Communication fault early warning method and device for power system, and medium

Abstract

The invention provides a communication fault early warning method and device for an electric power system and a medium, and relates to the technical field of electric power systems, and the method comprises the steps: monitoring communication quality parameters between a transformer substation and a concentrator in the electric power system and electric variable data of communication transmission, determining a communication fault time axis, and indexing to obtain adjacent electric variable data; performing error analysis and error correction to obtain corrected adjacent electrical variable data; setting an integrated analysis coefficient, and performing integrated analysis supplementary generation of the missing electric variable data to obtain supplementary electric variable data; and generating complete electrical variable data, carrying out substation anomaly analysis and prediction, obtaining an anomaly analysis result, and carrying out early warning when an anomaly occurs. According to the invention, the technical problem of data missing caused by communication faults between the transformer substation and the concentrator in the prior art can be solved, the technical target of accurately compensating electric energy data missing during the communication faults is achieved, and the technical effect of improving the operation efficiency of a power system is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a communication fault early warning method, device and medium for use in power systems. Background Art

[0002] In modern power systems, communication between substations and concentrators is a key link to ensure the accuracy of power dispatching, load management, and power metering. However, communication failures occur from time to time, posing great challenges to power calculation and load problem prediction. Current technologies usually rely on stable communication links to transmit electrical variable data in real time, but when communication failures occur between substations and concentrators, the loss of power data or transmission delays will lead to increased errors in power calculation, thereby affecting the accuracy of load forecasting. Data loss not only weakens the operating efficiency of the power system, but may also lead to misjudgment of load conditions, thereby affecting the stability of the power grid.

[0003] At present, the existing technology often finds it difficult to effectively deal with the problem of missing power data during the fault period when dealing with communication failures. Although some systems try to supplement data and correct errors through historical data, the compensation effect is not ideal due to the lack of accurate analysis of the communication failure time. 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 performing data compensation, the existing methods often ignore the correlation between the data before and after the communication failure, and fail to fully consider the impact of the communication failure on the transmission of power data. This deficiency causes the compensated data to still have errors, affecting the subsequent power calculation and load forecasting. When dealing with data errors, the existing technology mainly relies on simple linear interpolation or static compensation methods based on historical data, which cannot dynamically adapt to changes in actual fault scenarios. For example, linear interpolation ignores the volatility and complexity of power data and cannot accurately reflect the power load during the fault period. Although the static compensation method based on historical data can partially correct the data error, it cannot be accurately adjusted according to the communication failure time and specific circumstances, resulting in unsatisfactory compensation effect. Since these methods lack dynamic analysis and adjustment of data errors, the final generated electric energy data often has large deviations in practical applications, which in turn affects the load forecasting and scheduling decisions of the power system.

[0004] To sum up, the existing technology has the following technical problems: when dealing with data missing and errors caused by communication failures between substations and concentrators, there is a lack of accurate analysis of the communication failure time, the inability to accurately judge the length of data missing, and unreasonable setting of the compensation ratio. In addition, the data correlation before and after the failure is not fully considered in the data compensation process, resulting in low accuracy of the compensated electric energy data, which affects the operating 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 fault warning method, equipment and medium for an electric power system, so as to solve the technical problems in the prior art that, when processing data missing and errors caused by communication failures between substations and concentrators, there is a lack of accurate analysis of the communication failure time, the inability to accurately judge the length of data missing and the unreasonable setting of the compensation ratio. In addition, in the data compensation process, the correlation between the data before and after the failure is not fully considered, resulting in low accuracy of the compensated electric energy data, which affects the operating efficiency of the power system and the reliability of load forecasting.

