Communication Fault Warning Method, Device and Medium for Power System

Abstract

The present application provides a communication fault warning method, device and medium for a power system, relating to the technical field of power systems, including: monitoring communication quality parameters and electrical variable data transmitted in communication between substations and concentrators in the power system, determining a communication fault time axis, and indexing to obtain adjacent electrical variable data; performing error analysis and error correction to obtain corrected adjacent electrical variable data; setting an integrated analysis coefficient, performing integrated analysis and supplementation generation of missing electrical variable data to obtain supplemented electrical variable data; generating complete electrical variable data, performing abnormal analysis and prediction of substations to obtain an abnormal analysis result, and giving a warning when an abnormality occurs. Through the present application, the technical problem of data loss caused by communication faults between substations and concentrators in the prior art can be solved, the technical goal of accurately compensating for the loss of electrical energy data during communication faults can be achieved, and the technical effect of improving the operation efficiency of the power system can be achieved.

Description

Technical Field

[0001] This application relates to the technical field of power systems, and particularly to a communication fault warning method, device, and medium for power systems. Background Art

[0002] In modern power systems, the communication between substations and concentrators is a key link to ensure the accuracy of power dispatching, load management, and power energy metering. However, communication faults occur frequently, posing great challenges to power energy calculation and load problem prediction. Current technologies usually rely on stable communication links to transmit electrical variable data in real time. However, when a communication fault occurs between a substation and a concentrator, the loss or transmission delay of power energy data will lead to an increase in the error of power energy calculation, thereby affecting the accuracy of load prediction. Data loss not only weakens the operation efficiency of the power system but also may lead to incorrect judgments on the load conditions, thus affecting the stability of the power grid.

[0003] Currently, when dealing with communication faults, existing technologies often have difficulty effectively coping with the problem of missing power energy data during the fault period. Although some systems attempt to supplement data and correct errors through historical data, due to the lack of precise analysis of the communication fault time, the compensation effect is not ideal. Usually, it is impossible to accurately judge the length of data missing during the fault period, or it is impossible to reasonably set the compensation ratio, resulting in a large deviation between the supplemented data and the actual situation. In addition, when existing methods perform data compensation, they often ignore the correlation between data before and after the communication fault and fail to fully consider the impact of communication faults on power energy data transmission. This deficiency makes the compensated data still have errors, affecting subsequent power energy calculation and load prediction. When dealing with data errors, existing technologies mainly rely on simple linear interpolation or static compensation methods based on historical data, which cannot dynamically adapt to the changes in actual fault situations. For example, linear interpolation ignores the volatility and complexity of power energy data and cannot accurately reflect the power load situation during the fault period. While static compensation methods based on historical data can partially correct data errors, they cannot be precisely adjusted according to the communication fault time and specific circumstances, resulting in an unsatisfactory compensation effect. Due to the lack of dynamic analysis and adjustment of data errors, the generated power energy data often has a large deviation in actual applications, thereby affecting the load prediction and dispatching decision-making of the power system.

[0004] In summary, in the prior art, when dealing with data loss and errors caused by communication failures between substations and concentrators, there are problems such as the lack of precise analysis of communication failure times, the inability to accurately determine the length of data loss, and the unreasonable setting of compensation ratios. In addition, the data correlation before and after the failure is not fully considered during the data compensation process, resulting in low accuracy of the compensated electrical energy data, which affects the operation efficiency of the power system and the reliability of load forecasting. Summary of the Invention

[0005] The purpose of this application is to provide a communication failure warning method, device, and medium for a power system to solve the technical problems in the prior art. When dealing with data loss and errors caused by communication failures between substations and concentrators, there are problems such as the lack of precise analysis of communication failure times, the inability to accurately determine the length of data loss, and the unreasonable setting of compensation ratios. In addition, the data correlation before and after the failure is not fully considered during the data compensation process, resulting in low accuracy of the compensated electrical energy data, which affects the operation efficiency of the power system and the reliability of load forecasting.

[0006] In view of the above problems, this application provides a communication failure warning method, device, and medium for a power system.

