Metering acquisition full-scene automatic simulation detection method and system

Abstract

The invention discloses a metering acquisition full-scene automatic simulation detection method and system. The method comprises the following steps: selecting a detection target for detected equipment, and associating a transformer area topology template, an impedance parameter and a load strategy; a multi-bypass wiring technology is utilized to automatically switch physical line connection through a network-to-relay, and a topological structure of a target station area is reconstructed; the output of the adjustable impedance equipment is adjusted through a compensation algorithm, so that the line impedance of the tested equipment is consistent with the target impedance value; automatically controlling the controllable load device and generating a load time sequence; issuing an instruction to the tested equipment and acquiring response data; and the response data, the topological structure of the target transformer area, the line impedance and the load time sequence are stored in an associated mode, the matching degree and the impedance deviation of a topology recognition result and a transformer area topology template are calculated based on a graph isomorphism algorithm, and a detection report is generated. The method has the advantages that full-scene automation of measurement acquisition equipment detection is realized, and the detection efficiency, accuracy and repeatability are improved.

Description

Technical Field

[0001] This application relates to the field of power system automation testing technology, specifically to a full-scenario automated simulation testing method and system for metering acquisition. Background Technology

[0002] With the deepening of smart grid construction, power metering and electricity consumption information collection systems have become core infrastructure for power grid operation monitoring, load management, and electricity billing. At the distribution substation side, a large number of metering and data collection devices, including meters, concentrators, measuring switches, communication units, and modules, are deployed on-site. These devices collectively constitute the metering and data collection link at the substation side, and their operational status directly affects the accuracy, completeness, and real-time performance of electricity consumption data. To ensure the reliable operation of the data collection system, operating units need to conduct comprehensive testing on the communication capabilities, topology identification capabilities, impedance calculation capabilities, and performance under different load conditions of the aforementioned devices before they are connected to the grid or during operation and maintenance.

[0003] Currently, the testing of metering and data acquisition equipment generally adopts a decentralized construction model of "one type of equipment, one testing device": electricity meters are equipped with dedicated electricity meter testing stations, concentrators with concentrator testing stations, measuring switches with measuring switch testing stations, and communication units and modules are also equipped with their own independent testing fixtures. The testing logic, testing items, and judgment criteria of each type of testing device are mostly fixed designs, and can only execute preset test procedures for a single type of equipment. This decentralized testing model has the following technical drawbacks:

[0004] First, the testing platform is fragmented and lacks multi-device collaborative testing capabilities. Because different devices rely on independent testing units, joint testing across device types is difficult to conduct, making it impossible to verify the collaborative operation performance of devices such as meters, concentrators, measuring switches, and communication units under complex field conditions from a holistic system perspective. For example, the topology identification results of the measuring switch need to be reported to the main station via the concentrator, but existing single-device testing devices cannot fully simulate this end-to-end data link.

[0005] Secondly, the detection of transformer topology identification capability relies on manual operation, which is inefficient and prone to errors. The topology identification function of the measuring switch needs to be verified for accuracy under different branch and node power conditions. Traditional testing devices often use manual plugging and unplugging of cables or moving of physical switches to construct different topology configurations. Each time a topology is switched, the testing personnel need to rewire according to the wiring diagram, which is cumbersome, time-consuming, and frequent plugging and unplugging can easily lead to poor contact or line damage, posing safety hazards.

[0006] Third, impedance calculation capability testing relies on manual adjustment, making it difficult to guarantee test accuracy. To verify the accuracy of impedance calculation by the measuring switch, different line impedance values ​​need to be applied to the device under test during testing. Existing testing devices typically use adjustable impedance boxes with manual knob adjustments. Testers adjust the boxes step by step and manually record the impedance calculation results reported by the device, then compare them with preset values. The workload for testing multiple impedances and various combinations of operating conditions is enormous, and manual adjustment and reading errors are difficult to avoid, affecting the objectivity of the test results.

[0007] Fourth, the load scenarios are too simple and lack repeatability. To simulate equipment response under different power consumption scenarios, varying load conditions need to be constructed during testing. Existing tests mostly use fixed loads or manually opening and closing load circuits, which makes it difficult to accurately control the timing, amplitude, and combination of load changes. This results in poor consistency of operating conditions between different batches of tests, making it impossible to guarantee the comparability and authority of test conclusions.

[0008] Furthermore, with the widespread adoption of advanced applications such as low-voltage distribution area topology identification, fault location, and line loss analysis, the collaborative relationships between metering and data acquisition devices are becoming increasingly complex. The industry has placed new demands on testing technology, requiring "full-scenario, full-link, and configurable" solutions. This necessitates verifying the entire system's response behavior under complex conditions such as topology changes, impedance anomalies, load surges, and communication disturbances in a near-realistic simulation environment. Traditional testing devices relying solely on single equipment and single-scenario approaches can no longer meet these technological development needs. Summary of the Invention

[0009] This application provides a fully automated simulation testing method and system for metering data acquisition, which solves the problems of low testing efficiency, large testing errors, and inability to achieve multi-device collaboration and fully automated testing when testing metering data acquisition equipment using existing methods.

[0010] This application provides a full-scenario automated simulation testing method for metering acquisition, which is applied to a full-scenario automated simulation testing system for metering acquisition. The system includes the device under test, a network-to-relay converter, an adjustable impedance device, a controllable load device, and physical circuitry. The method specifically includes a testing task configuration step, a scenario construction step, an impedance adjustment step, a load control step, a testing step, and a result generation step.

[0011] The detection task configuration step is used to configure detection items, detection cases, and detection sets, select detection targets for the device under test, and associate them with corresponding transformer area topology templates, impedance parameters, and load strategies. The scenario construction step reconstructs the target transformer area topology structure based on the transformer area topology template, using multi-bypass cabling technology and the network-to-relay system to automatically switch the physical line connections. The impedance adjustment step adjusts the actual output of the adjustable impedance device based on the impedance parameters using a compensation algorithm, ensuring that the line impedance applied to the device under test by the adjustable impedance device matches the target impedance value of the impedance parameters. The load control step is based on the load... The load strategy automatically controls controllable load devices and generates load timing sequences to dynamically simulate load change characteristics under actual operating scenarios. The detection step involves issuing detection commands to the device under test and collecting the response data of the device under test in real time, generating a comprehensive detection conclusion based on the response data. The result generation step involves associating and storing the response data with the target transformer area topology, the line impedance, and the load timing sequence, and calculating the matching degree between the topology identification result of the device under test and the transformer area topology template using a graph isomorphism algorithm based on the associated stored data, calculating the impedance deviation of each branch of the target transformer area topology, and generating a detection report.

