CN114969167A - Intelligent power grid monitoring comprehensive management system and method based on digitization - Google Patents
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Abstract
The invention discloses a data-based intelligent power grid monitoring integrated management system and a method, wherein the integrated management system comprises a power data monitoring module, a duration judging module, a candidate picture selecting module, a main picture selecting module and a main picture control module, the power data monitoring module acquires power data in each monitoring picture, if a certain electric power data exists in a certain monitoring picture and is in an abnormal range, the duration judgment module is enabled to acquire the duration of the electric power data in the abnormal range, if the duration is longer than the duration threshold, the power data is the observation data, the candidate picture selection module selects the monitoring picture containing the observation data as the candidate picture, and then selecting a main picture from the candidate pictures, and amplifying the main picture to a monitor by the main picture control module.
Description
Technical Field
The invention relates to the technical field of power grid monitoring, in particular to a data-based intelligent power grid monitoring comprehensive management system and method.
Background
The power grid refers to a whole formed by a substation and a power transmission and distribution line of various voltages in a power system. People's family life, social life can not leave the electricity, and electricity is one of the most important thing in life, consequently need effectively monitor the electric wire netting operation data when the electric wire netting moves, can in time carry out the testing and maintenance to the electric wire netting when discovering unusually.
In the prior art, when the power grid runs, monitoring data are uploaded to a monitoring master station in real time, once abnormity occurs, a monitor continuously calls different monitoring pictures, manual analysis is performed on the monitoring data, judgment is made according to personal experience, however, the monitoring picture data are more, the monitor needs to consume longer time when abnormity judgment is performed, and the efficiency is relatively low.
Disclosure of Invention
The invention aims to provide a comprehensive monitoring management system and a comprehensive monitoring management method for a smart power grid based on datamation, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a digitalized intelligent power grid monitoring integrated management system comprises a power data monitoring module, a duration judging module, a candidate picture selecting module, a main picture selecting module and a main picture control module, wherein the power data monitoring module acquires power data in each monitoring picture, if a certain power data exists in a certain monitoring picture and is in an abnormal range, the duration judging module acquires the duration of the power data in the abnormal range, if the duration is greater than a duration threshold, the power data is observed data, the candidate picture selecting module selects a monitoring picture containing the observed data as a candidate picture, if the number of the candidate pictures in each monitoring picture is only one, the candidate picture is selected as a main picture, and if the number of the candidate pictures is greater than one, the main picture selection module analyzes the data information of each candidate picture, selects a main picture from the candidate pictures, and the main picture control module amplifies the main picture to a monitor.
Further, the main picture selecting module comprises an expert database, a set comparison module and a historical anomaly analysis module, wherein the expert database is used for storing the abnormal set information of the power data and the corresponding main picture, the set comparison module acquires a set of observation data in all candidate pictures as a monitoring set, the monitoring set is compared with the abnormal set information of the power data in the patent database, if the similarity between a certain set of abnormal set information of the power data and the monitoring set is greater than a similarity threshold value, the main picture corresponding to the abnormal set information of the power data is directly acquired, and otherwise, the historical anomaly analysis module selects the main picture according to the historical anomaly condition of the candidate pictures.
Further, the history anomaly analysis module includes an item index calculation module, a picture index acquisition module, a correlation index acquisition module, a comprehensive index calculation module and a comprehensive index sorting module, where the item index calculation module acquires that a component item of observed data in a candidate picture is a reference item, and a component item of each observed data when the observed data historically appears in the candidate picture, and then an item index P of the candidate picture is Ns/Nd, where Ns is the number of times that the component item of the observed data when the observed data historically appears in the candidate picture is the reference item, and Nd is the number of times that the observed data historically appears in the candidate picture, and the picture index acquisition module then obtains the picture index of the candidate picture
The method comprises the steps that m is the number of items of observation data in a candidate picture, b is the number of items of all power data in the candidate picture, a correlation index acquisition module acquires the correlation condition of each historical monitoring picture and calculates the correlation index V of a certain candidate picture, a comprehensive index calculation module calculates the comprehensive index Z of each candidate picture to be 0.6U + 0.4V, a comprehensive index sorting module sorts the comprehensive indexes of the candidate pictures in a descending order, the first picture is selected as a main picture, and the rest candidate pictures are sorted behind the main picture in a descending order of the comprehensive index and displayed.
