CN112345972B - Power distribution network line transformation relation abnormity diagnosis method, device and system based on power failure event - Google Patents
Power distribution network line transformation relation abnormity diagnosis method, device and system based on power failure event Download PDFInfo
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Abstract
The invention discloses a power distribution network line transformation relation abnormity diagnosis method, device and system based on a power failure event, wherein the method comprises the steps of generating a historical power failure distribution transformer set based on acquired power data of a distribution transformer; acquiring a bus and a distribution transformer nearby based on longitude and latitude information of a power failure distribution transformer in the power failure distribution transformer set; calculating the related coefficient indexes of the power failure distribution transformer and the bus nearby to find out the suspected bus; screening all lines under suspected corresponding buses of the power failure distribution transformer; calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and searching for a power outage distribution transformer number duty ratio index threshold; and screening out suspected corresponding lines of the power outage distribution transformer based on the threshold value, and finding out the power outage distribution transformer with wrong line transformation relation and the suspected corresponding lines. The invention has simple calculation, can help operators to find abnormal line transformation relation distribution transformers in time and recommend the line to which the transformer belongs.
Description
Technical Field
The invention belongs to the field of medium-voltage distribution network line transformation relation abnormality diagnosis, and particularly relates to a distribution network line transformation relation abnormality diagnosis method, device and system based on a power failure event, which are suitable for a medium-voltage distribution network.
Background
The medium-voltage distribution network line transformation relationship is the relationship of mutual connection among the medium-voltage bus, the distribution transformer load, the interconnection switch and other devices, and describes the power supply path from the medium-voltage bus to the distribution transformer load. The manually maintained energy management system (Power Management System, PMS) mainly depends on the field investigation of basic staff, and due to the factors of complicated equipment, long time consumption, high investigation difficulty and the like, the correct medium-voltage distribution network line change relation is difficult to obtain, so that the actual field is inconsistent with the PMS line change relation, and further, the problems of high potential safety hazards of line overhaul, high calculation error of medium-voltage line loss rate, low reliability analysis accuracy and the like are caused, and the construction process of a first-class distribution network is severely restricted.
Therefore, the medium-voltage distribution network line transformation relation abnormity diagnosis method is an important research topic, and the research result can help operators to find out the line transformation relation mistake pair distribution transformer in time, recommend the suspected application specific line of the distribution transformer for the distribution transformer, and effectively tamp the network operation and maintenance account foundation.
Disclosure of Invention
Aiming at the problems, the invention provides a power distribution network line transformation relation abnormity diagnosis method, device and system based on a power failure event, which can be used for identifying the connection errors of the power distribution network line transformation relation of any scale and recommending correct connection lines.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
in a first aspect, the present invention provides a power distribution network cable change relationship anomaly diagnosis method based on a power outage event, including:
generating a historical power failure distribution transformer set based on the acquired power data of the distribution transformers;
acquiring voltage measurement data of a bus and a distribution transformer nearby the power failure distribution transformer and the bus nearby the power failure distribution transformer based on longitude and latitude information of the power failure distribution transformers in the power failure distribution transformer set;
calculating the related coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus;
screening all lines under suspected corresponding buses of the power failure distribution transformer;
Calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power outage distribution transformer number duty ratio index threshold;
and screening out suspected corresponding lines of the power failure distribution transformer based on the obtained threshold value, and finally finding out the power failure distribution transformer with wrong line transformation relation and the suspected corresponding lines.
Optionally, the method for generating the historical power outage distribution transformer set includes:
certain distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,...,p k,i ,...,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer;
if distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,...,p k,j ]0 or null, generating a distribution transformer M j Data segment [ i, …, j ]]For breaking fragments in power failure, distribution transformer M j Then the power failure distribution transformer;
based on the rule for screening the power outage distribution transformers, historical power outage distribution transformers are screened from the acquired power data of the distribution transformers, and a power outage distribution transformer set M= { M is generated 1 ,M 2 ,...,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
Optionally, the step of obtaining the voltage measurement data of the bus and the distribution transformer nearby and the bus nearby based on the longitude and latitude information of the power outage distribution transformer in the power outage distribution transformer set includes the following steps:
And calculating a bus set within a set threshold from the geographical range of the power failure distribution transformer based on longitude and latitude information of each distribution transformer in the power failure distribution transformer set, and acquiring voltage measurement data of the bus set and lower line statistics thereof.
