Multi-machine co-control power distribution network distributed protection terminal self-healing collaborative test method

Abstract

The invention discloses a multi-machine co-control power distribution network distributed protection terminal self-healing collaborative test method. The method comprises the following steps: generating diversified fault scene test cases according to preset topology and power distribution network distributed protection self-healing terminal configuration; the multi-terminal synchronous control unit is used for synchronously triggering action instructions of a plurality of distributed protection terminals, and simulating an information interaction and collaborative decision process between the terminals; action time, logic judgment results, fault isolation and power supply recovery path indexes of each terminal are recorded in real time through a data acquisition and analysis module; according to a preset self-healing function evaluation system, performing quantitative evaluation on the accuracy, timeliness and coordination of the multi-terminal coordination action, and generating a test report; a multi-machine simultaneous control test system with a three-level architecture of a cloud platform layer, an edge control layer and an equipment layer is constructed, and a standardized test process and a quantitative evaluation system are combined, so that comprehensive verification of the collaborative self-healing function of the distributed protection terminal of the power distribution network is realized.

Description

Technical Field

[0001] This invention relates to a self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks, and particularly relates to the field of power system technology. Background Technology

[0002] As a crucial link directly connecting the power system and users, the distribution network's operational stability directly determines the reliability of power supply, playing an irreplaceable role in ensuring people's livelihoods, industrial production, and socio-economic development. With the advancement of new power system construction, the distribution network exhibits new characteristics such as "high penetration of distributed energy resources, dynamic changes in network topology, and diversified load types." Traditional centralized fault handling modes are no longer sufficient to meet the demand for rapid self-healing. Distributed protection terminal collaborative self-healing technology has become the core means to solve the problem of rapid fault location, isolation, and power restoration in the distribution network.

[0003] Currently, the deployment scale of distributed protection and self-healing systems in power distribution networks continues to expand, but the supporting testing technologies have significant shortcomings: Limited testing scenarios: Existing testing methods only verify the independent functions of a single protection terminal, and cannot simulate the collaborative interaction process of multiple terminals under complex actual working conditions such as "single-point fault superimposed topology reconstruction", "multi-point concurrent fault propagation" and "faults under distributed energy output fluctuations", resulting in test results being out of touch with the actual operation scenario.

[0004] Insufficient time synchronization accuracy: Multi-terminal collaborative self-healing relies on millisecond-level or even microsecond-level time synchronization to ensure the consistency of action timing. Existing test systems mostly use ordinary network clock synchronization, with synchronization accuracy only reaching the millisecond level or above, which cannot meet the timing verification requirements of multi-terminal collaborative decision-making and is prone to misjudgment of test results.

[0005] The evaluation system is fragmented: Current assessments of self-healing functions often focus on single indicators such as "fault isolation time" and "power restoration rate," lacking a quantitative evaluation system that covers the accuracy of coordinated actions, timing coordination, and anti-interference robustness, making it difficult to comprehensively measure the reliability of multi-terminal collaborative self-healing.

[0006] Low testing efficiency: Traditional testing requires manual configuration of fault parameters, manual recording of terminal action data, and manual analysis of test results. For complex scenarios, the testing cycle can take several days, and test cases are difficult to reuse, which cannot meet the needs of batch debugging and iterative optimization of distribution network protection terminals.

[0007] In summary, existing testing technologies cannot comprehensively, accurately, and efficiently verify the collaborative self-healing function of distributed protection terminals in distribution networks. There is an urgent need to build a collaborative testing scheme that covers "complex scenario simulation, high-precision synchronous control, quantitative evaluation, and automated testing". Summary of the Invention

[0008] This invention provides a self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks to overcome the shortcomings of existing testing methods that are difficult to fully verify the collaborative self-healing function of multiple distributed protection terminals under complex fault scenarios.