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

[0007] In a first aspect, the present application provides a communication fault early warning method for a power system, comprising: monitoring the communication quality parameters and the electrical variable data of the communication transmission between the substation and the concentrator in the power system, after the communication quality parameters determine that a communication fault has occurred, determining the communication fault timeline where the communication fault has occurred, and indexing and obtaining the adjacent electrical variable data of the communication transmission 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 time axis length of the communication fault timeline and the fault communication quality parameters, and obtaining corrected adjacent electrical variable data; setting an integrated analysis coefficient according to the time axis length of the communication fault timeline, and performing integrated analysis and supplementary generation of the missing electrical variable data in the communication fault timeline based on the corrected adjacent electrical variable data, and obtaining supplementary electrical variable data; combining the corrected adjacent electrical variable data and the supplementary electrical variable data to generate complete electrical variable data, perform substation abnormality analysis and prediction, obtain abnormality analysis results, and issue an early warning when an abnormality occurs.

[0008] In a second aspect, the present application further provides an electronic device, including:

[0009] at least one processor;

[0010] a memory communicatively coupled to the at least one processor;

[0011] 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 the power system as described in any one of the first aspects above.

[0012] In a third aspect, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed, the steps of the communication fault warning method for a power system described in any one of the above-mentioned first aspects are implemented.

[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 electric variable data transmitted by communication between the substation and the concentrator in the power system, after the communication quality parameters determine that a communication failure occurs, the communication failure timeline where the communication failure occurs is determined, and the adjacent electric variable data transmitted by communication within a preset time range before the communication failure timeline is indexed and obtained; according to the time axis length of the communication failure timeline and the fault communication quality parameters, the adjacent electric variable data are subjected to error analysis and error correction to obtain corrected adjacent electric variable data; according to the time axis length of the communication failure timeline, an integrated analysis coefficient is set, and based on the corrected adjacent electric variable data, an integrated analysis and supplementary generation of the missing electric variable data in the communication failure timeline is performed to obtain supplementary electric variable data; in combination with the corrected adjacent electric variable data and the supplementary electric variable data, complete electric variable data is generated, and abnormal analysis and prediction of the substation are performed to obtain abnormal analysis results, and an early warning is issued when an abnormality occurs, so as to achieve the technical goal of accurately compensating for the missing electric energy data during the communication failure, and achieve 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 solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0017] Figure 1 A flow chart of a communication fault warning method for a power system according to the present application;

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

[0019] Description of reference numerals:

[0020] Bus 100 , receiver 101 , processor 102 , transmitter 103 , memory 104 , bus interface 105 . DETAILED DESCRIPTION

[0021] This application provides a communication fault warning method, device and medium for power systems, which solves the existing problems in the prior art, such as the lack of accurate analysis of communication fault time, the inability to accurately determine the length of data missing, and unreasonable compensation ratio setting when processing data missing and errors caused by communication faults between substations and concentrators. In addition, the data correlation before and after the fault is not fully considered in the data compensation process, resulting in low accuracy of compensated electric energy data, which affects the operating efficiency of the power system and the reliability of load forecasting. The technical goal of accurately compensating for the missing electric energy data during communication faults is achieved, and the technical effect of improving the operating efficiency of the power system and the accuracy of load forecasting is achieved.

[0022] Below, 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 part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0023] For example, please refer to the attached Figure 1 , the present application provides a communication fault early warning method for a power system, which specifically includes the following steps:

[0024] Step 1: Monitor the communication quality parameters and the electrical variable data of the communication transmission between the substation and the concentrator in the power system. After the communication quality parameters determine that a communication failure has occurred, determine the communication failure timeline where the communication failure occurred, and index and obtain the adjacent electrical variable data of the communication transmission within a preset time range before the communication failure 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 the communication quality parameters identify the communication fault, the specific time period in which the fault occurs, that is, the communication fault timeline, is determined. For example, the sensors in the substation monitor the substation quantity data (voltage and current, etc.) and transmit them to the concentrator for centralized analysis, and monitor the quality parameters of communication transmission (such as delay or bandwidth). When a communication failure occurs (such as the delay is greater than the threshold) and the substation quantity data cannot be transmitted, the timeline of the fault, that is, the time period, and the adjacent substation quantity data transmitted within the preset time range before the timeline are determined, and then the cause and consequence of the fault are analyzed, and an important basis is provided for the repair and prevention of the fault, so that communication failures can be better dealt with, and the stability of data transmission and the reliability of power system operation can be ensured.

