Automatic determination and maintenance system for open-phase fault of high-voltage side of transformer

Abstract

The invention provides a transformer high-voltage side open-phase fault automatic determination and maintenance system, and relates to the technical field of data processing, and the system is used for calculating the effective value and the phase difference of each phase voltage according to a preprocessed low-voltage side voltage data set, calculating the amplitude relation coefficient, the standard deviation and the phase characteristic of the three-phase voltage, and calculating the phase difference of the three-phase voltage. Calculating a low-voltage side characteristic deviation factor according to the open-phase characteristic data and a preset open-phase model, judging whether the three-phase voltage of the low-voltage side has an open-phase fault characteristic or not, calculating an amplitude ratio of each phase voltage, and comparing the amplitude ratio with the preset open-phase model; judging whether the amplitude ratio of the low-voltage side voltage meets the high-voltage side open-phase working condition or not, calculating a high-voltage side characteristic deviation factor, comparing the high-voltage side characteristic deviation factor with a preset open-phase model, judging whether the high-voltage side has an open-phase fault or not, and obtaining an open-phase judgment result. Whether the open-phase fault occurs at the high-voltage side can be determined through the voltage at the low-voltage side of the transformer.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to an automatic determination and maintenance system for a transformer high-voltage side phase-loss fault. Background Art

[0002] Transformers are core equipment in power systems and are widely used in transmission and distribution systems to achieve voltage up and down conversion. During operation, a phase loss fault may occur on the high-voltage side of the transformer, resulting in voltage imbalance on the low-voltage side, affecting normal power supply. The current common phase loss detection method mainly relies on manual inspections, but this method not only has a slow detection speed, but is also easily affected by the experience of operation and maintenance personnel, which may lead to unstable fault identification accuracy.

[0003] For example, in a 10kV distribution line in a certain area, a distribution transformer with a Dyn11 connection group was operating in a phase-loss state due to the blowing of the A-phase fuse on the high-voltage side. However, since the low-voltage side of the transformer was still able to output three-phase voltage, only the voltage amplitude changed. As a result, the on-site operation and maintenance personnel failed to immediately identify the phase-loss fault when initially measuring the three-phase voltage on the low-voltage side, which may cause delays in fault detection and affect power supply stability and safety. Summary of the invention

[0004] The purpose of the present invention is to provide a system for automatically determining and repairing a transformer high-voltage side phase loss fault, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A transformer high-voltage side phase loss fault automatic determination and maintenance system, the system comprising:

[0007] The voltage characteristic module is used to calculate the effective value and phase difference of each phase voltage according to the preprocessed low-voltage side voltage data set to obtain a voltage characteristic data set;

[0008] A phase loss feature module is used to calculate the amplitude relationship coefficient, standard deviation and phase characteristics of the three-phase voltage according to the voltage feature data set to obtain the phase loss feature data set;

[0009] The analysis module is used to calculate the low-voltage side characteristic deviation factor according to the phase loss characteristic data and the preset phase loss model, and determine whether the three-phase voltage on the low-voltage side has phase loss fault characteristics, and obtain the low-voltage side phase loss abnormal signal;

[0010] A preliminary determination module is used to calculate the amplitude ratio of each phase voltage according to the abnormal phase loss signal on the low-voltage side, and compare it with the preset phase loss model to determine whether the amplitude ratio of the low-voltage side voltage meets the phase loss condition on the high-voltage side, and obtain preliminary phase loss determination data;

[0011] A phase loss determination module is used to calculate the high-voltage side characteristic deviation factor based on the preliminary phase loss determination data, and compare it with the preset phase loss model to determine whether there is a phase loss fault on the high-voltage side and obtain a phase loss determination result;

[0012] The alarm module is used to determine the fault impact range according to the phase loss judgment result and the distribution network topology information, generate a phase loss fault signal, and send it to the maintenance end.

[0013] Furthermore, the voltage characteristic module includes:

[0014] The effective value calculation unit is used to perform a square operation on the instantaneous voltage data collected on the low-voltage side to obtain square voltage data; accumulate the square voltage data within a preset time length, and then take the average value to obtain mean square voltage data; perform a square root operation on the mean square voltage data to obtain effective value data of the three-phase voltage on the low-voltage side;

[0015] The phase difference calculation unit is used to convert the effective value data to obtain the fundamental phase data of the three-phase voltage; the phase difference data is obtained by calculating the difference between the fundamental phase data of the three-phase voltage.

[0016] Furthermore, the phase loss feature module includes:

[0017] The voltage amplitude relationship calculation unit is used to determine the maximum value, minimum value and intermediate value of the three-phase voltage on the low-voltage side according to the effective value data, and obtain the low-voltage side voltage sorting data; according to the low-voltage side voltage sorting data, determine the sum of the intermediate value of the three-phase voltage and the minimum value of the three-phase voltage, and compare it with the maximum value of the three-phase voltage to obtain the low-voltage side voltage amplitude relationship coefficient;

[0018] The standard deviation calculation unit is used to calculate the mean of the effective values ​​of the three-phase voltages according to the effective value data to obtain the mean data, and calculate the deviation between the effective value data and the mean data of the three-phase voltages according to the mean data to obtain the deviation data; according to the deviation data, calculate the variance and standard deviation of the three-phase voltages to obtain the standard deviation data;

[0019] The phase characteristic calculation unit is used to obtain phase characteristic data by calculating the absolute deviation value of the phase difference data of the three-phase voltage.

[0020] Furthermore, the analysis module includes:

[0021] A low-voltage side reference data acquisition unit is used to extract the historical phase-loss low-voltage side voltage database of the corresponding transformer model and connection group according to a preset phase-loss model to obtain low-voltage side reference data;

[0022] A low-voltage side characteristic deviation factor calculation unit is used to fuse the low-voltage side voltage change rate, the historical low-voltage side voltage change rate, the low-voltage side voltage standard deviation and the historical low-voltage side voltage standard deviation according to the phase loss characteristic data and the low-voltage side reference data to obtain the low-voltage side characteristic deviation factor;

[0023] The characteristic analysis unit is used to determine whether the three-phase voltage on the low-voltage side meets the phase loss fault characteristics based on the low-voltage side characteristic deviation factor and the preset low-voltage side deviation threshold. When the result is yes, a low-voltage side phase loss abnormal signal is generated.

[0024] Furthermore, the preliminary determination module includes:

[0025] The amplitude ratio calculation unit is used to obtain the total voltage data by calculating the sum of the three-phase voltage effective value data; according to the total voltage data, the amplitude ratios of the three-phase voltage effective value data and the total voltage data are calculated respectively to obtain the three-phase amplitude ratio data set;

[0026] The preliminary phase loss judgment unit is used to extract the low-voltage side amplitude ratio corresponding to the high-voltage side phase loss condition according to a preset phase loss model, and obtain a phase loss amplitude ratio data set; based on the three-phase amplitude ratio data set and the phase loss amplitude ratio data set, it is judged whether the three-phase voltage amplitude ratio meets the high-voltage side phase loss condition. When the result is yes, the preliminary phase loss judgment data is obtained.

[0027] Furthermore, the phase loss determination module includes:

[0028] The high-voltage side data acquisition unit is used to collect the voltage, current and power of the current high-voltage side of the transformer to obtain a real-time high-voltage side data set;

[0029] A high-voltage side parameter data acquisition unit is used to extract a historical phase-loss high-voltage side database of a corresponding transformer model and connection group according to a preset phase-loss model to obtain high-voltage side reference data;

[0030] A high-voltage side characteristic deviation factor calculation unit, used for calculating a high-voltage side characteristic deviation factor according to a real-time high-voltage side data set and high-voltage side reference data;

[0031] The phase loss determination unit is used to determine whether there is a phase loss fault on the high-voltage side according to the high-voltage side characteristic deviation factor and a preset high-voltage side deviation threshold, and when the result is yes, a phase loss determination result is generated.