Further, the correlation index obtaining module calculates the correlation index of a candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitoring pictures with observed data when the j th observed data history becomes the observed data, a j The number of times of history abnormality occurrence of the jth observed data in the candidate picture is C.
A comprehensive management method for monitoring of a smart power grid based on datamation comprises the following steps:
acquiring power data in each monitoring picture, if a certain monitoring picture has a certain power data in an abnormal range,
acquiring the duration of the electric power data in the abnormal range, if the duration is greater than the duration threshold, the electric power data is observed data,
setting the monitor picture containing the observation data as the candidate picture,
if the number of candidate pictures in each monitored picture is only one, the candidate picture is the main picture,
otherwise, analyzing the data information of each candidate picture, and selecting a main picture from the candidate pictures;
and amplifying the main picture to a monitor.
Further, the selecting the main picture from the candidate pictures includes:
an expert database is pre-established and used for storing abnormal set information of the power data and corresponding main pictures,
acquiring a set of observation data in all candidate pictures as a monitoring set, comparing the monitoring set with the abnormal set information of the power data in the patent database,
if the similarity between a certain group of abnormal power data set information and the monitoring set is greater than the similarity threshold, directly acquiring a main picture corresponding to the group of abnormal power data set information;
otherwise, selecting the main picture according to the historical abnormal condition of the candidate picture.
Further, the selecting the main picture according to the historical abnormal condition of the candidate picture comprises:
obtaining the reference item of the observed data in a candidate frame, and the item index P of the candidate frame is Ns/Nd for each observed data item when the observed data appears in history in the candidate frame, where Ns is the number of times the reference item of the observed data appears in history in the candidate frame, and Nd is the number of times the observed data appears in history in the candidate frame,
then the picture index of that candidate picture
Wherein m is the number of items of observation data in the candidate frame, b is the number of items of all power data in the candidate frame,
collecting historical association conditions of each monitoring picture, calculating association index V of a certain candidate picture,
then the composite index Z of each candidate frame is 0.6U + 0.4V,
and sorting the comprehensive indexes of all the candidate pictures from small to large, and selecting the picture which is sorted first as a main picture.
Further, the calculating the relevance index V of a certain candidate picture includes:
the correlation index of the candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitored pictures with observed data when the j th observed data history of the candidate picture becomes observed data, a j The number of times of history abnormality occurrence of the jth observed data in the candidate picture is C.
Further, the sorting the composite indexes of the candidate pictures according to the order from small to large further comprises:
and sequencing the rest candidate pictures behind the main picture according to the sequence of the comprehensive indexes from small to large.
Compared with the prior art, the invention has the following beneficial effects: according to the method and the device, when the data in the plurality of monitoring pictures are abnormal, the display of the monitoring pictures is prioritized according to the abnormal data item condition and the historical power abnormal condition on the monitoring pictures, so that a monitor can more quickly find the point of the power abnormal fault according to the abnormal data of the monitoring pictures, the manual workload of the monitor is reduced, and the working efficiency of the monitor is improved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a module schematic diagram of a data-based smart grid monitoring integrated management system according to the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a digitalized intelligent power grid monitoring integrated management system comprises a power data monitoring module, a duration judging module, a candidate picture selecting module, a main picture selecting module and a main picture control module, wherein the power data monitoring module acquires power data in each monitoring picture, if a certain power data exists in a certain monitoring picture and is in an abnormal range, the duration judging module acquires the duration of the power data in the abnormal range, if the duration is greater than a duration threshold, the power data is observed data, the candidate picture selecting module selects a monitoring picture containing the observed data as a candidate picture, if the number of the candidate pictures in each monitoring picture is only one, the candidate picture is selected as the main picture, and if the number of the candidate pictures is greater than one, and the main picture selection module analyzes the data information of each candidate picture, selects a main picture from the candidate pictures, and amplifies the main picture to a monitor.
The main picture selecting module comprises an expert database, a set comparison module and a historical anomaly analysis module, wherein the expert database is used for storing electric power data anomaly set information and a corresponding main picture, the set comparison module acquires a set of observation data in all candidate pictures as a monitoring set, the monitoring set is compared with the electric power data anomaly set information in a patent database, if the similarity between a certain set of electric power data anomaly set information and the monitoring set is greater than a similarity threshold value, the main picture corresponding to the set of electric power data anomaly set information is directly acquired, and otherwise, the historical anomaly analysis module selects the main picture according to the historical anomaly condition of the candidate pictures.