[0012] Furthermore, the scenario construction steps specifically include a transformer area topology template preset step, a line multiplexing step, a switch matrix acquisition step, and a topology structure switching step.

[0013] The transformer area topology template preset step is used to preset two or more transformer area topology templates. Each transformer area topology template corresponds to a set of logical nodes, line connection relationships, and the corresponding network-to-relay channel open / close status. The line multiplexing step is to multiplex the line connection relationships corresponding to the transformer area topology templates into the physical lines, so that each physical line corresponds to two or more sets of logical nodes. The switch matrix acquisition step is to convert the transformer area topology templates corresponding to the multiplexed line connection relationships into switch matrices. The topology switching step is based on the obtained switch matrix to generate control commands executed by the network-to-relay, so as to realize the switching of the device under test from the current topology to the target transformer area topology.

[0014] Furthermore, the impedance adjustment step specifically includes a line detection step, a target range determination step, and an impedance error calculation step.

[0015] The line testing step involves testing the adjustable impedance device and phase corresponding to each physical line according to the configured testing items; the target range determination step involves monitoring the inherent impedance value in the physical line in real time based on the target impedance value, calculating the compensation amount, and determining the target range of the adjustable impedance device on each phase; the impedance error calculation step involves calculating the impedance error between the impedance calculation result of the tested device and the target impedance value when the phase range of the adjustable impedance device is not at the target range.

[0016] Furthermore, the load control steps specifically include a load policy configuration step, an instruction filtering step, and a load shutdown step.

[0017] The load strategy configuration step involves configuring the load switching mode, power level combination, minimum on-time, minimum off-time, and load change interval according to the load circuit and phase to form the load strategy; the instruction filtering step involves periodically generating load control instructions according to the load strategy, and filtering load control instructions that exceed the threshold based on the relationship between the total load of the current controllable load devices and a preset load threshold; the load shutdown step involves performing zeroing and disconnection operations on all controllable load devices until all controllable load devices are shut down.

[0018] Furthermore, the detection steps specifically include detection item execution steps, detection case execution steps, and detection set execution steps.

[0019] The execution steps for each test item are based on the test content and criteria defined in the test item, issuing corresponding instructions to the device under test, and monitoring whether its response data meets the criteria requirements to verify the compliance of a single functional point or a single business capability. The execution steps for each test case are based on the execution order and dependencies defined in the test case, executing the test items sequentially to form a complete test process, and summarizing the verification results of each test item. The execution steps for each test set are based on the transformer topology template, impedance parameters, and load strategies associated in the test set, sequentially calling the scenario construction step, the impedance adjustment step, and the load control step to construct the test environment, and executing the test cases to generate a comprehensive test conclusion.

[0020] Furthermore, the detection steps also include physical detection steps, simulation detection steps, and hybrid detection steps.

[0021] The physical testing step involves issuing testing commands to the physical device in the connected device under test (DUT) and receiving the response data returned by the physical device in real time as the physical testing result. The simulation testing step is used to call simulated voltage, current, event sequences, and communication messages to replace some or all of the physical electrical quantities input to the DUT. At the same time, it issues testing commands to the DUT and collects the response data of the DUT under the simulated input in real time as the simulation testing result. The hybrid testing step involves executing the physical testing step and the simulation testing step separately, comparing and analyzing the physical testing result and the simulation testing result to generate a hybrid testing result.

[0022] Furthermore, the full-scenario automated simulation detection method for metering acquisition also includes a dynamic configuration step. The dynamic configuration step is used to parse a preset schema file, extract hardware linkage rules from the schema file, dynamically generate configurable detection parameters based on the hardware linkage rules and the current hardware status, and generate corresponding hardware control instructions based on the detection parameters and the hardware linkage rules to collaboratively construct the detection environment.

[0023] Furthermore, generating the detection report specifically includes a graph structure transformation step, an isomorphism judgment step, a topology graph generation step, and a topology graph annotation step.

[0024] The graph structure conversion step converts the topology identification result of the device under test into a first graph structure and the transformer area topology template into a second graph structure. The isomorphism judgment step, based on a graph isomorphism algorithm, compares the first graph structure and the second graph structure node by node and edge by edge to determine whether they are isomorphic. If so, the topology identification is correct; if not, the differences between the first graph structure and the second graph structure are identified and marked. The topology graph generation step generates a topology graph based on the comparison results of the first graph structure and the second graph structure, and marks the actual impedance value and theoretical impedance value of each physical line on the topology graph. The topology graph annotation step marks the matching status or deviation degree of each physical line on the topology graph and generates the test report.

[0025] Furthermore, this application discloses a full-scenario automated simulation and detection system for metering acquisition, comprising a controller, the controller including a memory and a processor, the memory being used to store executable program code; the processor being used to read the executable program code to run a computer program corresponding to the executable program code to execute at least one step in the full-scenario automated simulation and detection method for metering acquisition.

[0026] Furthermore, the metering acquisition full-scenario automated simulation testing system also includes physical circuits, network-to-relay, adjustable impedance devices, controllable load devices, and the device under test.

[0027] The physical circuit is laid out using multi-bypass wiring technology; the input terminal of the network-to-relay is connected to the controller, and its output terminal is connected to a node of the physical circuit; the adjustable impedance device is connected in series in the physical circuit and is connected to the controller; the controllable load device includes multiple controllable load units, which are connected to different phases and circuits of the physical circuit through load switches, and the controllable load device is connected to the controller; the device under test is electrically connected to the corresponding node of the physical circuit.

