Represents the physical distance between nodes i and j, which directly affects the connection quality. Represents the distance decay parameter that is dynamically adjusted according to the parent-child relationship in the hierarchical index tree. When i is the parent or child of j, The value is 2, which increases the connection priority. Represents the distance attenuation parameter, which is used to adjust the effect of distance on connection strength. In power systems, the longer the distance, the higher the cost and complexity of establishing a stable connection. As the distance increases, the more significant the effect of distance is in the attenuation function, causing the strength of long-distance connections to decrease faster. It is usually between 0.01 and 1, depending on the physical size of the network and the sensitivity of the connection cost. If the distance in the power system has a greater impact on the connection cost, a value close to 1 should be selected. If the distance has a smaller impact, a smaller value, such as 0.1, can be selected. Indicates the adjustment parameters of connection quality and interface flexibility. This is an adjustment connection flag. and dynamic interface generation Parameters that affect the final result, The larger the value, the more attention is paid to the contribution of these technical parameters to network optimization. This is usually used to emphasize the importance of connection quality and interface flexibility. It is generally between 0.5 and 10. If the performance of the system is very sensitive to connection quality and interface flexibility (such as high reliability systems), a higher value can be selected. Otherwise, a medium or low value can be selected. Indicates whether there is a direct hierarchical relationship between node i and node j. When node i and node j are directly connected in the hierarchical index tree, , when node i and node j are not directly connected in the hierarchical index tree, , Indicates whether nodes i and j dynamically generate interface points through the subsystem. When the interface between nodes i and j is dynamically generated based on system requirements and conditions, , when the interface between nodes i and j is not dynamically generated based on system requirements and conditions, , Indicates whether there is a direct parent-child relationship between nodes i and j. When node i is the direct parent or child of node j, , when node i is not the direct parent or child of node j, .

[0048] The output result of the hierarchical optimization network structure function based on the circuit topology diagram is , the node level is optimized by adjusting the parameters in the level optimization network structure function.

[0049] when When the node level reaches the optimization standard, the node connections are drawn to form a circuit topology diagram.

[0050] It should be noted that the output power system model includes comparing and analyzing the circuit topology diagram after node optimization with the power system structure, identifying the nodes and connections in the topology and evaluating the compatibility, checking the correct transmission and execution of data flows and control commands in the new topology, modeling all subsystems and levels, and the program automatically integrates the model into a complete power system model, combining the actual parameters of the power system, and generating a model file in CIM format.

[0051] It should also be noted that when the condition that i and j are not equal is mentioned, this is to ensure that a node is not compared or connected to itself. In the power network or any graphical structure, a node itself does not need to establish a connection with itself. Therefore, when discussing the relationship between two nodes or calculating the distance or connection strength between two nodes in the summation process, two different nodes are always considered. According to the changes in system requirements and external conditions, the network connection is dynamically adjusted. This is often overlooked in the prior art, resulting in the system not responding quickly or effectively when an emergency occurs. The present invention ensures that the power system can quickly adapt to load changes by adjusting the interface configuration in real time, improves the stability and flexibility of the system, and optimizes the power network structure by combining the hierarchical relationship and dynamic interface characteristics to make it more efficient and reliable. Traditional power system design often ignores the possibility of dynamic interaction and optimization between levels. The present invention achieves more accurate load distribution and energy utilization by introducing a hierarchical optimization network structure function, reduces energy loss, and optimizes the system according to actual operation data and performance indicators by automatically adjusting the parameters in the hierarchical optimization network structure function. This continuous optimization process makes the power system not only efficient in the design stage, but also continuously improves performance and efficiency in long-term operation.

[0052] S3: Simulate the power system through the power system model and obtain simulation data, and verify the data by interacting with models at all levels.

[0053] Furthermore, obtaining simulation data includes configuring the upper computer interface to receive interactive data from models at all levels of the power system, including real-time data of generator sets, real-time data of transformers, and real-time data of protection devices. The interface program checks and re-aggregates the interactive data, verifies the data integrity and format, and the aggregated data is encapsulated into a data packet based on the TCP / IP protocol and sent to the simulation server. After receiving the data packet, the simulation server interacts with the system model through the received data at all levels.

[0054] It should be noted that data verification includes when simulation is being performed, the server continuously exchanges data with the host computer interface, updates the simulation status and results, continuously monitors the simulation results, adjusts the model parameters or simulation settings in real time, and generates simulation reports based on the simulation results for reference by system engineers and decision makers for system optimization, fault analysis and future planning.

[0055] It should also be noted that, through the intelligent design of the host computer program, the integrity and format correctness of the data can be automatically checked, and then the data can be encapsulated into a data packet based on the TCP / IP protocol and sent to the simulation server. The content of our invention is superior to the traditional manual or semi-automatic data processing method, and improves the speed and accuracy of data processing, so that the system can reflect the current power grid status in real time and provide instant data support for system decision-making. The server can dynamically adjust the parameters of the simulation model according to the received data, which enhances the adaptability and accuracy of the simulation. In addition, the server continuously exchanges data with the host computer, updates the simulation status and results in real time, and ensures the continuity and real-time nature of the simulation process. This continuous monitoring and instant feedback mechanism is often missing in the prior art, and can improve the efficiency of fault diagnosis and the safety of system operation.

