CN117849691B - Multi-dimensional collaborative operation monitoring and early warning system and method for capacitive voltage transformer - Google Patents
Multi-dimensional collaborative operation monitoring and early warning system and method for capacitive voltage transformer Download PDFInfo
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Abstract
The invention belongs to the technical field of power engineering, and discloses a multi-dimensional collaborative operation monitoring and early warning system and method for a capacitive voltage transformer, wherein the method senses the operation state of a transformer substation according to multi-dimensional operation data of the capacitive voltage transformer, and matches voltage measurement data, fault recording data and switch position information with a breaker, the capacitive voltage transformer and a current transformer in a primary operation diagram of the transformer substation according to different attributes of the data, and inverts the real-time primary operation mode of the transformer substation according to the fault recording data and the switch position information; setting a monitoring threshold according to different homologous attributes of the capacitive voltage transformer, and differentially combining the operation states of the capacitive voltage transformer; and according to the fusion judgment of the voltage measurement data and the fault recording data, the capacitor voltage transformer corresponding to the abnormal voltage measurement data and the fault recording data exists in early warning, the abnormal reason of the capacitor voltage transformer is diagnosed, the accuracy of abnormality diagnosis is improved, and the false alarm rate is reduced.
Description
Technical Field
The invention relates to the technical field of power data monitoring and diagnosis, in particular to a multi-dimensional cooperative operation monitoring and early warning system and method for a capacitive voltage transformer.
Background
A Capacitive Voltage Transformer (CVT) is an important power device of a substation, and mainly provides a voltage signal for a measurement and relay protection device. The capacitive voltage transformer is widely applied to a high-voltage system due to the advantages of good insulativity, economy, anti-ferroresonance and the like, and the metering performance of the capacitive voltage transformer can be gradually reduced due to the influence of factors such as temperature, electromagnetic field and the like in the long-term operation process, so that the measurement error is changed. Therefore, it is necessary to digitally monitor the operation state of the capacitive voltage transformer, so as to ensure that the measurement error meets the related precision requirement.
The existing online detection method is generally based on inter-phase comparison of voltage values of the monitoring capacitor voltage transformer, mapping errors exist in background data in the transmission process, accuracy of the monitoring data is affected, and the method cannot cope with complex and variable running conditions of a power system.
Disclosure of Invention
In order to eliminate the defect of low accuracy of a single data source, the invention provides a multi-dimensional collaborative capacitive voltage transformer operation monitoring and early warning system and method, which are used for guiding the capacitive voltage transformer operation monitoring work and ensuring the safe, stable and economic operation of a power system.
The technical scheme adopted by the invention is as follows: a multi-dimensional cooperative operation monitoring and early warning method for a capacitive voltage transformer comprises the following steps:
step one, acquiring multidimensional operation data of a capacitive voltage transformer in real time, wherein the multidimensional operation data comprises voltage measurement data, fault recording data, switch position information and primary operation diagram switch position information of a transformer substation of a power system, and performing noise reduction treatment on the voltage measurement data to obtain noise-reduced voltage measurement data;
sensing the operation state of the transformer substation according to the multidimensional operation data of the capacitive voltage transformer, matching the voltage measurement data, fault recording data and switch position information with a breaker, the capacitive voltage transformer and a current transformer in a primary operation diagram of the transformer substation according to different attributes of the data, inverting the real-time primary operation mode of the transformer substation according to the fault recording data and the switch position information, and classifying the fault recording data and the voltage measurement data according to the homology attributes of measurement nodes, wherein the fault recording data and the voltage measurement data are classified into direct homology, alternate homology and pressure ratio homology;
Step three, setting monitoring threshold values according to different homologous attributes of the capacitive voltage transformer, and differentially combining the monitoring operation states of the capacitive voltage transformer;
And fourthly, judging and early warning the existence of the capacitive voltage transformer corresponding to the abnormal voltage measurement data and the fault recording data according to the fusion of the voltage measurement data and the fault recording data, and diagnosing the abnormal reason of the capacitive voltage transformer.
