CN113625058A - Early warning method and system for monitoring transformer bushing based on abnormal point group - Google Patents
Early warning method and system for monitoring transformer bushing based on abnormal point group Download PDFInfo
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- CN113625058A CN113625058A CN202110931922.4A CN202110931922A CN113625058A CN 113625058 A CN113625058 A CN 113625058A CN 202110931922 A CN202110931922 A CN 202110931922A CN 113625058 A CN113625058 A CN 113625058A
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
- G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
- G01R27/26—Measuring inductance or capacitance; Measuring quality factor, e.g. by using the resonance method; Measuring loss factor; Measuring dielectric constants ; Measuring impedance or related variables
- G01R27/2688—Measuring quality factor or dielectric loss, e.g. loss angle, or power factor
- G01R27/2694—Measuring dielectric loss, e.g. loss angle, loss factor or power factor
Abstract
The application relates to the technical field of on-line monitoring and early warning of a power grid, and provides an early warning method and system for monitoring a transformer bushing based on abnormal point groups, wherein on-line monitoring data of a dielectric loss value of the transformer bushing is obtained by setting a basic threshold value of the dielectric loss value of the transformer bushing; judging abnormal data points, and dynamically adjusting data acquisition frequency after the abnormal data points are found; constructing a group to be detected; and monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, and judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer bushing and perform early warning. The early warning method and system based on abnormal point group monitoring transformer bushing provided by the application can reduce the false alarm condition generated by the operation fluctuation of the existing online monitoring device or the power system under the condition of not replacing the online monitoring device, and effectively improve the accuracy of early warning.
Description
Technical Field
The application relates to the technical field of online monitoring and early warning of a power grid, in particular to an early warning method and system for monitoring a transformer bushing based on abnormal point groups.
Background
The transformer bushing is a core device in the power system, and the safety and the stability of the transformer bushing are guaranteed to play a vital role in the power system. Therefore, in the actual use process, insulation monitoring needs to be carried out on the transformer bushing, and defects in the transformer bushing are warned in time.
The online monitoring data of the transformer bushing mainly depends on the insulation performance of the bushing, but is influenced by various environmental factors such as temperature, humidity and system operating voltage. At present, the national standard of China does not specify an early warning strategy for online monitoring of transformer bushing insulation, and only specifies an offline early warning standard in a preventive test procedure of power equipment.
The early warning strategies recommended by each transformer bushing monitoring manufacturer are different, the early warning threshold value is not sensitive enough, the condition of false alarm or missing alarm to a certain extent exists, the insulation defect of the transformer bushing cannot be found timely and accurately, the potential safety hazard is large, and the actual application requirement cannot be met.
Disclosure of Invention
In order to solve the above problem, a first aspect of the present application provides an early warning method for monitoring a transformer bushing based on an abnormal point group, which is characterized by comprising:
and acquiring a dielectric loss value basic threshold value and online monitoring data of the transformer bushing.
And comparing the on-line monitoring data with the dielectric loss value basic threshold value according to the dielectric loss value basic threshold value of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point.
And according to the preliminary data abnormal points, increasing the sampling frequency and shortening the sampling period within the range of the preliminary data abnormal points to obtain further data abnormal points, and constructing the group to be detected by using the further data abnormal points.
And monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer and perform early warning.
Optionally, the step of comparing the online monitoring data with the dielectric loss value basic threshold specifically includes: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
Optionally, the determining whether the group to be detected is abnormal according to the number of the further data abnormal points includes the following steps:
and setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers.
Using a numerical comparison method, if L is larger than M, the abnormal data points are detected to be abnormal; and if L is less than M, restoring the initial sampling frequency.
Optionally, the number P of data exception points for exiting the exception is also included.
And if the P is less than or equal to the L and less than or equal to the M, continuing to perform sampling analysis.
And if L is less than P, restoring the initial sampling frequency.
Optionally, the basic early warning threshold of the transformer bushing dielectric loss value is 0.5.