[0028] This application provides a fully automated simulation testing method and system for metering acquisition. By incorporating the metering acquisition devices under test into the same system for centralized management and collaborative testing, it solves the problems of fragmented traditional decentralized testing platforms and the inability to conduct joint testing. Through multi-bypass cabling technology, various line topologies are reused within a limited physical space, and with the automated switching of the network-to-relay matrix, rapid reconstruction of the transformer area topology is achieved. By real-time monitoring of the inherent impedance of physical lines and using a compensation algorithm to adjust the output of adjustable impedance devices, the influence of the system's own line impedance on the test results is eliminated, ensuring the accuracy of impedance application. The test items, test cases, and test sets are configured in a three-level manner, combined with a dynamic configuration mechanism, to achieve collaborative control of test parameters and hardware, reducing process modification costs. A graph isomorphism algorithm is used to automatically compare topology identification results, combined with impedance deviation calculation, to generate a visual report, achieving automated result judgment. This application eliminates the risk of manual operation; the input conditions for each test can be recorded and replayed, supporting full playback and audit traceability of the testing task, significantly improving the testing efficiency and accuracy of metering acquisition devices, and ensuring the repeatability and objectivity of the test results. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a schematic diagram of the fully automated simulation and detection system for metering data acquisition described in the embodiments of this application; Figure 2 This is a flowchart of the automated simulation and detection method for metering data acquisition in all scenarios described in the embodiments of this application; Figure 3This is a flowchart of the scene construction steps described in the embodiments of this application; Figure 4 This is a flowchart of the impedance adjustment steps described in the embodiments of this application; Figure 5 This is a flowchart of the load control steps described in the embodiments of this application; Figure 6 This is the flow chart of the detection steps described in the embodiments of this application. Figure 1 ; Figure 7 This is the flow chart of the detection steps described in the embodiments of this application. Figure 2 ; Figure 8 This is a flowchart illustrating the generation of a test report as described in an embodiment of this application; Figure 9 This is an example of the generated visual topology map described in the embodiments of this application. Detailed Implementation

[0031] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] In existing technologies, when conducting network access testing, operational spot checks, and fault reproduction on various metering and data acquisition devices such as electricity meters, concentrators, measuring switches, communication units, and modules, the current testing methods rely on manual plugging and unplugging of cables to switch topologies, manual adjustment of impedance using knobs, and manual opening and closing of load circuits. This results in problems such as low testing efficiency, high operational risks, incomplete scenario coverage, and difficulty in coordinating testing of multiple devices.

[0033] This application constructs a unified testing platform to achieve automatic reconstruction of transformer topology, automatic adjustment of line impedance, and automatic generation of load scenarios, providing a full-scenario, automated, and repeatable simulation testing platform for metering and data acquisition equipment. Specifically, it includes the following:

[0034] like Figure 1 As shown, this application provides a full-scenario automated simulation and testing system for metering acquisition, including a user layer, a kernel layer, an acquisition layer, and a hardware layer. The hardware layer includes a controller (not shown), physical circuits (not shown), a network-to-relay (not shown), an adjustable impedance device (not shown), a controllable load device (not shown), and the device under test (not shown).

[0035] The physical circuit is laid out using multi-bypass wiring technology; the input terminal of the network-to-relay is connected to the controller, and its output terminal is connected to a node of the physical circuit; the adjustable impedance device is connected in series in the physical circuit and is connected to the controller; the controllable load device includes multiple controllable load units, which are connected to different phases and circuits of the physical circuit through load switches, and the controllable load device is connected to the controller; the device under test is electrically connected to the corresponding node of the physical circuit, and the device under test is the multi-type metering and acquisition device.

[0036] Specifically, the physical lines are laid out using multi-bypass cabling technology, which reuses lines of various topologies on the same physical platform, enabling limited physical space to support the testing needs of various transformer area topologies.

[0037] Multi-bypass cabling technology refers to a cabling design method that, within a limited physical space, reuses the line connection relationships of various transformer area topologies into the same set of physical lines, allowing each physical line to carry different logical connection relationships under different detection tasks. Combined with network-to-relay matrix and switch matrix control, it realizes dynamic mapping and automated switching between physical lines and logical topologies.

[0038] The input terminal of the network-to-relay is connected to the controller, and its output terminal is connected to each node of the physical line. It is used to dynamically switch the on / off state between each node according to the switch matrix command issued by the controller, so as to realize the automatic reconstruction of the transformer area topology.

[0039] The adjustable impedance device is connected in series in a designated branch of the physical line, and the control terminal of the adjustable impedance device is connected to the controller. It is used to adjust its own impedance value according to the impedance adjustment command, and after being superimposed with the inherent impedance of the physical line, it provides a preset target impedance for the device under test.

[0040] The controllable load device includes multiple controllable load units, each of which is connected to different phases and circuits of the physical line via a load switch. The control terminal of the controllable load device is connected to the controller to generate load timing according to the load strategy and dynamically simulate the load change characteristics under actual operating scenarios.

[0041] The device under test is electrically connected to the corresponding node of the physical line to access the reconstructed transformer substation topology for testing.

[0042] Its technical advantages lie in the fact that the multi-bypass cabling technology combined with the network-to-relay matrix transforms the switching of transformer topology from manual cable plugging and unplugging to automated control, supporting rapid reconstruction of various topology configurations within a limited space, significantly improving testing efficiency and scene coverage; the superposition compensation mechanism of adjustable impedance devices and inherent line impedance eliminates the influence of the testing system's own line impedance on the test results, ensuring impedance application accuracy and providing a reliable basis for measuring the impedance calculation capability of the device under test; the multi-unit independent control capability of the controllable load device supports the generation of load timing according to preset modes, random fluctuations, or real load curves, realizing dynamic simulation of complex operating conditions; the centralized control of each execution unit by the controller automates the entire process of topology switching, impedance adjustment, and load construction, eliminating the risks of manual operation and ensuring the safety and repeatability of the testing process.

[0043] The controller includes a memory and a processor. The memory is used to store executable program code. The processor is used to read the executable program code to run a computer program corresponding to the executable program code, so as to execute at least one step in the full-scene automated simulation detection method for metering acquisition, realize the detection of metering acquisition equipment, and realize the hardware support of the detection method.

[0044] like Figure 2 As shown, this application also provides a full-scenario automated simulation and testing method for metering acquisition, applied to the full-scenario automated simulation and testing system for metering acquisition, specifically including step S1) testing task configuration step, step S2) scenario construction step, step S3) impedance adjustment step, step S4) load control step, step S5) testing step and step S6) result generation step.

[0045] Step S1) Detection task configuration step, used to configure detection items, detection cases and detection sets, select detection targets for the device under test, and associate the corresponding transformer area topology template, impedance parameters and load strategy.