Further preferably, in the third step, setting the monitoring threshold according to different homology attributes of the capacitive voltage transformer includes: respectively setting abnormal early warning thresholds of direct homologous, interphase homologous and voltage ratio homologous capacitive voltage transformers;
For direct homology, characterizing the same two same-phase other capacitive voltage transformer voltage measurement data anomaly pre-warning threshold ERR 1ph on different measurement nodes with electrical connections: Wherein, the method comprises the steps of, wherein, 、Respectively measuring errors of voltages of two capacitive voltage transformers;
for interphase homology, representing three-phase imbalance early warning threshold values of voltage correlation relations of three-phase capacitive voltage transformers of same measuring node ：
，
Wherein UA, UB , UC are A, B, C phase voltage measurement data of the same node after noise reduction treatment,For root mean square values of the three-phase voltage measurement data during the monitoring period,、、The voltage measurement deviation of the A, B, C-phase capacitive voltage transformer is respectively;
For interphase homology, representing three-phase unbalance degree early warning threshold value of voltage correlation relationship of three-phase capacitive voltage transformers of the same measuring node in ten monitoring periods ：
，
Wherein UA i ,UBi ,UCi is A, B, C phase voltage measurement data of the same node after noise reduction treatment in a monitoring period i, i is a monitoring period ordinal number,Is the root mean square value of UA i ,UBi ,UCi,、、The voltage measurement deviation of the A, B, C-phase capacitive voltage transformer is respectively;
For voltage comparison homology, the early warning threshold value of the correlation relation of the measured voltages of the same capacitive voltage transformers on the measuring nodes with different voltage classes is represented ：
，
Wherein U AH、UBH、UCH is A, B, C phase high voltage side measured voltage value, U AL、UBL、UCL is A, B, C phase low voltage side measured voltage value,、The voltage measurement errors of the high-voltage side capacitive voltage transformer and the low-voltage side capacitive voltage transformer are respectively measured.
Specifically, the second step includes:
Matching and corresponding the voltage channel waveform of the fault wave recording data with a capacitive voltage transformer in a primary operation diagram of the transformer substation according to the switch position information, and matching and corresponding the voltage measurement data with the capacitive voltage transformer in the primary operation diagram of the transformer substation;
matching and corresponding the switch position information with a breaker in a primary operation diagram of the transformer substation;
matching the fault recording data with corresponding breaker ledger and position information;
Based on the principle that the sum of primary current vectors of the same bus in fault wave recording data is zero, the ratio of the high voltage side and the low voltage side of the transformer is consistent with the transformation ratio, the real-time primary operation mode of the transformer substation is inverted and verified.
More specifically, based on the principle that the sum of vector of primary current of the same bus in fault wave recording data is zero, and the ratio of the high voltage side and the low voltage side of the transformer is consistent with the transformation ratio, inverting and verifying the real-time primary operation mode of the transformer substation comprises the following steps:
Classifying fault wave recording data and voltage measurement data according to the homology attribute of the measurement nodes: the voltage measurement data of the same capacitive voltage transformer on different measurement nodes with electric connection are directly homologous, namely the voltage values measured by the capacitive voltage transformers are equal, and the data errors only come from the measurement errors of the capacitive voltage transformers; the voltage measurement data of different phase capacitive voltage transformers on the same measurement node are phase-to-phase homology, namely, three-phase voltage dynamic balance measured by the capacitive voltage transformers, the data error is derived from the measurement error of the capacitive voltage transformers and the phase-to-phase voltage difference of the power grid, and the phase-to-phase voltage difference of the power grid of the same transformer substation is kept consistent at the same moment; the voltage measurement data of the same capacitive voltage transformer on different voltage class measurement nodes are of the same voltage ratio, namely, the voltage ratios of different voltage classes measured by the capacitive voltage transformer are consistent with the operation voltage ratio of the transformer, and the data errors are derived from the measurement errors of the capacitive voltage transformer and the voltage ratio errors of the transformer at different voltage classes.
In the third step, when the voltage of the capacitive voltage transformer is monitored based on fault recording data, fault recording monitoring voltage errors caused by external faults, power system disturbance and operation mode change are eliminated, and the following conditions are satisfied: Collecting voltage values of A, B, C three-phase capacitive voltage transformers in fault wave recording; no voltage values are recorded for the unsatisfactory fault log waveform segments, wherein And f c is the fault record sampling rate, and f 0 is the operating frequency of the power system.