This application second aspect provides an early warning system based on unusual some crowd monitoring transformer bushing, the system includes: the device comprises an acquisition module, a preliminary data abnormal point module, a group to be detected module and an early warning module.
The acquisition module is used for acquiring the dielectric loss value basic threshold value and the online monitoring data of the transformer bushing.
And the preliminary data abnormal point module is used for comparing the on-line monitoring data with the dielectric loss value basic threshold value according to the dielectric loss value basic threshold value of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point.
And the group detection module is used for increasing sampling frequency and shortening sampling period within the range of the preliminary data abnormal points according to the preliminary data abnormal points to obtain further data abnormal points, and constructing a group to be detected by using the further data abnormal points.
The early warning module is used for monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer and carry out early warning.
Optionally, the step of comparing the online monitoring data with the dielectric loss value basic threshold specifically includes: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
Optionally, the determining whether the group to be detected is abnormal according to the number of the further data abnormal points includes the following steps:
and setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers.
Using a numerical comparison method, if L is larger than M, the abnormal data points are detected to be abnormal; and if L is less than M, restoring the initial sampling frequency.
Optionally, the number P of data exception points for exiting the exception is also included.
And if the P is less than or equal to the L and less than or equal to the M, continuing to perform sampling analysis.
And if L is less than P, restoring the initial sampling frequency.
Optionally, the basic early warning threshold of the transformer bushing dielectric loss value is 0.5.
The method comprises the steps of setting a basic threshold value of a transformer bushing dielectric loss value to obtain transformer bushing dielectric loss value on-line monitoring data; judging abnormal data points, and dynamically adjusting data acquisition frequency after the abnormal data points are found; constructing a group to be detected; and monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, and judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer bushing and perform early warning. According to the early warning method and system for monitoring the transformer bushing based on the abnormal point group, the false alarm condition generated by the operation fluctuation of the existing online monitoring device or the power system is reduced under the condition that the online monitoring device is not replaced, and the early warning accuracy is effectively improved.
Drawings
In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of an early warning method for monitoring a transformer bushing based on an abnormal point group according to an embodiment of the present application;
fig. 2 is a structural diagram of an early warning system for monitoring a transformer bushing based on an abnormal point group according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, a flowchart of an early warning method for monitoring a transformer based on an abnormal point group is provided in the embodiment of the present application.
A first aspect of an embodiment of the present application provides an early warning method for monitoring a transformer bushing based on an abnormal point group, including:
s101, obtaining a dielectric loss value basic threshold value and online monitoring data of the transformer bushing.
The threshold is set according to actual requirements, and in the embodiment of the application, the dielectric loss value basic threshold is 0.5.
And S102, comparing the on-line monitoring data with the dielectric loss value basic threshold according to the dielectric loss value basic threshold of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point.
The step of comparing the on-line monitoring data with the dielectric loss value basic threshold specifically comprises the following steps: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
Recording the dielectric loss value monitoring numerical value of the transformer bushing dielectric loss value on-line monitoring device in real time, when finding that the newly-added dielectric loss value monitoring numerical value exceeds a threshold value, regarding the point as an abnormal point, and sending the information of the point to a display end to remind monitoring personnel to pay attention.
S103, according to the preliminary data abnormal points, increasing sampling frequency and shortening sampling period in the range of the preliminary data abnormal points to obtain further data abnormal points, and constructing the group to be detected by using the further data abnormal points.
Changing the sampling frequency of the dielectric loss value of the transformer bushing of the abnormal point, shortening the sampling period, and acquiring more sampling points under the condition of unchanged time to form a group delta to be detected of each abnormal data point.
And S104, monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer bushing and perform early warning.
Wherein, the step of judging whether the group to be detected is abnormal according to the number of the further data abnormal points comprises the following steps:
setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers;
acquiring the number L of abnormal points in a group delta to be detected, and simultaneously setting a sensitivity value M and the number P of abnormal data points quitting according to the required sensitivity; and comparing L, M, P values.
