Test information management method and system based on low-voltage power distribution network

Abstract

The invention discloses a test information management method and system based on a low-voltage power distribution network, and relates to the technical field of smart power grids and the Internet of Things, and the method comprises the steps: collecting and preprocessing power data, uploading the preprocessed data to a distributed account book through an API interface, and obtaining the test information of the distributed account book through a query interface of the distributed account book. And performing statistical analysis on data on the distributed account book by using a big data analysis technology, analyzing test requirements of the low-voltage power distribution network according to a generated analysis report, and generating an initial test strategy. And according to the initial test strategy, constructing a simulation environment of the low-voltage power distribution network, executing the initial test strategy in the simulation environment, recording a test result, and simulating test scenes under different working conditions according to the constructed simulation environment of the low-voltage power distribution network. According to the method, better effects are achieved in the aspects of data acquisition, equipment reliability and stability, testing and resource allocation.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grid and Internet of Things, and in particular to a test information management method and system based on a low-voltage distribution network. Background Art

[0002] As an important part of the power system, the low-voltage distribution network is responsible for distributing electric energy from the high-voltage transmission network to end users. With the rapid development of the Internet of Things, big data and blockchain technology, the management and maintenance methods of the low-voltage distribution network are also constantly innovating. The data acquisition technology of sensors and smart devices is gradually applied to the monitoring of low-voltage distribution networks. By collecting electrical parameters, environmental parameters and mechanical parameters in real time, the operating status of the power grid can be fully understood. The processing and analysis of these data still face many challenges. How to efficiently manage and utilize these data has become a research focus.

[0003] In the field of smart grid and Internet of Things analysis, the existing data management methods mostly use centralized storage, and the security and reliability of data cannot be fully guaranteed. Failures in the central server can lead to large amounts of data loss or tampering. Data analysis technologies mostly rely on traditional statistical methods, which make it difficult to detect potential failures and abnormal conditions in a timely manner. Test strategy generation and simulation environment construction are mostly based on empirical rules, which lack scientificity and cannot fully cover the test requirements under various working conditions. This limits the level of intelligent management of low-voltage distribution networks and affects the stable operation of the power grid and user experience. Summary of the invention

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

[0005] Therefore, the technical problem solved by the present invention is: it is difficult for the existing data management methods to timely detect potential faults and abnormal conditions, and how to solve the problems of inconsistent data management, poor security and test strategy generation that cannot fully cover the test requirements under various working conditions in the existing low-voltage distribution network testing.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: A test information management method based on a low-voltage distribution network, comprising: collecting power data and preprocessing it, and uploading the preprocessed data to a distributed ledger through an API interface;

[0007] Through the query interface of the distributed ledger, use big data analysis technology to perform statistical analysis on the data on the distributed ledger and generate an analysis report;

[0008] According to the generated analysis report, analyze the test requirements of the low-voltage distribution network and generate the initial test strategy;

[0009] According to the initial test strategy, a simulation environment of the low-voltage distribution network is constructed, the initial test strategy is executed in the simulation environment, and the test results are recorded;

[0010] According to the constructed low-voltage distribution network simulation environment, test scenarios under different working conditions are simulated.

[0011] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, the preprocessing process of the collected data includes collecting electrical parameters, environmental parameters and mechanical parameters, and preprocessing the data by filtering, denoising and normalizing methods.

[0012] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, the step of uploading to the distributed ledger includes packaging the preprocessed data into JSON format, using HTTP POST request, sending the packaged data to the distributed ledger through the API interface, verifying the received data on the server side of the distributed ledger, and storing the verified data in the distributed ledger.

[0013] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, it monitors and identifies abnormal conditions in power equipment in real time through the query, statistical analysis and time series analysis methods of distributed ledger data, and generates detailed analysis reports to improve the ability of equipment operation monitoring and risk management.

[0014] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, the test requirements are graded according to abnormal situations, and the abnormal nodes mentioned in the report are tested and feedback is established, and the test strategy is continuously optimized according to the test results.

