Intelligent substation protection acceptance and test device and method

Abstract

The invention relates to the technical field of intelligent substation protection acceptance and test, in particular to an intelligent substation protection acceptance and test device and method, and discloses the intelligent substation protection acceptance and test device and the test method applying the device. The intelligent substation protection acceptance and test device comprises a core control module, an analog quantity generation module, a digital quantity input and output module, a communication test module, a data analysis and processing module and a man-machine interaction module, and all the modules work cooperatively to achieve acceptance and test of an intelligent substation protection system. According to the intelligent substation protection acceptance and test method, the acceptance test is completed through connection establishment, parameter setting and calibration, multi-scene test, data processing and report generation and result auditing in sequence. Efficient, comprehensive and accurate testing of the intelligent substation protection system is achieved, and safe and stable operation of a power grid is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent substation protection acceptance and testing, and is an intelligent substation protection acceptance and testing device and method. BACKGROUND

[0002] With the transformation of the power system to intelligence and digitization, intelligent substations have become a core component of power grid construction, and the reliability of their protection systems is directly related to the safe and stable operation of the power grid. However, the current intelligent substation protection acceptance and testing work still faces many problems to be solved. The traditional testing method mainly relies on manual operation of multiple scattered testing equipment such as relay protection testers, multimeters, oscilloscopes, etc. The testing personnel need to connect the equipment one by one, set parameters, and record data, and the whole process is tedious and inefficient. For large intelligent substations, the number of protection devices is large and the functions are complex, and it often takes a lot of time to complete a comprehensive acceptance test using the traditional method, which seriously affects the construction progress and operation and maintenance efficiency of the substation.

[0003] At the same time, the traditional testing method lacks systematic fault self-diagnosis and trend prediction capabilities. The massive data generated during the testing process need to be analyzed manually by the testing personnel, which not only requires a lot of labor, but also is prone to misjudgment due to human factors. Since intelligent substations use new technologies such as digital sampling, network communication, and intelligent terminals, traditional testing equipment cannot effectively cover these new functions, and cannot simulate complex fault scenarios and network anomalies, making it difficult to discover some potential device defects and system risks, which poses a risk to the safe operation of the power grid.

[0004] In addition, the compatibility and integration of existing testing equipment are low, and the communication protocols and interface standards of protection devices produced by different manufacturers differ, requiring testing personnel to be equipped with multiple adaptation equipment, increasing testing costs and operation difficulty. Moreover, the management and analysis of testing data lack a unified platform, and the data are scattered and stored in different formats, making it difficult to conduct in-depth mining and horizontal comparison, and unable to provide strong data support for the optimization and upgrading of the protection system. The existence of these problems seriously restricts the quality and efficiency of intelligent substation protection acceptance and testing work, and cannot meet the high requirements of modern power grids for the safe and stable operation of intelligent substations. SUMMARY

[0005] The present application provides an intelligent substation protection acceptance and testing device and method, which overcomes the shortcomings of the prior art and effectively solves the problems of low efficiency, poor accuracy, and single function of traditional testing methods, which cannot meet the needs of intelligent substation protection acceptance and testing.

[0006] One of the technical solutions of this invention is achieved through the following measures: an intelligent substation protection acceptance and testing device, comprising a core control module, an analog quantity generation module, a digital quantity input / output module, a communication testing module, a data analysis and processing module, and a human-machine interaction module. These modules work collaboratively to achieve the acceptance and testing of the intelligent substation protection system. The core control module is used for real-time processing of high-speed data, running test control programs, coordinating the work of each module, and generating test reports. The analog quantity generation module is used to accurately simulate voltage and current signals under normal and fault conditions in the intelligent substation, adjusting the amplitude, frequency, and phase of the signals. The digital quantity input / output module is used for real-time monitoring and control of the digital input and output of the protection device. The communication testing module is used to simulate network storms, packet loss, and delays, and to monitor network traffic. The data analysis and processing module is used to perform in-depth analysis of the received test data to evaluate the action behavior of the protection device. The human-machine interaction module supports test parameter setting, test process initiation, and test result viewing, and displays the test results in the form of data reports, waveform graphs, and bar charts.

[0007] The following are further optimizations and / or improvements to one of the above-mentioned technical solutions: The aforementioned core control module may include an FPGA and an embedded processor. The FPGA is used to process high-speed data from the analog signal generation module and the digital input / output module in real time, while the embedded processor is used to receive user instructions, run test control programs, coordinate the work of each module, and generate detailed test reports.