The historical anomaly analysis module comprises an item index calculation module, a picture index acquisition module, a correlation index acquisition module, a comprehensive index calculation module and a comprehensive index sorting module, wherein the item index calculation module acquires that a component item of observed data in a certain candidate picture is a reference item, and a component item of each piece of observed data when the observed data appears in history in the candidate picture, so that an item index P of the candidate picture is Ns/Nd, wherein Ns is the number of times that the component item of the observed data when the observed data appears in history in the candidate picture is the reference item, Nd is the number of times that the observed data appears in history in the candidate picture, and the picture index acquisition module acquires the picture index of the candidate picture
Wherein m is the number of items of observation data in the candidate picture, b is the number of items of all power data in the candidate picture, the association index acquisition module collects the association condition of each historical monitoring picture and calculates the association index V of a certain candidate picture, the comprehensive index calculation module calculates the comprehensive index Z of each candidate picture to be 0.6U + 0.4V, and the comprehensive index calculation module calculates the comprehensive index Z of each candidate picture to be 0.6U + 0.4VAnd the comprehensive index sorting module sorts the comprehensive indexes of all candidate pictures from small to large, selects the first picture as a main picture, and sorts the rest candidate pictures behind the main picture according to the sequence of the comprehensive indexes from small to large.
The correlation index acquisition module calculates the correlation index of a certain candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitoring pictures with observed data when the j th observed data history becomes the observed data, a j The number of times of history abnormal occurrence of the jth observed data in the candidate picture is C.
A comprehensive management method for monitoring a smart power grid based on datamation comprises the following steps:
acquiring power data in each monitoring picture, if a certain monitoring picture has a certain power data in an abnormal range,
acquiring the duration of the power data in the abnormal range, if the duration is greater than a duration threshold, the power data is observed data,
setting the monitor picture containing the observation data as the candidate picture,
if the number of candidate pictures in each monitoring picture is only one, the candidate picture is the main picture,
otherwise, analyzing the data information of each candidate picture, and selecting a main picture from each candidate picture; when the data in only one monitoring picture is abnormal, the power abnormity point can be found directly according to the data of the monitoring picture;
amplifying the main picture to a monitor;
the selecting the main picture from the candidate pictures comprises the following steps:
an expert database is pre-established, the expert database is used for storing the abnormal set information of the power data and the corresponding main picture, the expert database is established according to the historical experience of the monitor,
acquiring a set of observation data in all candidate pictures as a monitoring set, and comparing the monitoring set with the abnormal set information of the power data in the patent database, for example, 2 monitoring pictures in all the monitoring pictures belong to the candidate pictures: monitoring images 1 and 2, wherein the observation data in the monitoring image 1 are data items a1 and a4, the observation data in the monitoring image 2 are data items b2 and b3, the monitoring sets are data items a1, data items a4, data items b2 and data items b3, and if the expert database has abnormal power data set information of data items a1, data items a4, data items b2 and data items b3, the main image corresponding to the abnormal power data set information is acquired;
if the similarity between a certain group of abnormal power data set information and the monitoring set is greater than the similarity threshold, directly acquiring a main picture corresponding to the group of abnormal power data set information;
otherwise, selecting the main picture according to the historical abnormal condition of the candidate picture.