[0009] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention discloses a self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks, comprising the following testing logic: 1) Based on the preset topology of the distribution network distributed protection self-healing system and the configuration of the distribution network distributed protection self-healing terminal, generate diverse fault scenario test cases, covering single-point faults, multi-point concurrent faults and fault superposition network reconstruction conditions. 2) By utilizing a multi-terminal synchronous control unit, the action commands of multiple distributed protection terminals are triggered synchronously, simulating the information interaction and collaborative decision-making process between terminals; 3) The data acquisition and analysis module records the action time, logic judgment results, fault isolation, and key indicators of power restoration path of each terminal in real time; 4) Based on the preset self-healing function evaluation system, the accuracy, timeliness and coordination of multi-terminal collaborative actions are quantitatively evaluated, and a test report is generated. The self-healing protection system includes a cloud platform layer as the intelligent hub, a device layer as the physical signal source, and an edge control layer as the real-time collaborative hub connecting the cloud and field devices.

[0010] Furthermore, the cloud platform layer includes test task management, providing centralized capabilities for creating, storing, orchestrating, and reusing complex test cases, significantly improving test preparation efficiency and standardization; performance evaluation and analysis, leveraging the powerful computing capabilities of the cloud to deeply mine massive amounts of test data, automatically calculating key performance indicators such as action time, positioning accuracy, and recovery time, conducting comparative analysis, trend prediction, bottleneck identification, and compliance verification, providing data support for product optimization and decision-making; and result visualization, transforming complex data into intuitive charts and automated test reports, making test results and system status readily apparent.

[0011] Furthermore, the cloud platform layer has the following functions: Full lifecycle management of test cases: Provides a visual test case editing tool, which supports users to generate a three-level test case library of "basic scenario test cases - complex scenario test cases - extreme scenario test cases" according to different types of distribution network topologies, distribution network distributed protection terminal configurations, and fault types. It also supports test case storage, version management, and reuse, reducing the workload of repetitive configuration. Distributed computing power scheduling and deep analysis: Utilize cloud-based distributed computing power to process massive amounts of test data uploaded from the edge layer in real time, automatically calculate key indicators such as action response time, coordination deviation, and fault location accuracy, and identify the coordination performance between distributed protection self-healing terminals of various distribution networks through trend analysis; Visualized results presentation and report generation: The analysis results are transformed into "time-series flowcharts, indicator comparison radar charts, and fault evolution dynamic simulation charts", and test reports that meet the power industry standards are automatically generated, supporting report export and online traceability.

[0012] Furthermore, the equipment layer is equipped with a signal generator, which, according to the instructions of the edge controller, accurately simulates the operation or fault state of the power grid and injects voltage and current signals into the terminal.

[0013] Furthermore, the device layer serves as the material foundation for building a reliable testing environment, providing high-fidelity physical stimuli for the terminals. The terminals are the objects under test and service targets of the framework, representing the secondary equipment actually deployed in the power grid. Through cloud management, edge control, and device stimuli, the testing framework comprehensively verifies the functional correctness, performance indicators, and interoperability of these terminals in terms of protection, control, automation, communication, and collaborative logic, ensuring their ability to guarantee the safe, reliable, efficient, and self-healing operation of the power grid.

[0014] Furthermore, the edge control layer has an edge collaboration controller, which is responsible for parsing cloud commands and distributing them to the device layer and terminal layer, executing local control logic, monitoring status and providing feedback, and making collaborative judgments in complex multi-terminal interaction scenarios.

[0015] Furthermore, the edge collaboration controller has the following functions: High-precision clock synchronization: The "BeiDou + PTPv2" dual-mode clock synchronization protocol is adopted to distribute time signals with nanosecond precision to the device layer and terminal layer, ensuring that the current / voltage signals output by multiple signal generators and the action commands of multiple protection terminals are based on a unified time reference, thus meeting the timing verification requirements of collaborative self-healing. Command parsing and collaborative judgment: Real-time parsing of test case commands issued from the cloud, breaking them down into "signal generator control commands and terminal action trigger commands", and dynamically adjusting command priorities according to the test scenario; at the same time, judging the collaborative decision-making process of multiple terminals to ensure no command conflicts; Local fault tolerance and data preprocessing: It has local fault detection capabilities, such as signal generator disconnection or terminal communication interruption; it can automatically trigger backup plans, such as switching to a backup signal generator or enabling locally cached test cases; it compresses and preprocesses the collected raw data to reduce the amount of data transmitted to the cloud and reduce network bandwidth pressure.