Optionally, the method for searching the suspected bus comprises the following steps:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
and screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
Optionally, the calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, evaluating and seeking the power outage distribution transformer number duty ratio index threshold value includes the following steps:
calculating the power failure distribution transformer number ratio index P of all lines j The historical power failure distribution transformer number duty ratio index data set P is formed;
the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values P in the data set P j The corresponding distribution transformer belongs to the precision and recall ratio of the route;
calculating a derived index F1 based on the precision and recall j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
Optionally, the power failure distribution transformer number duty ratio index P j The calculation method of (1) is as follows:
for all lines under suspected bus in a certain area, calculating the number T of distribution transformers for power failure of each line under suspected bus j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j 。
Optionally, based on the obtained threshold value, the suspected line to be attributed to the power outage distribution transformer is screened out, and finally the power outage distribution transformer with the wrong line transformation relation and the suspected line to be attributed to the power outage distribution transformer are found out, including the following steps:
carrying out preset judging steps on all power-off distribution transformers and the wires under the buses nearby, and finally obtaining a power-off distribution transformer set, a power-off distribution transformer number proportion index data set of all wires under the buses nearby the power-off distribution transformers, a power-off distribution transformer number proportion index threshold value of all wires under the suspected buses, all distribution transformers with abnormal suspected wire transformation relations and suspected corresponding wires under the suspected buses;
the preset judging step comprises the following steps: if the suspected line under the bus of the power-off distribution transformer is in power-off in a typical time period, and the index value of the number of the distribution transformers in power-off is higher than the index threshold value of the number of the power-off distribution transformers, the power-off distribution transformer is judged to be a suspected line transformation relationship abnormal distribution transformer, otherwise, the power-off distribution transformer is judged to be a line transformation relationship normal distribution transformer.
In a second aspect, the present invention provides a power distribution network cable change relation abnormality diagnosis device based on a power outage event, including:
the generation unit is used for generating a historical power failure distribution transformer set based on the acquired power data of the distribution transformer;
the first calculation unit is used for obtaining the bus and the distribution transformer nearby and the voltage measurement data of the bus nearby based on the longitude and latitude information of the power failure distribution transformer in the power failure distribution transformer set;
the second calculation unit is used for calculating the correlation coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus which should be affiliated;
the first screening unit is used for screening all lines under the suspected corresponding bus of the power failure distribution transformer;
the third calculation unit is used for calculating the power failure distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power failure distribution transformer number duty ratio index threshold;
and the judging unit is used for screening out the suspected affiliated lines of the power failure distribution transformer based on the obtained threshold value, and finally finding out the power failure distribution transformer with wrong line transformation relation and the suspected affiliated lines thereof.
Optionally, the method for generating the historical power outage distribution transformer set includes:
Certain distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,...,p k,i ,...,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer;
if distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,...,p k,j ]0 or null, generating a distribution transformer M j Data segment [ i, …, j ]]For breaking fragments in power failure, distribution transformer M j Then the power failure distribution transformer;
based on the rule for screening the power outage distribution transformers, historical power outage distribution transformers are screened from the acquired power data of the distribution transformers, and a power outage distribution transformer set M= { M is generated 1 ,M 2 ,...,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
Optionally, the method for searching the suspected bus comprises the following steps:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
And screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
Optionally, the method for searching the suspected bus comprises the following steps:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
and screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
Optionally, the calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, evaluating and seeking a threshold value of the power outage distribution transformer number duty ratio index, includes the following steps:
calculating the power failure distribution transformer number ratio index P of all lines j The historical power failure distribution transformer number duty ratio index data set P is formed;
the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values P in the data set P j The corresponding distribution transformer belongs to the precision and recall ratio of the route;
based on the precision sumCalculating derived index F1 from recall ratio j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
Optionally, the power failure distribution transformer number duty ratio index P j The calculation method of (1) is as follows:
for all lines under suspected bus in a certain area, calculating the number T of distribution transformers for power failure of each line under suspected bus j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j 。
Optionally, based on the obtained threshold value, the suspected line to be attributed to the power outage distribution transformer is screened out, and finally the power outage distribution transformer with the wrong line transformation relation and the suspected line to be attributed to the power outage distribution transformer are found out, including the following steps:
carrying out preset judging steps on all power-off distribution transformers and the wires under the buses nearby, and finally obtaining a power-off distribution transformer set, a power-off distribution transformer number proportion index data set of all wires under the buses nearby the power-off distribution transformers, a power-off distribution transformer number proportion index threshold value of all wires under the suspected buses, all distribution transformers with abnormal suspected wire transformation relations and suspected corresponding wires under the suspected buses;
the preset judging step comprises the following steps: if the suspected line under the bus of the power-off distribution transformer is in power-off in a typical time period, and the index value of the number of the distribution transformers in power-off is higher than the index threshold value of the number of the power-off distribution transformers, the power-off distribution transformer is judged to be a suspected line transformation relationship abnormal distribution transformer, otherwise, the power-off distribution transformer is judged to be a line transformation relationship normal distribution transformer.