[0015] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, wherein: according to the topological structure and parameters of the actual low-voltage distribution network, its simulation environment is configured, and its performance, faults, and resource consumption are calculated; the calculation process needs to be calculated based on actual performance indicators, expected performance indicators, number of faults, total number of tests, labor costs, equipment costs and energy consumption costs.

[0016] As a preferred solution of the test information management method based on the low-voltage distribution network described in the present invention, wherein: according to the constructed simulation environment of the low-voltage distribution network, the test scenarios under different working conditions are simulated, including the following steps: applying the results of the initial test strategy to the simulation environment, running the simulation to simulate the performance of the equipment under different test scenarios, designing the simulation evaluation formula, and calculating the evaluation score of each test scenario. The expression is as follows.

[0017]

[0018] Where E is the simulation evaluation score under different test scenarios, M is the number of test scenarios, and w c is the weight of the cth test scenario, p c Score the performance of the cth test scenario, g c is the failure rate of the cth test scenario, r c is the resource consumption of the cth test scenario, α is the sensitivity coefficient of the failure rate, β is the adjustment coefficient of resource consumption, s c The policy score of the cth test scenario, where c is the test scenario index.

[0019] Another object of the present invention is to provide a test information management system based on a low-voltage distribution network, which can determine a test requirement list and design an optimization strategy formula by analyzing the fault analysis results and trend predictions in the analysis report to evaluate the comprehensive score of the test strategy, thereby solving the problem that the current traditional technology has difficulty in timely detecting potential faults and abnormal conditions.

[0020] As a preferred solution of the test information management system based on the low-voltage distribution network described in the present invention, it includes: a data acquisition module, a data upload module, a data analysis module, a test generation module, a construction and execution module, and a working condition simulation module.

[0021] The data acquisition module is used to collect electrical parameters, environmental parameters and mechanical parameters, and perform preprocessing.

[0022] The data upload module is used to upload the preprocessed data to the distributed ledger through the API interface.

[0023] The data analysis module is used to perform statistical analysis on the data on the distributed ledger through the query interface of the distributed ledger using big data analysis technology to generate an analysis report.

[0024] The strategy generation module is used to generate an analysis report, analyze the test requirements of the low-voltage distribution network, and generate an initial test strategy.

[0025] The construction and execution module is used for the initial test strategy, constructing a simulation environment for the low-voltage distribution network, executing the initial test strategy in the simulation environment, and recording the test results.

[0026] The simulation module is used to construct a simulation environment for a low-voltage distribution network and simulate test scenarios under different working conditions.

[0027] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of a test information management method based on a low-voltage distribution network.

[0028] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a test information management method based on a low-voltage distribution network.

[0029] Beneficial effects of the present invention: The test information management method based on the low-voltage distribution network provided by the present invention performs preliminary processing on the collected data through the collected current, voltage, temperature, humidity and vibration frequency parameters, thereby ensuring the consistency and reliability of the data, uploading the collected data to the distributed ledger through the API interface, and verifying and storing the data on the server side, thereby ensuring the safe transmission and storage of the data, real-time query and acquisition of historical data on the distributed ledger, using big data analysis technology to perform statistical analysis on the data, timely discovering potential faults and abnormal conditions, improving the reliability and stability of the equipment, analyzing the fault analysis results and trend predictions in the report, determining the test requirements list, designing an optimization strategy formula, and evaluating the comprehensive score of the test strategy, thereby ensuring the comprehensiveness and effectiveness of the test, reducing unnecessary tests, improving test efficiency, reducing operation and maintenance costs, optimizing resource allocation, and discovering and solving potential problems before actual operation through simulation testing. The present invention achieves better results in data collection, equipment reliability and stability, testing, and resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0031] Figure 1 An overall flow chart of a test information management method based on a low-voltage distribution network provided for the first embodiment of the present invention.