[0016] The beneficial effects achieved by this invention are as follows: By constructing a multi-machine co-control test environment, integrating a distribution network simulation system, a multi-terminal synchronous control unit, and a data acquisition and analysis module, it can simulate fault types, fault propagation processes, and network topology changes in different areas of the distribution network. This invention can realistically simulate the actual operating environment of the distributed protection terminal in the distribution network, comprehensively verify the effectiveness and reliability of the multi-terminal collaborative self-healing function, provide a scientific testing basis for the debugging and optimization of the distributed protection system of the distribution network, and help improve the power supply reliability and self-healing capability of the distribution network. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a system connection diagram of the present invention; Figure 2 This is a schematic diagram of the platform architecture of the present invention; Figure 3 This is a schematic diagram of the testing cloud platform functionality of the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] Example 1 like Figure 1-3 As shown, a self-healing collaborative testing method for distributed protection terminals in a multi-machine co-controlled distribution network includes the following test logic: First, based on the pre-defined topology of the distribution network distributed protection self-healing system and the configuration of the distributed protection self-healing terminals, diverse fault scenario test cases are generated, covering single-point faults, multi-point concurrent faults, and fault superposition network reconstruction. Second, using a multi-terminal synchronous control unit, action commands for multiple distributed protection terminals are triggered synchronously, simulating the information interaction and collaborative decision-making process between terminals. Subsequently, the data acquisition and analysis module records key indicators such as the action time, logical judgment results, fault isolation, and power restoration path of each terminal in real time. Finally, based on the pre-defined self-healing function evaluation system, the accuracy, timeliness, and coordination of the multi-terminal collaborative actions are quantitatively evaluated, and a test report is generated. Cloud Platform Layer The cloud platform layer, serving as the intelligent hub of the entire framework, offers core functions including test task management, providing centralized capabilities for creating, storing, orchestrating, and reusing complex test cases, significantly improving test preparation efficiency and standardization; performance evaluation and analysis, leveraging the powerful computing capabilities of the cloud to deeply mine massive amounts of test data, automatically calculating key performance indicators such as action time, positioning accuracy, and recovery time, conducting comparative analysis, trend prediction, bottleneck identification, and compliance verification, providing data support for product optimization and decision-making; and result visualization, transforming complex data into intuitive charts and automated test reports, making test results and system status readily apparent. The cloud platform layer digitizes and intelligentizes the testing process, serving as the core engine for enhancing the value of the testing system and driving performance optimization. Its main functions include: Full lifecycle management of test cases: Provides a visual test case editing tool, which supports users to generate a three-level test case library of "basic scenario test cases - complex scenario test cases - extreme scenario test cases" according to different types of distribution network topologies, distribution network distributed protection terminal configurations, and fault types. It also supports test case storage, version management, and reuse, reducing the workload of repetitive configuration.

[0020] Distributed computing power scheduling and deep analysis: Utilizing cloud-based distributed computing power, massive test data uploaded from the edge layer is processed in real time, automatically calculating key indicators such as action response time, coordination deviation, and fault location accuracy. Furthermore, trend analysis is used to identify the coordination performance between distributed protection self-healing terminals in various distribution networks.

[0021] Visualized results presentation and report generation: The analysis results are transformed into "time-series flowcharts, indicator comparison radar charts, and fault evolution dynamic simulation charts", and test reports that meet the power industry standards are automatically generated, supporting report export and online traceability.