[0032] Furthermore, the preset phase loss model includes:

[0033] Historical phase-loss low-voltage side voltage database, used to store the effective value, amplitude ratio and phase difference of the three-phase voltage on the low-voltage side during historical phase-loss faults;

[0034] The historical phase-loss high-voltage side database is used to store the voltage RMS value, current value and power value before and after the phase-loss on the high-voltage side during historical phase-loss faults;

[0035] The historical phase loss condition classification database is used to store historical phase loss fault types and their data.

[0036] Furthermore, the historical missing phase low-voltage side voltage database includes:

[0037] Collect the three-phase voltage on the low-voltage side when the transformer phase failure occurs, and obtain the historical low-voltage side voltage effective value data;

[0038] According to the historical RMS voltage data of the low-voltage side, the amplitude ratio of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated to obtain the historical phase failure voltage ratio range;

[0039] According to the historical RMS voltage data of the low-voltage side, the phase difference of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated, and the historical phase failure phase angle variation range is obtained.

[0040] Furthermore, the historical phase-loss high-voltage side database includes:

[0041] Collect the effective value of the high-voltage side voltage before and after the phase failure occurs, and obtain the historical effective value data of the high-voltage side voltage;

[0042] Collect the high-voltage side current values ​​before and after the phase failure occurs to obtain historical high-voltage side current value data;

[0043] The high-voltage side power values ​​before and after the phase failure occurs are collected to obtain historical high-voltage side power value data.

[0044] Furthermore, the historical phase-loss condition classification database includes:

[0045] According to the transformer model and connection group, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the connection type data;

[0046] According to the different phase missing faults on the high-voltage side, the historical phase missing low-voltage side voltage data and the historical phase missing high-voltage side voltage data are classified to obtain the phase missing type data;

[0047] According to the load conditions, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the load type data.

[0048] The above solution of the present invention includes at least the following beneficial effects:

[0049] The present invention extracts the voltage effective value and phase difference of each phase from the low-voltage side voltage data set, obtains the voltage characteristic data set by calculation, and can convert the original voltage data into structured characteristic information, which not only realizes the accurate restoration of the three-phase voltage amplitude and phase state, but also improves the system's responsiveness to changes in the voltage state on the low-voltage side. When a phase loss occurs on the high-voltage side of the transformer, although the low-voltage side may still maintain a three-phase output, the slight difference between the voltage amplitude and phase will be captured in time through this function to form a measurable characteristic indicator, thereby providing an accurate and quantifiable characteristic basis for subsequent modules. In particular, when it is impossible to intuitively judge whether the low-voltage side is abnormal in traditional methods, the pre-emptive and accuracy of phase loss detection are significantly improved through structured analysis, which provides a basic basis for establishing a multi-level judgment mechanism and effectively reduces the misjudgment and missed judgment caused by inaccurate manual experience judgment.

[0050] The present invention constructs a phase-loss feature data set by calculating the amplitude relationship coefficient, standard deviation and phase characteristics of the three-phase voltage on the low-voltage side. By introducing the calculation of the amplitude relationship coefficient, the imbalance characteristics existing in the voltage can be effectively judged. Combined with the comprehensive judgment of the standard deviation and phase characteristics, a multi-dimensional abnormality judgment basis is constructed, so that the system has a strong anti-interference ability. When there are interference factors such as instantaneous fluctuations and load changes in the power grid, conventional disturbances and structural anomalies can be distinguished by statistical methods, thereby improving the robustness of phase-loss anomaly identification. In addition, the generated feature data has a certain normalization ability and model adaptability, and can adapt to the voltage status under different transformer models and operating environments, which significantly improves the overall generalization ability and deployment efficiency of the system.

[0051] The present invention calculates the low-voltage side characteristic deviation factor by introducing a fusion analysis method of historical data model and current phase-loss characteristic data, and judges whether the three-phase voltage on the low-voltage side has a phase-loss characteristic based on this. It breaks through the limitation of traditional low-voltage side judgment relying on a single physical quantity, and realizes a fault identification mechanism based on multi-parameter fusion. The low-voltage side characteristic deviation factor comprehensively considers multiple dimensions such as voltage change rate, standard deviation, and historical data comparison to form a quantitative evaluation model for voltage anomalies, so that the system has the ability to identify global trend changes from local data, which greatly improves the accuracy and timeliness of judgment. At the same time, an adaptive deviation threshold mechanism is introduced, which can adjust the judgment standard according to factors such as the connection group of the transformer and the historical operating status, thereby avoiding misidentification or missed detection.

[0052] The present invention calculates the amplitude ratio of the three-phase voltage and compares it with the typical characteristics in the preset phase loss model to determine whether the voltage amplitude ratio meets the typical operating condition of phase loss on the high-voltage side, thereby forming preliminary phase loss judgment data. The ratio processing method eliminates the interference of absolute voltage value fluctuations on fault identification, so that the system can maintain a high recognition accuracy when the voltage level changes and the operating load differs greatly. The amplitude ratio construction method enables the judgment logic to have the ability of relative evaluation, and can identify phase loss characteristics through internal proportional relationships, which significantly improves the ability of phase loss identification to resist voltage fluctuations. Through the comparison mechanism with the preset phase loss model, the fault judgment result has a clear operating condition reference standard, avoiding the uncertainty caused by experience or threshold judgment, and effectively improving the overall accuracy and response speed of the system's multi-level judgment architecture.

[0053] The present invention uses preliminary phase loss judgment data to further collect real-time voltage, current and power data on the high-voltage side, and compares them with reference data in the historical database. Finally, by calculating the characteristic deviation factor of the high-voltage side, it is determined whether there is a phase loss fault. The in-depth analysis capability of the operating status of the high-voltage side and the accuracy of fault location are improved. By introducing multi-dimensional real-time physical quantities as input data, not only the system's ability to understand the nature of the fault is enhanced, but also the speed of identifying abnormal operating trends on the high-voltage side is improved. The calculation mechanism of the characteristic deviation factor can obtain the similarity between the current state and the phase loss model through quantitative analysis, ensuring that fault identification is not only real-time, but also has a high degree of judgment accuracy. It can also call the corresponding phase loss model for comparison according to the differences in different wiring methods and transformer models, thereby realizing personalized judgment, enhancing the system's adaptability to complex power grid environments, and providing accurate information for subsequent maintenance.

[0054] The present invention constructs an automatic judgment and maintenance scheme that can judge the phase loss fault on the high-voltage side of the transformer in real time under the running state through modular structural design and multi-level data processing logic. A bottom-up data flow and a top-down decision-making feedback mechanism are formed between the modules of the system, which ensures the logical consistency and data closed-loop of the whole process from data collection, feature extraction, model comparison to result output. The overall architecture not only improves the accuracy and real-time performance of the judgment results, but also solves the judgment lag problem caused by traditional reliance on manual inspection methods. Especially in different operating environments, different wiring methods and different load conditions, the system can automatically call the corresponding model for judgment according to the actual parameters, which enhances the system's adaptability and generalization capabilities. At the same time, the system structure supports distributed deployment and can be widely used in various application scenarios such as urban power grids, rural power grids and industrial parks. Through the automatic identification and positioning of voltage anomalies, the intelligence level of distribution network operation is significantly improved, providing strong support for fault warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The present invention provides a flowchart of a system for automatically determining and repairing a transformer high-voltage side phase loss fault. DETAILED DESCRIPTION

[0056] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0057] like Figure 1 As shown, an embodiment of the present invention provides a system for automatically determining and repairing a transformer high-voltage side phase loss fault, the system comprising:

[0058] The voltage characteristic module is used to calculate the effective value and phase difference of each phase voltage according to the preprocessed low-voltage side voltage data set to obtain a voltage characteristic data set;

[0059] A phase loss feature module is used to calculate the amplitude relationship coefficient, standard deviation and phase characteristics of the three-phase voltage according to the voltage feature data set to obtain the phase loss feature data set;

[0060] The analysis module is used to calculate the low-voltage side characteristic deviation factor according to the phase loss characteristic data and the preset phase loss model, and determine whether the three-phase voltage on the low-voltage side has phase loss fault characteristics, and obtain the low-voltage side phase loss abnormal signal;

[0061] A preliminary determination module is used to calculate the amplitude ratio of each phase voltage according to the abnormal phase loss signal on the low-voltage side, and compare it with the preset phase loss model to determine whether the amplitude ratio of the low-voltage side voltage meets the phase loss condition on the high-voltage side, and obtain preliminary phase loss determination data;

[0062] A phase loss determination module is used to calculate the high-voltage side characteristic deviation factor based on the preliminary phase loss determination data, and compare it with the preset phase loss model to determine whether there is a phase loss fault on the high-voltage side and obtain a phase loss determination result;

[0063] The alarm module is used to determine the fault impact range based on the phase loss judgment result and the distribution network topology information, generate a phase loss fault signal, and send it to the maintenance end.

