Power distribution network automation master station multi-terminal coordination verification method, system and device and storage medium

Abstract

The invention relates to the technical field of power distribution automation system verification, in particular to a power distribution network automation master station multi-terminal coordination verification method, system and device and a storage medium. Acquiring system parameters of a master station of the power distribution network and constructing a verification topology, wherein the verification topology comprises a connection relationship and a communication path between the master station and a plurality of terminal devices; a multi-terminal cooperative operation scene is simulated by verifying topology, state response data of each terminal is collected, a cooperative response mode is identified, and a communication adaptation layer is established to realize protocol conversion and data format unification between terminal devices of different manufacturers; a verification scene library including normal operation, fault switching and load change is generated according to the actual operation condition of the power distribution network, a coordination instruction is issued to the multiple terminal devices through the communication adaptation layer, a terminal response time sequence and an execution result are collected, and multi-terminal coordination verification is completed; and comprehensively evaluating the terminal response consistency, the communication path stability and the coordination control in the verification process, and generating a verification report.

Description

Technical Field

[0001] This invention relates to the field of power distribution automation system verification technology, and in particular to a method, system, equipment and storage medium for multi-terminal coordinated verification of power distribution automation master station. Background Technology

[0002] As the scale of the power distribution network continues to expand, the number of terminal devices connected to the master station has increased significantly. These devices come from multiple manufacturers, models, and protocols. The master station needs to achieve unified management and coordinated control of hundreds or even thousands of terminal devices, which places more stringent requirements on the master station's multi-terminal coordination capabilities.

[0003] Existing verification methods for distribution network automation master stations suffer from the following problems: First, the verification methods primarily rely on single-point testing, performing functional verification on individual terminal devices, lacking comprehensive assessment of multi-terminal collaborative operation scenarios, and failing to detect conflicts and anomalies in the multi-terminal coordination process; Second, terminal devices from different manufacturers use different communication protocols, including IEC104, IEC101, Modbus, and others, and existing verification platforms lack unified protocol adaptation, making it difficult to verify multi-protocol terminal access and resulting in insufficient compatibility testing coverage; Third, abnormal situations such as communication interruptions and equipment failures occur during distribution network operation, requiring the master station to have path switching and fault recovery capabilities, but existing verification methods lack sufficient depth in verifying these complex fault scenarios; Fourth, remote setting issuance and online maintenance are important functions of the master station, but existing verification methods lack verification of key aspects such as setting issuance timing and multi-terminal setting consistency. Summary of the Invention

[0004] In view of the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the problem to be solved by this invention is how to address the shortcomings of existing power distribution network automation master station verification methods in areas such as multi-terminal coordination verification, protocol compatibility verification, fault scenario verification, and setpoint management verification.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for multi-terminal coordinated verification of a distribution network automation master station, which includes acquiring system parameters of the distribution network master station and constructing a verification topology, wherein the verification topology includes the connection relationship and communication path between the master station and multiple terminal devices; The verification topology simulates a multi-terminal collaborative operation scenario, collects status response data from each terminal, identifies collaborative response modes, and establishes a communication adaptation layer based on the identified collaborative response modes. The communication adaptation layer is used to realize protocol conversion and data format unification between terminal devices from different manufacturers. Based on the actual operating conditions of the distribution network, a verification scenario library containing normal operation, fault switching and load change is generated. The scenarios in the verification scenario library are called, and coordination instructions are sent to multiple terminal devices through the communication adaptation layer. The terminal response timing and execution results are collected to complete the multi-terminal coordination verification. A comprehensive evaluation is conducted on the consistency of terminal responses, the stability of communication paths, and the effectiveness of coordination and control during the verification process, and a verification report is generated.

[0007] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the step of obtaining distribution network master station system parameters and constructing verification topology includes: obtaining the topology information of the master station system, including terminal device type, communication interface configuration and network connection method; and establishing a terminal device classification model based on the functional attributes and communication characteristics of the terminal devices. Based on the terminal device classification model, a verification topology structure including a master station node, terminal nodes, and communication links is constructed. To verify the assignment of status monitoring points to each node in the topology, which are used to record the node's operating status and interaction data.

[0008] The beneficial effects of this preferred technical solution are as follows: by acquiring the topology information of the main station system, the terminal devices are classified and modeled according to their functional attributes and communication characteristics, which can clearly sort out the connection relationship between the main station and various types of terminal devices; based on the classification model, a verification topology structure including the main station node, terminal nodes and communication links is constructed; status monitoring points are assigned to each node to realize the full recording of the node's operating status and interaction data, ensuring the data integrity and traceability of the verification process.

[0009] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the method for identifying the coordinated response mode includes: sending test instructions to each terminal device through the verification topology, recording the response time and execution status of each terminal; analyzing the response timing relationship of multiple terminal devices when receiving the same instruction, and extracting the coordinated features between terminals; Based on the temporal relationship and state change pattern of the terminal response, a collaborative response mode is summarized. The aforementioned collaborative response pattern will be used as a reference benchmark for subsequent coordination verification.

[0010] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the establishment of the communication adaptation layer includes identifying the communication protocol types supported by each terminal device in the verification topology. For different protocol types, a protocol conversion rule base is established, which includes data frame format mapping relationships and information point conversion rules; The protocol conversion rule base enables adaptive conversion of master station commands to different terminal protocol formats. Establish a communication status monitoring mechanism to track the connection status and data transmission quality of each communication link in real time.

[0011] The beneficial effects of this preferred technical solution are as follows: By identifying the communication protocol types supported by each terminal device in the verification topology, a protocol conversion rule base is established for different protocols such as IEC104, IEC101, and Modbus, realizing standardized management of data frame format mapping and information point conversion rules; the master station instructions are adaptively converted into different terminal protocol formats through the protocol conversion rule base, solving the compatibility problem of multi-vendor, multi-protocol terminal device access verification; at the same time, communication status monitoring is established to track the connection status and data transmission quality of each communication link in real time, enabling timely detection of communication anomalies and providing technical support for realizing verification scenarios in a real operating environment.