[0026] Step 2: 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.

[0027] Specifically, according to the time length of the communication fault time axis and the communication quality parameters during the fault, the adjacent electrical variable data is analyzed for errors, the impact of the communication fault on the accuracy of data transmission is evaluated, and the possible errors in the electrical variable data can be identified. Then, the adjacent electrical variable data is corrected for errors using the analysis results to restore the accuracy of the data as much as possible, thereby obtaining more reliable corrected electrical variable data, ensuring that the data of the power system can still maintain high accuracy when a communication fault occurs, and providing accurate information for subsequent decision-making and analysis. For example, communication performance may have been attenuated before the communication fault occurs, resulting in errors in the transmitted adjacent electrical variable data. Therefore, the errors (such as voltage errors, etc.) in the adjacent electrical variable data are analyzed based on the time axis length and the fault communication quality parameters (reflecting the scale of the communication fault), and then corrections are made based on the errors.

[0028] Step three: according to the time axis length of the communication fault time axis, set the integrated analysis coefficient, and based on the corrected adjacent electrical variable data, perform integrated analysis and supplementary generation of the missing electrical variable data within the communication fault time axis to obtain supplementary 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 supplement process. Then, based on the corrected adjacent electric variable data, the integrated analysis coefficient is used to perform integrated analysis and supplementary generation on the missing electric variable data in the communication fault time axis, and then generate supplementary electric variable data to fill the data lost due to the communication fault, thereby ensuring that the data of the power system remains complete and accurate, and providing reliable support for subsequent analysis and decision-making. For example, based on the corrected adjacent substation quantity data, the missing substation quantity data that has not been successfully transmitted in the fault time axis is predicted and supplemented, wherein the integrated analysis coefficient is set according to the length of the time axis. The longer the time axis, the larger the integrated analysis coefficient, the more generation branches are used, and the integrated analysis and supplementary generation of the missing electric variable data is performed.

[0030] Step 4: 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 substations, obtain abnormal analysis results, and issue an early warning when an abnormality occurs.

[0031] Specifically, by combining the corrected adjacent electrical variable data with the supplemented electrical variable data, complete electrical variable data is generated, ensuring the continuity and integrity of the data, that is, combining the corrected and supplemented electrical variable data to obtain complete electrical variable data. Using complete data to perform abnormal analysis and prediction of substations can identify and predict possible abnormal situations, that is, perform abnormal analysis and prediction of substations, such as analyzing whether power fluctuations or load overloads occur, and perform abnormal analysis and prediction based on methods in the prior art. When an abnormality is detected, an early warning is issued in a timely manner to help operation and maintenance personnel take measures in advance to avoid the impact of potential faults on the power system, and then through data integration and analysis, not only the accuracy of abnormality 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 loss of electric energy data during the communication fault, and achieve the technical effect of improving the operating efficiency of the power system and the accuracy of load forecasting.

[0033] Furthermore, the present application also includes:

[0034] Monitor and collect the communication quality parameters between the substation and the concentrator in the power system, as well as the electrical variable data transmitted by the substation to the concentrator; determine whether a communication failure occurs based on the communication quality parameters, and if so, determine the communication failure timeline based on the time frame information of the appearance and disappearance of the faulty communication quality parameters; if not, continue to monitor the communication quality parameters; and obtain adjacent electrical variable data within a preset time range before the communication failure timeline based on the monitored and collected electrical variable data by index.

[0035] Specifically, the communication quality parameters between the substation and the concentrator in the power system are monitored and collected, that is, the quality of the communication link is monitored 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 will help to accurately locate and solve the problem, that is, collect the electrical variable data transmitted from the substation to the concentrator, thereby reducing power system anomalies caused by communication failures.

[0036] Next, the communication quality parameters are judged to see if there is a communication failure. If an abnormal signal is detected in the communication quality parameters, it indicates that there may be a communication failure, and further analysis of the specific circumstances of the failure is required. If the judgment result shows that the communication quality is normal, monitoring will continue to ensure the continued stability of communication. Through this continuous monitoring and judgment process, the power system can take preventive and repair measures before or when a fault occurs to ensure the reliability of the power system.