[0032] Figure 2 A system configuration diagram of a test information management method based on a low-voltage distribution network provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0034] Example 1, reference Figure 1, as an embodiment of the present invention, provides a test information management method based on a low-voltage distribution network, comprising:

[0035] S1: Collect power data and pre-process it, and upload the pre-processed data to the distributed ledger through the API interface.

[0036] The power data includes electrical parameters, environmental parameters and mechanical parameters. The electrical parameters include current and voltage, the environmental parameters include temperature and humidity, and the mechanical parameters include the electromagnetic force of the motor and the combustion force of the engine. The periodically changing external force causes mechanical vibration, and the preprocessing includes filtering, denoising and normalization.

[0037] Furthermore, a low-pass filter is used to remove high-frequency noise and retain low-frequency signals, a median filter is used to remove random noise in the data, and a Kalman filter is used for dynamic denoising to adapt to data changes and convert data of different dimensions and magnitudes to the same dimension and magnitude for subsequent data processing and analysis. The pre-processed data is packaged into JSON format and sent to the distributed ledger through the API interface using an HTTP POST request.

[0038] It should be noted that the received data is verified on the server side of the distributed ledger, and the verified data is stored in the distributed ledger.

[0039] S2: Through the query interface of the distributed ledger, use big data analysis technology to perform statistical analysis on the data on the distributed ledger and generate an analysis report.

[0040] Use exponential smoothing to establish the trend forecasting formula S t =αy t +(1-α)S t-1 Predict the trend of real-time data changes, S t is the smoothed predicted value, y t is the actual observed value at the current moment, S t-1 is the smoothed forecast value of the previous moment, α is the smoothing factor, which ranges from 0 to 1, indicating the importance of the current data (usually 0.1≤α≤0.3). This formula can be used to predict future trends. t+1 =αy t +(1-α)S t , future value S t+1 The current data value S is smoothed by a given smoothing factor α. t+1 and the previous prediction value S t Calculated by weighted average.

[0041] By configuring the chain code query interface, the historical data of power data on the distributed ledger can be queried and obtained in real time. The data on the distributed ledger can be statistically analyzed using big data analysis technology to calculate the average, maximum, minimum and standard deviation of the power data. Based on the time series analysis method, a trend chart of each power data over time is drawn. Based on the trend chart, the abnormal voltage fluctuation, current mutation, temperature and vibration frequency that occur during equipment operation are identified and recorded. The average, maximum, minimum and standard deviation of current, voltage, temperature, humidity and vibration frequency are summarized, all detected abnormalities are listed, and the results of the detected abnormalities are integrated into an analysis report.

[0042] Furthermore, by calculating the maximum and minimum values ​​of the parameters, data points that are beyond the normal range can be quickly identified to preliminarily determine whether there are abnormal conditions. Nodes with voltage fluctuations exceeding the set range are identified, with voltage fluctuations exceeding ±5%, nodes with current mutations, with current changes exceeding 10% of the average current value, nodes with temperatures exceeding the normal operating range, with temperatures exceeding 40°C or below 10°C, nodes with vibration frequencies or amplitudes exceeding the set range, with vibration frequencies exceeding 50Hz or amplitudes exceeding 0.1mm, and abnormal conditions are recorded and analyzed to help technicians gain a deeper understanding of the cause of the failure and develop maintenance and improvement measures.

[0043] S3: According to the generated analysis report, analyze the test requirements of the low-voltage distribution network and generate an initial test strategy.

[0044] According to abnormal voltage fluctuation, abnormal current mutation, abnormal temperature and abnormal vibration frequency, the low-voltage distribution network testing requirements are divided into three priorities: high, medium and low.

[0045] For high-priority nodes, tests are conducted once a week, for medium-priority nodes, tests are conducted once a month, and for low-priority nodes, tests are conducted once a quarter. According to the abnormality type, voltage stability test, current mutation test, and temperature monitoring test items are planned. Measure the voltage value to check the voltage fluctuation, measure the current value to check the current mutation, measure the temperature value to check the temperature abnormality, measure the vibration frequency and amplitude to check the vibration abnormality, establish a feedback mechanism, and continuously optimize the test strategy according to the test results.