[0012] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the generation of a verification scenario library containing normal operation, fault switching and load change includes setting normal operation scenarios according to the characteristics of distribution network operation, including basic functional scenarios such as data acquisition, remote control operation and setpoint issuance; Define fault scenarios, including abnormal situations such as single terminal failure, communication interruption, and multipath switching; Define load variation scenarios, including concurrent requests from multiple terminals and high system load operation scenarios; Various scenarios are organized into a verification scenario library, and expected verification results are configured for each scenario.

[0013] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the step of completing the multi-terminal coordination verification includes: selecting a scenario to be verified from a verification scenario library, and parsing the verification steps and control logic in the scenario. Following the verification steps, coordination instructions are sent to relevant terminal devices through the communication adaptation layer; Real-time collection of response data from each terminal device, including command execution status, response time, and return information; By comparing the actual verification results with the expected results of the scenario, we can determine the implementation status of the multi-terminal coordination function.

[0014] As a preferred embodiment of the multi-terminal coordination verification method for a distribution network automation master station according to the present invention, the comprehensive evaluation of the terminal response consistency, communication path stability and coordination control effectiveness during the verification process includes: evaluating the response consistency of each terminal based on terminal response data and determining the synchronization of multi-terminal coordinated execution. Based on communication status monitoring data, assess the stability of the communication path and determine the reliability of the communication link; Based on the comparison of verification results, the effectiveness of coordinated control is evaluated, and the master station's control capability over multiple terminals is determined. Based on the above evaluation results, a verification report containing verification conclusions and improvement suggestions is generated.

[0015] Secondly, embodiments of the present invention provide a multi-terminal coordination and verification system for a distribution network automation master station, which includes a topology construction module for acquiring system parameters of the distribution network master station and constructing a verification topology. The scenario simulation module is used to simulate a multi-terminal collaborative operation scenario through the verification topology, collect the status response data of each terminal, and identify the collaborative response mode. The adaptation layer establishment module is used to establish a communication adaptation layer based on the identified collaborative response pattern; The scenario library generation module is used to generate a verification scenario library based on the actual operating conditions of the power distribution network. The coordination and verification module is used to call the scenarios in the verification scenario library to complete multi-terminal coordination and verification; The evaluation module is used to comprehensively evaluate the verification process and generate a verification report.

[0016] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program instructions, when executed by the processor, implement the steps of the multi-terminal coordination and verification method for distribution network automation master station as described in the first aspect of the present invention.

[0017] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the multi-terminal coordination and verification method for distribution network automation master station as described in the first aspect of the present invention.

[0018] The beneficial effects of this invention are as follows: By acquiring the system parameters of the distribution network master station and constructing a verification topology, this invention clarifies the connection relationship and communication path between the master station and multiple terminal devices, solving the problem of unclear terminal device connection relationships in traditional methods; by simulating multi-terminal collaborative operation scenarios and identifying collaborative response modes, a communication adaptation layer is established to achieve protocol conversion and data format unification between terminal devices from different manufacturers, solving the technical defects of existing technologies such as prominent information silos in intelligent measurement and control terminals, single networking methods, and difficulties in accessing multi-protocol terminals; by generating a verification scenario library covering normal operation, fault switching, and load changes, and by issuing coordination commands to multiple terminal devices through the communication adaptation layer, this invention solves the problem of information transmission omissions or the need for large-scale adjustments when traditional fixed networking faces communication overload, achieving comprehensive coverage of the actual operating conditions of the distribution network; and by comprehensively evaluating the consistency of terminal response, the stability of communication paths, and the coordination and controllability, a verification report is generated. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used 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 those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart for the multi-terminal coordination verification method of the distribution network automation master station; Figure 2 A diagram of computer equipment used for verifying the multi-terminal coordination method of the distribution network automation master station; Figure 3 Another flowchart for the multi-terminal coordination verification method of the distribution network automation master station. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0024] Example 1 Reference Figure 1 - Figure 2 This is the first embodiment of the present invention, which provides a multi-terminal coordination verification method for a distribution network automation master station, including: S100: Obtain the system parameters of the distribution network master station and construct the verification topology. The verification topology includes the connection relationship and communication path between the master station and multiple terminal devices.

[0025] S200: By verifying the topology simulation of multi-terminal collaborative operation scenarios, it collects the status response data of each terminal, identifies the collaborative response mode, and establishes a communication adaptation layer based on the identified collaborative response mode. The communication adaptation layer is used to realize protocol conversion and data format unification between terminal devices from different manufacturers.

[0026] S300: Based on the actual operating conditions of the distribution network, it generates a verification scenario library containing normal operation, fault switching and load changes, calls the scenarios in the verification scenario library, sends coordination instructions to multiple terminal devices through the communication adaptation layer, collects the terminal response timing and execution results, and completes multi-terminal coordination verification.

[0027] S400: Conducts a comprehensive evaluation of the consistency of terminal response, stability of communication paths, and effectiveness of coordination and control during the verification process, and generates a verification report.

[0028] It should be noted that in the multi-terminal coordination verification process of the distribution network automation master station, traditional verification methods are difficult to simulate real multi-terminal collaborative operation scenarios because terminal equipment from different manufacturers uses different communication protocols and data formats. This technical solution can accurately describe the connection relationship and communication path between the master station and each terminal equipment by constructing a verification topology architecture; by identifying collaborative response modes and establishing a communication adaptation layer, it can achieve adaptive conversion between different protocols, solving the compatibility verification problem of multi-protocol terminal equipment; by generating a verification scenario library covering normal operation, fault switching, and load changes, it can cover various operating conditions in the actual operation of the distribution network, thereby achieving comprehensive verification of the multi-terminal coordination capability of the master station system.