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

[0038] Finally, based on the monitored and collected electrical variable data, the adjacent electrical variable data within the preset time range before the communication fault time axis is indexed and obtained. By analyzing the electrical variable data before the communication fault occurs, we can have a deeper understanding of the possible causes and precursors of the fault, thus providing an important reference for fault warning and prevention, and at the same time helping to take effective measures in advance when similar faults occur in the future to reduce the impact of the fault on the power system.

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

[0040] Furthermore, the present application also includes:

[0041] Acquire the time axis length of the communication fault time axis and the sequence of fault communication quality parameters within the communication fault time axis; perform error impact analysis of the communication fault on the adjacent electrical variable data based on the time axis length and the sequence of fault communication quality parameters to obtain communication impact error parameters; use the communication impact error parameters to perform error correction calculations on the adjacent electrical variable data to obtain corrected adjacent electrical variable data.

[0042] Specifically, obtaining the length of the communication fault timeline and the sequence of fault communication quality parameters within the timeline, that is, by determining the duration of the fault and collecting the communication quality parameters during this period (such as delay, packet loss rate, etc.), can provide necessary data support for subsequent error analysis, which can not only reflect the severity of the fault, but also help understand the impact of the fault on data transmission.

[0043] Next, according to the time axis length and the fault communication quality parameter sequence, the error impact of the communication fault on the adjacent electrical variable data is analyzed to obtain the communication impact error parameter, 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 the communication quality parameters, the possible errors in the data transmitted during the fault can be quantified, thus providing a basis for subsequent corrections.

[0044] Subsequently, the communication impact error parameters are used to perform error correction calculations on adjacent electrical variable data to obtain corrected adjacent electrical variable data, that is, by adjusting the electrical variable data affected by the communication failure, 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 of the power system.

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

[0046] Furthermore, the present application also includes:

[0047] According to the monitoring records of the electric variable data of the communication failures occurring in the historical time of the substation and the concentrator, a sample time axis length set and a sample fault communication quality parameter sequence set of the sample communication failure time axis are collected, and according to the errors between the transmitted adjacent electric variable data and the actual electric variable data, a sample communication impact error parameter set is obtained by marking; the sample time axis length set, the sample fault communication quality parameter sequence set and the sample communication impact error parameter set are used as supervised training data to train an electric variable error analyzer; based on the electric variable error analyzer, an error impact analysis is performed on the time axis length and the fault communication quality parameter sequence to obtain communication impact error parameters.

[0048] Specifically, based on the electrical variable data monitoring records of communication failures in substations and concentrators in historical time, a set of sample time axis lengths and a set of sample failure communication quality parameter sequences of the sample communication failure time axis are collected. That is, a sample library is constructed by reviewing historical data, which contains detailed information when the communication failure occurs, such as the duration of the failure and the changes in communication quality, laying the foundation for subsequent error analysis.

[0049] Next, based on the errors 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, the specific impact of the communication failure on the data is determined by comparing the difference between the electrical variable data transmitted during the fault and the actual measured value, which provides a direct reference for subsequent analysis, so that the data can be corrected more accurately.

[0050] Then, the sample time axis length set, the sample fault communication quality parameter sequence set and the sample communication impact error parameter set are used as supervised training data to train the electrical variable error analyzer. By inputting them into the machine learning model, it learns and understands the possible impact of electrical variable data under different fault conditions, and then uses it to predict the impact of future communication failures on the data.

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

[0052] By building a sample library from historical communication fault data, training an electrical variable error analyzer, and applying the analyzer to perform error impact analysis on new fault scenarios, we can finally obtain the communication impact error parameters, thereby ensuring that the data analysis of the power system is more accurate and reliable when a communication fault occurs.