In a third aspect, the invention provides a power distribution network cable change relation abnormality diagnosis system based on a power failure event, which comprises a storage medium and a processor;
the storage medium is used for storing instructions;
the processor is operative according to the instructions to perform the steps of the method according to any one of the first aspects.
Compared with the prior art, the invention has the beneficial effects that:
(1) The invention learns the historical mass data change trend in a data driving mode, calculates the threshold value of the power failure distribution transformer number of the line for judging whether the line change relation is abnormal, and avoids manual assignment.
(2) The invention can directly determine the suspected application specific line of the power failure distribution transformer with the wrong line change relation according to the longitude and latitude information, and avoids the blind line inspection of field operators.
(3) The invention has simple calculation and clear principle, can help distribution network operators to find the distribution transformer with wrong line change relation in time and recommend the suspected line to be affiliated, is convenient for the operators to adjust the line change relation in time, and has good application prospect.
Drawings
In order that the invention may be more readily understood, a more particular description of the invention will be rendered by reference to specific embodiments that are illustrated in the appended drawings, in which:
FIG. 1 is a flow chart of a method for diagnosing a change relation abnormality of a medium voltage distribution network cable based on a power failure event according to the present invention;
fig. 2 is a schematic diagram of a medium voltage distribution network line transformation relationship.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the detailed description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The principle of application of the invention is described in detail below with reference to the accompanying drawings.
Example 1
The embodiment of the invention provides a power distribution network cable change relation abnormity diagnosis method based on a power failure event, which comprises the following steps:
generating a historical power outage distribution transformer set based on the acquired power data of the distribution transformers;
in a specific implementation manner of the embodiment of the present invention, the specific implementation process of step (a) is:
and screening the distribution transformer to be processed in an energy management system (the system is a system existing in the prior art) based on the power information of the distribution transformer, and reading the power measurement data and the basic equipment information thereof stored in the distribution transformer corresponding to the existing system. For a certain distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,…,p k,i ,…,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer; if distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,…,p k,j ]If empty, a distribution transformer M is generated j Data segment [ i, …, j ]]For the power failure fragments of the distribution transformer, M j The power outage distribution transformer.
Repeating the steps until all the distribution transformers finish judgment, and generating a power failure distribution transformer information set M= { M 1 ,M 2 ,…,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
Step (B) obtaining the bus and the distribution transformer nearby and the voltage measurement data of the bus nearby based on the longitude and latitude information of the power failure distribution transformer in the power failure distribution transformer set;
in a specific implementation manner of the embodiment of the present invention, the step (B) specifically includes the following substeps:
step 1: distribution transformer M for power failure j Based on longitude and latitude information, calculating a bus set F5 km away from the geographical range of the distribution transformer;
step 2: the medium-voltage distribution network to be processed is selected from an energy management system (the system is a system existing in the prior art), the linear transformation relation of the busbar-distribution transformer load stored in the prior system is read, statistical voltage data of the power outage distribution transformer and the nearby busbars which are sampled once every 15min is derived, and the sampling frequency which is sampled once every 15min can be modified according to actual conditions.
The method further comprises the step of carrying out the complement processing on the voltage measurement data of the bus, and particularly adopting a linear interpolation method to carry out the complement processing on the voltage data which is originally acquired, wherein the basic idea is that an interpolation function can approximately replace an original function, the interpolation function is a one-time polynomial class, and the interpolation error on each interpolation node is required to be 0. Let the known raw data f (x i ) Wherein x is i (i=0, 1,2,3, …, n), n being the length of the sampled raw data, the linear interpolation now constructs a functionSo that the absolute value of the error |r (x) | is small over the whole original data interval, i.e.:
interpolation function based on the construction is now performedIf there is a data loss in the original data at i=m, i.e. f (m) is null, then +.>The missing condition of the voltage data of the original sample is complemented.