[0008] The aforementioned data analysis and processing module can utilize multi-dimensional big data analysis algorithms to perform correlation analysis on analog signal data, digital interactive data, and network communication data, thereby uncovering logical relationships and abnormal features between the data.

[0009] The aforementioned data analysis and processing module can incorporate a machine learning-based fault diagnosis model. By comparing the action data of the protection device under normal operation and fault conditions, it can accurately identify the risk of malfunction, failure to operate, and potential fault hazards of the protection device.

[0010] The aforementioned data analysis and processing module can be linked with the communication testing module to synchronously collect the action response data of the protection device when simulating network anomaly scenarios. It can then perform coupled analysis by combining network anomaly parameters with action response delay and logical correctness to generate an assessment report on the impact of the network environment on protection performance.

[0011] The second technical solution of the present invention is achieved through the following measures: a method for acceptance and testing of intelligent substation protection, applied to an intelligent substation protection acceptance and testing device, comprising the following steps: Step 1: establishing a connection between the intelligent substation protection acceptance and testing device and the intelligent substation, and checking the connection reliability and test environment; Step 2: setting test parameters through the human-machine interaction module, and starting device initialization and analog channel calibration; Step 3: sequentially conducting normal operation state simulation tests, single fault simulation tests, complex fault combination simulation tests, and network anomaly simulation tests, simultaneously collecting analog signals, digital interaction data, and network communication data; Step 4: using a data analysis and processing module to perform correlation analysis and fault diagnosis on the collected test data; Step 5: generating a test report containing test items, result evaluation, fault location, and rectification suggestions based on the analysis results.

[0012] The following are further optimizations and / or improvements to the second technical solution of the above invention: The single fault simulation test in step three above can include single-phase grounding faults and three-phase short-circuit faults. The analog quantity generation module outputs voltage and current signals that conform to the corresponding fault characteristics, and the digital quantity input / output module synchronously simulates the fault change signal.

[0013] The complex fault combination simulation test in step three above can simulate scenarios where phase-to-phase short circuits and overloads, ground faults and frequency anomalies occur simultaneously, and precisely control the analog quantity generation module and digital quantity input / output module to output composite fault signals.

[0014] The correlation analysis in step four above may include multi-dimensional coupling calculations of the amplitude deviation of analog signals, the message delay of digital interaction, and the packet loss rate of network communication to pinpoint the root cause of abnormal operation of the protection device.

[0015] The above may also include step six: test result review, whereby the tester confirms the accuracy of the report. If any abnormalities are found, the tester returns to the corresponding test step for retesting. After the review is passed, the device and the intelligent substation protection equipment are reset.

[0016] This invention automates, refines, and improves the efficiency of acceptance testing and evaluation of intelligent substation protection systems. The various modules of the device work collaboratively, covering the entire process from analog signal generation and digital signal interaction to network communication testing and data analysis. It can simulate various fault scenarios and network anomalies, comprehensively testing the performance and reliability of the protection devices. The testing methods are clear and logically rigorous, forming a complete closed loop from device connection to report generation, effectively reducing manual intervention and improving testing efficiency and data accuracy. Furthermore, the application of big data analysis algorithms and fault diagnosis models allows for in-depth analysis of potential information within the test data, accurately locating potential faults, providing strong support for the optimized operation and maintenance of intelligent substation protection systems, and significantly improving the safety and stability of power grid operation. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of the intelligent substation protection acceptance and testing device according to an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram illustrating the working principle of the intelligent substation protection acceptance and testing device according to an embodiment of the present invention.

[0019] Figure 3 This is a flowchart illustrating the intelligent substation protection acceptance and testing method according to an embodiment of the present invention. Detailed Implementation