[0046] S4: According to the initial test strategy, a simulation environment of the low-voltage distribution network is constructed, the initial test strategy is executed in the simulation environment, and the test results are recorded.

[0047] According to the topology and parameters of the actual low-voltage distribution network, the simulation environment is configured to ensure the accuracy and reliability of the simulation results. According to the actual performance indicators and expected performance indicators, the performance score is calculated to evaluate the performance of the simulation results. The performance score calculation formula is as follows.

[0048]

[0049] A i is the actual performance index of the i-th test node, E i is the expected performance index of the i-th test node, p is the performance score, and w i is the weight of the i-th test node. The failure rate is calculated based on the number of failures and the total number of tests; the resource consumption is calculated based on the labor cost, equipment cost and energy cost; further, the simulation environment is configured based on the topology and parameters of the actual low-voltage distribution network; the performance score is calculated based on the actual performance indicators and the expected performance indicators; the failure rate is calculated based on the number of failures and the total number of tests, which provides support for fault analysis and prevention and helps improve the reliability and safety of the low-voltage distribution network. The expression for calculating the failure rate is as follows.

[0050]

[0051] F i is the number of failures of the i-th test node, T i is the total number of tests for the i-th test node, g is the failure rate, and the resource consumption is calculated based on the labor cost, equipment cost, and energy cost, which provides support for cost control and optimization, reduces operation and maintenance costs, and improves economic benefits. The expression for calculating resource consumption is as follows.

[0052]

[0053] f h,i is the labor cost of the i-th test node, f d,i is the equipment cost of the ith test node, f e,i is the energy consumption cost of the i-th test node, and r is the resource consumption.

[0054] S5: Based on the constructed low-voltage distribution network simulation environment, simulate the test scenarios under different working conditions.

[0055] The results of the initial test strategy are applied to the simulation environment, and simulations are run to simulate the device performance under different test scenarios. The simulation evaluation formula is designed to calculate the evaluation score of each test scenario. The expression is as follows.

[0056]

[0057] Where E is the simulation evaluation score under different test scenarios, M is the number of test scenarios, and wc is the weight of the cth test scenario, p c Score the performance of the cth test scenario, g c is the failure rate of the cth test scenario, r c is the resource consumption of the cth test scenario, α is the sensitivity coefficient of the failure rate, β is the adjustment coefficient of resource consumption, s c The policy score of the cth test scenario, where c is the test scenario index.

[0058] Furthermore, by applying the initial test strategy to the simulation environment, the device performance under different working conditions such as normal operation, high load, low load, voltage fluctuation, abnormal temperature, abnormal humidity and fault injection is simulated.

[0059] It should be noted that potential problems were discovered in the simulation environment and repaired before actual operation, which avoided failures and downtime in actual operation. The test strategy was evaluated and optimized through simulation, which improved the overall performance and management level.

[0060] Embodiment 2 is an embodiment of the present invention, which provides a test information management method based on a low-voltage distribution network. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0061] First of all, in order to verify the effectiveness of the test information management method based on the low-voltage distribution network, detailed experimental preparation was carried out. First, a low-voltage distribution network was selected as the research object. The network contains multiple key nodes to monitor current, voltage, temperature, humidity and vibration frequency parameters. In order to ensure the accuracy and reliability of the data, high-precision sensors were used to collect these parameters in the experiment. Compared with the data processing method of the prior art, the existing technology usually relies on a single centralized database to store and analyze data. This method is not only inefficient, but also vulnerable to security threats. The present invention proposes a new solution to upload the preprocessed data to the distributed ledger through the API interface, thereby realizing secure sharing and efficient management of data.