[0007] In the first aspect, this application provides a communication failure warning method for a power system, including: monitoring the communication quality parameters and the electrical variable data transmitted in the communication between the substation and the concentrator in the power system. After determining that a communication failure occurs through the discrimination of the communication quality parameters, determining the communication failure time axis when the communication failure occurs, and indexing and obtaining the adjacent electrical variable data transmitted in the preset time range before the communication failure time axis; performing error analysis and error correction on the adjacent electrical variable data according to the time axis length of the communication failure time axis and the failed communication quality parameters to obtain corrected adjacent electrical variable data; setting an integrated analysis coefficient according to the time axis length of the communication failure time axis, and based on the corrected adjacent electrical variable data, performing integrated analysis and supplementation generation of the missing electrical variable data within the communication failure time axis to obtain supplementary electrical variable data; combining the corrected adjacent electrical variable data and the supplementary electrical variable data to generate complete electrical variable data, performing abnormal analysis and prediction on the substation, obtaining an abnormal analysis result, and giving a warning when an abnormality occurs.

[0008] In the second aspect, this application also provides an electronic device, including:

[0009] At least one processor;

[0010] A memory communicatively connected to the at least one processor;

[0011] Wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the steps of the communication fault warning method for a power system according to any one of the above first aspects.

[0012] In a third aspect, a computer-readable storage medium has a computer program stored thereon, and the computer program, when executed, implements the steps of the communication fault warning method for a power system according to any one of the above first aspects.

[0013] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0014] By monitoring the communication quality parameters and the electrical variable data transmitted in the communication between the substation and the concentrator in the power system, after determining a communication fault based on the discrimination of the communication quality parameters, a communication fault time axis of the communication fault is determined, and adjacent electrical variable data transmitted in a preset time range before the communication fault time axis is indexed and obtained; according to the time axis length of the communication fault time axis and the fault communication quality parameters, error analysis and error correction are performed on the adjacent electrical variable data to obtain corrected adjacent electrical variable data; according to the time axis length of the communication fault time axis, an integrated analysis coefficient is set, and based on the corrected adjacent electrical variable data, integrated analysis and supplementation generation of the missing electrical variable data within the communication fault time axis are performed to obtain supplementary electrical variable data; by combining the corrected adjacent electrical variable data and the supplementary electrical variable data, complete electrical variable data is generated, abnormal analysis and prediction of the substation are performed to obtain an abnormal analysis result, and a warning is given when an abnormality occurs, achieving the technical goal of accurately compensating for the missing electrical energy data during the communication fault and achieving the technical effect of improving the operation efficiency of the power system and the accuracy of load prediction.

[0015] The above description is only an overview of the technical solutions of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specific embodiments of this application are specifically given. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of this application, nor is it used to limit the scope of this application. Other features of this application will become easily understandable through the following description. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only exemplary. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on the provided drawings.

[0017] Figure 1 It is a schematic flowchart of the communication fault warning method for the power system of the present application;

[0018] Figure 2 It is a schematic structural diagram of an exemplary electronic device of the present application.

[0019] Explanation of reference numerals:

[0020] Bus 100, Receiver 101, Processor 102, Transmitter 103, Memory 104, Bus Interface 105. Detailed implementation manners

[0021] By providing a communication fault warning method, device and medium for the power system, the present application solves the technical problems existing in the prior art. When dealing with data loss and errors caused by communication faults between substations and concentrators, there is a lack of precise analysis of communication fault time, inability to accurately judge the length of data loss, and unreasonable setting of compensation ratio. In addition, during the data compensation process, the data correlation before and after the fault is not fully considered, resulting in low accuracy of the compensated electrical energy data, affecting the operation efficiency of the power system and the reliability of load forecasting. The technical goal of accurately compensating for the data loss during communication faults is achieved, and the technical effect of improving the operation efficiency of the power system and the accuracy of load forecasting is achieved.

[0022] Next, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. In addition, it should be noted that for the sake of description, only the parts related to the present application are shown in the accompanying drawings rather than all.

[0023] Embodiment 1. Please refer to the attached Figure 1 , the present application provides a communication fault warning method for the power system, which specifically includes the following steps:

[0024] Step 1: Monitor the communication quality parameters and the electrical variable data transmitted between the substation and the concentrator in the power system. After determining a communication fault based on the communication quality parameters, determine the communication fault timeline when the communication fault occurs, and index and obtain the adjacent electrical variable data transmitted within a preset time range before the communication fault timeline.