Further preferably, in the fourth step, the voltage measurement data and the fault recording data use the same voltage abnormality early warning threshold, the switch position information changes, and three kinds of homology relations of direct homology, interphase homology and voltage ratio homology of different capacitive voltage transformers are rechecked.
Preferably, in the fourth step, when the fault recording data is greater than the preset early warning threshold, the capacitive voltage transformer corresponding to the early warning recording channel is abnormal; when the voltage measurement data is found to be larger than the set early warning threshold value, the background starts fault recording of the capacitive voltage transformer, the accuracy of the voltage measurement data is checked according to the fault recording data, and the running state of the capacitive voltage transformer is judged.
Further preferably, in the fourth step, the process of diagnosing the cause of the abnormality of the capacitive voltage transformer specifically includes: collecting typical defects or voltage measurement data errors of a capacitive voltage transformer, including secondary winding defects, primary winding defects, body insulation faults and data transmission mapping errors, and forming a capacitive voltage transformer defect characteristic data set; carrying out abnormal data fusion and defect characteristic extraction on the voltage measurement data and the fault recording data after the noise reduction treatment to obtain a fault characteristic data set for removing the influence of voltage fluctuation of the power system; selecting a supervised learning algorithm model to fit a fault characteristic data set, training and optimally monitoring the fault characteristics to obtain an abnormal capacitance type voltage transformer diagnosis model; and inputting the real-time monitoring data into an abnormal capacitive voltage transformer diagnosis model to diagnose the cause of the abnormality of the capacitive voltage transformer.
The invention provides a multi-dimensional cooperative operation monitoring and early warning system of a capacitive voltage transformer, which comprises the following components: the system comprises a real-time monitoring module, an operation sensing module, a data fusion module and a state early warning module, wherein the real-time monitoring module is used for collecting, transmitting and storing multidimensional operation data of a capacitive voltage transformer of a power system in real time; the real-time monitoring module is in communication connection with the operation sensing module; the operation sensing module reconstructs a primary operation mode of the transformer substation based on the multidimensional operation data of the capacitive voltage transformer to obtain a real-time primary operation mode of the transformer substation; the operation sensing module is in communication connection with the data fusion module, and the data fusion module updates the node connection relation according to a real-time one-time operation mode of the transformer substation, and performs topology matching on voltage measurement data, fault recording data and switch position information and a transformer, a breaker, a current transformer and a capacitive voltage transformer of the transformer substation; the data fusion module is in communication connection with the state early warning module, and the state early warning module carries out early warning on the abnormal capacitance type voltage transformer.
Further preferably, the multidimensional operation data of the capacitive voltage transformer includes: real-time voltage measurement data and switch position information of different nodes of the transformer substation are obtained through a power grid operation scheduling system; real-time fault wave recording data obtained by a power grid fault wave recording master station; a primary operation diagram of the transformer substation is acquired through a power grid production management and control system; the fault recording data are measured through the capacitive voltage transformer protection secondary winding and transmitted to the power grid fault recording master station, and the voltage measurement data are measured through the capacitive voltage transformer measurement secondary winding and transmitted to the power grid operation scheduling system.
Further preferably, the noise reduction processing for the voltage measurement data includes: according to wavelet multi-resolution analysis, coiflet layers of wavelet are selected as wavelet substrates, 5 layers of wavelet decomposition and quantization threshold are carried out on voltage measurement data, a soft threshold fitting method is adopted for the quantization threshold selection, a soft threshold noise reduction method is utilized for decoupling wavelet decomposition factors, finally, the 5 th layer of low-frequency factors and the 1 st-5 th layer of high-frequency factors subjected to threshold quantization are combined, inverse wavelet transformation is reconstructed, and noise-reduced voltage measurement data are obtained.