[0062] During the experiment, the collected data was first filtered, denoised and normalized to eliminate noise and inconsistencies in the data. The preprocessed data was converted into JSON format and sent to the distributed ledger through an HTTP POST request. The server side of the distributed ledger strictly verified the received data, and only the verified data would be stored in the ledger. This process not only improves the security of the data, but also ensures the consistency and integrity of the data.

[0063] Next, through the query interface of the distributed ledger, the stored data was analyzed in depth using big data analysis technology. The analysis covered the query of historical data, calculation of the average, maximum and minimum values ​​of parameters, drawing of trend graphs, identification and recording of fault conditions. Based on the analysis results, a test requirement list for the low-voltage distribution network was formulated, and an initial test strategy was generated based on the list. In order to evaluate the effectiveness of the test strategy, a simulated low-voltage distribution network environment was constructed, and the test strategy was executed in this environment, the test results were recorded, and a simulation evaluation formula was designed to quantify the performance under different test scenarios.

[0064] Compared with the prior art, the advantage of the present invention is that it can realize decentralized storage of data, improve data security, and improve data processing efficiency. Through the application of distributed ledger technology, transparent sharing of data is realized. Test demand analysis and strategy generation based on big data analysis technology make testing more accurate and effective, and reduce unnecessary waste of resources, as shown in Table 1 below.

[0065] Table 1 Experimental data table

[0066]

[0067] It can be clearly seen from the data in the above table that the test information management method based on the low-voltage distribution network proposed in the present invention has shown significant advantages in many aspects. First of all, whether it is the measurement value of current or voltage, the method of the present invention is more stable and accurate than the prior art. At node 1, the current measured by the present invention is 12.5A, while the prior art is 9.0A. At node 6, the voltage measured by the present invention is 221.3V, while the prior art is 206.7V. Higher voltage measurement accuracy helps to detect voltage fluctuations in time, so as to take measures to avoid equipment damage and power loss, and ensure the stable operation of the power grid.

[0068] Secondly, the present invention also performs well in temperature control. Among all the test nodes, the temperatures recorded by the present invention are lower than those of the prior art. The temperature of node 3 is 23.7°C, while that of the prior art is 34.5°C. Lower temperature means better equipment operation and lower failure rate, which is crucial to extending equipment service life and reducing maintenance costs.

[0069] More importantly, the present invention not only improves the security and reliability of data by introducing distributed ledger technology and big data analysis, but also greatly improves the efficiency and accuracy of data analysis. This improvement is of great significance for the construction and operation and maintenance of smart grids. Through real-time monitoring and analysis, potential problems can be quickly discovered and solved, avoiding misjudgments due to delayed or inaccurate data.

[0070] Example 3, reference Figure 2 , as an embodiment of the present invention, provides a test information management system based on a low-voltage distribution network, including a data acquisition module, a data upload module, a data analysis module, a test generation module, a construction and execution module, and a working condition simulation module.

[0071] The data acquisition module is used to collect electrical parameters, environmental parameters and mechanical parameters, and perform preprocessing.

[0072] The data upload module is used to upload the preprocessed data to the distributed ledger through the API interface.

[0073] The data analysis module is used to perform statistical analysis on the data on the distributed ledger through the query interface of the distributed ledger using big data analysis technology to generate an analysis report.

[0074] The strategy generation module is used to generate an analysis report, analyze the test requirements of the low-voltage distribution network, and generate an initial test strategy.

[0075] The construction and execution module is used for the initial test strategy, constructing a simulation environment for the low-voltage distribution network, executing the initial test strategy in the simulation environment, and recording the test results.

[0076] The simulation module is used to construct a simulation environment for a low-voltage distribution network and simulate test scenarios under different working conditions.

[0077] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0078] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0079] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0080] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A test information management method based on a low voltage distribution network, characterized in that: include: Collect power data and pre-process it, and upload the pre-processed data to the distributed ledger through the API interface; Through the query interface of the distributed ledger, use big data analysis technology to perform statistical analysis on the data on the distributed ledger and generate an analysis report; According to the generated analysis report, analyze the test requirements of the low-voltage distribution network and generate the initial test strategy; According to the initial test strategy, a simulation environment of the low-voltage distribution network is constructed, the initial test strategy is executed in the simulation environment, and the test results are recorded; According to the constructed simulation environment of the low-voltage distribution network, test scenarios under different working conditions are simulated.