[0064] In an embodiment of the present invention, a voltage characteristic module is used to calculate the effective value and phase difference of each phase voltage according to the preprocessed low-voltage side voltage data set to obtain a voltage characteristic data set, which can effectively capture the initial characteristics of voltage imbalance; a phase loss characteristic module is used to calculate the amplitude relationship coefficient, standard deviation and phase characteristics of the three-phase voltage according to the voltage characteristic data set to obtain a phase loss characteristic data set, thereby improving the system's ability to identify atypical phase loss faults; an analysis module is used to calculate the low-voltage side characteristic deviation factor according to the phase loss characteristic data and a preset phase loss model, and to determine whether the three-phase voltage on the low-voltage side has a phase loss fault characteristic, thereby obtaining a low-voltage side phase loss abnormal signal, thereby enhancing the ability to determine the changing trend of the voltage imbalance characteristic.

[0065] The preliminary judgment module is used to calculate the amplitude ratio of each phase voltage according to the abnormal phase loss signal on the low-voltage side, and compare it with the preset phase loss model to determine whether the amplitude ratio of the low-voltage side voltage meets the phase loss condition on the high-voltage side, and obtain preliminary phase loss judgment data, which can filter out the influence of absolute voltage fluctuation on the judgment accuracy, so as to more accurately identify the voltage imbalance structure caused by phase loss; the phase loss judgment module is used to calculate the high-voltage side characteristic deviation factor according to the preliminary phase loss judgment data, and compare it with the preset phase loss model to determine whether there is a phase loss fault on the high-voltage side, and obtain the phase loss judgment result, so as to avoid false alarm problems caused by load disturbance or harmonic pollution on the low-voltage side, and improve the accuracy of the final judgment result of the system; the alarm module is used to determine the fault impact range according to the phase loss judgment result and the distribution network topology information, generate a phase loss fault signal, and send it to the maintenance end, so as to realize the rapid tracing and precise positioning of the fault, and significantly improve the fault response efficiency.

[0066] Among them, the alarm module is used to determine the fault impact range according to the phase loss judgment result and the distribution network topology information, generate a phase loss fault signal, and send it to the maintenance end, specifically including:

[0067] First, the phase loss determination result from the phase loss determination module is received, and the number, real-time monitoring time and fault characteristic information of the transformer equipment with phase loss fault on the high-voltage side are obtained. Then, through the pre-stored distribution network topology database, the upstream and downstream electrical equipment information connected to the transformer with phase loss fault is retrieved, including adjacent transformer equipment, line branches and load node information, and the electrical connection relationship and spatial position distribution between the equipment are obtained, so as to preliminarily determine the scope of the power grid area that may be affected by the phase loss fault.

[0068] Next, the alarm module performs data fusion analysis on the topological structure information obtained above, and analyzes the possible extension path of the current phase failure in the distribution network by constructing a network topology model based on graph theory. The breadth-first search algorithm is used to traverse the distribution network topology map, and the faulty device node is used as the starting point to expand layer by layer. The impact of the fault signal on adjacent branches and load nodes is determined, and the power supply dependency of each node is marked during the traversal process, thereby accurately defining the scope of the fault area and the specific location of the users or power supply nodes that may be affected.

[0069] Then, the alarm module classifies the above traversal results into fault levels. According to the preset fault severity assessment standards, it comprehensively considers multiple parameters such as the affected range, the importance of the load involved, the number of affected users, etc., and determines the severity level of the phase loss fault. It matches the corresponding alarm mode and information content according to different levels, and automatically generates a complete phase loss fault signal. The signal includes the fault transformer number, the time of fault occurrence, the fault level assessment, the specific scope of the affected power supply area, and the name information of the important users or loads involved, so as to facilitate the precise implementation of subsequent maintenance work.

[0070] Finally, the alarm module automatically sends the complete phase loss fault signal to the maintenance terminal, dispatching control center and mobile maintenance terminal equipment of the operation and maintenance personnel in the corresponding area through the communication network. At the same time, real-time recording and data archiving are carried out in the background of the monitoring system to achieve rapid notification and handling tracking of faults.

[0071] In a preferred embodiment of the present invention, the voltage characteristic module includes:

[0072] The effective value calculation unit is used to perform a square operation on the instantaneous voltage data collected on the low-voltage side to obtain square voltage data; accumulate the square voltage data within a preset time length, and then take the average value to obtain mean square voltage data; perform a square root operation on the mean square voltage data to obtain effective value data of the three-phase voltage on the low-voltage side;

[0073] The phase difference calculation unit is used to convert the effective value data to obtain the fundamental phase data of the three-phase voltage; the phase difference data is obtained by calculating the difference between the fundamental phase data of the three-phase voltage.

[0074] In an embodiment of the present invention, an effective value calculation unit is used to perform a square operation on the instantaneous voltage data collected on the low-voltage side to obtain square voltage data; the square voltage data is accumulated within a preset time length, and then the mean is taken to obtain the mean square voltage data; the mean square voltage data is squared to obtain the effective value data of the three-phase voltage on the low-voltage side, which can directly characterize the stability and effectiveness of the actual output voltage on the low-voltage side of the transformer, so that the voltage characteristic data can accurately reflect the operating state of the transformer, and provide an important quantitative basis for the subsequent accurate identification of phase loss faults; the phase difference calculation unit is used to convert the effective value data to obtain the fundamental phase data of the three-phase voltage; by calculating the difference in the fundamental phase data between the three-phase voltages, the phase difference data is obtained, which realizes the refined processing of the low-voltage side voltage characteristic data, and significantly improves the system's perception of abnormal voltage conditions on the low-voltage side, providing a solid and accurate feature basis for the subsequent automatic detection of phase loss faults.

[0075] The phase difference calculation unit is used to convert the effective value data to obtain the fundamental phase data of the three-phase voltage; the phase difference data is obtained by calculating the difference between the fundamental phase data of the three-phase voltages, specifically including:

[0076] First, the three-phase voltage RMS data collected on the low-voltage side is preprocessed, and the collected time-domain RMS voltage data is Fourier transformed to extract the fundamental frequency component in each phase voltage signal, and then the phase value corresponding to the fundamental frequency is accurately calculated. Specifically, the fast Fourier transform algorithm is used to accurately convert the original time-domain RMS signal into a frequency domain signal, which significantly improves the accuracy of the fundamental phase data calculation and ensures that the subsequent analysis and judgment process based on phase information has higher stability and reliability.

[0077] After successfully obtaining the fundamental phase data of the three-phase voltage, further pairwise phase difference calculations are performed, and the three-phase voltage fundamental phase data are combined and difference calculations are performed, that is, the difference between the fundamental phase of phase A voltage and the fundamental phase of phase B voltage, the difference between the fundamental phase of phase B voltage and the fundamental phase of phase C voltage, and the difference between the fundamental phase of phase C voltage and the fundamental phase of phase A voltage are calculated respectively to form three pairs of phase difference data. The phase value at the fundamental frequency is uniformly used as the calculation basis during calculation, which ensures the accuracy and uniformity of the phase difference data and avoids errors caused by inconsistent frequency components.