[0025] Specifically, by monitoring the communication quality parameters and electrical variable data (such as voltage and current) between the substation and the concentrator in the power system, after determining a communication fault based on the communication quality parameters, determine the specific time period when the fault occurs, that is, the communication fault timeline. For example, sensors in the substation monitor variable electrical data (such as voltage and current) and transmit it to the concentrator for centralized analysis, and monitor the quality parameters of the communication transmission (such as delay or bandwidth). When a communication fault occurs (such as the delay being greater than the threshold) and variable electrical data cannot be transmitted, determine the timeline, that is, the time period when the fault occurs, and the adjacent variable electrical data transmitted within a preset time range before the timeline, and then analyze the causes and consequences of the fault, and provide an important basis for the repair and prevention of the fault, so as to better handle communication faults and ensure the stability of data transmission and the reliability of power system operation.

[0026] Step 2: Perform error analysis and error correction on the adjacent electrical variable data according to the time axis length of the communication fault timeline and the fault communication quality parameters to obtain corrected adjacent electrical variable data.

[0027] Specifically, according to the time length of the communication fault timeline and the communication quality parameters during the fault period, perform error analysis on the adjacent electrical variable data to evaluate the impact of the communication fault on the accuracy of data transmission, and identify possible errors in the electrical variable data. Then, use the analysis results to perform error correction on the adjacent electrical variable data to restore the accuracy of the data as much as possible, so as to obtain more reliable corrected electrical variable data, ensuring that the data of the power system can still maintain high precision when a communication fault occurs, and providing accurate information for subsequent decision-making and analysis. For example, before the communication fault occurs, there may have been a decline in communication performance, resulting in errors in the adjacent electrical variable data transmitted. Therefore, based on the time axis length and the fault communication quality parameters (reflecting the scale of the communication fault), analyze the errors (such as voltage errors) existing in the adjacent electrical variable data, and then perform correction according to the errors.

[0028] Step 3: Set an integrated analysis coefficient according to the time axis length of the communication fault timeline, and perform integrated analysis and supplementation generation of the missing electrical variable data within the communication fault timeline based on the corrected adjacent electrical variable data to obtain supplemented electrical variable data.

[0029] Specifically, according to the time length of the communication fault time axis, an integrated analysis coefficient is set to adjust and optimize the subsequent data supplementation process. Then, based on the corrected adjacent electrical variable data, using the integrated analysis coefficient, the missing electrical variable data within the communication fault time axis is subjected to integrated analysis and supplemented generation, thereby generating supplementary electrical variable data to fill the data lost due to communication faults, ensuring the integrity and accuracy of the power system data, and providing reliable support for subsequent analysis and decision-making. For example, according to the corrected adjacent variable data, the missing variable data that has not been successfully transmitted within the fault time axis is predicted and supplemented. Among them, the integrated analysis coefficient is set according to the time axis length. The longer the time axis, the larger the integrated analysis coefficient, and the more generation branches are adopted for the integrated analysis and supplementary generation of the missing electrical variable data.

[0030] Step Four: Combine the corrected adjacent electrical variable data and the supplementary electrical variable data to generate complete electrical variable data, conduct abnormal analysis and prediction of the substation, obtain the abnormal analysis result, and give an early warning when an abnormality occurs.

[0031] Specifically, by combining the corrected adjacent electrical variable data with the supplementary electrical variable data, complete electrical variable data is generated, ensuring the continuity and integrity of the data, that is, combining the corrected and supplementary electrical variable data to obtain complete electrical variable data. Using the complete data for abnormal analysis and prediction of the substation can identify and predict possible abnormal situations, that is, conduct abnormal analysis and prediction of the substation. For example, analyze whether there is power fluctuation or load overload, and conduct abnormal analysis and prediction based on the methods in the prior art. When an abnormality is detected, an early warning is issued in a timely manner to help the operation and maintenance personnel take measures in advance to avoid the impact of potential faults on the power system. Furthermore, through the integration and analysis of data, not only the accuracy of abnormal detection is improved, but also the safety and stability of the power system are enhanced.

[0032] The communication fault early warning method for the power system can achieve the technical goal of accurately compensating for the missing electrical energy data during communication faults, and achieve the technical effect of improving the operation efficiency of the power system and the accuracy of load prediction.