[0022] Edge control layer The edge control layer serves as a real-time collaborative hub connecting the cloud and field devices, handling tasks requiring high timeliness and reliability. Its core lies in the edge collaborative controller, responsible for parsing cloud commands and distributing them to the device and terminal layers, executing local control logic, monitoring status and providing feedback, and making collaborative judgments in complex multi-terminal interaction scenarios. Clock synchronization is a fundamental function, distributing high-precision time signals to the device and terminal layers through a precise protocol to ensure the time consistency of the entire system. Test task scheduling efficiently and systematically manages the local test task queue, resource allocation, and anomaly handling. Signal logic analysis performs real-time parsing of the acquired raw signals, preliminary logic state judgment, and simple fault diagnosis, and performs data preprocessing to reduce the burden on the cloud. The edge layer compensates for the lack of real-time performance in the cloud, ensuring accurate test execution and reliable results.

[0023] High-precision clock synchronization: The "BeiDou + PTPv2" dual-mode clock synchronization protocol is adopted to distribute time signals with nanosecond precision to the device layer and terminal layer, ensuring that the current / voltage signals output by multiple signal generators and the action commands of multiple protection terminals are based on a unified time reference, thus meeting the timing verification requirements for collaborative self-healing.

[0024] Command parsing and collaborative judgment: Real-time parsing of test case commands issued from the cloud, breaking them down into "signal generator control commands and terminal action trigger commands", and dynamically adjusting command priorities according to the test scenario; at the same time, judging the collaborative decision-making process of multiple terminals to ensure no command conflicts.

[0025] Local fault tolerance and data preprocessing: It has local fault detection capabilities, such as signal generator disconnection or terminal communication interruption; it can automatically trigger backup plans, such as switching to a backup signal generator or enabling locally cached test cases; it compresses and preprocesses the collected raw data to reduce the amount of data transmitted to the cloud and reduce network bandwidth pressure.

[0026] Equipment layer The device layer is the physical signal source of the entire test framework, with a high-precision signal generator at its core. Following instructions from the edge controller, the signal generator accurately simulates power grid operation or fault conditions, injecting voltage and current signals into the terminal. The performance indicators of the test equipment are the core guarantee of test effectiveness: high-precision output ensures highly accurate voltage and current amplitudes; excellent time synchronization capabilities ensure strict synchronization between multiple outputs and multiple devices, forming the basis for tests that rely on precise timing functions; extremely low waveform distortion indicates a highly pure output signal, close to an ideal waveform, ensuring the authenticity of the test signal and avoiding misjudgments due to defects in the signal source itself. As the material foundation for building a reliable test environment, the core function of the device layer is to provide high-fidelity physical stimulation to the terminal.

[0027] The terminal in the device layer is the object under test and the service target of the framework, representing the secondary equipment actually deployed in the power grid.

[0028] The testing framework comprehensively verifies the functional correctness, performance indicators, and interoperability of these terminals in terms of protection, control, automation, communication, and collaborative logic through cloud management, edge control, and device incentives, ensuring their ability to guarantee the safe, reliable, efficient, and self-healing operation of the power grid.

[0029] First, the test scenarios are more realistic. Through multi-machine control and a three-level architecture, it can simulate complex scenarios of "faults, distributed energy sources, and topology changes" superimposed on the distribution network. The test results can better reflect the collaborative self-healing capabilities of the terminals in actual operation, providing a reliable basis for the field deployment of distribution network protection systems.

[0030] Significantly improved verification accuracy: Nanosecond-level clock synchronization and collaborative arbitration mechanism ensure the verification accuracy of multi-terminal action timing and avoid test misjudgment caused by synchronization errors; high-precision signal generator provides high-fidelity physical excitation, further improving the accuracy of test results.

[0031] Secondly, the evaluation results are more comprehensive and reliable. The multi-dimensional quantitative evaluation system covers the core performance indicators of collaborative self-healing, which can comprehensively measure the functional correctness and reliability of the terminal, and provide accurate data support for the design optimization of the terminal.