[0020] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0021] The present invention will be further described below with reference to embodiments: Example 1: As Figure 1 and Figure 2As shown in the figure, this embodiment provides an acceptance and testing device for intelligent substation protection, including a core control module, an analog quantity generation module, a digital quantity input / output module, a communication testing module, a data analysis and processing module, and a human-machine interaction module. These modules work collaboratively to achieve the acceptance and testing of the intelligent substation protection system. The core control module processes high-speed data in real time, runs test control programs, coordinates the work of each module, and generates test reports. The analog quantity generation module accurately simulates voltage and current signals under normal and fault conditions in the intelligent substation, adjusting the amplitude, frequency, and phase of the signals. The digital quantity input / output module monitors and controls the digital inputs and outputs of the protection device in real time. The communication testing module simulates network storms, packet loss, and latency anomalies, while also monitoring network traffic. The data analysis and processing module performs in-depth analysis of the received test data to evaluate the behavior of the protection device. The human-machine interaction module supports setting test parameters, starting the test process, and viewing test results, displaying the results in the form of data reports, waveform graphs, and bar charts. The device integrates multiple testing functions into one unit, eliminating the need for manual switching between multiple devices and greatly simplifying the testing process. Each module has a clear division of labor and works together efficiently, which can comprehensively cover the testing needs of intelligent substation protection systems and lay a hardware foundation for subsequent accurate testing.

[0022] In this embodiment, the core control module may include an FPGA (Field-Programmable Gate Array) and an embedded processor. The FPGA is used to process high-speed data from the analog signal generation module and the digital input / output module in real time. The embedded processor is used to receive user instructions, run test control programs, coordinate the work of each module, and generate detailed test reports. The FPGA is responsible for real-time processing of high-speed data, such as quickly scheduling and processing data from the analog signal generation module and the digital input / output module; the embedded processor runs the test control program, coordinates the work of each module, receives user instructions, and generates reports based on test results. The FPGA has high-speed data processing capabilities, ensuring real-time response of analog and digital data; the embedded processor is responsible for overall coordination, ensuring the orderly progress of the test process. The two work together to improve the overall operating efficiency and control accuracy of the device.

[0023] In this embodiment, the data analysis and processing module can utilize multi-dimensional big data analysis algorithms to perform correlation analysis on analog signal data, digital interactive data, and network communication data, uncovering logical relationships and anomaly characteristics between the data. This breaks down data silos, enabling deep fusion analysis of multiple data types, and more comprehensively capturing the operating status information of the protection device, providing rich data support for fault diagnosis.

[0024] In this embodiment, the data analysis and processing module can incorporate a machine learning-based fault diagnosis model. By comparing the action data of the protection device under normal operation and fault conditions, it can accurately identify the risk of malfunction, failure to operate, and potential fault hazards of the protection device. Leveraging the autonomous learning and recognition capabilities of the machine learning model, the accuracy and intelligence of fault diagnosis are improved, reducing the subjectivity and errors of manual analysis.

[0025] In this embodiment, the data analysis and processing module can be linked with the communication testing module to synchronously collect the action response data of the protection device when simulating network anomaly scenarios. Combined with network anomaly parameters, action response delay, and logical correctness, a coupled analysis is performed to generate an assessment report on the impact of the network environment on protection performance. This enables correlation analysis between network status and protection device performance, clarifies the degree of impact of network anomalies on the protection system, and provides a basis for optimizing network configuration and improving the fault tolerance of the protection system.

[0026] In this invention, such as Figure 2 As shown, the core control generator (i.e., the core control module) first initiates commands to drive analog quantity testing, outputting GOOSE messages and analog voltage / current signals to the smart substation. Simultaneously, the core control generator tests the communication link of the smart substation. Afterwards, all data generated from the analog quantity and communication tests are aggregated, analyzed, and processed, and the results are displayed to the user through a mobile interface. This achieves simulation testing, communication testing, and data visualization of the smart substation protection system. Ultimately, it realizes full coverage of the smart substation protection system from signal simulation and communication testing to data processing and result display, forming the core logical framework for ensuring the comprehensiveness and accuracy of the protection system acceptance testing.