[0046] Specifically, each of the aforementioned test items describes the test content and corresponding criterion threshold for a single functional point or single business capability; each of the aforementioned test cases combines multiple of the aforementioned test items according to a preset execution order and dependency relationship to form a complete test process applicable to a specific device type or a specific test target; each of the aforementioned test sets binds one or more of the aforementioned test cases with the transformer topology template, impedance parameters, and load strategy required to execute the test, forming a test scheme that can be executed with one click; finally, a test target is selected for the connected device under test, and the corresponding test set is retrieved from the preset test set according to the test target to complete the initial configuration of the test task.

[0047] Its technical advantages are as follows: First, the three-level configuration structure of test items, test cases, and test sets decouples the test content, test process, and test environment parameters, enabling business personnel to flexibly construct new test solutions through combination and binding operations without modifying the underlying program, significantly reducing the system transformation costs brought about by new business requirements or new procedure versions. Second, binding the transformer area topology template, impedance parameters, and load strategies with test cases standardizes and repeats the execution environment configuration of each test task, ensuring that the same test solution has consistent input conditions when executed at different times and in different batches, improving the comparability of test results. Third, by selecting test targets for the device under test and automatically associating them with the corresponding test sets, the test task can be quickly initialized, laying the foundation for subsequent automated test processes.

[0048] Step S2) Scenario construction step: Based on the transformer area topology template, using multi-bypass cabling technology, the physical line connection is automatically switched through the network-to-relay relay to reconstruct the target transformer area topology.

[0049] like Figure 3 As shown, step S2) scenario construction step specifically includes step S21) transformer area topology template preset step, step S22) line multiplexing step, step S23) switch matrix acquisition step and step S24) topology structure switching step.

[0050] Step S21) Presetting the transformer area topology template: Preset two or more transformer area topology templates. Each transformer area topology template corresponds to a set of logical nodes, line connection relationships and the corresponding network to relay channel opening and closing status. In this application, there are 156 transformer area topology templates. The types of transformer area topology templates can be increased or decreased according to needs.

[0051] Step S22) Line multiplexing step: The line connection relationship corresponding to the transformer area topology template is reused in the physical line, so that each physical line corresponds to two or more sets of logical nodes.

[0052] Step S23) Switch matrix acquisition step: Convert the transformer area topology template corresponding to the multiplexed line connection relationship into a switch matrix.

[0053] Step S24) Topology switching step: Based on the obtained switch matrix, generate the control command executed by the network-to-relay to realize the switching of the device under test from the current topology to the target area topology.

[0054] In this application, dynamic reorganization of hardware resources is driven by pre-set transformer area topology templates. First, the system pre-sets two or more transformer area topology templates. Each template defines the logical node distribution, line connection relationships, and corresponding network-to-relay channel opening / closing states that should be present when the device under test (DUT) is connected to the detection system. Based on multi-bypass cabling technology, the line connection relationships corresponding to various transformer area topology templates are reused within a limited number of physical lines, allowing each physical line to carry different logical connection relationships under different topology templates, thus achieving decoupling and mapping between physical resources and logical topology. When a target transformer area topology template is selected for the detection task, the system converts the target template into a switch matrix. The rows and columns of the switch matrix correspond to physical ports, and the matrix elements represent the on / off states between ports. Based on the switch matrix, the system generates all network-to-relay control commands at once, which are executed in parallel through the network-to-relay matrix, enabling the connection states of the physical lines to quickly switch from the current topology to the target transformer area topology, completing the automated construction of the detection scenario.

[0055] Its technical advantages are as follows: First, it reuses the line connection relationships of various transformer area topology templates on a limited physical line, enabling the testing system to support the testing needs of various topology forms within a limited laboratory space, significantly improving the utilization rate of hardware resources. Second, the one-time command issuance mechanism based on the switch matrix reduces the time required for topology switching from several minutes of traditional manual cable plugging and unplugging to milliseconds, and the switching process requires no manual intervention, completely eliminating the risk of misoperation. Third, each topology switch is executed based on a preset template, ensuring that the same topology template presents a completely consistent line connection state when executed at different times and in different batches, providing a physical basis for the repeatability of test results. Fourth, the automated topology reconstruction capability enables the testing system to cover various business scenarios such as normal operation, topology changes, and branch faults, providing a comprehensive verification method for verifying the topology recognition capability of the device under test.

[0056] Step S3) Impedance adjustment step: Based on the impedance parameters, the actual output of the adjustable impedance device is adjusted by a compensation algorithm so that the line impedance applied by the adjustable impedance device to the device under test is consistent with the target impedance value of the impedance parameters.

[0057] like Figure 4 As shown, step S3) impedance adjustment step specifically includes step S31) line detection step, step S32) target range determination step and step S33) impedance error calculation step.

[0058] Step S31) Line detection step: Based on the configured detection items, detect the adjustable impedance device and phase corresponding to each physical line.

[0059] Step S32) Target range determination step: Based on the target impedance value, monitor the inherent impedance value in the physical line in real time, calculate the compensation amount, and determine the target range of the adjustable impedance device on each phase. The compensation amount represents the difference between the target impedance value and the inherent impedance value.

[0060] Step S33) Impedance error calculation step: When the phase range of the adjustable impedance device is not at the target range, calculate the impedance error between the impedance calculation result of the device under test and the target impedance value.

[0061] The impedance calculation result represents the application of a line impedance consistent with the target impedance value to the device under test after superimposing the actual output impedance of the adjustable impedance device with the inherent impedance of the physical line; the device under test measures the line impedance applied to its port based on its built-in impedance measurement function, and uses the measured impedance value as the impedance calculation result.

[0062] The impedance error represents the difference between the calculated impedance of the device under test and the target impedance value.

[0063] In this application, the impedance distribution in the physical circuit is precisely controlled based on the impedance parameters configured for the testing task. First, according to the test requirements defined in the testing items, each physical circuit requiring impedance adjustment is determined, and a corresponding adjustable impedance device and its corresponding phase are selected for each physical circuit. Before performing impedance adjustment, the system monitors the inherent impedance value of the connecting wires in the physical circuit in real time. This inherent impedance value originates from the physical circuit of the testing system itself, contact resistance, and other objectively existing electrical characteristics. Based on the target impedance value in the impedance parameters, the system calculates a compensation amount using a compensation algorithm. This compensation amount is the difference between the target impedance value and the inherent impedance value. Based on the compensation amount, the system determines the target range to be set for each phase of the adjustable impedance device, ensuring that the actual output impedance value of the adjustable impedance device, when superimposed with the inherent impedance value, equals the target impedance value. After adjustment, the system collects the impedance calculation results reported by the device under test, compares the impedance calculation results with the target impedance value, and calculates the impedance error. This impedance error is used to quantitatively evaluate the impedance calculation capability of the device under test.