The selecting the main picture according to the historical abnormal condition of the candidate picture comprises the following steps:
acquiring a component item of observation data in a certain candidate picture as a reference item, and a component item of each piece of observation data when the observation data appears in history in the candidate picture, wherein an item index P of the candidate picture is Ns/Nd, wherein Ns is the number of times the observation data appears in history in the candidate picture as the reference item, and Nd is the number of times the observation data appears in history in the candidate picture, and the application considers that different power faults can cause the abnormity of the same power data item, so that the abnormal power data items are combined for analysis, when the abnormal combination situation of the power data items is more rare, the particularity of the power abnormity can be reflected, and a monitor is more helpful to find the power abnormity junction point more quickly; for example, if the observed data of a certain time in the monitor screen 1 is the data item a1 or the data item a4, the data item a1 or the data item a4 constitutes the constituent items of the observed data of the certain time;
then the picture index of that candidate picture
Wherein m is the number of items of observation data in the candidate screen, b is the number of items of all power data in the candidate screen, and the more power data abnormal data items displayed on the monitoring screen, the more the monitoring screen is helpful for the monitor to judge the power abnormality;
collecting the association condition of each historical monitoring picture, and calculating the association index of a certain candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitored pictures with observed data when the j th observed data history of the candidate picture becomes observed data, a j For the number of times of history abnormality occurrence of jth observation data in the candidate frame, C is the number of times of abnormality occurrence in the history monitoring frame, for example, 1 observation data item in a certain candidate frame is data item d1, then m is 2, then the average number of other monitoring frames with abnormal data when abnormality occurs in the history of data item d1 is respectively obtained, it is assumed that there are 3 times of history abnormality occurrence of data item d1, other monitoring frames with observation data when abnormality occurs for the first time are 1, other monitoring frames with observation data when abnormality occurs for the second time are 3, monitoring frames with other observation data when abnormality occurs for the third time are 2, then T corresponding to the data item d1 is T j When a data item abnormality occurs in a certain candidate screen and the number of monitoring screens with other data item abnormalities is small, the more characteristic the candidate screen is, the more representative the electric power abnormality is, thereby being helpful for a monitor to judge the electric power abnormality; if one electric power data item is in the history abnormal process, the abnormal timesThe electric power data items are fewer, and the stronger the characteristic of each electric power data item is, the more the electric power data items are favorable for judging the nodes of the electric power abnormity;
the comprehensive index Z of a certain candidate picture is 0.6 × U +0.4 × V, and when the comprehensive index of a certain candidate picture is smaller, the specificity in the data information in the candidate picture is stronger, so that the abnormal analysis of the monitor can be helped, the first candidate picture is placed on the main picture, and the other candidate pictures are placed behind the main picture for displaying, so that the rapid analysis of the monitor is facilitated, and the working efficiency of the monitor is improved;
and sorting the comprehensive indexes of all candidate pictures from small to large, selecting the first picture as a main picture, and sorting the rest candidate pictures behind the main picture according to the sequence of the comprehensive indexes from small to large.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A digitalized intelligent power grid monitoring integrated management system is characterized by comprising a power data monitoring module, a duration judging module, a candidate picture selecting module, a main picture selecting module and a main picture control module, wherein the power data monitoring module acquires power data in each monitoring picture, if a certain power data exists in a certain monitoring picture and is in an abnormal range, the duration judging module acquires the duration of the power data in the abnormal range, if the duration is greater than a duration threshold, the power data is observation data, the candidate picture selecting module selects a monitoring picture containing the observation data as a candidate picture, if the number of the candidate pictures in each monitoring picture is only one, the candidate picture is selected as the main picture, and if the number of the candidate pictures is greater than one, the main picture selection module analyzes the data information of each candidate picture, selects a main picture from the candidate pictures, and the main picture control module amplifies the main picture to a monitor.
2. The intelligent power grid monitoring integrated management system based on the digitization of claim 1, wherein: the main picture selecting module comprises an expert database, a set comparison module and a historical anomaly analysis module, wherein the expert database is used for storing electric power data anomaly set information and a corresponding main picture, the set comparison module acquires a set of observation data in all candidate pictures as a monitoring set, the monitoring set is compared with the electric power data anomaly set information in a patent database, if the similarity between a certain set of electric power data anomaly set information and the monitoring set is greater than a similarity threshold value, the main picture corresponding to the set of electric power data anomaly set information is directly acquired, and otherwise, the historical anomaly analysis module selects the main picture according to the historical anomaly condition of the candidate pictures.