Calculating the related coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus;
in a specific implementation manner of the embodiment of the present invention, the step (C) specifically includes the following steps:
and obtaining a calculation formula of a correlation index between each power failure distribution transformer and a bus nearby, wherein the correlation index is used for measuring the connection relation between the distribution transformer and the bus, and is obtained by comparing the similarity of the voltage data of the distribution transformer and the voltage data of the bus, and the similarity is calculated through a Pearson correlation coefficient, as shown in fig. 2. When the bus voltage fluctuates, the voltage of the distribution transformer on the circuit is driven to fluctuate, namely the voltage curves of the two have similarity. If a certain distribution transformer is connected to the line in error, the voltage fluctuation of the distribution transformer and the voltage fluctuation of the bus are not similar, and the pearson correlation coefficient is low. The calculation formula of the correlation coefficient index is as follows:
Wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing nearby bus voltage measurement data; />Representing the average value of the voltage measurement data of the nearby bus; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
and screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the nearby buses, introducing the proper data into the related index calculation formula, calculating to obtain related coefficient index values between each power outage distribution transformer and the nearby buses, forming a related coefficient index data set, and screening the nearby buses suspected to belong to the power outage distribution transformer and the lower lines thereof based on the related coefficient index data set.
Screening all lines under suspected corresponding buses of the power failure distribution transformer;
step (E), calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power outage distribution transformer number duty ratio index threshold;
in a specific implementation manner of the embodiment of the present invention, the step (E) specifically includes the following substeps:
Step 1: taking a certain 1 day in history as a typical historical time period, reading all power failure distribution transformers in the ground city as T= { T 1 ,T 2 …T k -wherein k is the number of power outage distribution transformers for the ground;
step 2: selecting M in the power outage distribution transformer set according to the step (D) j The power failure fragments of a certain day are taken as a typical time period, and the number T of distribution transformers for power failure of each line under the suspected bus is calculated for all lines under the suspected bus in a certain city j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j ：
Repeating the steps to calculate the power failure distribution transformer number ratio index P of all lines j Constitute historical power failure distribution transformer number and occupy than index data set P = { P 1 ,P 2 ,…,P l }。
Step 3: the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values in the data set PP j The corresponding distribution transformer belongs to the precision and recall ratio of the route;
calculating a derived index F1 based on the precision and recall j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
Step (F) based on the obtained threshold value, screening out the suspected line of the power failure distribution transformer, and finally finding out the power failure distribution transformer with wrong line transformation relation and the suspected line of the power failure distribution transformer;
in a specific implementation manner of the embodiment of the present invention, the step (F) specifically includes the following substeps:
if the index value of the power failure distribution transformer number ratio of the power failure distribution transformer and the lines in the bus nearby is lower than the index threshold value of the power failure distribution transformer number ratio, judging that the distribution transformer is a normal distribution transformer with a linear transformation relationship, otherwise, judging that the distribution transformer is a suspected linear transformation relationship abnormal distribution transformer, and forming a suspected linear transformation relationship abnormal distribution transformer set N= { N 1 ,N 2 ,…,N l And recording the suspected line information under the corresponding nearby bus, wherein l is the number of the power outage distribution transformers with abnormal suspected line change relation after the ground city is judged.
Repeating the steps until all the power failure distribution transformers in the set M are judged, and finding out the suspected corresponding line of the power failure distribution transformer with the wrong line transformation relation.
Example 2
Based on the same inventive concept as embodiment 1, an embodiment of the present invention provides a power distribution network cable change relation abnormality diagnosis device based on a power outage event, including:
the generation unit is used for generating a historical power failure distribution transformer set based on the acquired power data of the distribution transformer;
the first calculation unit is used for obtaining the bus and the distribution transformer nearby and the voltage measurement data of the bus nearby based on the longitude and latitude information of the power failure distribution transformer in the power failure distribution transformer set;
the second calculation unit is used for calculating the correlation coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus which should be affiliated;
the first screening unit is used for screening all lines under the suspected corresponding bus of the power failure distribution transformer;
the third calculation unit is used for calculating the power failure distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power failure distribution transformer number duty ratio index threshold;
and the judging unit is used for screening out the suspected affiliated lines of the power failure distribution transformer based on the obtained threshold value, and finally finding out the power failure distribution transformer with wrong line transformation relation and the suspected affiliated lines thereof.