[0064] Its technical advantages are as follows: First, by monitoring the inherent impedance value of the physical circuit in real time and using a compensation algorithm for dynamic correction, the influence of the circuit impedance of the testing system itself on the test results is eliminated, ensuring that the actual circuit impedance applied to the device under test is highly consistent with the preset target impedance value, significantly improving the accuracy and fairness of the test; Second, the target range of the adjustable impedance device is automatically determined based on the compensation amount, replacing the traditional manual knob adjustment method, making the impedance adjustment process fully automated, and greatly improving the testing efficiency under multiple impedances and various combined working conditions; Third, by collecting the impedance calculation results reported by the device under test and comparing them with the target impedance value to calculate the impedance error, the impedance calculation capability of the device under test is quantitatively measured, providing objective and quantifiable data support for equipment performance evaluation; Fourth, the entire impedance adjustment process is automatically recorded by the system and can be repeatedly executed, ensuring that the same impedance configuration has consistent input conditions in different batches of testing, improving the comparability and traceability of the test results.

[0065] Step S4) Load control step: Based on the load strategy, the controllable load device is automatically controlled and a load timing sequence is generated to dynamically simulate the load change characteristics under the actual operating scenario.

[0066] like Figure 5 As shown, step S4) load control step specifically includes step S41) load policy configuration step, step S42) instruction filtering step and step S43) load shutdown step.

[0067] Step S41) Load strategy configuration step: Configure the load switching mode, power level combination, minimum turn-on time, minimum turn-off time and load change interval according to the load circuit and phase to form the load strategy.

[0068] Step S42) Instruction filtering step, load control instructions are generated periodically according to the load strategy, and load control instructions that exceed the threshold are filtered according to the relationship between the total load of the current controllable load device and a preset load threshold.

[0069] Step S43) Load shutdown step: Perform zeroing and disconnection operations on all controllable load devices until all controllable load devices are shut down.

[0070] In this application, the output of the controllable load device is dynamically scheduled according to the load strategy configured for the detection task. First, the load strategy is formed by configuring the load switching mode, power level combination, minimum on-time, minimum off-time, and load change interval according to the load circuit and phase settings. The load strategy supports multiple generation methods, such as preset modes, random fluctuations, or real load curves. During the detection process, the system periodically generates load control commands according to the load strategy. Each load control command corresponds to the specific operation of one or more controllable load units. Before executing the load control command, the system monitors the current total load of the controllable load device in real time and compares the current total load with a preset load threshold. If executing a load control command would cause the current total load to exceed the preset load threshold, the command is filtered and not executed, thereby ensuring that load fluctuations during the detection process remain within a safe range. When the detection task ends, the system automatically performs zeroing and disconnection operations on all controllable load units and continuously monitors until it is confirmed that all controllable load units have been safely shut down, avoiding equipment damage and safety hazards caused by residual load.

[0071] Its technical advantages are as follows: First, automated control based on load strategy replaces the traditional manual opening and closing of load loops, transforming load scenario construction from manual operation to programmed automatic execution, significantly improving detection efficiency and the precision of scenario simulation. Second, real-time filtering of load control commands through preset load thresholds effectively prevents load fluctuations from exceeding the system's safe range, ensuring the safety of equipment and personnel during the detection process. Third, the load strategy supports multiple generation methods, including preset modes, random fluctuations, and real load curves, enabling the detection system to simulate various actual operating scenarios from steady-state operation to load mutations and extreme conditions, providing a comprehensive testing method for verifying the response capability of the device under test under different load conditions. Fourth, the automatic zeroing and disconnection mechanism and retry confirmation process at the end of the test completely eliminate the risk of residual load, improving the safety and reliability of the detection system. Fifth, each load sequence is automatically generated by the system according to the strategy and can be repeatedly executed, ensuring consistent input conditions for the same load scenario in different batches of testing, improving the comparability and repeatability of the test results.

[0072] Step S5) Detection step: Send a detection command to the device under test and collect the response data of the device under test in real time, and generate a comprehensive detection conclusion based on the response data.

[0073] like Figure 6 As shown, step S5) the detection step specifically includes step S51) the detection item execution step, step S52) the detection case execution step, and step S53) the detection set execution step.

[0074] Step S51) Execution of the test item: Based on the test content and criteria defined in the test item, send corresponding instructions to the device under test and monitor whether its response data meets the criteria requirements to verify the compliance of a single function point or a single business capability.

[0075] Step S52) Detection test case execution steps: Based on the execution order and dependencies defined in the detection test cases, the detection items are executed sequentially to form a complete detection process, and the verification results of each detection item are summarized.

[0076] Step S53) Detection set execution step: Based on the transformer area topology template, impedance parameters and load strategy associated with the detection set, the scenario construction step, the impedance adjustment step and the load control step are called in sequence to build the detection environment, and the detection test cases are executed to generate comprehensive detection conclusions.

[0077] In this application, the system utilizes the detection set, detection cases, and detection items defined in the detection task configuration steps to achieve automated construction of the detection environment and standardized execution of the detection process. First, based on the transformer topology template, impedance parameters, and load strategies associated with the detection set, the system sequentially calls the scenario construction step, the impedance adjustment step, and the load control step to complete the automated construction of the target detection environment. Then, according to the execution order and dependencies defined in the detection cases, the system executes each detection item one by one: for each detection item, the system issues corresponding detection instructions to the device under test according to the detection content defined in the detection item, and collects the response data returned by the device under test in real time; the response data is compared with the preset criteria in the detection item to determine whether the single functional point or single business capability meets the standard, and the verification result is recorded. After completing the execution of all detection items in the detection cases, the system summarizes the verification results of each detection item, combines them with the environmental parameters bound to the detection set, and generates a comprehensive detection conclusion. This comprehensive detection conclusion is used to comprehensively evaluate the capability level of the device under test under a specific detection target.