[0033] Furthermore, this application also includes:

[0034] Monitor and collect the communication quality parameters between the substation and the concentrator within the power system, as well as the electrical variable data transmitted from the substation to the concentrator; determine whether a communication fault occurs by discriminating the communication quality parameters. If so, determine the communication fault time axis according to the time frame information of the occurrence and disappearance of the faulty communication quality parameters. If not, continue to monitor the communication quality parameters; according to the monitored and collected electrical variable data, index and obtain the adjacent electrical variable data within a preset time range before the communication fault time axis.

[0035] Specifically, monitor and collect the communication quality parameters between substations and concentrators in the power system, that is, monitor the quality of the communication link in real time to ensure the normal operation of the power system. If any problems occur during the communication process, timely acquisition and analysis of data help to accurately locate and solve the problems, that is, collect the electrical variable data transmitted from the substation to the concentrator, thereby reducing the anomalies in the power system caused by communication failures.

[0036] Next, determine whether there is a communication failure by discriminating the communication quality parameters. If an abnormal signal is detected in the communication quality parameters, it indicates that there may be a communication failure, and at this time, it is necessary to further analyze the specific situation of the failure. If the discrimination result shows that the communication quality is normal, continue to monitor to ensure the continuous stability of the communication. Through this continuous monitoring and discrimination process, the power system can take preventive and repair measures before or just after a failure occurs to ensure the reliability of the power system.

[0037] When a communication failure is detected, it is necessary to determine the time axis of the communication failure based on the time frame information of the appearance and disappearance of the faulty communication quality parameters, and then accurately identify the time point and duration of the failure, so as to provide a clear time basis for subsequent fault troubleshooting and solution. By constructing the time axis of the communication failure, it is possible to better understand the nature and scope of influence of the failure, and provide guidance for formulating corresponding repair strategies.

[0038] Finally, according to the monitored and collected electrical variable data, index and obtain the adjacent electrical variable data within a preset time range before the communication failure time axis. By analyzing the electrical variable data before the communication failure occurs, it is possible to more deeply understand the possible causes and precursors of the failure, thus providing an important reference for fault warning and prevention, and at the same time helping to take effective measures in advance when similar failures occur in the future to reduce the impact of the failure on the power system.

[0039] By real-time monitoring and discriminating the communication quality, constructing the fault time axis, and combining the analysis of electrical variable data, it is possible to effectively warn of and prevent communication failures in the power system, thereby improving the stability and reliability of the power system.

[0040] Furthermore, this application also includes:

[0041] Obtain the time axis length of the communication failure time axis and the sequence of faulty communication quality parameters within the communication failure time axis; according to the time axis length and the sequence of faulty communication quality parameters, conduct an analysis of the error impact of the communication failure on the adjacent electrical variable data to obtain a communication impact error parameter; use the communication impact error parameter to perform error correction calculation on the adjacent electrical variable data to obtain corrected adjacent electrical variable data.

[0042] Specifically, obtain the length of the communication fault time axis and the sequence of fault communication quality parameters within this time axis. That is, by determining the duration of the fault occurrence and collecting communication quality parameters (such as delay, packet loss rate, etc.) during this period, it can provide necessary data support for subsequent error analysis, not only reflecting the severity of the fault but also helping to understand the impact of the fault on data transmission.

[0043] Next, based on the time axis length and the sequence of fault communication quality parameters, conduct an analysis of the error impact of the communication fault on adjacent electrical variable data to obtain communication impact error parameters, and then analyze how the communication fault affects the accuracy of the electrical variable data. By comparing the electrical variable data before and after the fault and combining with the communication quality parameters, it is possible to quantify the possible errors in the transmitted data during the fault period, thereby providing a basis for subsequent correction.

[0044] Subsequently, use the communication impact error parameters to perform error correction calculations on the adjacent electrical variable data to obtain corrected adjacent electrical variable data. That is, by adjusting the electrical variable data affected by the communication fault, its accuracy is restored. The corrected data will be closer to the actual situation, thereby improving the reliability and availability of the data and providing a more accurate basis for further analysis and decision-making in the power system.

[0045] By obtaining the fault time axis and its related communication quality parameters, analyzing the error impact of the fault on the data, and performing corresponding error corrections, accurate electrical variable data is finally obtained, thus ensuring more reliable and accurate data analysis in the power system.