[0029] Step S100 acquires the distribution network master station system parameters and constructs the verification topology, clarifying the connection relationship and communication path between the master station and multiple terminal devices. Step S200 simulates multi-terminal collaborative operation scenarios and establishes a communication adaptation layer to achieve protocol conversion and data format unification between terminal devices from different manufacturers, resolving compatibility issues in multi-protocol terminal access verification. Step S300 generates a verification scenario library and completes multi-terminal coordination verification, covering actual operating conditions such as normal distribution network operation, fault switching, and load changes. Step S400 comprehensively evaluates terminal response consistency, communication path stability, and coordination controllability, generating a verification report to quantitatively evaluate the multi-terminal coordination capability of the master station system.

[0030] Example 2 Reference Figure 1 - Figure 3 This is the second embodiment of the present invention.

[0031] In this embodiment, step S100 involves obtaining the distribution network master station system parameters and constructing a verification topology. The verification topology includes the connection relationships and communication paths between the master station and multiple terminal devices, and includes the following A1 steps: A1: Obtain the parameters of the distribution network master station system and construct a verification topology, including obtaining the topology information of the master station system, including terminal equipment type, communication interface configuration and network connection method; and establishing a terminal equipment classification model based on the functional attributes and communication characteristics of the terminal equipment. Based on the terminal device classification model, a verification topology structure including master station node, terminal node and communication link is constructed; To verify the assignment of status monitoring points to each node in the topology, which are used to record the node's operating status and interaction data.

[0032] Specifically, the system obtains the topology information of the master station system. This topology information includes the type identifiers, communication interface configuration parameters, and network connection methods of various terminal devices in the distribution network. Terminal device types include, but are not limited to, distribution terminal units (DTUs), fault indicator units (FTUs), and pole-mounted switch monitoring terminals (TTUs). Communication interface configuration parameters cover underlying communication parameters such as communication port number, baud rate, data bits, and stop bits. The network connection method describes the communication link topology between the terminal devices and the master station.

[0033] Based on the terminal device classification model, a verification topology structure is constructed, which includes a master station node, terminal nodes, and communication links. In this verification topology structure, the master station node acts as the core control node, responsible for issuing instructions to each terminal node and receiving data uploaded by the terminal. The terminal nodes are organized according to the device classification model, and terminal nodes of the same type form a node set in the topology structure. The communication links describe the connection relationship between the master station node and each terminal node, and each communication link identifies the link type, transmission medium, communication protocol, and link identifier.

[0034] To verify the allocation of status monitoring points to each node in the topology, these points are used to record the node's operational status and interactive data. The allocation of status monitoring points follows the principle of full coverage, meaning that status monitoring points must be set up for both the master node and all terminal nodes. The status monitoring points of the master node record information such as the content of the instructions sent by the master, the instruction timestamp, the received terminal response data, and the data reception timestamp. The status monitoring points of the terminal nodes record information such as the time when the terminal receives the instruction, the instruction parsing result, the execution status, the response data generation time, and the data transmission time. The status monitoring points of the communication link record communication quality indicators such as the link's connection status, data transmission delay, packet loss rate, and retransmission count.

[0035] After verifying the topology construction, establish a system state vector to verify the overall state of the system at a certain moment; System state vector: (1) In the formula, Let i be the system state vector at time i. Data acquisition status. The status of the communication link. Status of the terminal device. To control the state of the command, In response to status information.

[0036] The data acquisition status describes the data acquisition frequency, data type, and data quality of each terminal node; the communication link status describes the connection status, communication latency, and transmission error rate of each communication link; the terminal device status describes the operating status, fault status, and configuration status of each terminal node; the control command status describes the type of command issued by the master station, the target terminal, and the command parameters; and the response status information describes the terminal's response time, execution result, and returned data.

[0037] To describe the coordination relationship between multiple terminals, a multi-terminal coordination matrix needs to be established. The multi-terminal coordination matrix is ​​defined by equation (2). (2) In the formula, For multi-terminal coordination matrix, Let m be the coordination coefficient between the i-th master station and the j-th terminal, m be the number of master stations, and n be the number of terminals.

[0038] The coordination coefficient reflects the degree of coordination between the master station and the terminal. The larger the coordination coefficient, the higher the priority of the terminal in coordination and control.

[0039] In this embodiment, step S200 verifies the multi-terminal collaborative operation scenario by simulating the topology, collects the status response data of each terminal, identifies the collaborative response mode, and establishes a communication adaptation layer based on the identified collaborative response mode. The communication adaptation layer is used to realize protocol conversion and data format unification between terminal devices from different manufacturers, including the following steps B1-B2: B1: Identify collaborative response patterns, including sending test commands to each terminal device through topology verification and recording the response time and execution status of each terminal; Analyze the response timing relationship of multiple terminal devices when receiving the same instruction, and extract the collaborative features between terminals; Based on the temporal relationship and state change pattern of the terminal response, a collaborative response mode is summarized. The collaborative response model will be used as a reference benchmark for subsequent coordination and verification.

[0040] Specifically, in identifying the coordinated response mode, it is first necessary to send test commands to each terminal device through topology verification. These test commands include telemetry data retrieval commands, remote signaling status query commands, remote control operation commands, setpoint reading commands, and setpoint distribution commands. The transmission of each type of command must comply with the requirements of the distribution network communication protocol, including command format, information point encoding, data length, and verification method. When sending test commands, the precise timestamp of the command transmission needs to be recorded for subsequent calculation of terminal response time.

[0041] After the terminal receives the test command, it is necessary to record the response time and execution status of each terminal. The response time refers to the time interval from when the terminal receives the command to when it returns the response data. The execution status includes status codes such as command execution success, execution failure, parameter error, and device busy. By statistically analyzing the response times of multiple terminals, the distribution characteristics of terminal response times can be obtained, including statistics such as average response time, standard deviation of response time, maximum response time, and minimum response time.

[0042] This study analyzes the timing relationships of responses from multiple terminal devices when receiving the same instruction. When the master station sends the same type of instruction to multiple terminals simultaneously or sequentially, the response times of different terminals will vary. Based on the timing relationships and state change patterns of the terminal responses, a collaborative response pattern is summarized. This collaborative response pattern includes the time characteristics, state characteristics, and data characteristics of the terminal responses. The time characteristics describe the distribution and timing of the terminal response times; the state characteristics describe the transition patterns of the terminal execution states and the frequency of abnormal states; and the data characteristics describe the format characteristics, numerical range, and correlations of the data returned by the terminals. Through the analysis of a large amount of test data, several typical collaborative response patterns can be summarized, each corresponding to a specific terminal combination and application scenario.