[0078] Its technical advantages are as follows: First, based on the hierarchical execution mechanism of "test set - test case - test item", the testing process is transformed from a traditional fixed procedure into a configurable and programmable automated process, allowing business personnel to flexibly adjust the testing content without modifying the underlying code. Second, the binding of environmental parameters (topology, impedance, load) to test cases in the test set ensures that each test is executed in a standardized simulation environment, and the input conditions of different batches of tests are highly consistent, significantly improving the repeatability and comparability of test results. Third, the item-by-item execution of test items and real-time criterion comparison realize the automated verification of the single functional point and comprehensive business capabilities of the device under test, replacing the traditional method of human intervention and greatly improving testing efficiency and accuracy. Fourth, the fully automated execution of the entire process, from environment construction, instruction issuance, data collection to conclusion generation, requires no human intervention, achieving a complete business experience, effectively reducing the risk of manual operation, and improving the concurrent processing capability of testing tasks.

[0079] like Figure 7 As shown, step S5) the detection step also includes step S54) physical detection step, step S55) simulation detection step and step S56) hybrid detection step.

[0080] Step S54) Physical inspection step: issue inspection instructions to the physical device in the connected device under test, and receive the response data returned by the physical device in real time as the physical inspection result.

[0081] Step S55) Simulation detection step: call the simulated voltage, current, event sequence and communication message to replace part or all of the physical electrical quantities input to the device under test, and at the same time issue a detection command to the device under test, and collect the response data of the device under test under the simulation input in real time as the simulation detection result.

[0082] Step S56) Hybrid detection step: Perform the physical detection step and the simulation detection step respectively, compare and analyze the physical detection results and the simulation detection results, and generate hybrid detection results.

[0083] This application supports the flexible selection and combination of multiple detection modes to meet the verification needs of different testing scenarios. In physical detection mode, the system directly issues detection commands to the physical device in the connected device under test (DUT) and receives the response data returned by the physical device in real time as the physical detection result. This mode is suitable for verifying the actual operating performance of the DUT under actual hardware conditions. In simulation detection mode, the system calls a simulation platform to generate simulated voltage, current, event sequences, and communication messages to replace some or all of the physical electrical quantities input to the DUT. At the same time, it issues detection commands to the DUT and collects the response data of the DUT under simulated input in real time as the simulation detection result. This mode is suitable for conducting large-scale testing or extreme condition simulation without occupying the resources of real equipment. In the hybrid testing mode, the system executes the physical testing mode and the simulation testing mode respectively, obtains the physical testing results and the simulation testing results, and compares and analyzes the two sets of results under the same testing configuration to generate hybrid testing results. The hybrid testing results are used to evaluate the consistency of the performance of the device under test in the physical environment and the simulation environment, or to verify the accuracy of the simulation platform in simulating real working conditions.

[0084] The technical advantages are as follows: First, the physical testing mode ensures that the testing system has the ability to directly test real equipment, meeting the practical application needs such as network access testing and operational spot checks. Second, the simulation testing mode, by simulating electrical inputs, enables the testing system to conduct large-scale testing and simulate high-risk scenarios such as faults, disturbances, and extreme operating conditions without occupying real equipment or affecting the operation of real transformer substations, significantly expanding the testing coverage. Third, the hybrid testing mode, through comparative analysis of physical testing results and simulation testing results, can verify the consistency of the response of the tested equipment under different input conditions and evaluate the simulation accuracy of the simulation platform for real operating conditions, providing dual assurance for the reliability of the testing results. Fourth, the three testing modes share the same set of testing task configuration, environment construction, and result management mechanisms, achieving seamless switching and data interoperability between modes, eliminating the need for repeated configuration of testing processes, and significantly improving the flexibility and resource utilization of the testing system.

[0085] Step S6) Result generation step: The response data is associated and stored with the target transformer area topology, the line impedance and the load timing. Based on the associated and stored data, the matching degree between the topology identification result of the device under test and the transformer area topology template is calculated by the graph isomorphism algorithm. The impedance deviation of each branch of the target transformer area topology is also calculated, and a test report is generated.

[0086] The matching degree is calculated as follows: based on the graph isomorphism algorithm, the topology identification result is compared with the graph structure of the transformer area topology template node by node and edge by edge to determine whether the two are isomorphic.

[0087] The impedance deviation calculation process is as follows: the system extracts the calculated impedance values ​​of each branch reported by the device under test from the response data, and at the same time obtains the target impedance values ​​of each branch set in the impedance parameters; the calculated impedance values ​​are compared with the target impedance values ​​branch by branch, and the difference between the two is the impedance deviation of the branch; based on whether the impedance deviation is within the preset allowable range, it is determined whether the impedance calculation capability of the device under test meets the standard.

[0088] like Figure 8 As shown, generating the detection report specifically includes steps S61) graph structure transformation, S62) isomorphism judgment, S63) topology graph generation, and S64) topology graph annotation.

[0089] Step S61) Graph structure conversion step: convert the topology identification result of the device under test into a first graph structure, and convert the transformer area topology template into a second graph structure.

[0090] Step S62) Isomorphism judgment step: Based on the graph isomorphism algorithm, the first graph structure and the second graph structure are compared node by node and edge by edge to determine whether they are isomorphic; if yes, the topology recognition is correct; if no, the differences between the first graph structure and the second graph structure are identified and marked.

[0091] Step S63) Topology diagram generation step: Generate a topology diagram based on the comparison results of the first diagram structure and the second diagram structure, and mark the actual impedance value and theoretical impedance value of each physical line on the topology diagram. The topology diagram is a visual topology diagram.

[0092] Step S64) Topology Map Annotation Step: Mark the matching status or deviation degree of each physical line on the topology map and generate the detection report.

[0093] like Figure 9 The image shown is a visual topology diagram example generated based on the comparison results of the first and second diagram structures, with the matching status or degree of deviation of each physical line marked.