[0046] Furthermore, this application also includes:

[0047] According to the monitoring records of electrical variable data with communication faults in the substation and concentrator within the historical time, collect the set of sample time axis lengths of the sample communication fault time axis and the set of sample fault communication quality parameter sequences, and label and obtain the set of sample communication impact error parameters according to the error between the transmitted adjacent electrical variable data and the actual electrical variable data; use the set of sample time axis lengths, the set of sample fault communication quality parameter sequences, and the set of sample communication impact error parameters as supervised training data to train the electrical variable error analyzer; based on the electrical variable error analyzer, conduct an error impact analysis on the time axis length and the sequence of fault communication quality parameters to obtain communication impact error parameters.

[0048] Specifically, according to the monitoring records of electrical variable data with communication faults in the substation and concentrator within the historical time, collect the set of sample time axis lengths of the sample communication fault time axis and the set of sample fault communication quality parameter sequences. That is, by reviewing historical data, a sample library is constructed, which contains detailed information when the communication fault occurs, such as the duration of the fault and the change in communication quality, laying a foundation for subsequent error analysis.

[0049] Next, based on the error between the transmitted adjacent electrical variable data and the actual electrical variable data, a set of sample communication impact error parameters is marked. That is, in the sample data, by comparing the difference between the electrical variable data transmitted during the fault and the actual measured value, the specific impact of the communication fault on the data is determined, providing a direct reference for subsequent analysis, so that the data can be corrected more accurately.

[0050] Then, using the set of sample time axis lengths, the set of sample fault communication quality parameter sequences, and the set of sample communication impact error parameters as supervised training data, an electrical variable error analyzer is trained. By inputting it into a machine learning model, it learns and understands the possible impacts on electrical variable data under different fault conditions, and then is used to predict the impact of future communication faults on the data.

[0051] Finally, based on the electrical variable error analyzer, an error impact analysis is performed on the time axis length and the sequence of fault communication quality parameters to obtain communication impact error parameters. The trained electrical variable error analyzer can analyze new communication fault scenarios and predict their impacts on electrical variable data, thereby generating communication impact error parameters, and further correcting and optimizing the accuracy of power data.

[0052] By constructing a sample library from historical communication fault data, training an electrical variable error analyzer, and applying this analyzer to perform an error impact analysis on new fault scenarios, communication impact error parameters are finally obtained, so as to ensure that the data analysis of the power system is more accurate and reliable when a communication fault occurs.

[0053] Furthermore, this application also includes:

[0054] Set an integration analysis coefficient according to the ratio of the time axis length of the communication fault time axis to the preset time axis length; train an electrical variable data supplementer including multiple electrical variable data supplement branches; calculate and set the number of supplement branches according to the integration analysis coefficient and the number of the multiple electrical variable data supplement branches; use the electrical variable data supplement branches with the number of supplement branches to perform an integrated analysis and supplement of the missing electrical variable data within the communication fault time axis for the corrected adjacent electrical variable data to generate multiple branch supplementary electrical variable data, and fuse them to obtain supplementary electrical variable data.

[0055] Specifically, an integration analysis coefficient is set according to the ratio of the time length of the communication fault time axis to the preset time axis length, that is, by comparing the actual fault time with the preset time, a proportional coefficient is obtained, which is used to adjust the accuracy and range of data supplement in subsequent analysis, and further reflects the relationship between the fault duration and the standard time, providing an important reference for the data supplement process.

[0056] Next, train an electrical variable data supplementer that includes multiple electrical variable data supplement branches. Train a power system capable of generating multiple supplement plans through a machine learning model to ensure that when facing different fault scenarios, the lost electrical variable data can be flexibly supplemented. The multi-branch supplementer improves the robustness of the power system, enabling it to handle various complex fault situations.

[0057] Then, calculate and set the obtained number of supplement branches according to the integrated analysis coefficient and the number of multiple electrical variable data supplement branches, and determine how many different supplement branches need to be generated during a fault to ensure that the coverage of data supplementation is wide enough to fill the data lost during a communication fault.