[0043] To quantify the dynamic response characteristics, a system dynamic response model is introduced, defined by equation (3).

[0044] (3) In the formula, The system outputs a response. For the transfer function matrix, To control the input, This is a disturbance signal.

[0045] The system output response represents the terminal device's response to the master station's instructions, the control input represents the control instructions issued by the master station, and the disturbance signal represents external interference factors that affect the system response, such as communication interference and load changes.

[0046] B2: Establish a communication adaptation layer, including identifying and verifying the types of communication protocols supported by each terminal device in the topology; For different protocol types, a protocol conversion rule base is established, which includes data frame format mapping relationships and information point conversion rules; The protocol conversion rule base enables adaptive conversion of master station commands to different terminal protocol formats; Establish a communication status monitoring mechanism to track the connection status and data transmission quality of each communication link in real time.

[0047] Specifically, verify the communication protocol types supported by each terminal device in the topology. Commonly used communication protocols in distribution network automation include various international standard protocols such as IEC60870-5-104, IEC60870-5-101, Modbus-RTU, Modbus-TCP, and DNP3.0, as well as some manufacturer-defined proprietary protocols. The IEC104 protocol uses TCP / IP as the transport layer, supporting network communication and remote access; the IEC101 protocol uses serial communication, suitable for point-to-point or multi-point connections; the Modbus protocol is simple to implement and widely used in industrial automation.

[0048] The protocol conversion rule base comprises two parts: data frame format mapping relationships and information point conversion rules. The data frame format mapping relationships define the correspondence between data frame structures of different protocols, including mapping rules for various fields such as start identifier, length field, type identifier, information body address, information element, timestamp, and checksum. For example, the type identifier M_SP_NA_1 in the IEC104 protocol represents single-point information and needs to be mapped to the corresponding function code and data format in the Modbus protocol. The information body address in the IEC104 protocol uses 24-bit encoding, while the Modbus protocol typically uses 16-bit register addresses, requiring the definition of an address mapping algorithm.

[0049] The master station achieves adaptive conversion of master station commands to different terminal protocol formats through a protocol conversion rule base. First, the master station generates control commands in a standard protocol format, which serves as the internal representation format of the communication adaptation layer. Then, based on the target terminal's protocol type, the corresponding conversion rule is queried from the protocol conversion rule base. Next, the command is format converted according to the conversion rule, including adjusting the data frame structure, converting information point encoding, and calculating checksums. The converted command conforms to the target terminal's protocol requirements and can be correctly parsed and executed by the terminal.

[0050] The protocol conversion process can be mathematically described by equation (4), protocol adaptation conversion: (4) In the formula, For the target protocol format, For protocol adaptation matrix, The source protocol format, This is the protocol offset.

[0051] The communication status monitoring mechanism needs to track the connection status and data transmission quality of each communication link in real time: Connection status monitoring includes detecting whether the communication link is established, whether the connection is maintained, and status changes such as disconnection and reconnection. Data transmission quality monitoring includes statistical data such as transmission delay, packet loss rate, bit error rate, and retransmission rate; the transmission delay is calculated by equation (5), and the terminal response time is predicted: (5) In the formula, For terminal response time, For processing time, For network transmission time, For execution time, For feedback time.

[0052] To assess the reliability of a communication system, a communication reliability assessment model is introduced, defined by equation (6). Communication reliability assessment: (6) In the formula, For communication reliability, Let be the failure probability of the i-th component. This is the timeout period. This is the communication cycle.

[0053] By continuously monitoring and evaluating communication reliability, trends of declining communication quality can be detected in a timely manner, and preventive measures can be taken to avoid communication interruptions.

[0054] To optimize load distribution in multi-path communication scenarios, communication load balancing calculations are required. The communication load balancing index is defined by equation (7). Communication load balancing: (7) In the formula, For load balancing metrics, Let be the load of the i-th communication link.

[0055] When multiple terminal devices can communicate with the main station through different paths, reasonable allocation of communication load can avoid overloading of a single link.

[0056] In this embodiment, step S300 generates a verification scenario library containing normal operation, fault switching, and load changes based on the actual operating conditions of the distribution network. It then calls upon scenarios from this library, sends coordination commands to multiple terminal devices through the communication adaptation layer, collects terminal response timing and execution results, and completes multi-terminal coordination verification. This includes the following steps C1-C2: C1: Generate a library of verification scenarios including normal operation, fault switching and load change. This includes setting normal operation scenarios based on the characteristics of the distribution network, including basic functional scenarios such as data acquisition, remote control operation and setpoint issuance. Define fault scenarios, including abnormal situations such as single terminal failure, communication interruption, and multipath switching; Define load variation scenarios, including concurrent requests from multiple terminals and high system load operation scenarios; Various scenarios are organized into a verification scenario library, and expected verification results are configured for each scenario.

[0057] Specifically, a normal operation scenario is set according to the characteristics of the distribution network: the data acquisition scenario simulates the process of the master station periodically summoning telemetry data from the terminal equipment, including the acquisition of operating parameters such as voltage, current, active power, reactive power, and frequency; the data acquisition cycle can be set according to the importance of the data. Important data, such as the operating parameters of the main transformer, may need to be acquired once per second, while secondary data, such as ambient temperature, may only need to be acquired once per minute. The optimization of the data acquisition cycle can be calculated using equation (8). The data acquisition cycle optimization is as follows: (8) In the formula, The optimal acquisition period is... Due to data error, For the cost of communication, To delay losses, These are the weighting coefficients.

[0058] This formula takes into account multiple factors such as data error, communication cost, and latency loss, and obtains the optimal acquisition period through weighted summation.