[0053] Furthermore, the present application also includes:

[0054] According to the ratio of the time axis length of the communication fault time axis to the preset time axis length, an integrated analysis coefficient is set; an electric variable data supplementer including multiple electric variable data supplement branches is trained; according to the integrated analysis coefficient and the number of the multiple electric variable data supplement branches, the number of supplement branches is calculated and set; the electric variable data supplement branches with the number of supplement branches are used to perform integrated analysis and supplement generation of the missing electric variable data in the communication fault time axis for the corrected adjacent electric variable data, and multiple branch supplemented electric variable data are obtained, and the supplemented electric variable data are obtained by fusion.

[0055] Specifically, the integrated 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 supplementation in subsequent analysis. It then reflects the relationship between the fault duration and the standard time, and provides an important reference for the data supplement process.

[0056] Next, an electric variable data supplementer including multiple electric variable data supplementation branches is trained. A power system capable of generating multiple supplementation schemes is trained through a machine learning model to ensure that the lost electric variable data can be flexibly supplemented when facing different fault scenarios. The multi-branch supplementer improves the robustness of the power system, enabling it to cope with various complex fault situations.

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

[0058] Next, the supplementary branch of the electric variable data with the number of supplementary branches is adopted to perform integrated analysis and supplementary generation of the missing electric variable data within the communication fault time axis of the corrected adjacent electric variable data, and multiple branch supplementary electric variable data are obtained. By generating multiple different supplementary data branches, the missing data during the communication fault period is filled, so as to restore the real situation as much as possible. The branch supplementary electric variable data is fused. During the fusion process, the mean of the supplementary electric variable data of each branch is calculated. For example, for voltage data, the mean value of the voltage supplementary data generated by all supplementary data branches is calculated as the final supplementary electric variable data, which can effectively reduce the error caused by the deviation of a single branch data, thereby improving the accuracy and reliability of the supplementary data. The supplementary electric variable data finally obtained can not only fill the missing during the communication fault period, 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, the preset time axis length is the maximum time axis length in the historical time, and the integrated analysis coefficient is multiplied by the number as the number of supplementary branches. The larger the time axis length, the larger the scale of the communication fault, the larger the integrated analysis coefficient, the more variable data supplementary branches are used, and the higher the accuracy.

[0059] By setting the integrated analysis coefficient, training the data supplementation model, calculating the number of supplementary branches, and supplementing the missing data, we finally obtained complete and accurate electrical variable data to cope with the problem of missing data information during communication failures, thereby improving the data reliability of the power system.

[0060] Furthermore, the present application also includes:

[0061] According to the electric variable data monitoring records of communication failures that occurred in the substation and the concentrator within the historical period, sample-corrected adjacent electric variable data sets and sample-missing electric variable data sets are collected; the sample-corrected adjacent electric variable data sets and the sample-missing electric variable data sets are divided into K parts to obtain K sets of training data, where K is an integer greater than 1; the K sets of training data are respectively used to train to obtain K electric variable data supplementation branches, and an electric variable data supplementer is obtained.

[0062] Specifically, based on the monitoring records of electric variable data of substations and concentrators with communication failures in historical time, sample correction adjacent electric variable data sets and sample missing electric variable data sets are collected. That is, by collecting past fault records, the corrected electric variable data and the data lost during the fault are extracted, which provides a basis for subsequent data analysis and supplementation, ensuring that the model can accurately understand and process data in actual fault scenarios.

[0063] Next, the sample-corrected adjacent electrical variable data set and the sample-missing electrical variable data set are K-folded to obtain K training data, 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 the model from overfitting and ensuring that the model has good performance on different data subsets, thereby improving the accuracy of data supplementation.

[0064] Then, K pieces of training data are used to train K electrical variable data supplement branches to obtain an electrical variable data supplementer. That is, K different electrical variable data supplement branches are trained through multiple training data sets, which together constitute a complete data supplementer, which can cope with the missing electrical variable data under different fault conditions and ensure that the final data supplement plan has high reliability and accuracy.

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

[0066] Furthermore, the present application also includes:

[0067] Combine the corrected adjacent electrical variable data and supplementary electrical variable data, as well as the electrical variable data when no communication failure occurs in the communication quality parameters, to generate complete electrical variable data; perform substation abnormality analysis and prediction based on the complete electrical variable data to obtain abnormality analysis results.