[0058] Next, use the electrical variable data supplement branches with the number of supplement branches to perform integrated analysis and supplementation generation of the missing electrical variable data within the communication fault time axis for the corrected adjacent electrical variable data, obtaining multiple branch-supplemented electrical variable data. By generating multiple different supplement data branches, the missing data during the communication fault is filled, thereby trying to restore the real situation as much as possible. In the process of fusing the branch-supplemented electrical variable data, calculate the mean value of the electrical variable data supplemented by each branch. For example, for voltage data, calculate the average value of the voltage supplement data generated by all supplement data branches as the final supplemented electrical variable data, which can effectively reduce the error caused by the deviation of single-branch data, thereby improving the accuracy and reliability of the supplemented data. The finally obtained supplemented electrical variable data can not only fill the missing data during the communication fault, but also be close to the real data as a whole, providing more reliable data support for subsequent power system analysis and load forecasting, making the data more complete and accurate. For example, if the preset time axis length is the maximum time axis length within the historical time, multiply the integrated analysis coefficient by the quantity as the number of supplement branches. The larger the time axis length, the larger the communication fault scale, the larger the integrated analysis coefficient, and the more supplement branches of variable data are used, the higher the accuracy.

[0059] By setting the integrated analysis coefficient, training the data supplement model, calculating the number of supplement branches, and supplementing the missing data, complete and accurate electrical variable data are finally obtained to address the problem of missing data information during communication faults, thereby improving the data reliability of the power system.

[0060] Furthermore, this application also includes:

[0061] According to the monitoring records of electrical variable data with communication failures in the substation and concentrator over a historical period, collect sample-corrected adjacent electrical variable data sets and sample-missing electrical variable data sets; perform K-fold partitioning on the sample-corrected adjacent electrical variable data sets and sample-missing electrical variable data sets to obtain K training data sets, where K is an integer greater than 1; respectively use the K training data sets to train K electrical variable data supplement branches to obtain an electrical variable data supplementer.

[0062] Specifically, according to the monitoring records of electrical variable data with communication failures in the substation and concentrator over a historical period, collect sample-corrected adjacent electrical variable data sets and sample-missing electrical variable data sets, that is, by collecting past fault records, extract the electrical variable data that has been corrected, and the data lost during the fault, thereby providing the basis for subsequent data analysis and supplementation, ensuring that the model can accurately understand and process the data in actual fault scenarios.

[0063] Next, perform K-fold partitioning on the sample-corrected adjacent electrical variable data sets and sample-missing electrical variable data sets to obtain K training data sets, where K is an integer greater than 1. K-fold partitioning is a cross-validation method that divides the data set into K parts, so that the model can learn in multiple different training and validation processes, thereby effectively preventing overfitting of the model, and ensuring that the model has good performance on different data subsets, thus improving the accuracy of data supplementation.

[0064] Then, respectively use the K training data sets to train K electrical variable data supplement branches to obtain an electrical variable data supplementer, that is, train K different electrical variable data supplement branches through multiple training data sets, which together constitute a complete data supplementer, thereby being able to handle the missing electrical variable data in different fault situations, ensuring that the final data supplementation scheme has high reliability and accuracy.

[0065] By collecting historical communication fault data, performing K-fold partitioning to train multiple data supplement branches, and finally constructing an electrical variable data supplementer, it is ensured that the power system can accurately and effectively supplement the data missing during the fault, thereby improving the integrity and reliability of the power system data.

[0066] Furthermore, this application also includes:

[0067] Combine the corrected adjacent electrical variable data and the supplemented electrical variable data, as well as the electrical variable data when the communication quality parameter has no communication failure, to generate complete electrical variable data; perform abnormal analysis and prediction on the substation based on the complete electrical variable data to obtain an abnormal analysis result.

[0068] Specifically, by combining and correcting adjacent electrical variable data and supplementing electrical variable data, as well as electrical variable data when there is no communication fault in the communication quality parameter, complete electrical variable data is generated, that is, data from different sources are fused together to form a continuous and complete data set without missing values. Correcting adjacent electrical variable data makes up for the inconsistency before and after the fault, supplementing electrical variable data fills in the missing data during the fault, and electrical variable data during normal communication provides a basic reference. Through integration, it is ensured that the generated electrical variable data is both complete and reliable, laying a foundation for further analysis.