3. The intelligent power grid monitoring integrated management system based on the digitization of claim 2, wherein: the historical exceptionThe analysis module comprises an item index calculation module, a picture index acquisition module, a correlation index acquisition module, a comprehensive index calculation module and a comprehensive index sorting module, wherein the item index calculation module acquires that a component item of observation data in a certain candidate picture is a reference item, and a component item of each observation data in the candidate picture when the observation data appears historically, so that an item index P of the candidate picture is Ns/Nd, wherein Ns is the number of times that the component item of the observation data in the candidate picture appears historically is the reference item, Nd is the number of times that the observation data appears historically in the candidate picture, and the picture index acquisition module acquires the picture index of the candidate picture
The system comprises a correlation index acquisition module, a comprehensive index calculation module, a comprehensive index sorting module, a main picture selection module and a power data display module, wherein m is the item quantity of observation data in the candidate picture, b is the item quantity of all power data in the candidate picture, the correlation index acquisition module acquires the correlation condition of each historical monitoring picture and calculates the correlation index V of a certain candidate picture, the comprehensive index calculation module calculates the comprehensive index Z of each candidate picture to be 0.6U + 0.4V, the comprehensive index sorting module sorts the comprehensive indexes of the candidate pictures from small to large, the first picture is selected as the main picture, and the rest candidate pictures are sorted behind the main picture according to the sequence of the comprehensive indexes from small to large and displayed.
4. The intelligent power grid monitoring integrated management system based on the digitization of claim 3, wherein: the correlation index acquisition module calculates the correlation index of a candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitored pictures with observed data when the j th observed data history of the candidate picture becomes observed data, a j The history of the j observed data in the candidate picture is abnormalC is the number of historical anomalies.
5. A comprehensive management method for monitoring of a smart power grid based on datamation is characterized by comprising the following steps: the comprehensive management method comprises the following steps:
acquiring power data in each monitoring picture, if a certain monitoring picture has a certain power data in an abnormal range,
acquiring the duration of the power data in the abnormal range, if the duration is greater than a duration threshold, the power data is observed data,
setting the monitor picture containing the observation data as the candidate picture,
if the number of the candidate pictures in each monitoring picture is only one, the candidate pictures are the main pictures,
otherwise, analyzing the data information of each candidate picture, and selecting a main picture from the candidate pictures;
and amplifying the main picture to a monitor.
6. The intelligent power grid monitoring comprehensive management method based on the digitization according to claim 5, wherein the intelligent power grid monitoring comprehensive management method comprises the following steps: the selecting the main picture from the candidate pictures comprises:
an expert database is pre-established and used for storing abnormal set information of the power data and corresponding main pictures,
acquiring a set of observation data in all candidate pictures as a monitoring set, comparing the monitoring set with the abnormal set information of the power data in the patent database,
if the similarity between a certain group of abnormal power data set information and the monitoring set is greater than the similarity threshold, directly acquiring a main picture corresponding to the group of abnormal power data set information;
otherwise, selecting the main picture according to the historical abnormal condition of the candidate picture.
7. The intelligent power grid monitoring comprehensive management method based on the digitization as claimed in claim 6, wherein: the selecting the main picture according to the historical abnormal condition of the candidate picture comprises the following steps:
obtaining the composition of observed data in a candidate frame as a reference item, and the composition of each observed data in the candidate frame when observed data is historically present, then the item index P of the candidate frame is Ns/Nd, where Ns is the number of times that the composition of observed data in the candidate frame is a reference item when observed data is historically present, and Nd is the number of times that observed data is historically present in the candidate frame,
then the picture index of that candidate picture
Wherein m is the number of items of observation data in the candidate frame, b is the number of items of all power data in the candidate frame,
collecting historical association conditions of each monitoring picture, calculating association index V of a certain candidate picture,
then the composite index Z of each candidate frame is 0.6U + 0.4V,
and sorting the comprehensive indexes of all the candidate pictures from small to large, and selecting the picture which is sorted first as a main picture.
8. The intelligent power grid monitoring comprehensive management method based on the datamation according to claim 7, wherein the method comprises the following steps: the calculating the association index V of a certain candidate picture comprises:
the correlation index of the candidate picture
Wherein S is the total number of all monitoring pictures, T j The j th observed data history of the candidate picture is the average value of the number of other monitored pictures with observed data when the j th observed data history of the candidate picture becomes observed data, a j The number of times of history abnormality occurrence of the jth observed data in the candidate picture is C.
9. The intelligent power grid monitoring comprehensive management method based on the datamation according to claim 7, wherein the method comprises the following steps: the sorting the comprehensive indexes of the candidate pictures according to the sequence from small to large further comprises:
and sequencing the rest candidate pictures after the main picture according to the sequence of the composite indexes from small to large.
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