[0056] Example 2

[0057] An embodiment of the present invention provides a multi-level graph-model integration method for power system modeling. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0058] First, a set of actual operation data of the power system is collected, including the output of different power stations, the operating status of substations, and load demand data. These data are obtained from the system's historical records and real-time monitoring system. The entire power system is decomposed into multiple levels, involving the system level, energy production level, transmission and distribution level, and control and operation level. The subsystems of each level are configured as multi-level components, and a detailed internal topology design is performed to ensure that all interface points can be dynamically generated and the connection identifiers of each level are correctly set. The multi-level components are connected using adaptive topology optimization technology, which includes analyzing the dynamic demand and real-time data of power flow to ensure that the circuit topology diagram can effectively reflect the operation requirements of the power system. A detailed simulation is performed through the set power system model to simulate various operation scenarios, such as high load, equipment failure, and energy scheduling. Various data in the simulation process are collected, interacted with the hierarchical model, and data verification is performed to ensure the accuracy and consistency of the simulation data, especially at the input and output points of the model. Refer to Table 1 to record and analyze the experimental data.

[0059] Table 1 Experimental data record table

[0060]

[0061] According to the analysis of the tabular data, it can be observed that the average load management at the system level shows the optimized distribution efficiency, reduces energy losses, stabilizes the average load at a high level, and ensures the stability of the system operation. The energy production level maintains a high voltage stability index while maintaining high output, indicating the effectiveness of the optimization model in maintaining production stability. The fault response time at the transmission level is short and the energy loss is low, showing the improvement of line optimization and rapid fault response capabilities. The fault response time at the control level is the fastest, indicating that the sensitivity and rapid scheduling capabilities of the control system have been improved. These data not only demonstrate the effectiveness of the multi-level graph-model integration method in power system modeling, but also reflect the improvements of our invention in system efficiency, stability, response speed and optimization cycle.

[0062] Example 3

[0063] Reference Figure 2 , as an embodiment of the present invention, provides a multi-level graphical model integration system for power system modeling, including a system hierarchical module, a topology optimization module, and a circuit simulation module.

[0064] The system hierarchical module is used to decompose the power system into multiple levels, encapsulate multi-level components of the multi-level subsystems, build the internal topology structure and dynamically generate interface points; the topology optimization module is used to add connection identifiers, connect multi-level components through interface points, use adaptive topology optimization to form a circuit topology diagram, and output the power system model; the circuit simulation module is used to simulate the power system through the power system model and obtain simulation data, and perform data verification by interacting with models at each level.

[0065] If the function is implemented in the form of 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, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), disk or optical disk, etc. Various media that can store program codes.

[0066] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0067] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0068] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logical function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A multi-level graph-model integration method for power system modeling, characterized in that: include: Decompose the power system into multiple levels, encapsulate the subsystems into multiple levels of components, build the internal topology and dynamically generate interface points; Add connection identifiers, connect multi-level components through interface points, use adaptive topology optimization to form a circuit topology diagram, and output the power system model; The circuit topology diagram formed by adaptive topology optimization includes adding connection identifiers, connecting multi-level components through interface points, and the connection identifiers show the connection mode, direction and attributes between different subsystems. The hierarchical index tree structure is integrated with the adaptive topology optimization algorithm, and the network structure is optimized through the hierarchical relationship of nodes and the dynamic interface generation characteristics of subsystems. The hierarchical optimization network structure function F'(x, K, S, H) of the circuit topology diagram is expressed as: Where x represents the position vector of the network node, K represents the hierarchical connection identification matrix, S represents the hierarchical index matrix, H represents the matrix derived from the hierarchical index tree, n represents the total number of nodes in the network, and L ij represents the load demand between nodes i and j, which is a measure of the power demand. ij represents the physical distance between nodes i and j, which directly affects the connection quality, δ ij Represents the distance decay parameter dynamically adjusted according to the parent-child relationship in the hierarchical index tree. When i is the parent or child of j, δ ij The value is 2, which enhances the connection priority. α represents the distance attenuation parameter, which is used to adjust the impact of distance on connection strength. γ represents the adjustment parameter for connection quality and interface flexibility. K ij Indicates whether there is a direct hierarchical relationship between node i and node j. When node i and node j are directly connected in the hierarchical index tree, K ij = 1, when node i and node j are not directly connected in the hierarchical index tree, K ij =0, S ij Indicates whether nodes i and j dynamically generate interface points through the subsystem. When the interface between nodes i and j is dynamically generated based on system requirements and conditions, S ij = 1, when the interface between nodes i and j is not dynamically generated based on system requirements and conditions, S ij =0,H ij Indicates whether there is a direct parent-child relationship between nodes i and j. When node i is the direct parent or child of node j, H ij = 1, when node i is not the direct parent or child of node j, H ij =0; The output result of the hierarchical optimization network structure function based on the circuit topology diagram is When , the node level is optimized by adjusting the parameters in the level optimization network structure function; when When the node level reaches the optimization standard, the node connections are drawn to form a circuit topology diagram; The power system is simulated and simulation data is obtained through the power system model, and data verification is performed by interacting with models at all levels.