According to the method, the operation state of the transformer substation is perceived according to the multidimensional operation data of the capacitive voltage transformer, voltage measurement data, fault recording data and switch position information are matched with a breaker, the capacitive voltage transformer and a current transformer in a primary operation diagram of the transformer substation according to different attributes of the data, and a real-time primary operation mode of the transformer substation is inverted according to the fault recording data and the switch position information; setting a monitoring threshold according to different homologous attributes of the capacitive voltage transformer, and differentially combining the operation states of the capacitive voltage transformer; the method has the advantages that the capacitor type voltage transformer corresponding to the abnormal voltage measurement data and the fault wave recording data is judged and early-warned according to the fusion of the voltage measurement data and the fault wave recording data, the abnormal reasons of the capacitor type voltage transformer are diagnosed, the protection winding and the measuring winding of the capacitor type voltage transformer are monitored in a multi-element mode, the real-time performance of the voltage measurement data and the advantage complementation of the fault wave recording accuracy are achieved, the accuracy of the abnormality diagnosis is improved, and the false alarm rate is reduced.
Drawings
Fig. 1 is a schematic diagram of a multi-dimensional collaborative operation monitoring and early warning system of a capacitive voltage transformer.
Fig. 2 is a flow chart of a method for monitoring and early warning of the multidimensional collaborative operation of the capacitive voltage transformer.
Detailed Description
The invention is further elucidated in detail below with reference to the drawings and the examples.
As shown in fig. 1, the multi-dimensional collaborative operation monitoring and early warning system of the capacitive voltage transformer comprises a real-time monitoring module, an operation sensing module, a data fusion module and a state early warning module, wherein the real-time monitoring module is used for collecting, transmitting and storing multi-dimensional operation data of the capacitive voltage transformer of the power system in real time; the real-time monitoring module is in communication connection with the operation sensing module; the operation sensing module reconstructs a primary operation mode of the transformer substation based on the multidimensional operation data of the capacitive voltage transformer to obtain a real-time primary operation mode of the transformer substation; the operation sensing module is in communication connection with the data fusion module, and the data fusion module updates the node connection relation according to a real-time one-time operation mode of the transformer substation, and performs topology matching on voltage measurement data, fault recording data, switch position information and power equipment such as a transformer, a circuit breaker, a current transformer, a capacitive voltage transformer and the like of the transformer substation; the data fusion module is in communication connection with the state early warning module, and the state early warning module carries out early warning on the abnormal capacitance type voltage transformer.
The multidimensional operation data of the capacitive voltage transformer comprises: real-time voltage measurement data and switch position information of different nodes of the transformer substation are obtained through a power grid operation scheduling system; real-time fault wave recording data obtained by a power grid fault wave recording master station; a primary operation diagram of the transformer substation is acquired through a power grid production management and control system; the fault recording data are measured through the capacitive voltage transformer protection secondary winding and transmitted to the power grid fault recording master station, and the voltage measurement data are measured through the capacitive voltage transformer measurement secondary winding and transmitted to the power grid operation scheduling system.
The voltage measurement data mapping times are more, the data volume is large, and uncertainty can exist, so the noise reduction processing of the voltage measurement data comprises the following steps: according to wavelet multi-resolution analysis, coiflet layers of wavelet are selected as wavelet substrates, 5 layers of wavelet decomposition and quantization threshold are carried out on voltage measurement data, a soft threshold fitting method is adopted for the quantization threshold selection, a soft threshold noise reduction method is utilized for decoupling wavelet decomposition factors, finally, the 5th layer of low-frequency factors and the 1 st-5 th layer of high-frequency factors subjected to threshold quantization are combined, inverse wavelet transformation is reconstructed, and noise-reduced voltage measurement data are obtained.