[0059] The remote control operation scenario simulates the process of the master station sending remote control commands to the terminal equipment to execute switch operations: Remote control operation is an important means of remote control of the power distribution network, including control actions such as circuit breaker opening and closing, disconnecting switch operation, and capacitor switching; The remote control operation scenario needs to verify the complete process of command sending between the master station and the terminal, the terminal's confirmation of command execution, and the reporting of operation results; The response time prediction of the remote control operation is calculated by equation (9), and the terminal response time prediction is: (9) In the formula, For terminal response time, For processing time, For network transmission time, For execution time, For feedback time.

[0060] The setting value issuance scenario simulates the process of the master station issuing setting parameters to protection devices or monitoring and control devices. The setting value issuance scenario requires processes such as setting value verification, setting value download and transmission, and setting value activation confirmation. Setting value verification includes: (10) In the formula, As a marker of the validity of the set value, For the new value, and For a fixed range, This is the result of the consistency check.

[0061] This verification process requires checking whether the set values ​​are within the allowable range and whether the constraints between the set values ​​are met. The success rate of setting out is calculated by formula (11), taking into account factors such as whether the set value matches the equipment capacity. (11) In the formula, To ensure the success rate of fixed-value distribution, For the number of successes, Number of attempts Incorrect time. This represents the total time.

[0062] This indicator reflects the reliability of the fixed value distribution function.

[0063] The effective time of the fixed value is calculated by formula (12). (12) In the formula, The effective time of the fixed value, For download time, To verify the time, This refers to the activation time.

[0064] It includes three parts: fixed download time, verification time, and switching time.

[0065] To ensure the quality of data collection, a quality assessment of the collected data is required. The data quality assessment is defined by equation (13). (13) In the formula, For data quality indicators, For effective data volume, Total data volume Due to data error, For the maximum permissible error, This is the data integrity coefficient.

[0066] The assessment considers multiple dimensions, including the proportion of data volume, the ratio of data error to allowable error, and the data integrity coefficient. Only data that passes the quality assessment can be used for subsequent state estimation and analysis calculations to ensure the accuracy of the verification results.

[0067] In large-scale data acquisition scenarios, in order to reduce communication bandwidth usage, the acquired data needs to be compressed. The data compression efficiency is calculated by equation (14). (14) In the formula, For compression efficiency, This represents the original data size. This is the size of the compressed data. For decompression time, This represents the total processing time.

[0068] This formula compares the data size before and after compression, while also taking into account the processing time required for decompression.

[0069] Setting up fault scenarios is to verify fault tolerance capabilities; fault scenarios include abnormal situations such as single terminal failure, communication interruption, and multipath switching; the single terminal failure scenario simulates the situation where a terminal device loses response or returns erroneous data, verifying the main station's ability to detect terminal faults and its handling strategies. The fault detection threshold is defined by equation (15). (15) In the formula, This is the fault detection threshold. This represents the mean value under normal conditions. denoted as the standard deviation of the normal state, and k as the confidence coefficient.

[0070] A terminal response parameter exceeding this threshold is considered a fault.

[0071] The failure probability assessment is calculated using equation (16). (16) In the formula, This represents the probability of failure. For feature vectors, For the weight vector, For scale parameters, This is the bias parameter.

[0072] Taking into account historical failure rates, current status, and environmental impact factors.

[0073] The scope of the fault's impact is calculated using equation (17). (17) In the formula, The scope of the fault's impact. Let be the impact index of the i-th device. For the probability of fault propagation, This represents the equipment importance coefficient.

[0074] Assess the impact of a single terminal failure on the entire system.

[0075] The communication interruption scenario simulates a situation where the communication link between the master station and the terminal is interrupted. Communication interruptions can be caused by various reasons, including network equipment failure, communication line failure, and electromagnetic interference. The multi-path switching scenario verifies the master station's response when switching between multiple communication paths. When the primary communication path experiences quality degradation or is about to be interrupted, the system should be able to switch to a backup path in advance to achieve seamless switching; the path selection evaluation is calculated using equation (18). (18) In the formula, The optimal path, The delay for the k-th path, For load, For cost, For risk coefficient, These are the weighting coefficients.

[0076] This formula takes into account multiple factors such as path delay, load, and cost to calculate the optimal path.

[0077] The switching time prediction is calculated using equation (19). (19) In the formula, To switch time, For the detection time, For decision-making time, For execution time, For stable time.

[0078] It includes multiple stages such as detection time, decision-making time, and connection time.

[0079] Path availability assessment is calculated using equation (20). (20) In the formula, For path availability, For the availability of the i-th link, To allow for maintenance time, This refers to the runtime.

[0080] The availability and maintenance time of each link were taken into account.

[0081] The load change scenario includes two typical situations: concurrent requests from multiple terminals and high-load operation. The concurrent request scenario simulates a situation where a large number of terminals simultaneously upload data to the master station or the master station simultaneously issues instructions to multiple terminals. During power grid faults or important operations, dozens or even hundreds of terminals may generate alarm information or status changes at the same time, and the master station needs to have the ability to handle a large number of concurrent requests. The high-load operation scenario simulates a state of high data throughput for a long time. The throughput is calculated by equation (21). (twenty one) In the formula, For system throughput, The amount of data processed in the i-th time unit. This is for maximum processing capacity.

[0082] This metric reflects the system's ability to process data per unit of time.

[0083] Resource utilization efficiency is calculated by equation (22). (twenty two) In the formula, To improve resource utilization efficiency, For actual use of resources, In order to allocate resources, For actual performance, For the desired performance.

[0084] This metric reflects the utilization of system resources, including the utilization rate of resources such as CPU, memory, and network bandwidth.

[0085] Organizing various scenarios into a verification scenario library requires establishing a standardized scenario description format and organizational structure. Each verification scenario includes elements such as scenario identifier, scenario name, scenario type, scenario description, preconditions, execution steps, expected results, and evaluation metrics; the expected results define the outcome that should be obtained when the scenario is executed normally.