[0027] In this invention, the core control module adopts an architecture combining a high-performance FPGA (Field-Programmable Gate Array) and an embedded processor. The FPGA is responsible for real-time processing of high-speed data, such as rapidly scheduling and processing data from the analog signal generation module and the digital input / output module. The embedded processor runs the test control program, coordinates the work of each module, receives user instructions, and generates reports based on the test results. At the same time, the core control module can also use processors with different architectures, such as using a dedicated digital signal processor (DSP) to replace the combination of FPGA and embedded processor, as long as it can meet the requirements of real-time data processing and control. The analog signal generation module can accurately simulate various voltage and current signals under normal and fault conditions in a smart substation. Employing Direct Digital Synthesis (DDS) technology, it allows for flexible adjustment of signal amplitude, frequency, and phase, achieving a simulation accuracy of 0.01%. For example, when simulating a three-phase short-circuit fault, it can accurately output a three-phase short-circuit current signal with the required amplitude and phase. The digital input / output module enables digital communication with the smart substation's protection devices, supporting communication protocols such as GOOSE and SV. It possesses high-speed data transmission and reception capabilities, enabling real-time monitoring and control of the protection device's digital inputs and outputs, and verifying the correctness of GOOSE message transmission and reception, as well as the synchronization accuracy of SV sampled values. The communication testing module conducts comprehensive testing of the smart substation's network communication, simulating network storms, packet loss, latency, and other abnormal conditions. It tests the communication reliability of protection devices in harsh network environments and analyzes network load through network traffic monitoring, assessing the impact of network performance on the protection system. Furthermore, the communication testing module can also simulate network anomalies using Software-Defined Networking (SDN) technology, allowing for flexible control of network traffic and topology through a controller to simulate network anomalies. The data analysis and processing module performs in-depth analysis of the received test data, using big data analysis algorithms and fault diagnosis models to evaluate the behavior of the protection device and determine whether it meets design requirements. For example, by comparing sampled data under normal operation and fault conditions, it identifies whether the action logic of the protection device is correct and whether there is a risk of malfunction or failure to act. The human-machine interaction module uses a touch-screen LCD display with a simple and intuitive interface. Users can set test parameters, start the test process, and view test results through the interface. The results are displayed in various forms such as data reports, waveforms, and bar charts, making it easy for users to quickly understand the test situation.

[0028] During operation, test parameters are first set through the human-machine interaction module, the core control module starts the device initialization, and coordinates all modules to enter the working state; the analog quantity generation module generates the required voltage and current signals, the digital quantity input / output module interacts with the protection device digitally, and the communication test module simulates network anomaly scenarios; the test data collected by each module is transmitted to the data analysis and processing module in real time for in-depth analysis, and finally the test results are displayed and a report is generated through the human-machine interaction module, realizing comprehensive and accurate testing of the intelligent substation protection system.

[0029] This invention enables efficient, comprehensive, and accurate testing of intelligent substation protection systems. It can simulate complex fault scenarios and cover testing content such as digital sampling and networked communication. It can promptly and accurately detect problems in protection devices and systems, ensuring the safe and stable operation of intelligent substations. The device includes a core control module, an analog quantity generation module, a digital quantity input / output module, a communication testing module, a data analysis and processing module, and a human-machine interaction module. All modules work together to complete the testing functions.

[0030] Example 2: As Figure 3 As shown, this embodiment provides a method for acceptance and testing of intelligent substation protection, applied to an intelligent substation protection acceptance and testing device, including the following steps: Step 1: Establish a connection between the intelligent substation protection acceptance and testing device and the intelligent substation, and check the connection reliability and test environment; Step 2: Set test parameters through the human-machine interaction module, and start device initialization and analog channel calibration; Step 3: Conduct normal operation simulation tests, single fault simulation tests, complex fault combination simulation tests, and network anomaly simulation tests in sequence, simultaneously collecting analog signals, digital interaction data, and network communication data; Step 4: Use the data analysis and processing module to perform correlation analysis and fault diagnosis on the collected test data; Step 5: Generate a test report containing test items, result evaluation, fault location, and rectification suggestions based on the analysis results. The standardized process ensures the standardization and comprehensiveness of the testing work; the end-to-end design from device connection to report generation automates the testing process, significantly improving testing efficiency.

[0031] In this embodiment, the single fault simulation test in step three can include single-phase grounding faults and three-phase short-circuit faults. The analog quantity generation module outputs voltage and current signals that conform to the characteristics of the corresponding faults, and the digital input / output module synchronously simulates fault change signals. This accurately simulates common single fault scenarios, comprehensively tests the operating performance of the protection device under typical faults, and ensures that the protection device can respond promptly and accurately.

[0032] In this embodiment, the complex fault combination simulation test in step three can simulate scenarios where phase-to-phase short circuits and overloads, ground faults and frequency anomalies occur simultaneously. It precisely controls the analog quantity generation module and digital input / output module to output composite fault signals. This simulates complex fault conditions that may occur in a smart substation, verifies the anti-interference capability and operational reliability of the protection device under extreme scenarios, and prevents protection failure due to complex faults.

[0033] In this embodiment, the correlation analysis in step four may include multi-dimensional coupled calculations of the amplitude deviation of analog signals, the message delay of digital interactions, and the packet loss rate of network communication to pinpoint the root cause of abnormal operation of the protection device. In-depth analysis of the correlations between various data types accurately identifies the key factors causing the protection device malfunction, providing precise direction for fault rectification.