Referring to fig. 2, a multi-dimensional cooperative operation monitoring and early warning method for a capacitive voltage transformer comprises the following steps:
step one, acquiring multidimensional operation data of a capacitive voltage transformer in real time, wherein the multidimensional operation data comprises voltage measurement data, fault recording data, switch position information and primary operation diagram switch position information of a transformer substation of a power system, and performing noise reduction treatment on the voltage measurement data to obtain noise-reduced voltage measurement data;
Sensing the operation state of the transformer substation according to the multidimensional operation data of the capacitive voltage transformer: according to different attributes of the data, matching the voltage measurement data, fault recording data and switch position information with a circuit breaker, a capacitive voltage transformer and a current transformer in a primary operation diagram of the transformer substation, inverting the real-time primary operation mode of the transformer substation according to the fault recording data and the switch position information, and classifying the fault recording data and the voltage measurement data according to the homology attribute of a measurement node, wherein the fault recording data and the voltage measurement data are classified into direct homology, alternate homology and pressure ratio homology;
Step three, setting monitoring threshold values according to different homologous attributes of the capacitive voltage transformer, and differentially combining the monitoring operation states of the capacitive voltage transformer;
And fourthly, judging and early warning the existence of the capacitive voltage transformer corresponding to the abnormal voltage measurement data and the fault recording data according to the fusion of the voltage measurement data and the fault recording data, and diagnosing the abnormal reason of the capacitive voltage transformer.
Specifically, the second step includes:
Matching and corresponding the voltage channel waveform of the fault wave recording data with a capacitive voltage transformer in a primary operation diagram of the transformer substation according to the switch position information, and matching and corresponding the voltage measurement data with the capacitive voltage transformer in the primary operation diagram of the transformer substation;
matching and corresponding the switch position information with a breaker in a primary operation diagram of the transformer substation;
matching the fault recording data with corresponding breaker ledger and position information;
Based on the principle that the sum of primary current vectors of the same bus in fault wave recording data is zero, the ratio of the high voltage side and the low voltage side of the transformer is consistent with the transformation ratio, the real-time primary operation mode of the transformer substation is inverted and verified.
More specifically, based on the principle that the sum of vector of primary current of the same bus in fault wave recording data is zero, and the ratio of the high voltage side and the low voltage side of the transformer is consistent with the transformation ratio, inverting and verifying the real-time primary operation mode of the transformer substation comprises the following steps:
Classifying fault wave recording data and voltage measurement data according to the homology attribute of the measurement nodes: the voltage measurement data of the same capacitive voltage transformer on different measurement nodes with electric connection are directly homologous, namely the voltage values measured by the capacitive voltage transformers are equal, and the data errors only come from the measurement errors of the capacitive voltage transformers; the voltage measurement data of different phase capacitive voltage transformers on the same measurement node are phase-to-phase homology, namely, three-phase voltage dynamic balance measured by the capacitive voltage transformers, the data error is derived from the measurement error of the capacitive voltage transformers and the phase-to-phase voltage difference of the power grid, and the phase-to-phase voltage difference of the power grid of the same transformer substation is kept consistent at the same moment; the voltage measurement data of the same capacitive voltage transformer on different voltage class measurement nodes are of the same voltage ratio, namely, the voltage ratios of different voltage classes measured by the capacitive voltage transformer are consistent with the operation voltage ratio of the transformer, and the data errors are derived from the measurement errors of the capacitive voltage transformer and the voltage ratio errors of the transformer at different voltage classes.
In the third step, setting the monitoring threshold according to different homology attributes of the capacitive voltage transformer includes: and respectively setting abnormal early warning thresholds of direct homologous, interphase homologous and voltage ratio homologous capacitive voltage transformers.
For direct homology, characterizing the same two same-phase other capacitive voltage transformer voltage measurement data anomaly pre-warning threshold ERR 1ph on different measurement nodes with electrical connections: Wherein, the method comprises the steps of, wherein, 、The voltage measurement errors of the two capacitive voltage transformers are respectively.
For interphase homology, representing three-phase imbalance early warning threshold values of voltage correlation relations of three-phase capacitive voltage transformers of same measuring node：
，
Wherein UA, UB , UC are A, B, C phase voltage measurement data of the same node after noise reduction treatment,For root mean square values of the three-phase voltage measurement data during the monitoring period,、、The voltage measurement deviation of the A, B, C-phase capacitive voltage transformer is respectively determined.
For interphase homology, representing three-phase unbalance degree early warning threshold value of voltage correlation relationship of three-phase capacitive voltage transformers of the same measuring node in ten monitoring periods：
，
Wherein UA i ,UBi ,UCi is A, B, C phase voltage measurement data of the same node after noise reduction treatment in a monitoring period i, i is a monitoring period ordinal number,Is the root mean square value of UA i ,UBi ,UCi,、、The voltage measurement deviation of the A, B, C-phase capacitive voltage transformer is respectively determined.