[0078] In a preferred embodiment of the present invention, the phase-loss characteristic module includes:

[0079] The voltage amplitude relationship calculation unit is used to determine the maximum value, minimum value and intermediate value of the three-phase voltage on the low-voltage side according to the effective value data, and obtain the low-voltage side voltage sorting data; according to the low-voltage side voltage sorting data, determine the sum of the intermediate value of the three-phase voltage and the minimum value of the three-phase voltage, and compare it with the maximum value of the three-phase voltage to obtain the low-voltage side voltage amplitude relationship coefficient;

[0080] The standard deviation calculation unit is used to calculate the mean of the effective values ​​of the three-phase voltages according to the effective value data to obtain the mean data, and calculate the deviation between the effective value data and the mean data of the three-phase voltages according to the mean data to obtain the deviation data; according to the deviation data, calculate the variance and standard deviation of the three-phase voltages to obtain the standard deviation data;

[0081] The phase characteristic calculation unit is used to obtain phase characteristic data by calculating the absolute deviation value of the phase difference data of the three-phase voltage.

[0082] In an embodiment of the present invention, a voltage amplitude relationship calculation unit is used to determine the maximum value, minimum value and intermediate value of the three-phase voltage on the low-voltage side according to the effective value data, and obtain the low-voltage side voltage sorting data; according to the low-voltage side voltage sorting data, determine the sum of the intermediate value of the three-phase voltage and the minimum value of the three-phase voltage, and compare it with the maximum value of the three-phase voltage to obtain the low-voltage side voltage amplitude relationship coefficient, quantify the amplitude difference characteristics between the three-phase voltages on the low-voltage side, and accurately identify the abnormal amplitude trend caused by the phase failure; the standard deviation calculation unit is used to calculate the mean of the effective values ​​of the three-phase voltages according to the effective value data to obtain the mean data, And based on the deviation between the effective value data and the mean data of the three-phase voltage, the deviation data is obtained; based on the deviation data, the variance and standard deviation of the three-phase voltage are calculated to obtain the standard deviation data, which eliminates the misjudgment interference caused by short-term fluctuations in the power grid and instantaneous changes in the load, and ensures that the identification of phase-loss characteristics can be applied to complex operating conditions; the phase characteristic calculation unit is used to obtain the phase characteristic data by calculating the absolute deviation value of the phase difference data of the three-phase voltage, which can timely and sensitively capture the phase abnormality on the low-voltage side caused by the phase loss on the high-voltage side, avoiding the missed judgment or delayed judgment caused by the unclear voltage amplitude abnormality.

[0083] In a preferred embodiment of the present invention, the analysis module comprises:

[0084] A low-voltage side reference data acquisition unit is used to extract the historical phase-loss low-voltage side voltage database of the corresponding transformer model and connection group according to a preset phase-loss model to obtain low-voltage side reference data;

[0085] A low-voltage side characteristic deviation factor calculation unit is used to fuse the low-voltage side voltage change rate, the historical low-voltage side voltage change rate, the low-voltage side voltage standard deviation and the historical low-voltage side voltage standard deviation according to the phase loss characteristic data and the low-voltage side reference data to obtain the low-voltage side characteristic deviation factor;

[0086] The characteristic analysis unit is used to determine whether the three-phase voltage on the low-voltage side meets the phase loss fault characteristics based on the low-voltage side characteristic deviation factor and the preset low-voltage side deviation threshold. When the result is yes, a low-voltage side phase loss abnormal signal is generated.

[0087] In an embodiment of the present invention, a low-voltage side reference data acquisition unit is used to extract the historical phase-loss low-voltage side voltage database of the corresponding transformer model and wiring group according to a preset phase-loss model to obtain low-voltage side reference data, thereby providing a historical reference standard for fault analysis and eliminating excessive reliance on experience in traditional manual diagnosis methods; a low-voltage side characteristic deviation factor calculation unit is used to fuse the low-voltage side voltage change rate, the historical low-voltage side voltage change rate, the low-voltage side voltage standard deviation and the historical low-voltage side voltage standard deviation according to the phase-loss characteristic data and the low-voltage side reference data to obtain a low-voltage side characteristic deviation factor, thereby realizing voltage anomaly detection. The quantitative characterization of the state ensures that fault analysis is not limited to qualitative judgment, but truly realizes quantitative diagnosis, thereby improving the sensitivity to voltage anomalies and the accuracy of judgment, and ensuring the quantitative distinction and accurate identification of fault states; the characteristic analysis unit is used to determine whether the three-phase voltage on the low-voltage side meets the phase loss fault characteristics based on the low-voltage side characteristic deviation factor and the preset low-voltage side deviation threshold. When the result is yes, a low-voltage side phase loss abnormal signal is generated, ensuring that the system's automatic identification of abnormal conditions has a high accuracy, avoiding the subjective judgment errors that exist in traditional manual analysis, and significantly improving the degree of automation of system fault identification.

[0088] Among them, the low-voltage side characteristic deviation factor calculation unit is used to fuse the low-voltage side voltage change rate, the historical low-voltage side voltage change rate, the low-voltage side voltage standard deviation and the historical low-voltage side voltage standard deviation according to the phase loss characteristic data and the low-voltage side reference data to obtain the low-voltage side characteristic deviation factor, which specifically includes:

[0089] The calculation formula of the low-pressure side characteristic deviation factor is: ;

[0090] in, is the low-pressure side characteristic deviation factor, is the difference between the mean values ​​of the low-voltage side voltage at adjacent time points, is the difference in historical low-voltage side voltage at adjacent time points, is the difference between adjacent time points, is the standard deviation of the low voltage side voltage, is the historical low voltage side voltage standard deviation, is the mean voltage on the low voltage side, is the historical low voltage side voltage average, is the difference in standard deviation of low voltage side voltage at adjacent time points, is the difference in the standard deviation of the historical low-voltage side voltage at adjacent time points, and is the coefficient.

[0091] The above formula realizes the accurate quantification and feature extraction of the difference between the current operating state of the low-voltage side of the transformer and the historical phase-loss fault state. First, the deviation comparison relationship between real-time and historical data is constructed by the difference between the mean value of the low-voltage side voltage at adjacent time points and the difference between the historical low-voltage side voltage. Then, the difference between the standard deviation of the low-voltage side voltage at adjacent time points and the historical low-voltage side standard deviation is used to construct the difference in fluctuation characteristics between real-time and historical data.

[0092] In addition, the numerator of the formula uses an exponential function to further perform nonlinear amplification on the difference between the current voltage standard deviation and the historical voltage standard deviation, and performs weighted calculation based on the time interval. This exponential amplification process makes the difference in voltage fluctuation characteristics more clearly magnified and presented, which helps the system respond quickly to small but critical voltage fluctuations and improves the sensitivity and recognition accuracy of early signs of phase loss faults.

[0093] The denominator of the formula divides the difference between the current and historical voltage averages by the historical voltage average, and combines it with the voltage standard deviation difference for normalization and scaling. Adding a constant in the denominator can effectively prevent the abnormal amplification of the deviation factor caused by a denominator that is too small, making the calculation result more stable and reliable and avoiding the risk of false alarms.

[0094] Through the comprehensive calculation of the above formula, the low-voltage side characteristic deviation factor finally outputted can reflect the degree of deviation between the current operating voltage state and the historical phase-loss fault state in a highly sensitive manner. The larger the value of this factor, the more significant the deviation between the current low-voltage side operating state and the typical phase-loss fault characteristics, thereby clearly revealing that a phase-loss fault may have occurred on the high-voltage side of the current transformer; otherwise, it means that the current state deviates little or not from the phase-loss state, which can be judged as a normal or temporary fluctuation state.

[0095] Among them, the characteristic analysis unit is used to judge whether the three-phase voltage on the low-voltage side meets the phase loss fault characteristics according to the low-voltage side characteristic deviation factor and the preset low-voltage side deviation threshold. When the result is yes, a low-voltage side phase loss abnormal signal is generated, which specifically includes:

[0096] First, the low-voltage side deviation threshold is called from the preset database: according to the current transformer model, connection group and load characteristics, the threshold parameter that matches the current actual operating status is selected from the pre-stored low-voltage side deviation threshold library. The called threshold is the statistical result of a large number of historical phase loss fault case analyses, which is representative and applicable to a certain extent and can ensure the accuracy of the judgment results of the analysis unit.