2. The test information management method based on the low voltage distribution network according to claim 1, characterized in that: The data collection and preprocessing process includes collecting electrical parameters, environmental parameters and mechanical parameters, and preprocessing the data by filtering, denoising and normalizing methods.

3. The test information management method based on the low voltage distribution network according to claim 2, characterized in that: The step of uploading to the distributed ledger includes packaging the preprocessed data into JSON format, using an HTTP POST request to send the packaged data to the distributed ledger through an API interface, verifying the received data on the server side of the distributed ledger, and storing the verified data in the distributed ledger.

4. The test information management method based on the low voltage distribution network as claimed in claim 3, characterized in that: The process of generating an analysis report includes real-time monitoring and identifying abnormal conditions in power equipment through querying distributed ledger data, statistical analysis and time series analysis methods, and using exponential smoothing method to determine the statistical data change trend and set the range at the same time. The part beyond the range is determined as the abnormal data part.

5. The test information management method based on the low voltage distribution network according to claim 4, characterized in that: The generating of the initial strategy includes generating abnormal situations by comparing the predicted change trend with the actual change trend, grading the test requirements according to the abnormal situations, testing the abnormal nodes mentioned in the report and establishing feedback, and continuously optimizing the test strategy according to the test results.

6. The test information management method based on the low voltage distribution network according to claim 5, characterized in that: The recording of test results includes configuring the simulation environment according to the topological structure and parameters of the actual low-voltage distribution network, and calculating its performance, failures, and resource consumption; the calculation process needs to be calculated based on actual performance indicators, expected performance indicators, number of failures, total number of tests, labor costs, equipment costs, and energy consumption costs.

7. The test information management method based on the low voltage distribution network according to claim 6, characterized in that: The test process includes, based on the constructed low-voltage distribution network simulation environment, simulating test scenarios under different working conditions, including applying the results of the initial test strategy to the simulation environment, running simulations to simulate the performance of equipment under different test scenarios, designing simulation evaluation formulas, and calculating the evaluation score of each test scenario, the expression is as follows; Where E is the simulation evaluation score under different test scenarios, M is the number of test scenarios, and w c is the weight of the cth test scenario, p c Score the performance of the cth test scenario, g c is the failure rate of the cth test scenario, r c is the resource consumption of the cth test scenario, α is the sensitivity coefficient of the failure rate, β is the adjustment coefficient of resource consumption, s c The strategy score of the cth test scenario, c is the test scenario index. This process is carried out in the simulation environment by comparing with the simulated prediction data in real time to detect the places that are out of range or have a large difference with the predicted change trend.

8. A system using the test information management method based on a low-voltage distribution network as claimed in any one of claims 1 to 7, characterized in that: Including data acquisition module, data upload module, data analysis module, test generation module, construction and execution module, working condition simulation module; The data acquisition module is used to collect electrical parameters, environmental parameters and mechanical parameters, and perform preprocessing; The data upload module is used to upload the pre-processed data to the distributed ledger through the API interface; The data analysis module is used to perform statistical analysis on the data on the distributed ledger through the query interface of the distributed ledger using big data analysis technology to generate an analysis report; The strategy generation module is used to generate an analysis report, analyze the test requirements of the low-voltage distribution network, and generate an initial test strategy; The construction and execution module is used for the initial test strategy, constructing a simulation environment for the low-voltage distribution network, executing the initial test strategy in the simulation environment, and recording the test results; The simulation module is used to construct a simulation environment for a low-voltage distribution network and simulate test scenarios under different working conditions.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the test information management method based on the low-voltage distribution network described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the test information management method based on a low-voltage distribution network described in any one of claims 1 to 7 are implemented.

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