For voltage comparison homology, the early warning threshold value of the correlation relation of the measured voltages of the same capacitive voltage transformers on the measuring nodes with different voltage classes is represented：
，
Wherein U AH、UBH、UCH is A, B, C phase high voltage side measured voltage value, U AL、UBL、UCL is A, B, C phase low voltage side measured voltage value,、The voltage measurement errors of the high-voltage side capacitive voltage transformer and the low-voltage side capacitive voltage transformer are respectively measured.
In the third step, when the voltage of the capacitive voltage transformer is monitored based on fault recording data, fault recording monitoring voltage errors caused by external faults, power system disturbance and operation mode change are eliminated, and the following conditions are satisfied: Collecting voltage values of A, B, C three-phase capacitive voltage transformers in fault wave recording; no voltage values are recorded for the unsatisfactory fault log waveform segments, wherein And f c is the fault record sampling rate, and f 0 is the operating frequency of the power system.
When the voltage is measured, taking the average value of the three voltage measured values in the monitoring period as voltage measured data according to the three voltage measured values as a monitoring period.
And screening the voltage channels for fault recording data, calculating the voltage values of the three-phase voltage channels according to the power frequency period, taking the voltage average value as fault recording voltage monitoring data when the voltage change rate of each phase of voltage in five continuous periods is less than 1% of the voltage average value, and removing the corresponding fault recording file when the voltage change rate in five continuous periods is greater than 1% of the voltage average value.
In the fourth step, the same voltage abnormality early warning threshold value is used for the voltage measurement data and the fault recording data, the switch position information is changed, and three kinds of homology relations of direct homology, interphase homology and voltage ratio homology of different capacitive voltage transformers are rechecked.
In the fourth step, when the fault recording data is greater than a preset early warning threshold value, the capacitive voltage transformer corresponding to the early warning recording channel is abnormal; when the voltage measurement data is found to be larger than the set early warning threshold value, the background starts fault recording of the capacitive voltage transformer, the accuracy of the voltage measurement data is checked according to the fault recording data, and the running state of the capacitive voltage transformer is judged.
In the fourth step, the process of diagnosing the cause of the abnormality of the capacitive voltage transformer specifically includes: collecting typical defects or voltage measurement data errors of a capacitive voltage transformer, including secondary winding defects, primary winding defects, body insulation faults and data transmission mapping errors, and forming a capacitive voltage transformer defect characteristic data set; carrying out abnormal data fusion and defect characteristic extraction on the voltage measurement data and the fault recording data after the noise reduction treatment to obtain a fault characteristic data set for removing the influence of voltage fluctuation of the power system; selecting a supervised learning algorithm model to fit a fault characteristic data set, training and optimally monitoring the fault characteristics to obtain an abnormal capacitance type voltage transformer diagnosis model; and inputting the real-time monitoring data into an abnormal capacitive voltage transformer diagnosis model to diagnose the cause of the abnormality of the capacitive voltage transformer.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. A multi-dimensional cooperative operation monitoring and early warning method for a capacitive voltage transformer is characterized by comprising the following steps:
step one, acquiring multidimensional operation data of a capacitive voltage transformer in real time, wherein the multidimensional operation data comprises voltage measurement data, fault recording data, switch position information and primary operation diagram switch position information of a transformer substation of a power system, and performing noise reduction treatment on the voltage measurement data to obtain noise-reduced voltage measurement data;
Sensing the operation state of the transformer substation according to the multidimensional operation data of the capacitive voltage transformer: according to different attributes of the data, matching the voltage measurement data, fault recording data and switch position information with a circuit breaker, a capacitive voltage transformer and a current transformer in a primary operation diagram of the transformer substation, inverting the real-time primary operation mode of the transformer substation according to the fault recording data and the switch position information, and classifying the fault recording data and the voltage measurement data according to the homology attribute of a measurement node, wherein the fault recording data and the voltage measurement data are classified into direct homology, alternate homology and pressure ratio homology;
Step three, setting monitoring threshold values according to different homologous attributes of the capacitive voltage transformer, and differentially combining the monitoring operation states of the capacitive voltage transformer;