[0068] Specifically, the corrected adjacent electrical variable data and supplemented electrical variable data, as well as the electrical variable data when the communication quality parameters did not have a communication failure, are combined to generate complete electrical variable data, that is, to fuse data from different sources together to form a continuous and complete data set without missing data. Corrected adjacent electrical variable data make up for the inconsistency before and after the failure, supplemented electrical variable data fill in the missing data during the failure, and electrical variable data when communication is normal provides a basic reference. The integration ensures that the generated electrical variable data is both complete and reliable, laying the foundation for further analysis.

[0069] Next, based on the generated complete electrical variable data, the substation abnormality analysis and prediction are carried out to obtain the abnormality analysis results, that is, the complete electrical variable data is used for in-depth analysis to detect possible abnormalities, identify current abnormalities, and predict possible problems in the future through historical data. The abnormality analysis results can help the power system to provide timely warnings, avoid potential failures, and guide operation and maintenance personnel to take corresponding preventive measures.

[0070] By integrating correction data, supplementary data and data during normal communication, complete electrical variable data is generated, and then the data is used to perform abnormal analysis and prediction of substations, and finally obtain abnormal analysis results, thereby improving the early warning capability and operational stability of the power system.

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

[0072] By monitoring the communication quality parameters and the electric variable data transmitted by communication between the substation and the concentrator in the power system, after the communication quality parameters determine that a communication failure occurs, the communication failure timeline where the communication failure occurs is determined, and the adjacent electric variable data transmitted by communication within a preset time range before the communication failure timeline is indexed and obtained; according to the time axis length of the communication failure timeline and the fault communication quality parameters, the adjacent electric variable data are subjected to error analysis and error correction to obtain corrected adjacent electric variable data; according to the time axis length of the communication failure timeline, an integrated analysis coefficient is set, and based on the corrected adjacent electric variable data, an integrated analysis and supplementary generation of the missing electric variable data in the communication failure timeline is performed to obtain supplementary electric variable data; in combination with the corrected adjacent electric variable data and the supplementary electric variable data, complete electric variable data is generated, and abnormal analysis and prediction of the substation are performed to obtain abnormal analysis results, and an early warning is issued when an abnormality occurs, so as to achieve the technical goal of accurately compensating for the missing electric energy data during the communication failure, and achieve 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 the power system in the aforementioned embodiment, the present application also provides an electronic device, comprising: 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 the power system described in any one of the aforementioned embodiment 1.

[0074] Attached Figure 2 This is a schematic diagram of the structure of an exemplary electronic device of this application. Figure 2 In the present invention, the bus architecture is represented by bus 100, which may include any number of interconnected buses and bridges, and bus 100 connects various circuits including one or more processors represented by processor 102 and memory represented by memory 104. Bus 100 may also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not 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, namely 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 three, based on the same inventive concept as the communication fault warning method for the power system in the aforementioned embodiment, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the steps of the communication fault warning method for the power system described in any one of the aforementioned embodiments one are implemented.

[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 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 will conform to 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 belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A communication fault early warning method for a power system, characterized in that: include: Monitor the communication quality parameters and the electric variable data transmitted by the communication between the substation and the concentrator in the power system, determine the communication fault time axis when the communication fault occurs after the communication quality parameters determine the communication fault occurs, and obtain the adjacent electric variable data transmitted by the communication within a preset time range before the communication fault time axis through indexing; 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 supplementary generation of missing electrical variable data within the communication fault time axis are performed to obtain supplementary electrical variable data; The corrected adjacent electric variable data and the supplementary electric variable data are combined to generate complete electric variable data, conduct abnormal analysis and prediction of substations, obtain abnormal analysis results, and issue early warnings when abnormalities occur.