[0094] In this application, the system associates and stores the response data of the device under test collected during the detection process with the target transformer area topology reconstructed in the scenario construction step, the line impedance set in the impedance adjustment step, and the load timing generated in the load control step, forming a complete detection dataset. This ensures that each detection result corresponds one-to-one with its execution environment parameters, providing a data foundation for subsequent analysis and traceability. At the data analysis level, the system automatically determines the topology identification results based on a graph isomorphism algorithm: the topology identification results reported by the device under test are converted into a first graph structure, and the preset transformer area topology template is converted into a second graph structure. Both the first and second graph structures use nodes to represent switches or meter box components and edges to represent connection relationships. The graph isomorphism algorithm compares the first and second graph structures node by node and edge by edge to determine if they are isomorphic. If they are isomorphic, the topology identification of the device under test is determined to be correct; if they are not isomorphic, the system automatically identifies and marks the nodes or branches where differences exist. Simultaneously, the system compares the calculated impedance value in the response data with the target impedance value to calculate the impedance deviation of each branch in the target transformer area's topology. In terms of result presentation, the system generates a visual topology map based on the comparison results, marking the actual and theoretical impedance values ​​of each physical line on the map. It then visually presents the matching status or degree of deviation of each branch through color differences, line type differences, or label differences, ultimately generating a test report that includes the visual topology map, impedance distribution map, and comprehensive test conclusions.

[0095] Its technical advantages are as follows: First, it associates and stores response data with detection environment parameters (topology, impedance, load), ensuring that each detection result has complete execution context information, providing data support for the full traceability and auditing of detection tasks. Second, based on the graph isomorphism algorithm-based topology comparison mechanism, it transforms the traditional topology identification result verification that relies on manual visual interpretation into automated and standardized mathematical judgment, significantly improving the accuracy and efficiency of topology identification capability detection. Third, through node-by-node and edge-by-edge isomorphic comparison and difference marking, it can not only determine whether the topology identification is correct, but also accurately locate incorrectly identified nodes or branches, providing guidance for fault analysis. Fourth, the generation of visualized topology diagrams and impedance distribution diagrams transforms abstract topological structures and numerical deviations into intuitive graphical presentations, enabling auditors to quickly grasp the detection results and locate the problems. Fifth, the entire result generation process is automated, requiring no manual intervention from data association, algorithm comparison, deviation calculation to report generation, ensuring the objectivity and repeatability of the detection results.

[0096] In this application, the full-scenario automated simulation detection method for metering acquisition further includes a step S7) dynamic configuration step, which is used to parse a preset schema file, extract hardware linkage rules from the schema file, dynamically generate configurable detection parameters based on the hardware linkage rules and the current hardware status, and generate corresponding hardware control instructions based on the detection parameters through the hardware linkage rules to collaboratively construct the detection environment.

[0097] Specifically, the system parses a preset schema file, which defines the mapping relationship and linkage logic between detection parameters and underlying hardware resources in a structured data format. Hardware linkage rules are extracted from this file, describing the bidirectional mapping relationship between detection parameters and the hardware states involved in the scene construction step, impedance adjustment step, or load control step. During the generation and interaction of the detection parameter configuration interface, the system dynamically generates configurable detection parameter options based on the hardware linkage rules and the current hardware state, and associates and binds the detection parameters with the corresponding hardware resources. When the user adjusts the detection parameters, the system maps the parameter changes to control commands for the corresponding hardware resources in real time according to the hardware linkage rules, and synchronously updates the hardware state displayed on the interface. Before the detection task is executed, the system generates corresponding hardware control commands based on the finally confirmed detection parameters and the hardware linkage rules, and sends them to the corresponding hardware resources in steps S2) scene construction, S3) impedance adjustment, and S4) load control, completing the collaborative configuration and construction of the detection environment.

[0098] Its technical advantages are as follows: First, based on the hardware linkage rules defined in the schema file, it decouples detection parameters from hardware resources, allowing business personnel to change the linkage relationship between detection parameters and hardware execution by adjusting the configuration file without modifying the underlying program code, significantly reducing system maintenance and upgrade costs. Second, during parameter configuration, it dynamically generates configurable parameter options in real time based on the hardware linkage rules and the current hardware status, ensuring that the detection parameters configured by the user always match the actual hardware capabilities, avoiding the risk of invalid configuration or hardware overload. Third, the real-time mapping mechanism between parameter adjustment and hardware command generation creates a closed-loop feedback between detection parameter configuration and hardware status changes, allowing users to perceive hardware responses directly in the configuration interface, improving the intuitiveness and accuracy of configuration interaction. Fourth, the automatic generation and issuance of hardware control commands before the execution of detection tasks ensures that the environment construction for each detection is based on the latest parameter configuration and hardware linkage rules, achieving standardization and automation of the detection process.

[0099] The advantages of this application are as follows: It provides a fully automated simulation testing method and system for metering acquisition across all scenarios. By incorporating the metering acquisition devices under test into the same system for centralized management and collaborative testing, it solves the problems of fragmented traditional distributed testing platforms and the inability to conduct joint testing. Through multi-bypass cabling technology, it reuses lines of various topologies within a limited physical space, and with the automated switching of the network-to-relay matrix, it achieves rapid reconstruction of the transformer area topology. By real-time monitoring of the inherent impedance of physical lines and using a compensation algorithm to adjust the output of adjustable impedance devices, it eliminates the influence of the system's own line impedance on the test results, ensuring the accuracy of impedance application. The test items, test cases, and test sets are configured in three levels, and combined with a dynamic configuration mechanism, it achieves collaborative control of test parameters and hardware, reducing process modification costs. It uses a graph isomorphism algorithm to automatically compare topology identification results, and combines impedance deviation calculation to generate a visual report, achieving automated result judgment. This application eliminates the risk of manual operation. The input conditions for each test can be recorded and replayed, supporting full playback and audit traceability of the test task, significantly improving the testing efficiency and accuracy of metering acquisition devices, and ensuring the repeatability and objectivity of the test results.