Step four, judging and early warning the existence of the capacitive voltage transformer corresponding to the abnormal voltage measurement data and the fault recording data according to the fusion of the voltage measurement data and the fault recording data, and diagnosing the abnormal reason of the capacitive voltage transformer;
The second step comprises the following steps:
Matching and corresponding the voltage channel waveform of the fault wave recording data with a capacitive voltage transformer in a primary operation diagram of the transformer substation according to the switch position information, and matching and corresponding the voltage measurement data with the capacitive voltage transformer in the primary operation diagram of the transformer substation;
matching and corresponding the switch position information with a breaker in a primary operation diagram of the transformer substation;
matching the fault recording data with corresponding breaker ledger and position information;
Based on the principle that the sum of primary current vectors of the same bus in fault wave recording data is zero, the ratio of the high voltage side and the low voltage side of the transformer is consistent with the transformation ratio, inverting and verifying the real-time primary operation mode of the transformer substation comprises the following steps:
Classifying fault wave recording data and voltage measurement data according to the homology attribute of the measurement nodes: the voltage measurement data of the same capacitive voltage transformer on different measurement nodes with electric connection are directly homologous, namely the voltage values measured by the capacitive voltage transformers are equal, and the data errors only come from the measurement errors of the capacitive voltage transformers; the voltage measurement data of different phase capacitive voltage transformers on the same measurement node are phase-to-phase homology, namely, three-phase voltage dynamic balance measured by the capacitive voltage transformers, the data error is derived from the measurement error of the capacitive voltage transformers and the phase-to-phase voltage difference of the power grid, and the phase-to-phase voltage difference of the power grid of the same transformer substation is kept consistent at the same moment; the voltage measurement data of the same capacitive voltage transformer on different voltage class measurement nodes are of the same voltage ratio, namely, the voltage ratios of different voltage classes measured by the capacitive voltage transformer are consistent with the operation voltage ratio of the transformer, and the data errors are derived from the measurement errors of the capacitive voltage transformer and the voltage ratio errors of the transformer at different voltage classes;
In the third step, setting the monitoring threshold according to different homology attributes of the capacitive voltage transformer includes: respectively setting abnormal early warning thresholds of direct homologous, interphase homologous and voltage ratio homologous capacitive voltage transformers;
For direct homology, characterizing the same two same-phase other capacitive voltage transformer voltage measurement data anomaly pre-warning threshold ERR 1ph on different measurement nodes with electrical connections: Wherein/> 、/>Respectively measuring errors of voltages of two capacitive voltage transformers;
For interphase homology, representing three-phase unbalance degree early warning threshold value of voltage correlation relationship of three-phase capacitive voltage transformers of the same measuring node in ten monitoring periods ：
，
Wherein UA i ,UBi ,UCi is A, B, C phase voltage measurement data of the same node after noise reduction treatment in a monitoring period i, i is a monitoring period ordinal number,Is the root mean square value of UA i ,UBi ,UCi,/>、/>、/>The voltage measurement deviation of the A, B, C-phase capacitive voltage transformer is respectively;
For voltage comparison homology, the early warning threshold value of the correlation relation of the measured voltages of the same capacitive voltage transformers on the measuring nodes with different voltage classes is represented ：
，
Wherein U AH、UBH、UCH is A, B, C phase high voltage side measured voltage value, U AL、UBL、UCL is A, B, C phase low voltage side measured voltage value,、/>The voltage measurement errors of the high-voltage side capacitive voltage transformer and the low-voltage side capacitive voltage transformer are respectively measured;
In the fourth step, the same voltage abnormality early warning threshold value is used for the voltage measurement data and the fault recording data, the switch position information is changed, and three kinds of homology relations of direct homology, interphase homology and voltage ratio homology of different capacitance type voltage transformers are rechecked; when the fault recording data is larger than a set early warning threshold value, the capacitive voltage transformer corresponding to the early warning recording channel is abnormal; when the voltage measurement data is found to be larger than the set early warning threshold value, the background starts fault recording of the capacitive voltage transformer, the accuracy of the voltage measurement data is checked according to the fault recording data, and the running state of the capacitive voltage transformer is judged.