[0097] Then, the obtained low-voltage side characteristic deviation factor is numerically compared with the low-voltage side deviation threshold. The system automatically performs numerical comparison operations to determine in real time whether the actual value of the deviation factor exceeds the corresponding preset threshold. If the deviation factor exceeds the threshold, it indicates that the current low-voltage side voltage change trend or fluctuation range has exceeded the normal range, reflecting the voltage characteristics of typical phase loss abnormality. If it does not exceed the threshold, it means that the voltage state is in a normal or allowable range of fluctuations.

[0098] Finally, when the result of the comparison analysis exceeds the threshold, the feature analysis unit immediately and automatically generates a low-voltage side phase loss abnormality signal; and sends a clearly marked phase loss abnormality flag information to the subsequent preliminary judgment module, which includes the currently detected deviation factor value, threshold information, transformer identification, timestamp and other key data.

[0099] In a preferred embodiment of the present invention, the preliminary determination module includes:

[0100] The amplitude ratio calculation unit is used to obtain the total voltage data by calculating the sum of the three-phase voltage effective value data; according to the total voltage data, the amplitude ratios of the three-phase voltage effective value data and the total voltage data are calculated respectively to obtain the three-phase amplitude ratio data set;

[0101] The preliminary phase loss judgment unit is used to extract the low-voltage side amplitude ratio corresponding to the high-voltage side phase loss condition according to a preset phase loss model, and obtain a phase loss amplitude ratio data set; based on the three-phase amplitude ratio data set and the phase loss amplitude ratio data set, it is judged whether the three-phase voltage amplitude ratio meets the high-voltage side phase loss condition. When the result is yes, the preliminary phase loss judgment data is obtained.

[0102] In an embodiment of the present invention, an amplitude ratio calculation unit is used to obtain total voltage data by calculating the sum of three-phase voltage effective value data; based on the total voltage data, the amplitude ratios of the three-phase voltage effective value data and the total voltage data are respectively calculated to obtain a three-phase amplitude ratio data set, effectively extracting the relative proportional relationship of the three-phase voltage, so that the system can identify voltage asymmetry. This operation eliminates the interference caused by the absolute voltage value difference under different load states, and improves the sensitivity and recognition accuracy of the real phase loss fault; a preliminary phase loss judgment unit is used to extract the low-voltage side amplitude ratio corresponding to the high-voltage side phase loss condition according to a preset phase loss model, and obtain a phase loss amplitude ratio data set; based on the three-phase amplitude ratio data set and the phase loss amplitude ratio data set, it is judged whether the three-phase voltage amplitude ratio meets the high-voltage side phase loss condition. When the result is yes, preliminary phase loss judgment data is obtained, the voltage characteristic difference of the phase loss fault is accurately identified, the misjudgment of the voltage abnormality signal is effectively prevented, and the reliability and stability of phase loss fault identification are further improved.

[0103] Among them, the phase loss preliminary judgment unit is used to extract the low-voltage side amplitude ratio corresponding to the high-voltage side phase loss condition according to the preset phase loss model, and obtain the phase loss amplitude ratio data set; according to the three-phase amplitude ratio data set and the phase loss amplitude ratio data set, it is judged whether the three-phase voltage amplitude ratio meets the high-voltage side phase loss condition. When the result is yes, the preliminary phase loss judgment data is obtained, which specifically includes:

[0104] First, according to the preset phase loss model, by accessing and querying the historical phase loss condition database, according to the transformer model, rated capacity and connection group, the historical high-voltage side phase loss condition data consistent with the current transformer conditions are extracted from the database. The historical condition data clearly includes the amplitude ratio range of the three-phase voltage corresponding to the low-voltage side when the high-voltage side has a phase loss, thereby obtaining a phase loss amplitude ratio data set suitable for the current transformer model. According to the current transformer operating environment information, the amplitude ratio feature range corresponding to the current condition is automatically retrieved and extracted from the database. This operation can realize the effective use of historical phase loss data and greatly improve the reliability and pertinence of data analysis.

[0105] Secondly, the phase loss amplitude ratio data set obtained in the previous step is compared and analyzed with the three-phase amplitude ratio data set obtained by real-time calculation. The specific operation method is: first, the amplitude ratio calculated in real time is taken for the three-phase voltages A, B, and C, and then compared with the corresponding phase loss amplitude ratio range in the database to determine whether the real-time three-phase amplitude ratio falls within the typical phase loss amplitude ratio range recorded in the database. For example, the upper and lower limits of the amplitude ratio when the phase is lost are recorded in the database. and , the amplitude ratio calculated in real time is recorded as , then judge respectively Whether the inequality condition is satisfied By performing this operation on phases A, B, and C respectively, it is possible to quickly and clearly confirm whether the three-phase voltage amplitude ratio relationship is consistent with the historical phase-loss characteristic data, thereby realizing the preliminary identification of the phase-loss fault. When the real-time calculated amplitude ratio of at least one phase of the three-phase voltage amplitude ratio meets the phase-loss amplitude ratio range recorded in the preset phase-loss model, that is, the real-time amplitude ratio data of the phase voltage falls within the characteristic data range, the preliminary phase-loss judgment unit confirms that the current voltage performance on the low-voltage side is consistent with the characteristics of the phase-loss operating condition on the high-voltage side.

[0106] In a preferred embodiment of the present invention, the phase loss determination module includes:

[0107] The high-voltage side data acquisition unit is used to collect the voltage, current and power of the current high-voltage side of the transformer to obtain a real-time high-voltage side data set;

[0108] A high-voltage side parameter data acquisition unit is used to extract a historical phase-loss high-voltage side database of a corresponding transformer model and connection group according to a preset phase-loss model to obtain high-voltage side reference data;

[0109] A high-voltage side characteristic deviation factor calculation unit, used for calculating a high-voltage side characteristic deviation factor according to a real-time high-voltage side data set and high-voltage side reference data;

[0110] The phase loss determination unit is used to determine whether there is a phase loss fault on the high-voltage side according to the high-voltage side characteristic deviation factor and a preset high-voltage side deviation threshold, and when the result is yes, a phase loss determination result is generated.

[0111] In the embodiment of the present invention, the high-voltage side data acquisition unit is used to collect the voltage, current and power of the current high-voltage side of the transformer to obtain a real-time high-voltage side data set. Through high-precision real-time data acquisition and processing, the timeliness and accuracy of the data in the system judgment process are guaranteed, and effective data guarantee is provided for subsequent feature analysis; the high-voltage side parameter data acquisition unit is used to extract the historical phase-loss high-voltage side database of the corresponding transformer model and wiring group according to the preset phase-loss model to obtain high-voltage side reference data. By introducing historical data, the stability and robustness of the system judgment are improved, and the judgment deviation caused by transformer differences is effectively reduced; The high-voltage side characteristic deviation factor calculation unit is used to calculate the high-voltage side characteristic deviation factor based on the real-time high-voltage side data set and the high-voltage side reference data. The fusion calculation of multi-dimensional parameters significantly improves the accuracy of the high-voltage side phase loss judgment and solves the technical defect that the single parameter judgment is easily affected by external interference; the phase loss judgment unit is used to judge whether there is a phase loss fault on the high-voltage side based on the high-voltage side characteristic deviation factor and the preset high-voltage side deviation threshold. When the result is yes, a phase loss judgment result is generated. Through threshold comparison and multi-dimensional cross-validation methods, the certainty of the high-voltage side phase loss judgment result is improved, avoiding the false alarm or omission caused by a single factor abnormality.

[0112] The high-voltage side characteristic deviation factor calculation unit is used to calculate the high-voltage side characteristic deviation factor according to the real-time high-voltage side data set and the high-voltage side reference data, specifically including:

[0113] The calculation formula of the high-voltage side characteristic deviation factor is: ;

[0114] in, is the high-voltage side characteristic deviation factor, is the voltage on the high voltage side of the current transformer, is the voltage on the historical high-voltage side, is the current on the high voltage side of the transformer, is the current on the historical high voltage side, is the active power on the high voltage side of the current transformer, is the historical active power on the high voltage side, is the apparent power on the high voltage side of the current transformer, , is the coefficient.