In a specific implementation manner of the embodiment of the present invention, the method for generating the historical power outage distribution transformer set includes:
certain distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,...,p k,i ,...,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer;
if distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,...,p k,j ]0 or null, generating a distribution transformer M j Data segment [ i, …, j ]]For breaking fragments in power failure, distribution transformer M j Then the power failure distribution transformer;
based on the rule for screening the power outage distribution transformers, historical power outage distribution transformers are screened from the acquired power data of the distribution transformers, and a power outage distribution transformer set M= { M is generated 1 ,M 2 ,...,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
In a specific implementation manner of the embodiment of the present invention, the method for searching the suspected bus includes:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
and screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
In a specific implementation manner of the embodiment of the present invention, the method for searching the suspected bus includes:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
And screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
In a specific implementation manner of the embodiment of the present invention, the calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, evaluating and seeking the power outage distribution transformer number duty ratio index threshold value includes the following steps:
calculating the power failure distribution transformer number ratio index P of all lines j The historical power failure distribution transformer number duty ratio index data set P is formed;
the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values P in the data set P j Corresponding arrangementThe electric transformer belongs to the precision and recall of the route;
calculating a derived index F1 based on the precision and recall j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
In a specific implementation manner of the embodiment of the present invention, the power outage distribution transformer number is a ratio index P j The calculation method of (1) is as follows:
for all lines under suspected bus in a certain area, calculating the number T of distribution transformers for power failure of each line under suspected bus j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j 。
In a specific implementation manner of the embodiment of the present invention, based on the obtained threshold value, a suspected corresponding line of the power outage distribution transformer is screened out, and finally, the power outage distribution transformer with a wrong line transformation relationship and the suspected corresponding line thereof are found out, including the following steps:
carrying out preset judging steps on all power-off distribution transformers and the wires under the buses nearby, and finally obtaining a power-off distribution transformer set, a power-off distribution transformer number proportion index data set of all wires under the buses nearby the power-off distribution transformers, a power-off distribution transformer number proportion index threshold value of all wires under the suspected buses, all distribution transformers with abnormal suspected wire transformation relations and suspected corresponding wires under the suspected buses;
The preset judging step comprises the following steps: if the suspected line under the bus of the power-off distribution transformer is in power-off in a typical time period, and the index value of the number of the distribution transformers in power-off is higher than the index threshold value of the number of the power-off distribution transformers, the power-off distribution transformer is judged to be a suspected line transformation relationship abnormal distribution transformer, otherwise, the power-off distribution transformer is judged to be a line transformation relationship normal distribution transformer.
Example 3
Based on the same inventive concept as embodiment 1, an embodiment of the present invention provides a power distribution network cable change relation abnormality diagnosis system based on a power outage event, including a storage medium and a processor;
the storage medium is used for storing instructions;
the processor is operative according to the instructions to perform the steps of the method according to any one of embodiment 1.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are all within the protection of the present invention.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (12)
1. A power distribution network cable transformation relation abnormity diagnosis method based on a power failure event is characterized by comprising the following steps:
generating a historical power failure distribution transformer set based on the acquired power data of the distribution transformers;
acquiring voltage measurement data of a bus and a distribution transformer nearby the power failure distribution transformer and the bus nearby the power failure distribution transformer based on longitude and latitude information of the power failure distribution transformers in the power failure distribution transformer set;
calculating the related coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus;
screening all lines under suspected corresponding buses of the power failure distribution transformer;
calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power outage distribution transformer number duty ratio index threshold;
screening out suspected corresponding lines of the power outage distribution transformer based on the obtained threshold value, and finally finding out the power outage distribution transformer with wrong line transformation relation and the suspected corresponding lines;
the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus is calculated, and the power outage distribution transformer number duty ratio index threshold is estimated and sought, and the method comprises the following steps:
Calculating the power failure distribution transformer number ratio index P of all lines j The historical power failure distribution transformer number duty ratio index data set P is formed;
the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values P in the data set P j The corresponding distribution transformer belongs to the precision and recall ratio of the route;
calculating a derived index F1 based on the precision and recall j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
2. The power distribution network cable transformation relationship anomaly diagnosis method based on the power outage event according to claim 1, wherein the generation method of the historical power outage distribution transformer set comprises the following steps:
distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,...,p k,i ,...,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer;
If distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,...,p k,j ]0 or null, generating a distribution transformer M j Data segment [ i, …, j ]]For breaking fragments in power failure, distribution transformer M j A power failure distribution transformer;
based on the rule for screening the power outage distribution transformers, historical power outage distribution transformers are screened from the acquired power data of the distribution transformers, and a power outage distribution transformer set M= { M is generated 1 ,M 2 ,...,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
3. The power distribution network cable change relation abnormality diagnosis method based on the power failure event according to claim 1, wherein the method comprises the following steps: the method for obtaining the bus and the distribution transformer nearby and the voltage measurement data of the bus nearby based on the longitude and latitude information of the power failure distribution transformer in the power failure distribution transformer set comprises the following steps:
and calculating a bus set within a set threshold from the geographical range of the power failure distribution transformer based on longitude and latitude information of each distribution transformer in the power failure distribution transformer set, and acquiring the bus set and voltage measurement data of the bus.