And if L is larger than M, judging that the group delta to be detected is a data abnormal point group theta, recording and sending to the front end for early warning.
And if the P is less than or equal to the L and less than or equal to the M, judging that the group delta to be detected needs to be observed continuously, and performing one round of sampling analysis.
If L is less than P, judging that the group delta to be detected does not form a data abnormal point group, and recovering the sampling frequency as false alarm.
Example 1:
in the actual use process, firstly, the basic early warning threshold value of the transformer bushing dielectric loss value online monitoring device is set to be 0.5, the acquisition period T of the online monitoring device is 2h, the sampling frequency f is 2h, and the number c of sampling points is 1.
Recording the dielectric loss value monitoring value of the transformer bushing dielectric loss value on-line monitoring device in real time, comparing the dielectric loss value monitoring value with a basic early warning threshold value of 0.5, when newly-added dielectric loss value monitoring value exceeds the threshold value, regarding the point as a data abnormal point, and sending the information of the point to a display end to remind monitoring personnel to pay attention.
And changing the sampling frequency f of the transformer bushing dielectric loss value on-line monitoring device of the data abnormal point to be (1/12) h, changing the number c of the sampling points to be 24, and acquiring 24 values within 2 hours to form a data abnormal point detection group delta.
Acquiring the number Q of data abnormal points in a group delta to be detected, and simultaneously setting a sensitivity value M and the number P of exiting abnormal data points according to the required sensitivity; and comparing Q, M, P values;
if Q is larger than M, judging that the group delta to be detected is a data abnormal point group theta, recording and sending the data abnormal point group theta to a wire harness end, and early warning a monitoring person;
if P is not more than Q and not more than M, judging that the group delta to be detected needs to be observed continuously, and carrying out one-round sampling analysis;
if Q is less than P, judging that the group delta to be detected does not form a data abnormal point group, judging the data abnormal point group as false alarm, and recovering the sampling frequency.
The following takes an example of a 500kV2 # main transformer phase B of a 500kV substation of a certain power supply bureau, and the specific implementation manner is as follows.
Setting a basic early warning threshold value to be 0.5, setting a collection period T to be 2h, setting a sampling frequency f to be 2h, and setting the number c of sampling points to be 1. Meanwhile, the sensitivity value M is set to 6 and the number P of exit abnormal data points is set to 3 according to the sensitivity set by the requirement. For monitoring data from 15 o 'clock to 23 o' clock on x-day of year x of 20xx, see table 1, which is conventional monitoring data.
TABLE 1 conventional monitoring data
And at the moment of 20xx/x/x 19:00, finding data abnormality with the dielectric loss value exceeding the basic early warning threshold value of 0.5, changing the sampling frequency f of the transformer bushing dielectric loss value on-line monitoring device to be (1/6) h, changing the number c of sampling points to be 12, and collecting 12 values within 2 hours to form a data abnormality point to-be-detected group delta. And acquiring the number L of the abnormal points in the group delta to be detected as 2, and comparing L, M, P. The abnormal point detection group δ is shown in table 2, and table 2 shows the abnormal point detection group δ.
And comparing, wherein the number L of the abnormal points in the group delta to be detected is less than P, the group delta to be detected does not form a data abnormal point group, the group delta to be detected is regarded as false alarm, and the sampling frequency is recovered.
TABLE 2 anomaly detection group δ
According to the technical scheme, the early warning method for monitoring the transformer bushing based on the abnormal point group, which is provided by the embodiment of the application, comprises the steps of obtaining the dielectric loss value basic threshold value and the online monitoring data of the transformer bushing; comparing the on-line monitoring data with the dielectric loss value basic threshold according to the dielectric loss value basic threshold of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point; according to the preliminary data abnormal points, increasing sampling frequency and shortening sampling period within the range of the preliminary data abnormal points to obtain further data abnormal points, and constructing a group to be detected by using the further data abnormal points; and monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, and judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer bushing and perform early warning. According to the early warning method and system for monitoring the transformer bushing based on the abnormal point group, the false alarm condition caused by the operation fluctuation of the existing online monitoring device or the power system is reduced under the condition that the online monitoring device is not replaced, and the early warning accuracy is effectively improved.