[0115] Among them, the calculation formula performs difference, ratio and exponential operations on the real-time operating parameters of the current transformer high-voltage side and the historical operating data to obtain a quantitative indicator that can accurately reflect the degree of difference between the current operating status of the transformer high-voltage side and the historical normal operating status. The core function of the formula is to use precise mathematical calculations to reflect whether there is a phase loss fault on the high-voltage side with the combined difference value of multiple operating parameters, thereby overcoming the limitations of single parameter judgment of traditional detection methods, so that abnormal operating conditions can be judged more precisely and intuitively, greatly improving the accuracy of fault judgment.

[0116] Specifically, the first term in the formula It reflects the relative amplitude of the difference between the current voltage and the historical voltage. By adjusting the sensitivity of the voltage difference, the formula can be adaptively adjusted for different transformer models and different voltage levels to ensure accurate response to voltage anomalies under different operating conditions. The second term of the formula Reflect the change of current, by controlling the weight of current difference, so as to flexibly optimize the contribution of current parameters to the judgment result in scenarios where the importance of current characteristics to phase loss judgment is different; the third item Reflecting power changes, by introducing the power change rate and adjusting the power characteristics, the robustness of the decision logic is significantly enhanced, the possibility of misjudgment caused by external disturbances is reduced, and the apparent power and exponential , effectively enhancing the nonlinear characterization capability of the abnormal degree of the current operating state, so that the deviation factor not only reflects the linear relationship between voltage, current and power, but also can accurately capture the nonlinear change trend, thereby improving the sensitivity and robustness of fault identification.

[0117] According to the high-voltage side characteristic deviation factor and the preset high-voltage side deviation threshold, it is determined whether there is a phase loss fault on the high-voltage side. If the result is yes, a phase loss determination result is generated, which specifically includes:

[0118] First, according to the calculation result of the high-voltage side characteristic deviation factor, the preset high-voltage side deviation threshold is retrieved from the system background preset model database. The preset high-voltage side deviation threshold is obtained after statistical analysis of the characteristic deviation factors corresponding to a large number of historical transformer high-voltage side phase loss faults. It is an important judgment basis for the system to determine the high-voltage side phase loss fault; then, the system compares the high-voltage side characteristic deviation factor with the preset high-voltage side deviation threshold item by item, and judges the difference between the current transformer high-voltage side operating state and the historical phase loss operating state in a quantitative manner, specifically including comparing the absolute value of the difference, the percentage of the difference or the comprehensive difference trend evaluation method, and through a strict data calculation process, it is clear whether the current state exceeds the allowable range of the normal operating state.

[0119] Secondly, if in the above comparative analysis, the high-voltage side characteristic deviation factor does not exceed the preset high-voltage side deviation threshold, the system determines that the current operating status of the high-voltage side of the transformer is normal, and continues to monitor the high-voltage side and conduct periodic data comparison and analysis without generating additional actions; and when the calculated high-voltage side characteristic deviation factor exceeds the preset high-voltage side deviation threshold, the phase loss confirmation procedure set in the system is triggered, and the cross-validation mechanism is further initiated, including re-analysis of multiple sets of continuous periodic data and re-confirmation of the correlation between voltage, current, and power, to verify whether the characteristic deviation exists continuously and stably, thereby effectively avoiding misjudgment caused by occasional instantaneous disturbances.

[0120] Finally, when the cross-validation mechanism confirms that the characteristic deviation factor on the high-voltage side has stably exceeded the preset threshold range for multiple consecutive cycles, and the multi-dimensional data verification results consistently meet the phase-loss characteristic conditions, the system confirms that there is a phase-loss fault on the high-voltage side of the transformer, and automatically calls the system's preset phase-loss judgment result generation module to accurately match the current actual operating status of the transformer with the preset fault condition type in the model library to generate a clear and specific phase-loss judgment result; the judgment result includes fault confirmation information, characteristic parameter information, fault severity information and preliminary positioning information, which is stored in the form of digital and structured data and further transmitted to the system's alarm module for sending alarm information to the maintenance terminal.

[0121] In a preferred embodiment of the present invention, the preset phase loss model includes:

[0122] Historical phase-loss low-voltage side voltage database, used to store the effective value, amplitude ratio and phase difference of the three-phase voltage on the low-voltage side during historical phase-loss faults;

[0123] The historical phase-loss high-voltage side database is used to store the voltage RMS value, current value and power value before and after the phase-loss on the high-voltage side during historical phase-loss faults;

[0124] The historical phase loss condition classification database is used to store historical phase loss fault types and their data.

[0125] In an embodiment of the present invention, a historical phase-loss low-voltage side voltage database is used to store the effective value, amplitude ratio and phase difference of the three-phase voltage on the low-voltage side during historical phase-loss faults, effectively establishing a reliable historical benchmark for low-voltage side voltage changes, and providing historical data support for the system to subsequently determine whether there is a phase-loss feature; a historical phase-loss high-voltage side database is used to store the effective value of the voltage, current value and power value before and after the phase loss on the high-voltage side during historical phase-loss faults. The system can accurately identify significant changes in electrical characteristics of the high-voltage side before and after the phase loss occurs, thereby enhancing the identification accuracy of the phase-loss fault and improving the accuracy and reliability of fault location and diagnosis; a historical phase-loss operating condition classification database is used to store historical phase-loss fault types and their data, significantly improving the versatility and adaptability of the phase-loss fault detection and analysis system, and avoiding misjudgment or missed judgment due to equipment differences and different operating conditions.

[0126] In a preferred embodiment of the present invention, the historical missing phase low-voltage side voltage database includes:

[0127] Collect the three-phase voltage on the low-voltage side when the transformer phase failure occurs, and obtain the historical low-voltage side voltage effective value data;

[0128] According to the historical RMS voltage data of the low-voltage side, the amplitude ratio of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated to obtain the historical phase failure voltage ratio range;

[0129] According to the historical RMS voltage data of the low-voltage side, the phase difference of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated, and the historical phase failure phase angle variation range is obtained.

[0130] In an embodiment of the present invention, the three-phase voltage on the low-voltage side is collected when a transformer phase loss fault occurs, and the historical low-voltage side voltage effective value data is obtained to ensure the reliability and accuracy of subsequent voltage feature calculations, thereby providing strong data support for determining a phase loss fault; based on the historical low-voltage side voltage effective value data, the amplitude ratio of the three-phase voltage on the low-voltage side when the phase loss fault occurs is calculated to obtain a historical phase loss voltage ratio range, which can effectively distinguish between normal voltage fluctuations and amplitude anomalies caused by fault conditions, and provide a clear and referenceable voltage amplitude feature threshold for phase loss fault determination; based on the historical low-voltage side voltage effective value data, the phase difference of the three-phase voltage on the low-voltage side when the phase loss fault occurs is calculated to obtain the historical phase loss phase angle variation range, and the phase loss feature is clearly provided to provide feature support in the phase dimension, which is particularly helpful in improving the sensitivity of the determination system to phase loss faults when the amplitude fluctuation is small.

[0131] Among them, the three-phase voltage on the low-voltage side when the transformer phase failure occurs is collected to obtain the historical low-voltage side voltage effective value data, including:

[0132] First, a high-precision voltage sensor is set at the output end of the low-voltage side of the transformer. The sensor can monitor and collect the instantaneous voltage data of the three phases A, B, and C on the low-voltage side of the transformer in real time. During the specific implementation, the sampling frequency of the sensor is set to at least 128 sampling points per power frequency cycle to ensure the precision and real-time performance of data collection. The collected data is converted into a digital signal through an analog-to-digital conversion circuit, and then transmitted to the data processing terminal in real time. It is cached and stored according to the data unit of each power frequency cycle. In the system background, the voltage effective value calculation algorithm is used to process the cached instantaneous voltage data, that is, the instantaneous value of each phase voltage is squared in turn and the square average of all sampling points in each cycle is obtained, and then the square root processing is performed to accurately obtain the periodic effective value data of each phase voltage to form the historical low-voltage side voltage effective value data.