[0100] The above provides a detailed description of the automated simulation detection method and system for full-scene metering data acquisition provided by this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A fully automated simulation and testing method for metering data acquisition, applied to a fully automated simulation and testing system for metering data acquisition, the system comprising a device under test, a network-to-relay converter, an adjustable impedance device, a controllable load device, and physical circuitry, characterized in that... The method specifically includes the following steps: The testing task configuration steps include configuring testing items, testing cases, and testing sets; selecting testing targets for the device under test; and associating the corresponding transformer area topology template, impedance parameters, and load strategies. The scenario construction step involves reconstructing the target transformer area topology structure by using multi-bypass cabling technology and automatically switching the physical line connections through the network-to-relay relay, based on the transformer area topology template. The impedance adjustment step involves adjusting the actual output of the adjustable impedance device based on the impedance parameters using a compensation algorithm, so that the line impedance applied by the adjustable impedance device to the device under test is consistent with the target impedance value of the impedance parameters. The load control step involves automatically controlling the controllable load device and generating a load time sequence based on the load strategy, dynamically simulating the load change characteristics under actual operating scenarios. The detection steps involve sending a detection command to the device under test and collecting the response data of the device under test in real time, and generating a comprehensive detection conclusion based on the response data. as well as The result generation step involves associating and storing the response data with the target transformer area topology, the line impedance, and the load timing. Based on the associated stored data, a graph isomorphism algorithm is used to calculate the matching degree between the topology identification result of the device under test and the transformer area topology template. The impedance deviation of each branch of the target transformer area topology is also calculated, and a test report is generated.

2. The automated simulation and detection method for full-scenario metering data acquisition as described in claim 1, characterized in that, The scene construction steps specifically include the following steps: The transformer area topology template preset steps include pre-setting two or more transformer area topology templates. Each transformer area topology template corresponds to a set of logical nodes, line connection relationships, and the corresponding network to relay channel opening and closing status. The line reuse step reuses the line connection relationship corresponding to the transformer area topology template into the physical line, so that each physical line corresponds to two or more sets of logical nodes. The step of obtaining the switch matrix involves converting the transformer topology template corresponding to the multiplexed line connection relationship into a switch matrix. as well as The topology switching step involves generating control commands for network-to-relay execution based on the obtained switch matrix, thereby enabling the tested device to switch from the current topology to the target area topology.

3. The automated simulation and detection method for full-scenario metering data acquisition as described in claim 1, characterized in that, The impedance adjustment step specifically includes the following steps: The line testing steps involve testing the adjustable impedance devices and phases corresponding to each physical line according to the configured testing items. The target range determination step involves, based on the target impedance value, monitoring the inherent impedance value in the physical circuit in real time, calculating the compensation amount, and determining the target range of the adjustable impedance device on each phase. as well as The impedance error calculation step involves calculating the impedance error between the impedance calculation result of the device under test and the target impedance value when the phase range of the adjustable impedance device is not at the target range.

4. The automated simulation and detection method for full-scenario metering data acquisition as described in claim 1, characterized in that, The load control steps specifically include the following steps: The load strategy configuration steps involve configuring the load switching mode, power level combination, minimum on-time, minimum off-time, and load change interval according to the load circuit and phase to form the load strategy. The instruction filtering step involves periodically generating load control instructions according to the load strategy, and filtering load control instructions that exceed the threshold based on the relationship between the total load of the current controllable load device and a preset load threshold. as well as The load shutdown procedure involves performing zeroing and disconnection operations on all controllable load devices until all controllable load devices are shut down.

5. The automated simulation and detection method for full-scene metering data acquisition as described in claim 1, characterized in that, The detection steps specifically include the following steps: The test item execution steps involve sending corresponding instructions to the device under test based on the test content and criteria defined in the test item, and monitoring whether its response data meets the criteria requirements in order to verify the compliance of a single function point or a single business capability. The test case execution steps are as follows: based on the execution order and dependencies defined in the test cases, the test items are executed sequentially to form a complete test process, and the verification results of each test item are summarized. as well as The detection set execution step involves sequentially calling the scenario construction step, the impedance adjustment step, and the load control step to construct the detection environment based on the transformer area topology template, impedance parameters, and load strategy associated with the detection set, and then executing the detection test cases to generate a comprehensive detection conclusion.

6. The automated simulation and detection method for full-scenario metering data acquisition as described in claim 1, characterized in that, The detection steps also include: The physical testing step involves issuing testing commands to the physical devices in the connected devices under test and receiving the response data returned by the physical devices in real time as the physical testing results. The simulation testing step involves calling simulated voltage, current, event sequences, and communication messages to replace some or all of the physical electrical quantities input to the device under test (DUT). Simultaneously, a testing command is issued to the DUT, and the response data of the DUT under the simulated input is collected in real time as the simulation testing result. The hybrid detection step involves performing the physical detection step and the simulation detection step separately, comparing and analyzing the physical detection results and the simulation detection results to generate a hybrid detection result.

7. The automated simulation and detection method for full-scene metering data acquisition as described in claim 5, characterized in that, Also includes: The dynamic configuration process involves parsing a preset schema file, extracting hardware linkage rules from the schema file, dynamically generating configurable detection parameters based on the hardware linkage rules and the current hardware status, and generating corresponding hardware control instructions based on the detection parameters and the hardware linkage rules to collaboratively construct the detection environment.

8. The automated simulation and detection method for full-scenario metering data acquisition as described in claim 1, characterized in that, Generating the test report specifically includes the following steps: The graph structure conversion step converts the topology identification result of the device under test into a first graph structure and the topology template of the transformer area into a second graph structure. The isomorphism judgment step, based on the graph isomorphism algorithm, compares the first graph structure and the second graph structure node by node and edge by edge to determine whether they are isomorphic; if so, output that the topology recognition is correct; if not, identify and mark the differences between the first graph structure and the second graph structure. The topology diagram generation step involves generating a topology diagram based on the comparison results between the first diagram structure and the second diagram structure, and marking the actual impedance value and theoretical impedance value of each physical line on the topology diagram. as well as The topology diagram annotation step involves marking the matching status or deviation degree of each physical line on the topology diagram and generating the detection report.

9. A fully automated simulation and detection system for metering data acquisition, comprising a controller, characterized in that, The controller includes: Memory, used to store executable program code; and The processor reads the executable program code to run the computer program corresponding to the executable program code, in order to perform at least one step in the full-scene automated simulation detection method for metering acquisition as described in any one of claims 1-8.

10. The metering acquisition full-scenario automated simulation detection system as described in claim 9, characterized in that, Also includes The physical wiring is laid out using multi-bypass cabling technology; A network-to-relay circuit, with its input connected to the controller and its output connected to a node in the physical circuit; An adjustable impedance device is connected in series in the physical circuit, and the adjustable impedance device is connected to the controller; A controllable load device includes multiple controllable load units, which are respectively connected to different phases and circuits of the physical line via load switches, and the controllable load device is connected to the controller; as well as The device under test is electrically connected to the corresponding node of the physical line.

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