4. The power distribution network cable change relation abnormality diagnosis method based on the power failure event according to claim 1, wherein the method comprises the following steps: the method for searching the suspected corresponding bus comprises the following steps:
Acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
and screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
5. The power distribution network cable change relation abnormality diagnosis method based on power outage event according to claim 1, wherein the power outage is characterized in thatDistribution transformer number duty ratio index P j The calculation method of (1) is as follows:
for all lines under suspected bus in a certain area, calculating the number T of distribution transformers for power failure of each line under suspected bus j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j 。
6. The power distribution network line transformation relation abnormity diagnosis method based on the power outage event according to claim 1, wherein the power outage distribution transformer suspected to be a line is screened out based on the obtained threshold value, and finally the power outage distribution transformer with the wrong line transformation relation and the suspected line to be the line are found out, and the method comprises the following steps:
carrying out preset judging steps on all power-off distribution transformers and the wires under the buses nearby, and finally obtaining a power-off distribution transformer set, a power-off distribution transformer number proportion index data set of all wires under the buses nearby the power-off distribution transformers, a power-off distribution transformer number proportion index threshold value of all wires under the suspected buses, all distribution transformers with abnormal suspected wire transformation relations and suspected corresponding wires under the suspected buses;
the preset judging step comprises the following steps: if the suspected line under the bus of the power-off distribution transformer is in power-off in a typical time period, and the index value of the number of the distribution transformers in power-off is higher than the index threshold value of the number of the power-off distribution transformers, the power-off distribution transformer is judged to be a suspected line transformation relationship abnormal distribution transformer, otherwise, the power-off distribution transformer is judged to be a line transformation relationship normal distribution transformer.
7. An abnormal diagnosis device of power distribution network cable transformation relation based on a power failure event is characterized by comprising the following components:
the generation unit is used for generating a historical power failure distribution transformer set based on the acquired power data of the distribution transformer;
the first calculation unit is used for obtaining the bus and the distribution transformer nearby and the voltage measurement data of the bus nearby based on the longitude and latitude information of the power failure distribution transformer in the power failure distribution transformer set;
the second calculation unit is used for calculating the correlation coefficient index of the power failure distribution transformer and the bus nearby, and finding out the suspected bus which should be affiliated;
the first screening unit is used for screening all lines under the suspected corresponding bus of the power failure distribution transformer;
the third calculation unit is used for calculating the power failure distribution transformer number duty ratio index corresponding to all lines under the suspected bus, and evaluating and seeking a power failure distribution transformer number duty ratio index threshold;
the judging unit is used for screening out the suspected affiliated lines of the power failure distribution transformer based on the obtained threshold value, and finally finding out the power failure distribution transformer with wrong line transformation relation and the suspected affiliated lines thereof;
the method for calculating the power outage distribution transformer number duty ratio index corresponding to all lines under the suspected bus comprises the following steps of:
Calculating the power failure distribution transformer number ratio index P of all lines j The historical power failure distribution transformer number duty ratio index data set P is formed;
the method for solving the threshold value of the power failure distribution transformer number ratio index by utilizing the confusion matrix method for supervised learning in the artificial intelligence specifically comprises the following steps:
respectively calculating different values P in the data set P j The corresponding distribution transformer belongs to the precision and recall ratio of the route;
calculating a derived index F1 based on the precision and recall j ：
Wherein A is j For the precision, R j Is the recall ratio;
after the calculation is completed, an evaluation index set F1= { F1 is formed 1 ,F1 2 ,…,F1 j ,…,F1 k -where k is the number of total lines under the suspected bus;
and searching the maximum value in the evaluation index set F1, and taking the power failure distribution transformer number duty ratio index corresponding to the maximum value as a power failure distribution transformer number duty ratio index threshold value.