2. The method for monitoring and early warning of multi-dimensional cooperative operation of a capacitive voltage transformer according to claim 1, wherein in the third step, when monitoring the voltage of the capacitive voltage transformer based on fault recording data, the method is characterized in that: Collecting voltage values of A, B, C three-phase capacitive voltage transformers in fault wave recording; no voltage values are recorded for the failing recording waveform segments, where/> And f c is the fault record sampling rate, and f 0 is the operating frequency of the power system.
3. The method for monitoring and early warning of multi-dimensional collaborative operation of a capacitive voltage transformer according to claim 1, wherein in the fourth step, the process for diagnosing the cause of the abnormality of the capacitive voltage transformer is specifically as follows: collecting typical defects or voltage measurement data errors of a capacitive voltage transformer, including secondary winding defects, primary winding defects, body insulation faults and data transmission mapping errors, and forming a capacitive voltage transformer defect characteristic data set; carrying out abnormal data fusion and defect characteristic extraction on the voltage measurement data and the fault recording data after the noise reduction treatment to obtain a fault characteristic data set for removing the influence of voltage fluctuation of the power system; selecting a supervised learning algorithm model to fit a fault characteristic data set, training and optimally monitoring the fault characteristics to obtain an abnormal capacitance type voltage transformer diagnosis model; and inputting the real-time monitoring data into an abnormal capacitive voltage transformer diagnosis model to diagnose the cause of the abnormality of the capacitive voltage transformer.
4. The capacitive voltage transformer multidimensional collaborative operation monitoring and early warning system for realizing the capacitive voltage transformer multidimensional collaborative operation monitoring and early warning method according to any one of claims 1-3 is characterized by comprising a real-time monitoring module, an operation sensing module, a data fusion module and a state early warning module, wherein the real-time monitoring module is used for collecting, transmitting and storing the capacitive voltage transformer multidimensional operation data of a power system in real time; the real-time monitoring module is in communication connection with the operation sensing module; the operation sensing module reconstructs a primary operation mode of the transformer substation based on the multidimensional operation data of the capacitive voltage transformer to obtain a real-time primary operation mode of the transformer substation; the operation sensing module is in communication connection with the data fusion module, and the data fusion module updates the node connection relation according to a real-time one-time operation mode of the transformer substation, and performs topology matching on voltage measurement data, fault recording data and switch position information and a transformer, a breaker, a current transformer and a capacitive voltage transformer of the transformer substation; the data fusion module is in communication connection with the state early warning module, and the state early warning module carries out early warning on the abnormal capacitance type voltage transformer.
5. The capacitive voltage transformer multidimensional collaborative operation monitoring and early warning system according to claim 4, wherein the capacitive voltage transformer multidimensional operation data comprises: real-time voltage measurement data and switch position information of different nodes of the transformer substation are obtained through a power grid operation scheduling system; real-time fault wave recording data obtained by a power grid fault wave recording master station; a primary operation diagram of the transformer substation is acquired through a power grid production management and control system; the fault recording data are measured through the capacitive voltage transformer protection secondary winding and transmitted to the power grid fault recording master station, and the voltage measurement data are measured through the capacitive voltage transformer measurement secondary winding and transmitted to the power grid operation scheduling system.
6. The system of claim 4, wherein the noise reduction processing of the voltage measurement data comprises: according to wavelet multi-resolution analysis, coiflet layers of wavelet are selected as wavelet substrates, 5 layers of wavelet decomposition and quantization threshold are carried out on voltage measurement data, a soft threshold fitting method is adopted for the quantization threshold selection, a soft threshold noise reduction method is utilized for decoupling wavelet decomposition factors, finally, the 5th layer of low-frequency factors and the 1 st-5 th layer of high-frequency factors subjected to threshold quantization are combined, inverse wavelet transformation is reconstructed, and noise-reduced voltage measurement data are obtained.
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