[0034] In this embodiment, step six may also be included: test result review, whereby the tester confirms the accuracy of the report. If any abnormalities are found, the test is retried from the corresponding test step. After the review is passed, the device and the intelligent substation protection equipment are reset. This adds a test result review step to ensure the accuracy of the test data and the reliability of the report; resetting the equipment after the test avoids affecting the normal operation of the protection system.

[0035] During operation, the system first establishes a reliable connection between the device and the smart substation and checks that the test environment meets the standards. Then, parameter settings and device calibration are completed through the human-machine interface module. Following this, various simulation tests are conducted sequentially, and data is collected synchronously. The data analysis and processing module is used to perform in-depth data analysis and fault diagnosis. Finally, a test report is generated, reviewed, and confirmed. The relevant equipment is then reset. The entire process is efficient and orderly, ensuring comprehensive and accurate test results. Specifically, the system first performs device connection and environmental checks, ensuring the test site is free of strong electromagnetic interference and has suitable temperature and humidity. The device is correctly connected to the protection devices, merging units, and smart terminals of the smart substation via dedicated cables, and the connection's firmness and power supply are checked. Next, device initialization and parameter settings are performed. The device power is turned on, and self-testing and initialization are waited for completion. Through the human-machine interface module, basic test parameters such as protection function type, analog amplitude range, and digital communication protocol version are set according to the model and configuration of the protection system being tested. After parameter settings are completed, the analog signal generation module is first calibrated. Known voltage and current signals are output to the analog input channel of the test device via a high-precision standard signal source. The device acquires the signals and compares them with standard values, automatically adjusting the analog signal generation module parameters to ensure output accuracy. Next, the communication test module is used to conduct communication link tests, sending simple test messages to check the continuity of communication links such as GOOSE and SV, confirming normal message transmission and reception, and statistically analyzing message loss rate and bit error rate. If problems are found, communication link faults are investigated. Subsequently, normal operation simulation tests, single fault simulation tests, complex fault combination simulation tests, and network anomaly simulation tests are conducted sequentially, simultaneously acquiring analog signals, digital interaction data, and network communication data. After the tests are completed, the data analysis and processing module performs in-depth analysis of the acquired data and automatically generates a detailed test report containing test items, test results, fault analysis, and rectification suggestions. Finally, the test personnel review the report for accuracy. After approval, the test device and the tested protection equipment are reset, restoring the equipment to its pre-test state, and the test site is tidied up, ending the test process.

[0036] It should be noted that, in this invention, FPGA refers to Field Programmable Gate Array, an integrated circuit with high flexibility and configurability, capable of high-speed data processing and logic control functions; an embedded processor is a microprocessor specifically designed for embedded systems, characterized by small size, low power consumption, and high reliability, capable of running specific control programs; GOOSE messages are substation event messages oriented towards general objects, used for rapid communication between devices in smart substations; SV sample values ​​refer to voltage and current sampling data obtained through digital sampling in smart substations; big data analysis algorithms refer to a set of algorithms capable of mining, analyzing, and processing massive amounts of multi-type data; and machine learning fault diagnosis models refer to models that autonomously learn fault characteristics through training data, enabling them to identify and diagnose equipment faults. The core control module uses a Xilinx Kintex-7 series FPGA (such as XC7K325T) and an STM32H7 series embedded processor (such as STM32H743VI). Both must meet performance parameters of a minimum clock frequency of 200MHz and a data processing bandwidth of 1Gbps. The analog signal generation module uses an AD9910 Direct Digital Synthesis (DDS) chip, whose output signal amplitude adjustment range must cover 0-1000V (voltage) and 0-5000A (current), with a frequency adjustment range of 45-65Hz and an analog accuracy of 0.01%. The digital input / output module must support GOOSE (IEC 61850-8-1) and SV (IEC 61850-8-1) standards. (61850-9-2) Communication protocol, data transmission and reception rate not less than 1Gbps, message synchronization accuracy error must be controlled within ±1μs; the network interface of the communication test module must be of type 1000BASE-T, the simulated network latency range must cover 0-500ms, and the packet loss rate adjustment range is 0-30%.

[0037] The above technical features constitute the embodiments of the present invention, which have strong adaptability and implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the needs of different situations.