8. The power distribution network cable transformation relationship abnormality diagnosis device based on a power outage event according to claim 7, wherein the method for generating the historical power outage distribution transformer set comprises:
certain distribution transformer M j Connected to the line f, distribution transformer M j The active power measurement data of (a) is P k ＝[p k,1 ,p k,2 ,...,p k,i ,...,p k,n ]N represents the number of the measuring data sampling points of the distribution transformer;
If distribution transformer M j Active power measurement data P of (a) k In successive data segments [ p ] k,i ,...,p k,j ]0 or null, generating a distribution transformer M j Data segment [ i, …, j ]]For breaking fragments in power failure, distribution transformer M j Then the power failure distribution transformer; based on the rule for screening the power outage distribution transformers, historical power outage distribution transformers are screened from the acquired power data of the distribution transformers, and a power outage distribution transformer set M= { M is generated 1 ,M 2 ,...,M l And the number of distribution transformers is equal to the number of distribution transformers subjected to power failure after screening.
9. The power distribution network cable change relation abnormality diagnosis device based on a power outage event according to claim 7, wherein the method for searching the suspected subordinate bus comprises the following steps:
acquiring a correlation coefficient index calculation formula between a power failure distribution transformer and a bus nearby the power failure distribution transformer, wherein the correlation coefficient index calculation formula is as follows:
wherein R represents a correlation coefficient index; x is X i Representing power outage distribution transformer voltage measurement data;representing the average value of voltage measurement data of a power failure distribution transformer; y is Y i Representing bus voltage measurement data near a distribution transformer in a power outage; />Representing the average value of bus voltage measurement data near the distribution transformer in power failure; n represents the length of the measured data of the voltage of the distribution transformer and the nearby bus in power failure;
And screening proper data from the obtained voltage measurement data of the power outage distribution transformer and the buses nearby, introducing the proper data into the correlation coefficient index calculation formula, calculating to obtain correlation coefficient index values among all buses in the power outage distribution transformer and the buses nearby, and screening out suspected buses and the lower lines thereof based on the correlation coefficient index values.
10. The power distribution network cable change relation abnormality diagnosis device based on a power failure event according to claim 7, wherein the power failure distribution transformer number duty ratio index P j The calculation method of (1) is as follows:
for all lines under suspected bus in a certain area, calculating the number T of distribution transformers for power failure of each line under suspected bus j Total distribution transformer quantity Z j Calculating the power failure distribution transformer number ratio index P j 。
11. The power distribution network cable transformation relationship abnormality diagnosis device based on a power outage event according to claim 7, wherein the power outage distribution transformer suspected to be a line is screened out based on the obtained threshold value, and finally the power outage distribution transformer with the wrong line transformation relationship and the suspected line to be the line are found out, comprising the following steps:
Carrying out preset judging steps on all power-off distribution transformers and the wires under the buses nearby, and finally obtaining a power-off distribution transformer set, a power-off distribution transformer number proportion index data set of all wires under the buses nearby the power-off distribution transformers, a power-off distribution transformer number proportion index threshold value of all wires under the suspected buses, all distribution transformers with abnormal suspected wire transformation relations and suspected corresponding wires under the suspected buses;
the preset judging step comprises the following steps: if the suspected line under the bus of the power-off distribution transformer is in power-off in a typical time period, and the index value of the number of the distribution transformers in power-off is higher than the index threshold value of the number of the power-off distribution transformers, the power-off distribution transformer is judged to be a suspected line transformation relationship abnormal distribution transformer, otherwise, the power-off distribution transformer is judged to be a line transformation relationship normal distribution transformer.
12. A power distribution network cable transformation relation abnormity diagnosis system based on a power failure event is characterized in that: including a storage medium and a processor;
the storage medium is used for storing instructions;
the processor being operative according to the instructions to perform the steps of the method according to any one of claims 1 to 6.
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