[0133] In a preferred embodiment of the present invention, the historical phase-loss high-voltage side database includes:

[0134] Collect the effective value of the high-voltage side voltage before and after the phase failure occurs, and obtain the historical effective value data of the high-voltage side voltage;

[0135] Collect the high-voltage side current values ​​before and after the phase failure occurs to obtain historical high-voltage side current value data;

[0136] The high-voltage side power values ​​before and after the phase failure occurs are collected to obtain historical high-voltage side power value data.

[0137] In an embodiment of the present invention, the effective value of the high-voltage side voltage before and after the phase failure occurs is collected to obtain historical high-voltage side voltage effective value data, which can accurately record the specific change trend of the voltage value before and after the phase failure occurs, provide a quantitative comparison basis, and lay a data foundation for the subsequent establishment of a high-voltage side voltage characteristic model; the high-voltage side current value before and after the phase failure occurs is collected to obtain historical high-voltage side current value data. By comparing the high-voltage side current before and after the fault, the abnormal current fluctuation trend caused by the phase failure can be revealed, which serves as a basis for distinguishing the supplementary voltage information; the high-voltage side power value before and after the phase failure occurs is collected to obtain historical high-voltage side power value data. The power value is the embodiment of the electric energy output after the voltage and current are coupled, and can reflect the degree of influence of the phase failure on the overall load power supply capacity.

[0138] Among them, the effective value of the high-voltage side voltage before and after the phase failure occurs is collected to obtain the historical effective value data of the high-voltage side voltage, which specifically includes:

[0139] The system needs to be equipped with a voltage monitoring device with high-frequency sampling capability installed on the high-voltage side incoming line end of the transformer to synchronously measure the A, B, and C three-phase voltages. The sampling device is a voltage transformer, which records the instantaneous value of each phase voltage in real time with a collection period of no more than 20ms. The collected data is transmitted to the local monitoring platform or the remote master station system. To ensure data integrity, the system retains the voltage sampling values ​​within 10 seconds before and after the fault, and records them in the cache area according to the timestamp, and then performs effective value calculation on the cached data: first, perform a square operation on the instantaneous value of each phase voltage collected, and then average it in a sliding time window manner to obtain the mean square value of the time period; finally, perform a square root operation on the mean square value to obtain the effective value sequence of each phase voltage. The system archives these voltage effective values ​​in time series to form a historical high-voltage side voltage effective value data set.

[0140] Among them, the high-voltage side current values ​​before and after the phase failure occurs are collected to obtain historical high-voltage side current value data, including:

[0141] The system realizes real-time acquisition of three-phase current signals based on the current transformer installed on the high-voltage side of the transformer in conjunction with the electric energy meter. The system needs to ensure that the acquisition accuracy reaches above 0.5S level and the sampling frequency is not less than 1kHz to ensure the continuity and true reflection of the current fluctuation data before and after the fault. When the fault prediction module triggers the phase loss warning signal, the system automatically extracts the current sampling data 5 seconds before and after that moment. The system performs a sliding window operation on each phase current data. The steps include: first square processing, then averaging the data in each window, and then performing square root calculation to obtain the effective value of the current in the window. After the calculation is completed, the current effective value data is arranged in chronological order, and bound to the transformer number, phase information and fault event number, and uploaded to the high-voltage side historical current database.

[0142] Among them, the high-voltage side power values ​​before and after the phase failure occurs are collected to obtain historical high-voltage side power value data, including:

[0143] Based on the acquired voltage and current data, the system uses synchronous sampling to align the two in the time domain, and completes the evaluation of power changes before and after the fault through the three-phase power calculation module. In each sampling cycle, the system performs operations: For each phase, calculate the active power , reactive power , apparent power ,in is the effective value of voltage and current at the corresponding moment, The phase difference between voltage and current is calculated by the time delay of synchronous sampling, and then the power of each phase is summed to obtain the total power value of the three phases. The system records the power data for no less than 10 sampling cycles before and after, and stores the power change curve in the historical high-voltage side power value data. Each set of power data is associated with the transformer number, sampling period and phase loss type label, which is convenient for subsequent classification and retrieval by fault scenario.

[0144] In a preferred embodiment of the present invention, the historical phase-loss condition classification database includes:

[0145] According to the transformer model and connection group, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the connection type data;

[0146] According to the different phase missing faults on the high-voltage side, the historical phase missing low-voltage side voltage data and the historical phase missing high-voltage side voltage data are classified to obtain the phase missing type data;

[0147] According to the load conditions, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the load type data.

[0148] In an embodiment of the present invention, historical phase-loss low-voltage side voltage data and historical phase-loss high-voltage side voltage data are classified according to the transformer model and wiring group to obtain wiring type data. By introducing the wiring group dimension to classify the data, the subsequent model calling process can select a matching phase-loss feature model according to the actual wiring method of the transformer, thereby improving the pertinence and accuracy of the analysis results; according to different phase loss faults on the high-voltage side, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain phase-loss type data. Through the refined classification of phase-loss types, the system can establish model templates for different phase loss situations, thereby improving the ability to recognize fault modes in the phase loss judgment process; according to the load conditions, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain load type data, which can enable the system to introduce a condition correction mechanism in the judgment process to improve the model's ability to adapt to complex operating environments.

[0149] Among them, according to the transformer model and connection group, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the connection type data, which specifically includes:

[0150] First, access the transformer asset management system or operation ledger database through the data interface to extract the unique identification number, equipment model information and wiring group parameters of each transformer. The wiring groups usually include Yyn0, Dyn11, Yd11 and other types. The system establishes a wiring group index table and marks transformers with the same wiring group with a unified category label.

[0151] Subsequently, by associating queries with the phase loss fault record database, the voltage data corresponding to all phase loss faults are screened out, including the effective value and phase angle of the three-phase voltage on the low-voltage side, and the three-phase voltage, current and power parameters on the high-voltage side. The system binds each set of phase loss fault data to the connection group of the transformer to which it belongs, and classifies and stores them according to the connection method.

[0152] Among them, according to the different phase loss faults on the high-voltage side, the historical phase loss low-voltage side voltage data and the historical phase loss high-voltage side voltage data are classified to obtain the phase loss type data, which specifically includes:

[0153] The system first extracts the missing phase type on the high-voltage side through the fault labeling information recorded in the phase loss event data table, including labels such as missing phase A, missing phase B, and missing phase C. If the original record does not show the missing phase label, the system will automatically analyze the effective value data of the high-voltage side voltage, automatically infer the missing phase based on the characteristics of the missing phase voltage dropping to zero or significantly lower, and supplement the missing label in a programmatic manner.

[0154] After completing phase identification, the system creates a corresponding data index file for each type of phase loss, and aggregates the low-voltage and high-voltage side voltage data, current data, and power data corresponding to the phase A loss event into one category; independent data sets are established for phase B loss and phase C loss respectively. For power systems with large amounts of data, they can be further subdivided, such as cross-labeling such as phase A loss - wiring group is Dyn11, load type is heavy load, etc.

[0155] Among them, according to the load conditions, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain load type data, which specifically includes:

[0156] The system first extracts the load information data corresponding to the phase loss event from the distribution automation system, including the three-phase current value, instantaneous power value, active power and reactive power components, and power factor. By analyzing the load-side electrical parameter curve during this time period, the system can calculate the average load level, load fluctuation degree and current imbalance factor during this period.

[0157] Based on these calculation results, the system divides the load conditions into several categories, such as heavy load operation, light load operation, fluctuating load operation, etc. At the same time, the system also divides the load conditions into resistive, inductive, capacitive or composite load types based on the load characteristics. The power factor range is used as the judgment basis. The power factor of the inductive load is lower than 0.85, and the power factor of the resistive load is close to 1. After the classification is completed, the system will archive the voltage, current and power data collected by the phase loss event under each type of load condition, and associate the wiring group with the phase loss type label to build a multi-dimensional label classification data model.