Claims

1. A smart substation protection acceptance and testing device, characterized in that, The intelligent substation protection system acceptance and testing device comprises a core control module, an analog quantity generation module, a digital quantity input and output module, a communication test module, a data analysis and processing module, and a man-machine interaction module, and each module cooperates to realize the acceptance and testing of the intelligent substation protection system. The core control module is used for real-time processing of high-speed data, running of a test control program, coordination of the work of each module, and generation of a test report. The analog quantity generation module is used for accurately simulating voltage and current signals under normal and fault conditions of the intelligent substation, and adjusting the amplitude, frequency, and phase of the signals. The digital quantity input and output module is used for real-time monitoring and control of the digital quantity input and output of the protection device. The communication test module is used for simulating network storm, packet loss, and delay network abnormal conditions, and simultaneously monitoring network traffic. The data analysis and processing module is used for deep analysis of the received test data to evaluate the action behavior of the protection device. The man-machine interaction module is used for supporting test parameter setting, test process starting, and test result viewing, and displaying the test results in the form of data reports, waveform diagrams, and column charts.

2. The smart substation protection acceptance and testing device of claim 1, wherein, The core control module comprises an FPGA and an embedded processor, the FPGA is used for real-time processing of high-speed data of the analog quantity generation module and the digital quantity input and output module, and the embedded processor is used for receiving user instructions, running a test control program, coordinating the work of each module, and generating a detailed test report. 3.The smart substation protection acceptance and test device according to claim 1 or 2, characterized in that, The data analysis and processing module uses a multi-dimensional big data analysis algorithm to perform correlation analysis on analog quantity signal data, digital quantity interaction data, and network communication data, and mines the logical correlation and abnormal characteristics among the data.

4. The smart substation protection commissioning and testing device of claim 3, wherein, The data analysis and processing module has a fault diagnosis model based on machine learning built in, which accurately identifies misoperation, refusal to operate, and potential fault risks of the protection device by comparing the action data of the protection device under normal operation and fault conditions.

5. The smart substation protection acceptance and testing device according to claim 1 or 2 or 4, characterized in that, The data analysis and processing module is linked with the communication test module to synchronously collect the action response data of the protection device when simulating network abnormal scenarios, and performs coupling analysis on the network abnormal parameters, action response delay, and logic correctness to generate an influence evaluation report of the network environment on the protection performance.

6. A method for smart substation protection acceptance and testing, characterized in that, The intelligent substation protection acceptance and testing device is applied to the intelligent substation protection acceptance and testing device of any one of claims 1 to 5, and comprises the following steps: Step one: connecting the intelligent substation protection acceptance and testing device with the intelligent substation, checking the connection reliability and test environment; Step two: setting test parameters through the man-machine interaction module, starting device initialization and analog quantity channel calibration; Step three: sequentially developing normal operation state simulation test, single fault simulation test, complex fault combination simulation test, and network abnormal simulation test, and synchronously collecting analog quantity signals, digital quantity interaction data, and network communication data; Step four: using the data analysis and processing module to perform correlation analysis and fault diagnosis on the collected test data; Step five: generating a test report comprising test items, result evaluation, fault positioning, and rectification suggestions according to the analysis results.

7. The intelligent substation protection commissioning and testing method of claim 6, wherein, The single fault simulation test in step three includes single-phase ground fault and three-phase short circuit fault. The voltage and current signals conforming to the corresponding fault characteristics are output by the analog quantity generation module, and the digital quantity input and output module synchronously simulates the fault variable position signal.

8. The smart substation protection commissioning and testing method of claim 6 or 7, wherein, The complex fault combination simulation test in step three simulates the scenario of simultaneous occurrence of phase-to-phase short circuit and overload, ground fault and frequency anomaly, and accurately controls the output of the composite fault signal by the analog quantity generation module and the digital quantity input and output module.

9. The smart substation protection commissioning and testing method of claim 6 or 7, wherein, The correlation analysis in step four includes multi-dimensional coupling calculation of the amplitude deviation of the analog quantity signal, the message delay of the digital quantity interaction, and the packet loss rate of the network communication, and locates the root cause of the abnormal action of the protection device.

10. The smart substation protection commissioning and testing method of claim 6 or 7, wherein, It also includes step six: test result review, which is performed by the test personnel to confirm the accuracy of the report. If there is an anomaly, the corresponding test step is returned for retesting. After the review is passed, the device and the intelligent substation protection equipment are reset.

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