2. The multi-level graph-model integration method for power system modeling according to claim 1, characterized in that: The multi-level component packaging includes analyzing the power system, determining the function and operation mode of the power system, decomposing the power system into multiple levels, including the system level, energy production level, transmission and distribution level, control and operation level, and breaking down each level into subsystems; System-level subsystems include overall management system and monitoring center; The energy production level subsystems include thermal power plants, nuclear power plants, wind farms, and solar power plants; Subsystems at the transmission and distribution level include high-voltage transmission grid, distribution network, and substations; The subsystems at the control and operation level include the regional dispatch center, automated control system, and fault detection system; Multi-level component packaging is performed on the hierarchical subsystems to build a hierarchical index tree. Subsystems are added and deleted by automatically updating the nodes in the hierarchical index tree. Each node N in the hierarchical index tree is represented as: N(i)=(id,parent,children) Among them, i is the index of the node, id is the unique identifier of the node, parent is the index of the parent node of the node, and children is the index of all child nodes; Adding a node is represented as: children parent ←children parent ∪{i new } Among them, children parent represents the index of all child nodes belonging to the parent node, ← represents the assignment operation, ∪ represents the addition operation, which adds the index of the new node to the list of child nodes of the parent node, {i new The index i of the newly added node new A collection of; Deleting a node is represented by: children parent ←children parent \{i remove } Among them, \ represents the delete operation, which removes the node from the child node list of the parent node, {i remove The index i of the node to be deleted remove A collection of .

3. The multi-level graph-model integration method for power system modeling according to claim 2, characterized in that: The said construction of internal topology structure and dynamic generation of interface points include defining the functions of each component, including power conversion, voltage adjustment, and signal processing, determining the connection requirements between components, including voltage, current and signal compatibility, and designing components in the electrical structure including transformers, capacitors, switches, and control logic. The system dynamically generates external input ports and output ports through the internal topology, defines the interface, determines the type of interface provided by each component to the outside, and dynamically configures the interface. Based on the scalability and compatibility of the system, the interface is automatically configured through the internal topology of the component and the external connection requirements, and the interface is integrated into the automation control system of the component. The interface is dynamically adjusted through the system status and external commands.

4. The multi-level graph-model integration method for power system modeling as claimed in claim 3, characterized in that: The output power system model includes comparing and analyzing the circuit topology diagram after node optimization with the power system structure, identifying the nodes and connections in the topology and evaluating the compatibility, checking the correct transmission and execution of data flows and control commands in the new topology, modeling all subsystems and levels, and the program automatically integrates the model into a complete power system model, combining the actual parameters of the power system, and generating a model file in CIM format.

5. The multi-level graph-model integration method for power system modeling according to claim 4, characterized in that: The acquisition of simulation data includes configuring a host computer interface to receive interactive data from models at all levels of the power system, including real-time data from generator sets, real-time data from transformers, and real-time data from protection devices. The interface program checks and re-aggregates the interactive data, verifies data integrity and format, and encapsulates the aggregated data into a data packet based on the TCP / IP protocol and sends it to a simulation server. After receiving the data packet, the simulation server interacts with the system model through the received data at all levels.

6. The multi-level graph-model integration method for power system modeling according to claim 5, characterized in that: The data verification includes when the simulation is performed, the server continuously exchanges data with the host computer interface, updates the simulation status and results, continuously monitors the simulation results, adjusts the model parameters or simulation settings in real time, and generates a simulation report based on the simulation results for reference by system engineers and decision makers to perform system optimization, fault analysis and future planning.

7. A system using the multi-level graph-model integration method for power system modeling as claimed in any one of claims 1 to 6, characterized in that: Including system hierarchical module, topology optimization module, circuit simulation module; The system hierarchical module is used to decompose the power system into multiple levels, encapsulate the hierarchical subsystems into multiple levels of components, build the internal topology and dynamically generate interface points; The topology optimization module is used to add connection identifiers, connect multi-level components through interface points, form a circuit topology diagram using adaptive topology optimization, and output a power system model; The circuit simulation module is used to simulate the power system through the power system model and obtain simulation data, and to verify the data by interacting with models at each level.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the multi-level graphical model integration method for power system modeling described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-level graphical model integration method for power system modeling described in any one of claims 1 to 6 are implemented.

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