[0158] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A transformer high-voltage side phase failure automatic determination and maintenance system, characterized in that: The system comprises: The voltage characteristic module is used to calculate the effective value and phase difference of each phase voltage according to the preprocessed low-voltage side voltage data set to obtain a voltage characteristic data set; A phase loss feature module is used to calculate the amplitude relationship coefficient, standard deviation and phase characteristics of the three-phase voltage according to the voltage feature data set to obtain the phase loss feature data set; The analysis module is used to calculate the low-voltage side characteristic deviation factor according to the phase loss characteristic data and the preset phase loss model, and determine whether the three-phase voltage on the low-voltage side has phase loss fault characteristics, and obtain the low-voltage side phase loss abnormal signal; A preliminary determination module is used to calculate the amplitude ratio of each phase voltage according to the abnormal phase loss signal on the low-voltage side, and compare it with the preset phase loss model to determine whether the amplitude ratio of the low-voltage side voltage meets the phase loss condition on the high-voltage side, and obtain preliminary phase loss determination data; A phase loss determination module is used to calculate the high-voltage side characteristic deviation factor based on the preliminary phase loss determination data, and compare it with the preset phase loss model to determine whether there is a phase loss fault on the high-voltage side and obtain a phase loss determination result; The alarm module is used to determine the fault impact range based on the phase loss judgment result and the distribution network topology information, generate a phase loss fault signal, and send it to the maintenance end.

2. The automatic determination and maintenance system for the phase loss fault on the high-voltage side of a transformer according to claim 1 is characterized in that: The voltage characteristic module comprises: The effective value calculation unit is used to perform a square operation on the instantaneous voltage data collected on the low-voltage side to obtain square voltage data; accumulate the square voltage data within a preset time length, and then take the average value to obtain mean square voltage data; perform a square root operation on the mean square voltage data to obtain effective value data of the three-phase voltage on the low-voltage side; The phase difference calculation unit is used to convert the effective value data to obtain the fundamental phase data of the three-phase voltage; the phase difference data is obtained by calculating the difference between the fundamental phase data of the three-phase voltage.

3. The automatic determination and maintenance system for the phase loss fault on the high-voltage side of a transformer according to claim 2 is characterized in that: The phase-loss characteristic module comprises: The voltage amplitude relationship calculation unit is used to determine the maximum value, minimum value and intermediate value of the three-phase voltage on the low-voltage side according to the effective value data, and obtain the low-voltage side voltage sorting data; according to the low-voltage side voltage sorting data, determine the sum of the intermediate value of the three-phase voltage and the minimum value of the three-phase voltage, and compare it with the maximum value of the three-phase voltage to obtain the low-voltage side voltage amplitude relationship coefficient; The standard deviation calculation unit is used to calculate the mean of the effective values ​​of the three-phase voltages according to the effective value data to obtain the mean data, and calculate the deviation between the effective value data and the mean data of the three-phase voltages according to the mean data to obtain the deviation data; according to the deviation data, calculate the variance and standard deviation of the three-phase voltages to obtain the standard deviation data; The phase characteristic calculation unit is used to obtain phase characteristic data by calculating the absolute deviation value of the phase difference data of the three-phase voltage.

4. The automatic determination and maintenance system for the transformer high-voltage side phase loss fault according to claim 3 is characterized in that: The analysis module comprises: A low-voltage side reference data acquisition unit is used to extract the historical phase-loss low-voltage side voltage database of the corresponding transformer model and connection group according to a preset phase-loss model to obtain low-voltage side reference data; A low-voltage side characteristic deviation factor calculation unit is used to fuse the low-voltage side voltage change rate, the historical low-voltage side voltage change rate, the low-voltage side voltage standard deviation and the historical low-voltage side voltage standard deviation according to the phase loss characteristic data and the low-voltage side reference data to obtain the low-voltage side characteristic deviation factor; The characteristic analysis unit is used to determine whether the three-phase voltage on the low-voltage side meets the phase loss fault characteristics based on the low-voltage side characteristic deviation factor and the preset low-voltage side deviation threshold. When the result is yes, a low-voltage side phase loss abnormal signal is generated.

5. The automatic determination and maintenance system for the transformer high-voltage side phase loss fault according to claim 4 is characterized in that: The preliminary determination module comprises: The amplitude ratio calculation unit is used to obtain the total voltage data by calculating the sum of the three-phase voltage effective value data; according to the total voltage data, the amplitude ratios of the three-phase voltage effective value data and the total voltage data are calculated respectively to obtain the three-phase amplitude ratio data set; The preliminary phase loss judgment unit is used to extract the low-voltage side amplitude ratio corresponding to the high-voltage side phase loss condition according to a preset phase loss model, and obtain a phase loss amplitude ratio data set; based on the three-phase amplitude ratio data set and the phase loss amplitude ratio data set, it is judged whether the three-phase voltage amplitude ratio meets the high-voltage side phase loss condition. When the result is yes, the preliminary phase loss judgment data is obtained.

6. The automatic determination and maintenance system for the phase loss fault on the high-voltage side of a transformer according to claim 5 is characterized in that: The phase loss determination module comprises: The high-voltage side data acquisition unit is used to collect the voltage, current and power of the current high-voltage side of the transformer to obtain a real-time high-voltage side data set; A high-voltage side parameter data acquisition unit is used to extract a historical phase-loss high-voltage side database of a corresponding transformer model and connection group according to a preset phase-loss model to obtain high-voltage side reference data; A high-voltage side characteristic deviation factor calculation unit, used for calculating a high-voltage side characteristic deviation factor according to a real-time high-voltage side data set and high-voltage side reference data; The phase loss determination unit is used to determine whether there is a phase loss fault on the high-voltage side according to the high-voltage side characteristic deviation factor and a preset high-voltage side deviation threshold, and when the result is yes, a phase loss determination result is generated.

7. The automatic determination and maintenance system for transformer high-voltage side phase loss fault according to claim 6 is characterized in that: The preset phase-loss model includes: Historical phase-loss low-voltage side voltage database, used to store the effective value, amplitude ratio and phase difference of the three-phase voltage on the low-voltage side during historical phase-loss faults; The historical phase-loss high-voltage side database is used to store the voltage RMS value, current value and power value before and after the phase-loss on the high-voltage side during historical phase-loss faults; The historical phase loss condition classification database is used to store historical phase loss fault types and their data.

8. The automatic determination and maintenance system for the transformer high-voltage side phase loss fault according to claim 7 is characterized in that: The historical phase-missing low-voltage side voltage database includes: Collect the three-phase voltage on the low-voltage side when the transformer phase failure occurs, and obtain the historical low-voltage side voltage effective value data; According to the historical RMS voltage data of the low-voltage side, the amplitude ratio of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated to obtain the historical phase failure voltage ratio range; According to the historical RMS voltage data of the low-voltage side, the phase difference of the three-phase voltage on the low-voltage side when the phase failure occurs is calculated, and the historical phase failure phase angle variation range is obtained.

9. The automatic determination and maintenance system for transformer high-voltage side phase loss fault according to claim 8 is characterized in that: The historical phase-loss high-voltage side database includes: Collect the effective value of the high-voltage side voltage before and after the phase failure occurs, and obtain the historical effective value data of the high-voltage side voltage; Collect the high-voltage side current values ​​before and after the phase failure occurs to obtain historical high-voltage side current value data; The high-voltage side power values ​​before and after the phase failure occurs are collected to obtain historical high-voltage side power value data.

10. The automatic determination and maintenance system for transformer high-voltage side phase loss fault according to claim 9 is characterized in that: The historical phase-loss condition classification database includes: According to the transformer model and connection group, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the connection type data; According to the different phase missing faults on the high-voltage side, the historical phase missing low-voltage side voltage data and the historical phase missing high-voltage side voltage data are classified to obtain the phase missing type data; According to the load conditions, the historical phase-loss low-voltage side voltage data and the historical phase-loss high-voltage side voltage data are classified to obtain the load type data.

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