[0069] Next, based on the generated complete electrical variable data, substation anomaly analysis and prediction are carried out to obtain anomaly analysis results, that is, in-depth analysis is performed using the complete electrical variable data to detect possible anomalies, identify current anomalies, and also predict possible future problems through historical data. The anomaly analysis results can help the power system give early warnings in a timely manner, avoid potential faults, and guide maintenance personnel to take corresponding preventive measures.

[0070] By integrating corrected data, supplementary data, and data during normal communication, complete electrical variable data is generated. Subsequently, this data is used for substation anomaly analysis and prediction, and finally anomaly analysis results are obtained, thereby improving the early warning ability and operation stability of the power system.

[0071] In summary, the communication fault early warning method for the power system provided by this application has the following technical effects:

[0072] By monitoring the communication quality parameter and the electrical variable data transmitted in the communication between the substation and the concentrator in the power system, after determining that there is a communication fault based on the discrimination of the communication quality parameter, the communication fault time axis when the communication fault occurs is determined, and the adjacent electrical variable data transmitted in the communication within a preset time range before the communication fault time axis is indexed and obtained; according to the time axis length of the communication fault time axis and the fault communication quality parameter, error analysis and error correction are performed on the adjacent electrical variable data to obtain corrected adjacent electrical variable data; according to the time axis length of the communication fault time axis, an integrated analysis coefficient is set, and based on the corrected adjacent electrical variable data, integrated analysis and supplementation generation of the missing electrical variable data within the communication fault time axis are performed to obtain supplementary electrical variable data; by combining the corrected adjacent electrical variable data and the supplementary electrical variable data, complete electrical variable data is generated, substation anomaly analysis and prediction are carried out to obtain anomaly analysis results, and early warnings are given when anomalies occur, achieving the technical goal of accurately compensating for the missing electrical energy data during the communication fault, and achieving the technical effect of improving the operation efficiency of the power system and the accuracy of load prediction.

[0073] Embodiment 2. Based on the inventive concept of the communication fault warning method for a power system in the foregoing embodiment, the present application further provides an electronic device, including: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the steps of the communication fault warning method for a power system described in any one of the foregoing Embodiment 1.

[0074] Appendix Figure 2 is a schematic structural diagram of an exemplary electronic device of the present application. In Figure 2 , the bus architecture is represented by bus 100. Bus 100 may include any number of interconnected buses and bridges. Bus 100 connects various circuits including one or more processors represented by processor 102 and a memory represented by memory 104 together. Bus 100 may also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and thus will not be further described herein. Bus interface 105 provides an interface between bus 100 and receiver 101 and transmitter 103. Receiver 101 and transmitter 103 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 102 is responsible for managing bus 100 and general processing, while memory 104 may be used to store data used by processor 102 when performing operations.

[0075] Embodiment 3. Based on the communication fault warning method for a power system in the foregoing embodiment and the same inventive concept, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, it implements the steps of the communication fault warning method for a power system described in any one of the foregoing Embodiment 1.

[0076] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A communication fault warning method for a power system, characterized in that Including: Monitoring the communication quality parameters and the electrical variable data transmitted between the substation and the concentrator in the power system. After determining a communication fault based on the communication quality parameters, determining the communication fault timeline when the communication fault occurs, and indexing and obtaining the adjacent electrical variable data transmitted within a preset time range before the communication fault timeline; Performing error analysis and error correction on the adjacent electrical variable data according to the timeline length of the communication fault timeline and the fault communication quality parameters to obtain corrected adjacent electrical variable data; Setting an integrated analysis coefficient according to the timeline length of the communication fault timeline, and based on the corrected adjacent electrical variable data, performing integrated analysis and supplementary generation of the missing electrical variable data within the communication fault timeline to obtain supplementary electrical variable data; Combining the corrected adjacent electrical variable data and the supplementary electrical variable data to generate complete electrical variable data, performing abnormal analysis and prediction of the substation, obtaining an abnormal analysis result, and giving an early warning when an abnormality occurs; Among them, monitoring the communication quality parameters and the electrical variable data transmitted between the substation and the concentrator in the power system. After determining a communication fault based on the communication quality parameters, determining the communication fault timeline when the communication fault occurs, and indexing and obtaining the adjacent electrical variable data transmitted within a preset time range before the communication fault timeline, includes: Monitoring and collecting the communication quality parameters between the substation and the concentrator in the power system, and the electrical variable data transmitted from the substation to the concentrator; Determining whether a communication fault occurs by discriminating the communication quality parameters. If so, determining the communication fault timeline according to the time frame information of the occurrence and disappearance of the fault communication quality parameters. If not, continuing to monitor the communication quality parameters; According to the monitored and collected electrical variable data, indexing and obtaining the adjacent electrical variable data within a preset time range before the communication fault timeline.