Referring to fig. 2, a structural diagram of an early warning system for monitoring a transformer bushing based on an abnormal point group is provided in the embodiment of the present application.
A second aspect of the embodiments of the present application provides an early warning system for monitoring a transformer bushing based on an abnormal point group, the system including: the device comprises an acquisition module, a preliminary data abnormal point module, a group to be detected module and an early warning module.
The acquisition module is used for acquiring the dielectric loss value basic threshold value and the online monitoring data of the transformer bushing.
And the preliminary data abnormal point module is used for comparing the on-line monitoring data with the dielectric loss value basic threshold value according to the dielectric loss value basic threshold value of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point.
And the group detection module is used for increasing sampling frequency and shortening sampling period within the range of the preliminary data abnormal points according to the preliminary data abnormal points to obtain further data abnormal points, and constructing a group to be detected by using the further data abnormal points.
The early warning module is used for monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer and carry out early warning.
The step of comparing the on-line monitoring data with the dielectric loss value basic threshold specifically comprises the following steps: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
Wherein, the step of judging whether the group to be detected is abnormal according to the number of the further data abnormal points comprises the following steps:
and setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers.
Using a numerical comparison method, if L is larger than M, the abnormal data points are detected to be abnormal; and if L is less than M, restoring the initial sampling frequency.
In addition, the number P of abnormal data points for exiting the abnormality is also included.
And if the P is less than or equal to the L and less than or equal to the M, continuing to perform sampling analysis.
And if L is less than P, restoring the initial sampling frequency.
And the basic early warning threshold value of the dielectric loss value of the transformer bushing is 0.5.
Inputting a dielectric loss value basic threshold value and online monitoring data of a transformer bushing into the acquisition module, transmitting the dielectric loss value basic threshold value and the online monitoring data of the transformer bushing to the preliminary data abnormal point module by the acquisition module, and comparing the online monitoring data with the dielectric loss value basic threshold value to obtain a preliminary data abnormal point; the preliminary data abnormal point module transmits the preliminary data abnormal points to the group module to be detected, increases sampling frequency and shortens sampling period within the range of the preliminary data abnormal points according to the preliminary data abnormal points to obtain further data abnormal points, and constructs a group to be detected according to the further data abnormal points; and the group module to be detected transmits the group to be detected to the early warning module, and the early warning module monitors the number of further data abnormal points in the group to be detected by using a numerical comparison method, judges whether the group to be detected is abnormal according to the number of the further data abnormal points, judges the running state of the transformer bushing and performs early warning.
According to the technical scheme, the early warning method and the early warning system for monitoring the transformer bushing based on the abnormal point group, provided by the embodiment of the application, acquire the online monitoring data of the transformer by setting the basic threshold of the dielectric loss value of the transformer bushing; judging abnormal data points, and dynamically adjusting data acquisition frequency after the abnormal data points are found; constructing a group to be detected; and monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, and judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer bushing and perform early warning. According to the early warning method and system for monitoring the transformer bushing based on the abnormal point group, the false alarm condition generated by the operation fluctuation of the existing online monitoring device or the power system is reduced under the condition that the online monitoring device is not replaced, and the early warning accuracy is effectively improved.
The present application has been described in detail with reference to specific embodiments and illustrative examples, but the description is not intended to limit the application. Those skilled in the art will appreciate that various equivalent substitutions, modifications or improvements may be made to the presently disclosed embodiments and implementations thereof without departing from the spirit and scope of the present disclosure, and these fall within the scope of the present disclosure. The protection scope of this application is subject to the appended claims.