[0086] C2: Complete multi-terminal coordinated verification, including selecting the scenario to be verified from the verification scenario library and parsing the verification steps and control logic in the scenario; Following the verification steps, coordination instructions are sent to relevant terminal devices through the communication adaptation layer; Real-time collection of response data from each terminal device, including command execution status, response time, and return information; By comparing the actual verification results with the expected results of the scenario, we can determine the implementation status of the multi-terminal coordination function.

[0087] Specifically, the scenario to be verified is selected from the verification scenario library: the scenario selection can be carried out by sequential traversal, executing all scenarios in the scenario library in turn; or by priority scheduling, executing scenarios with higher importance first; the verification steps describe the specific operation sequence of the scenario execution, and the control logic describes the execution relationship between the steps, including logical structures such as sequential execution, parallel execution, conditional execution, and loop execution.

[0088] According to the verification steps, the timing of issuing coordination instructions to relevant terminal devices through the communication adaptation layer needs to be precisely controlled: for sequentially executed steps, it is necessary to wait for the previous step to be completed before executing the next step; for parallel executed steps, it is necessary to issue instructions to multiple terminals simultaneously; for conditionally executed steps, it is necessary to determine whether to execute the step based on the execution results of the previous steps; for cyclically executed steps, it is necessary to repeat the execution a specified number of times or until the exit condition is met.

[0089] The response data includes three parts: instruction execution status, response time, and return information. Instruction execution status indicates the terminal's processing result of the instruction, including status codes such as successful execution, execution failure, parameter error, and device busy. Response time is the time interval from when the master station issues an instruction to when it receives the terminal's response. Response time is an important indicator for measuring the real-time performance of the system. Return information includes the data content returned by the terminal, such as telemetry data values, remote signaling status, and operation result confirmation.

[0090] To evaluate the effectiveness of multi-terminal coordinated control, it is necessary to establish a coordinated control objective function, which is defined by equation (23). (twenty three) In the formula, J is the coordination control objective function. These are the weighting coefficients. For the i-th terminal state, For the desired state, This is the weight matrix.

[0091] This function describes the optimization objective of coordinated control, which includes making the states of each terminal approach the desired state while minimizing the control cost; by solving this optimization problem, the optimal coordinated control strategy can be obtained.

[0092] Terminal response time is a key indicator for evaluating system performance, and the response time prediction model is given by equation (24).

[0093] (twenty four) In the formula, For terminal response time, For processing time, For network transmission time, For execution time, For feedback time.

[0094] Processing time depends on the hardware performance of the terminal device and the complexity of the software algorithm; network transmission time depends on communication distance, transmission rate and network congestion; queue waiting time increases when the system load is high.

[0095] The comparison between the actual verification results and the expected results of the scenario includes several aspects: First, comparing whether the terminal response time is within the expected range. If the actual response time exceeds the expected upper limit, it indicates that the system's real-time performance does not meet the requirements. Second, comparing whether the instruction execution success rate reaches the expected threshold. If the success rate is too low, it indicates that there are problems with the system's reliability. Third, comparing whether the data collection integrity rate meets the requirements. If data loss is severe, it indicates that the communication quality is poor. Finally, comparing whether the system resource consumption is within a reasonable range. If the resource consumption is too high, it indicates that there is room for optimization in the system design.

[0096] To determine the implementation status of multi-terminal coordination function, a coordination metric index needs to be constructed, defined by equation (25). (25) In the formula, As a coordination index, Let be the response latency of the i-th terminal. For average response delay, Let N be the standard deviation of latency, and N be the total number of terminals.

[0097] This indicator integrates multiple sub-indicators, including the standard deviation of response time for each terminal, the ratio of average response latency to expected system latency, and the ratio of latency standard deviation to system latency threshold. The closer the coordination index is to 1, the better the coordination among multiple terminals; a significant deviation from 1 indicates poor coordination between terminals and obvious inconsistencies in response.

[0098] During the verification process, it is also necessary to pay attention to the system's response performance. The response performance index is calculated by equation (26). (26) In the formula, In response to performance metrics, Let i be the response time. For reference only.

[0099] Response performance indicators are a direct reflection of the system's real-time performance. For power distribution automation systems, the response time for important control commands is generally required to be no more than 3 seconds, and the response time for data acquisition is no more than 5 seconds.

[0100] In this embodiment, step S400 comprehensively evaluates the consistency of terminal response, stability of communication path, and effectiveness of coordination control during the verification process, and generates a verification report, including the following step D1: D1: Conduct a comprehensive evaluation of the consistency of terminal responses, the stability of communication paths, and the effectiveness of coordination and control during the verification process, including evaluating the consistency of responses from each terminal based on terminal response data and determining the synchronicity of multi-terminal coordinated execution. Based on communication status monitoring data, assess the stability of the communication path and determine the reliability of the communication link; Based on the comparison of verification results, the effectiveness of coordinated control is evaluated, and the master station's control capability over multiple terminals is determined. Based on the above evaluation results, a verification report containing verification conclusions and improvement suggestions is generated.

[0101] Specifically, based on the terminal response data, the consistency of each terminal's response is evaluated, and the synchronicity of multi-terminal coordinated execution is judged: if the response times of multiple terminals are very close, for example, if the standard deviation of the response time is less than a certain threshold, then these terminals are considered to have good response consistency. At the same time, a coordination metric is constructed and calculated by equation (27). (27) In the formula, As a coordination index, Let be the response latency of the i-th terminal. For average response delay, Let N be the standard deviation of latency, and N be the total number of terminals.

[0102] This indicator comprehensively reflects the degree of synchronization of responses from multiple terminals.

[0103] Communication path stability assessment requires statistical analysis of indicators such as connection success rate, data transmission success rate, and communication delay variation rate of communication links. Communication reliability assessment is calculated using equation (28). (28) In the formula, For communication reliability, Let be the failure probability of the i-th component. This is the timeout period. This is the communication cycle.

[0104] This model comprehensively considers the failure probability and repair time of each link in the communication link to calculate the overall reliability of the link. By continuously monitoring communication reliability indicators, it can promptly detect trends of declining communication quality and take maintenance measures in advance.

[0105] Path availability assessment is defined by equation (29). (29) In the formula, For path availability, For the availability of the i-th link, To allow for maintenance time, This refers to the runtime.