2. The communication fault warning method for a power system according to claim 1, wherein Performing error analysis and error correction on the adjacent electrical variable data according to the timeline length of the communication fault timeline and the fault communication quality parameters to obtain corrected adjacent electrical variable data, includes: Obtaining the timeline length of the communication fault timeline and the sequence of fault communication quality parameters within the communication fault timeline; Performing an analysis of the error impact of the communication fault on the adjacent electrical variable data according to the timeline length and the sequence of fault communication quality parameters to obtain a communication impact error parameter; Using the communication impact error parameter to perform error correction calculation on the adjacent electrical variable data to obtain corrected adjacent electrical variable data.

3. The communication fault warning method for a power system according to claim 2, wherein, Performing an analysis of the error impact of the communication fault on the adjacent electrical variable data according to the timeline length and the sequence of fault communication quality parameters to obtain a communication impact error parameter, includes: According to the monitoring records of the electrical variable data when communication faults occurred in the substation and the concentrator in the historical time, collecting the set of sample timeline lengths of the sample communication fault timeline and the set of sequences of sample fault communication quality parameters, and marking and obtaining a set of sample communication impact error parameters according to the error between the transmitted adjacent electrical variable data and the actual electrical variable data; Using the set of sample time axis lengths, the set of sample fault communication quality parameter sequences, and the set of sample communication impact error parameters as supervised training data, train an electrical variable error analyzer; Based on the electrical variable error analyzer, perform an error impact analysis on the time axis length and the fault communication quality parameter sequence to obtain a communication impact error parameter.

4. The communication fault warning method for a power system according to claim 1, wherein According to the time axis length of the communication fault time axis, set an integration analysis coefficient, and based on the corrected adjacent electrical variable data, perform an integrated analysis and supplementation generation of the missing electrical variable data within the communication fault time axis, including: Set an integration analysis coefficient according to the ratio of the time axis length of the communication fault time axis to a preset time axis length; Train an electrical variable data supplementer including multiple electrical variable data supplement branches; According to the integration analysis coefficient and the number of the multiple electrical variable data supplement branches, calculate and set to obtain the number of supplement branches; Use the electrical variable data supplement branches with the number of supplement branches to perform an integrated analysis and supplementation generation of the missing electrical variable data within the communication fault time axis for the corrected adjacent electrical variable data, obtain multiple branch supplementary electrical variable data, and fuse to obtain supplementary electrical variable data.

5. The communication fault warning method for a power system according to claim 4, wherein, Training an electrical variable data supplementer including multiple electrical variable data supplement branches includes: According to the monitoring records of the electrical variable data with communication faults in the substation and concentrator historical time, collect a set of sample corrected adjacent electrical variable data and a set of sample missing electrical variable data; Perform K-fold partitioning on the set of sample corrected adjacent electrical variable data and the set of sample missing electrical variable data to obtain K sets of training data, where K is an integer greater than 1; Respectively use the K sets of training data to train and obtain K electrical variable data supplement branches to obtain an electrical variable data supplementer.

6. The communication fault warning method for a power system according to claim 1, wherein Combine the corrected adjacent electrical variable data and the supplementary electrical variable data to generate complete electrical variable data, perform substation anomaly analysis and prediction, and obtain an anomaly analysis result, including: Combine the corrected adjacent electrical variable data, the supplementary electrical variable data, and the electrical variable data when the communication quality parameter has no communication fault to generate complete electrical variable data; According to the complete electrical variable data, perform substation anomaly analysis and prediction to obtain an anomaly analysis result.

7. An electronic device, including: At least one processor; A memory communicatively connected to the at least one processor; Wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the communication fault warning method for a power system according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed, it implements the steps of the communication fault warning method for a power system according to any one of claims 1 to 6.

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