Claims (10)
1. An early warning method for monitoring a transformer bushing based on abnormal point groups is characterized by comprising the following steps:
acquiring a dielectric loss value basic threshold value and online monitoring data of a transformer bushing;
comparing the on-line monitoring data with the dielectric loss value basic threshold according to the dielectric loss value basic threshold of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point;
according to the preliminary data abnormal points, increasing sampling frequency and shortening sampling period within the range of the preliminary data abnormal points to obtain further data abnormal points, and constructing a group to be detected by using the further data abnormal points;
and monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the sleeve of the transformer and perform early warning.
2. The early warning method for monitoring the transformer bushing based on the abnormal point group as claimed in claim 1, wherein the step of comparing the on-line monitoring data with the dielectric loss value basic threshold specifically comprises: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
3. The early warning method for monitoring the transformer bushing based on the abnormal point group according to claim 1, wherein the step of judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points comprises the following steps:
setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers;
using a numerical comparison method, if L is larger than M, the abnormal data points are detected to be abnormal; and if L is less than M, restoring the initial sampling frequency.
4. The early warning method for monitoring the transformer bushing based on the abnormal point group according to claim 3, further comprising the number P of abnormal data points for exiting the abnormality;
if the P is not more than L and not more than M, continuing to perform sampling analysis;
and if L is less than P, restoring the initial sampling frequency.
5. The early warning method for monitoring the transformer bushing based on the abnormal point group as claimed in claim 1, wherein a basic early warning threshold value of the dielectric loss value of the transformer bushing is 0.5.
6. An early warning system for monitoring transformer bushings based on abnormal point groups, which is used for executing the early warning method for monitoring transformer bushings based on abnormal point groups as claimed in claims 1-5, and comprises: the system comprises an acquisition module, a preliminary data abnormal point module, a group to be detected module and an early warning module;
the acquisition module is used for acquiring the dielectric loss value basic threshold value and the online monitoring data of the transformer bushing;
the preliminary data abnormal point module is used for comparing the on-line monitoring data with the dielectric loss value basic threshold value according to the dielectric loss value basic threshold value of the transformer bushing and the on-line monitoring data to obtain a preliminary data abnormal point;
the group detection module is used for increasing sampling frequency and shortening sampling period within the range of the preliminary data abnormal points according to the preliminary data abnormal points to obtain further data abnormal points, and constructing a group to be detected by using the further data abnormal points;
the early warning module is used for monitoring the number of further data abnormal points in the group to be detected by using a numerical comparison method, judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points so as to judge the running state of the transformer and carry out early warning.
7. The early warning system for monitoring the transformer bushing based on the abnormal point group as claimed in claim 6, wherein the step of comparing the on-line monitoring data with the dielectric loss value basic threshold specifically comprises: and if the on-line monitoring data of the transformer bushing dielectric loss value is larger than the basic threshold value of the transformer bushing dielectric loss value, obtaining a preliminary abnormal data point.
8. The early warning system for monitoring the transformer bushing based on the abnormal point group as claimed in claim 6, wherein the step of judging whether the group to be detected is abnormal or not according to the number of the further data abnormal points comprises the following steps:
setting a sensitivity parameter M according to the required sensitivity, and counting the number L of the further data outliers;
using a numerical comparison method, if L is larger than M, the abnormal data points are detected to be abnormal; and if L is less than M, restoring the initial sampling frequency.
9. The early warning system for monitoring the transformer bushing based on the abnormal point group as claimed in claim 6, further comprising the number P of abnormal data points exiting the abnormality;
if the P is not more than L and not more than M, continuing to perform sampling analysis;
and if L is less than P, restoring the initial sampling frequency.
10. The early warning system for monitoring transformer bushings based on abnormal point groups as claimed in claim 6, wherein the basic early warning threshold value of the transformer bushing dielectric loss value is 0.5.
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| CN117110975A (en) * | 2023-10-23 | 2023-11-24 | 石家庄科林电力设计院有限公司 | Misalignment detection method and device for multipath electric energy metering device |
| CN117110975B (en) * | 2023-10-23 | 2024-02-09 | 石家庄科林电力设计院有限公司 | Misalignment detection method and device for multipath electric energy metering device |
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