[0106] The assessment takes into account the availability and maintenance time percentage of each communication link.

[0107] When the availability of the primary communication path decreases, the system should be able to switch to the backup path in a timely manner.

[0108] The decision-making basis for path switching is given by equation (30). (30) In the formula, The optimal path, The delay for the k-th path, For load, For cost, For risk coefficient, These are the weighting coefficients.

[0109] This formula takes into account multiple factors such as path delay, load, and cost to select the optimal communication path.

[0110] The time cost of the switching process is predicted by equation (31). (31) In the formula, To switch time, For the detection time, For decision-making time, For execution time, For stable time.

[0111] This includes the time required for multiple stages such as detection, decision-making, connection, and stabilization.

[0112] The evaluation of coordinated control based on verification results requires determining the master station's control capability over multiple terminals. Coordinated control capability includes multiple dimensions such as the arrival rate of control commands, execution rate, response time, and control accuracy. The objective function of coordinated control is defined by equation (32). (32) In the formula, J is the coordination control objective function. These are the weighting coefficients. For the i-th terminal state, For the desired state, This is the weight matrix.

[0113] This function describes the ideal coordinated control objective. By comparing the deviation between the actual execution result and the objective function, the effectiveness of the coordinated control can be quantitatively evaluated. If the deviation is small, it means that the coordinated control has achieved the expected effect. If the deviation is large, it is necessary to analyze the reasons and adjust the control strategy.

[0114] The system throughput is calculated using equation (33). (33) In the formula, For system throughput, The amount of data processed in the i-th time unit. This is for maximum processing capacity.

[0115] This metric reflects the amount of data processed by the system per unit time; by measuring the system throughput under different load conditions, the upper limit of the system's processing capacity can be determined.

[0116] Resource utilization efficiency is calculated using equation (34). (34) In the formula, To improve resource utilization efficiency, For actual use of resources, In order to allocate resources, For actual performance, For the desired performance.

[0117] Excessive resource utilization may lead to slower system response, while excessively low resource utilization indicates redundancy in the system design.

[0118] Based on the above evaluation results, a verification report is generated that includes verification conclusions and improvement suggestions. The verification report should include the following: The first part is a verification overview, describing the verification time, scope, participating equipment, execution scenario, and other basic information; the second part is verification result statistics, summarizing the actual values ​​and compliance status of each evaluation indicator; the third part is problem analysis, describing in detail the problems found during the verification process and their causes; the fourth part is improvement suggestions, proposing specific improvement measures and optimization schemes for the problems found; and the fifth part is the verification conclusion, giving the final conclusion as to whether the main station system has passed the verification.

[0119] The generation of the verification report requires statistical analysis and comprehensive judgment of a large amount of monitoring data; the response performance index is calculated by equation (35). (35) In the formula, In response to performance metrics, Let i be the response time. For reference only.

[0120] By comparing with system design metrics and industry standards, it can be determined whether the system performance meets the requirements. For metrics that do not meet the standards, the reasons should be analyzed in detail in the report, and targeted improvement measures should be proposed.

[0121] In summary, by establishing a system state vector and a multi-terminal coordination matrix, a quantitative description of the overall state of the verification system and a mathematical model of the terminal coordination relationship are achieved. The system dynamic response model analyzes the response characteristics of terminal devices to master station commands, extracts the collaborative features between terminals, and summarizes them into a collaborative response pattern. A protocol conversion rule base is established to achieve adaptive conversion between various communication protocols such as IEC104, IEC101, and Modbus. A communication reliability assessment model and load balancing index are also established to solve compatibility issues caused by differences in communication protocols between terminal devices from different manufacturers. A data acquisition cycle optimization model, a data quality assessment model, and a data compression efficiency model are constructed to achieve intelligent optimization of the data acquisition process and reduce communication bandwidth usage. Fault detection threshold, fault probability assessment, and fault impact range models, as well as path selection assessment and switching time prediction models, are established. The system's performance under high load conditions is evaluated through system throughput and resource utilization efficiency models.

[0122] Example 3 This study constructed a comprehensive verification platform comprising a master station system, various power distribution terminal equipment, and a communication network to verify the effectiveness and practicality of the multi-terminal coordination verification method. The test environment included one master station system, 15 FTU terminals, 8 DTU terminals, 5 fault indicators, and multiple communication protocols, covering equipment and communication methods from different manufacturers. The experiment spanned eight months, completing over 5000 coordinated control verifications and 1000 setpoint distribution tests.

[0123] Experimental results show the system's performance in different scenarios: Table 1: Performance Test Results of Multi-Terminal Coordination Verification

[0124] Table 2: Verification Results of the Fixed Value Management Function

[0125] Table 3: System Comprehensive Performance Verification Results

[0126] Experimental results show that this method significantly improves multi-terminal coordination verification, setpoint management, and overall system performance. The multi-terminal coordination success rate reaches 99.8%, the response time is controlled within 500ms, and the data quality remains above 98%. The setpoint management function achieves a success rate exceeding 99%, supports 35 different types of power distribution equipment, and improves compatibility by 58.3%. The overall system reliability reaches 99.2%, and the fault recovery time is reduced from 15 minutes to 3 minutes, providing strong technical support for the reliable operation of the power distribution automation master station system.

[0127] Example 4 The above is a schematic scheme for a multi-terminal coordination verification method for a distribution network automation master station. It should be noted that the technical solution of this multi-terminal coordination verification system for a distribution network automation master station belongs to the same concept as the technical solution of the aforementioned multi-terminal coordination verification method for a distribution network automation master station. Details not described in detail in this embodiment can be found in the description of the technical solution of the aforementioned multi-terminal coordination verification method for a distribution network automation master station.