2. The communication failure early warning method for a power system according to claim 1, characterized in that: Monitor the communication quality parameters and the electric variable data transmitted by the communication between the substation and the concentrator in the power system, determine the communication fault time axis when the communication fault occurs after the communication quality parameters determine the communication fault occurs, and obtain the adjacent electric variable data transmitted by the communication within a preset time range before the communication fault time axis by index, including: Monitoring and collecting communication quality parameters between the substation and the concentrator in the power system, and electrical variable data transmitted from the substation to the concentrator; Determine whether a communication failure occurs on the communication quality parameter, and if so, determine the communication failure timeline according to the time frame information of the appearance and disappearance of the faulty communication quality parameter, and if not, continue to monitor the communication quality parameter; According to the monitored and collected electrical variable data, adjacent electrical variable data within a preset time range before the communication fault time axis is obtained by indexing.

3. The communication failure early warning method for a power system according to claim 1, characterized in that: 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, including: Acquire the time axis length of the communication failure time axis and the fault communication quality parameter sequence within the communication failure time axis; According to the time axis length and the fault communication quality parameter sequence, performing error analysis on the adjacent electrical variable data caused by the communication fault, and obtaining a communication impact error parameter; The communication impact error parameter is used to perform error correction calculation on the adjacent electrical variable data to obtain corrected adjacent electrical variable data.

4. The communication failure early warning method for a power system according to claim 3, characterized in that: According to the time axis length and the fault communication quality parameter sequence, the error impact analysis of the communication fault on the adjacent electrical variable data is performed to obtain the communication impact error parameter, including: According to the monitoring records of the electric variable data of the communication failures in the substation and the concentrator in the historical time, a sample time axis length set and a sample fault communication quality parameter sequence set of the sample communication failure time axis are collected, and according to the errors between the transmitted adjacent electric variable data and the actual electric variable data, a sample communication impact error parameter set is obtained by marking; Using the sample time axis length set, the sample fault communication quality parameter sequence set and the sample communication impact error parameter set as supervised training data to train an electrical variable error analyzer; Based on the electrical variable error analyzer, error impact analysis is performed on the time axis length and the fault communication quality parameter sequence to obtain communication impact error parameters.

5. The communication failure early warning method for a power system according to claim 1, characterized in that: 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 supplementary generation of missing electrical variable data in the communication fault time axis are performed, including: Setting an integrated analysis coefficient according to a ratio of a time axis length of the communication fault time axis to a preset time axis length; training an electric variable data supplementer including a plurality of electric variable data supplementation branches; According to the integrated analysis coefficient and the number of the plurality of electrical variable data supplementary branches, the number of supplementary branches is calculated and set to obtain; The electrical variable data supplementary branches having the number of supplementary branches are adopted to perform integrated analysis and supplementary generation of the missing electrical variable data within the communication fault time axis on the corrected adjacent electrical variable data, to obtain multiple branch supplementary electrical variable data, and to fuse them to obtain supplementary electrical variable data.

6. The communication failure early warning method for power system according to claim 5, characterized in that: Training an electric variable data supplementer including a plurality of electric variable data supplementation branches, including: According to the monitoring records of the electric variable data of the substation and the concentrator in the historical time when the communication failure occurred, the sample correction adjacent electric variable data set and the sample missing electric variable data set are collected; Performing K-fold division on the sample-corrected adjacent electrical variable data set and the sample-missing electrical variable data set to obtain K pieces of training data, where K is an integer greater than 1; The K pieces of training data are respectively used to train and obtain K electrical variable data supplementation branches to obtain an electrical variable data supplementer.

7. The communication failure early warning method for a power system according to claim 1, characterized in that: Combining the corrected adjacent electric variable data and the supplementary electric variable data to generate complete electric variable data, performing abnormal analysis and prediction of substations, and obtaining abnormal analysis results, including: Combining the corrected adjacent electrical variable data and the supplemented electrical variable data, as well as the electrical variable data when the communication quality parameter does not have a communication failure, to generate complete electrical variable data; According to the complete electrical variable data, abnormal analysis and prediction of the substation are performed to obtain abnormal analysis results.

8. An electronic device comprising: at least one processor; a memory communicatively coupled to the at least one processor; 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 as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the steps of the communication failure early warning method for a power system described in any one of claims 1 to 7 are implemented.

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