[0032] Furthermore, testing efficiency is significantly improved. The full-process automation and test case reuse mechanism greatly shortens the testing cycle, reduces labor costs, and can meet the full lifecycle testing needs of distribution network protection terminals from R&D and debugging, factory inspection to on-site operation and maintenance.

[0033] Finally, it promotes industry standardization. The testing methods and evaluation system of this invention are compatible with relevant industry standards, and its test case library and report format can serve as reference templates for collaborative testing of distributed protection terminals in distribution networks, thus promoting the standardized development of industry testing technologies.

[0034] The four main features of this plan are: 1. A three-tiered, multi-machine, simultaneous control testing system enables high-fidelity simulation in complex scenarios. Breaking away from the traditional "single-machine testing" model, a three-tiered "cloud-edge-device" architecture is constructed: the cloud layer is responsible for generating complex test cases and conducting in-depth analysis; the edge layer achieves nanosecond-level clock synchronization and real-time collaborative control; and the device layer provides high-precision physical stimuli. The three layers work together to simulate complex scenarios involving the superposition of "faults, distributed energy fluctuations, and topology reconfiguration," solving the problems of existing test scenarios being too simplistic and disconnected from actual operation. At the same time, the multi-machine control mode supports the simultaneous testing of up to 10 protection terminals, meeting the verification requirements for large-scale terminal collaborative self-healing in the distribution network.

[0035] 2. The "dual-mode clock synchronization + collaborative arbitration" mechanism ensures the accuracy of timing verification across multiple terminals. By adopting "BeiDou + PTPv2" dual-mode clock synchronization, the time synchronization accuracy is improved to the nanosecond level, solving the problem of insufficient synchronization accuracy in the existing system. At the same time, the edge collaboration controller adds "collaboration judgment logic", which can dynamically adjust the priority of action commands of multiple terminals according to the test scenario, avoid command conflicts, ensure that the timing of actions of multiple terminals is consistent with the theoretical logic, and improve the timing verification accuracy of the collaborative self-healing function.

[0036] 3. A multi-dimensional quantitative evaluation system enables a comprehensive assessment of the collaborative self-healing function. A four-dimensional evaluation system covering "action accuracy, timing coordination, fault handling efficiency, and anti-interference robustness" has been established. Multiple quantifiable indicators have been designed, and qualified thresholds that match industry standards have been set to solve the problems of fragmentation and focus on only a single indicator in the existing evaluation system. At the same time, the cloud automatically calculates the indicators and generates visual reports through distributed computing power, which greatly improves the efficiency and credibility of test results analysis.

[0037] 4. Full lifecycle management and automation of test cases to improve testing efficiency and reusability. The cloud platform layer constructs a three-level test case library, supporting visual editing, version management, and reuse of test cases, reducing the workload of manual configuration. At the same time, it realizes full-process automation of "test case distribution, synchronous triggering, data collection, and report generation", shortening the testing cycle for complex scenarios from several days to several hours, meeting the needs of batch debugging and iterative optimization of distribution network protection terminals.

[0038] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention. The terminology used in the description of this application is only for describing specific embodiments and is not intended to limit the exemplary embodiments according to this application. For ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings indicate similar items, and therefore, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0039] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and are not limited in number; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0040] It should be noted that in the description of this application, the directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this application. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

Claims

1. A self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks, characterized in that, Includes the following steps: Based on the preset topology of the distribution network distributed protection self-healing system and the configuration of the distribution network distributed protection self-healing terminal, a variety of fault scenario test cases are generated, covering single-point faults, multi-point concurrent faults and fault superposition network reconstruction conditions. By utilizing a multi-terminal synchronous control unit, the action commands of multiple distributed protection terminals are triggered synchronously, simulating the information interaction and collaborative decision-making process between terminals; The data acquisition and analysis module records key indicators such as the action time, logic judgment results, fault isolation, and power restoration path of each terminal in real time. Based on the pre-set self-healing function evaluation system, the accuracy, timeliness and coordination of multi-terminal collaborative actions are quantitatively evaluated, and a test report is generated. The self-healing protection system includes a cloud platform layer as the intelligent hub, a device layer as the physical signal source, and an edge control layer as the real-time collaborative hub connecting the cloud and field devices.

2. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 1, characterized in that, The cloud platform layer includes test task management, providing centralized capabilities for creating, storing, orchestrating, and reusing complex test cases; performance evaluation and analysis, leveraging the powerful computing capabilities of the cloud to deeply mine massive amounts of test data, automatically calculating key performance indicators such as action time, positioning accuracy, and recovery time, conducting comparative analysis, trend prediction, bottleneck identification, and compliance verification, providing data support for product optimization and decision-making; and result visualization, transforming complex data into intuitive charts and automated test reports, making test results and system status readily apparent.

3. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 2, characterized in that, The cloud platform layer has the following functions: Full lifecycle management of test cases: Provides a visual test case editing tool, which supports users to generate a three-level test case library of "basic scenario test cases - complex scenario test cases - extreme scenario test cases" according to different types of distribution network topologies, distribution network distributed protection terminal configurations, and fault types. It also supports the storage, version management and reuse of test cases, reducing the workload of repetitive configuration. Distributed computing power scheduling and deep analysis: Utilizing cloud-based distributed computing power, massive test data uploaded from the edge control layer is processed in real time, and key indicators such as action response time, coordination deviation, and fault location accuracy are automatically calculated. Furthermore, trend analysis is used to identify the coordination performance between distributed protection self-healing terminals in various distribution networks. Visualized results presentation and report generation: The analysis results are transformed into "time series flowcharts, indicator comparison radar charts, and fault evolution dynamic simulation charts", and test reports that meet the power industry standards are automatically generated, supporting report export and online traceability.

4. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 1, characterized in that, The edge control layer is equipped with an edge collaboration controller, which is responsible for parsing cloud instructions and distributing them to the device layer and terminal layer, executing local control logic, monitoring status and providing feedback, and making collaborative judgments in complex multi-terminal interaction scenarios.

5. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 4, characterized in that, The edge collaboration controller has the following functions: High-precision clock synchronization: The "BeiDou + PTPv2" dual-mode clock synchronization protocol is adopted to distribute time signals with nanosecond precision to the device layer and terminal layer, ensuring that the current / voltage signals output by multiple signal generators and the action commands of multiple protection terminals are based on a unified time reference, thus meeting the timing verification requirements for collaborative self-healing. Command parsing and collaborative judgment: Real-time parsing of test case commands issued from the cloud, breaking them down into "signal generator control commands and terminal action trigger commands", and dynamically adjusting command priorities according to the test scenario; at the same time, judging the collaborative decision-making process of multiple terminals to ensure no command conflicts; Local fault tolerance and data preprocessing: It has local fault detection capabilities, such as signal generator disconnection or terminal communication interruption; it can automatically trigger backup plans, such as switching to a backup signal generator or enabling locally cached test cases; The collected raw data is compressed and preprocessed to reduce the amount of data transmitted to the cloud and reduce network bandwidth pressure.

6. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 1, characterized in that, The device layer is equipped with a signal generator, which, according to the instructions of the edge coordinating controller, accurately simulates the operation or fault state of the power grid and injects voltage and current signals into the terminal.

7. The self-healing collaborative testing method for distributed protection terminals in multi-machine co-control distribution networks according to claim 6, characterized in that, The device layer serves as the material foundation for building a reliable testing environment, providing high-fidelity physical stimuli for the terminal. The terminal is the object under test and the service target of the framework, representing the secondary equipment actually deployed in the power grid. Through cloud management, edge control, and device stimuli, the testing framework comprehensively verifies the terminal's functional correctness, performance indicators, and interoperability in terms of protection, control, automation, communication, and collaborative logic, ensuring its ability to guarantee the safe, reliable, efficient, and self-healing operation of the power grid.

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