[0128] This embodiment also provides a multi-terminal coordination and verification system for a distribution network automation master station, including: The topology building module is used to obtain the system parameters of the distribution network master station and build a verification topology; The scenario simulation module is used to simulate multi-terminal collaborative operation scenarios by verifying the topology, collect the status response data of each terminal, and identify the collaborative response mode. The adaptation layer establishment module is used to establish a communication adaptation layer based on the identified collaborative response pattern; The scenario library generation module is used to generate a verification scenario library based on the actual operating conditions of the power distribution network. The coordination and verification module is used to call scenarios in the verification scenario library to complete multi-terminal coordination and verification. The evaluation module is used to comprehensively evaluate the verification process and generate a verification report.

[0129] This embodiment also provides an electronic device suitable for multi-terminal coordinated verification of distribution network automation master stations, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the multi-terminal coordinated verification method of distribution network automation master stations as proposed in the above embodiment.

[0130] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the method for multi-terminal coordination and verification of distribution network automation master station as proposed in the above embodiments.

[0131] The storage medium proposed in this embodiment and the method for multi-terminal coordination and verification of distribution network automation master station proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0132] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0133] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for multi-terminal coordination verification of a distribution network automation master station, characterized in that: This includes acquiring the system parameters of the distribution network master station and constructing a verification topology, wherein the verification topology includes the connection relationship and communication path between the master station and multiple terminal devices; The verification topology simulates a multi-terminal collaborative operation scenario, collects status response data from each terminal, identifies collaborative response modes, and establishes a communication adaptation layer based on the identified collaborative response modes. The communication adaptation layer is used to realize protocol conversion and data format unification between terminal devices from different manufacturers. Based on the actual operating conditions of the distribution network, a verification scenario library containing normal operation, fault switching and load change is generated. The scenarios in the verification scenario library are called, and coordination instructions are sent to multiple terminal devices through the communication adaptation layer. The terminal response timing and execution results are collected to complete the multi-terminal coordination verification. A comprehensive evaluation is conducted on the consistency of terminal responses, the stability of communication paths, and the effectiveness of coordination and control during the verification process, and a verification report is generated.

2. The method for multi-terminal coordination and verification of a distribution network automation master station as described in claim 1, characterized in that: The step of obtaining the distribution network master station system parameters and constructing the verification topology includes: obtaining the topology information of the master station system, including terminal equipment type, communication interface configuration and network connection method; and establishing a terminal equipment classification model based on the functional attributes and communication characteristics of the terminal equipment. Based on the terminal device classification model, a verification topology structure including a master station node, terminal nodes, and communication links is constructed. To verify the assignment of status monitoring points to each node in the topology, which are used to record the node's operating status and interaction data.

3. The method for multi-terminal coordination verification of a distribution network automation master station as described in claim 2, characterized in that: The identification of collaborative response patterns includes sending test commands to each terminal device through a verification topology, recording the response time and execution status of each terminal, analyzing the response timing relationship of multiple terminal devices when receiving the same command, and extracting collaborative features between terminals. Based on the temporal relationship and state change pattern of the terminal response, a collaborative response mode is summarized. The aforementioned collaborative response pattern will be used as a reference benchmark for subsequent coordination verification.

4. The method for multi-terminal coordination verification of a distribution network automation master station as described in claim 3, characterized in that: The establishment of the communication adaptation layer includes identifying and verifying the types of communication protocols supported by each terminal device in the topology; For different protocol types, a protocol conversion rule base is established, which includes data frame format mapping relationships and information point conversion rules; The protocol conversion rule base enables adaptive conversion of master station commands to different terminal protocol formats. Establish a communication status monitoring mechanism to track the connection status and data transmission quality of each communication link in real time.

5. The method for multi-terminal coordination verification of a distribution network automation master station as described in claim 4, characterized in that: The generation of the verification scenario library includes normal operation, fault switching and load change, including setting normal operation scenarios based on the characteristics of distribution network operation, including basic functional scenarios such as data acquisition, remote control operation and setpoint issuance; Define fault scenarios, including abnormal situations such as single terminal failure, communication interruption, and multipath switching; Define load variation scenarios, including concurrent requests from multiple terminals and high system load operation scenarios; Various scenarios are organized into a verification scenario library, and expected verification results are configured for each scenario.

6. The method for multi-terminal coordination verification of a distribution network automation master station as described in claim 5, characterized in that: The process of completing multi-terminal coordinated verification includes selecting a scenario to be verified from the verification scenario library and parsing the verification steps and control logic in the scenario. Following the verification steps, coordination instructions are sent to relevant terminal devices through the communication adaptation layer; Real-time collection of response data from each terminal device, including command execution status, response time, and return information; By comparing the actual verification results with the expected results of the scenario, the implementation status of the multi-terminal coordination function can be determined.

7. The method for multi-terminal coordination verification of a distribution network automation master station as described in claim 6, characterized in that: The comprehensive evaluation of terminal response consistency, communication path stability, and coordination control effectiveness during the verification process includes assessing the consistency of each terminal response based on terminal response data and determining the synchronicity of multi-terminal coordinated execution. Based on communication status monitoring data, assess the stability of the communication path and determine the reliability of the communication link; Based on the comparison of verification results, the effectiveness of coordinated control is evaluated, and the master station's control capability over multiple terminals is determined. Based on the above evaluation results, a verification report containing verification conclusions and improvement suggestions is generated.

8. A multi-terminal coordination verification system for a distribution network automation master station, based on the multi-terminal coordination verification method for a distribution network automation master station according to any one of claims 1 to 7, characterized in that: It also includes a topology building module, used to obtain the distribution network master station system parameters and build a verification topology; The scenario simulation module is used to simulate a multi-terminal collaborative operation scenario through the verification topology, collect the status response data of each terminal, and identify the collaborative response mode. The adaptation layer establishment module is used to establish a communication adaptation layer based on the identified collaborative response pattern; The scenario library generation module is used to generate a verification scenario library based on the actual operating conditions of the power distribution network. The coordination and verification module is used to call the scenarios in the verification scenario library to complete multi-terminal coordination and verification; The evaluation module is used to comprehensively evaluate the verification process and generate a verification report.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the multi-terminal coordination and verification method for the distribution network automation master station as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the multi-terminal coordination and verification method for the distribution network automation master station as described in any one of claims 1 to 7.

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