CN114969167B - Intelligent power grid monitoring integrated management system and method based on data - Google Patents
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Abstract
The invention discloses a comprehensive management system and a method for monitoring a smart grid based on datamation, wherein the comprehensive 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 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 longer 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, then selects the main picture from the candidate picture, and the main picture control module amplifies the main picture to a monitor.
Description
Technical Field
The invention relates to the technical field of power grid monitoring, in particular to a comprehensive management system and method for intelligent power grid monitoring based on data.
Background
The power grid refers to an integral body formed by power transformation stations with various voltages and power transmission and distribution lines in a power system. The family life and the social life of people are all independent of electricity, and the electricity is one of the most important things in life, so that the running data of the power grid needs to be effectively monitored when the power grid runs, and the power grid can be timely detected and maintained when abnormality is found.
In the prior art, when the power grid is operated, monitoring data are uploaded to a monitoring master station in real time, once abnormality occurs, a monitor continuously calls different monitoring pictures, the monitoring data in the monitoring pictures are manually analyzed, judgment is made according to personal experience, but the monitoring picture data are relatively more, the monitor needs to consume relatively long time when judging the abnormality, and the efficiency is relatively low.
Disclosure of Invention
The invention aims to provide a comprehensive management system and method for intelligent power grid monitoring 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: the utility model provides a smart power grid monitoring integrated management system based on data, integrated management system includes electric power data monitoring module, duration judging module, candidate picture selection module, main picture selection module and main picture control module, electric power data monitoring module obtains the electric power data in each monitored picture, if there is certain electric power data in a certain monitored picture in the unusual scope, make duration judging module obtain the duration that this electric power data is in the unusual scope, if duration is longer than duration threshold value, this electric power data is observed data, candidate picture selection module selects the monitored picture that contains observed data as candidate picture, if the number of candidate picture in each monitored picture is only one, select this candidate picture as main picture, if the number of candidate picture is greater than one, main picture selection module analyzes the data information of each candidate picture, select main picture from the candidate picture, main picture control module amplifies main picture to the monitor.
Further, the main picture selection module comprises an expert database, a set comparison module and a history exception analysis module, wherein the expert database is used for storing the information of the power data exception sets and the corresponding main picture, the set comparison module obtains the set of the observation data in all candidate pictures as a monitoring set, compares the monitoring set with the information of the power data exception sets in the patent database, and directly obtains the main picture corresponding to the information of the power data exception sets if the similarity between the information of the power data exception sets and the monitoring set is greater than a similarity threshold value, otherwise, the history exception analysis module selects the main picture according to the history exception condition of the candidate pictures.
Further, 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 sequencing module, wherein the item index calculation module acquires the composition items of the observed data in a certain candidate picture as followsA reference item, and a composition item of each observation data when the observation data appears in the history in the candidate frame, then the item index P=Ns/Nd of the candidate frame, where Ns is the number of times the composition item of the observation data appears in the history in the candidate frame is the reference item, nd is the number of times the observation data appears in the history in the candidate frame, then the frame index acquisition module obtains the frame index of the candidate frameThe method comprises the steps of selecting a first picture to be a main picture, and sequencing the rest candidate pictures from small to large according to the sequence of the comprehensive indexes of the candidate pictures, wherein m is the item number of the observed data in the candidate pictures, b is the item number of all the electric power data in the candidate pictures, the correlation index acquisition module acquires the correlation condition of each monitoring picture of history, calculates the correlation index V of a certain candidate picture, the comprehensive index calculation module calculates the comprehensive index Z=0.6XU+0.4XV of each candidate picture, and the comprehensive index sequencing module sequences the comprehensive indexes of each candidate picture from small to large, selects the first picture to be the main picture, and sequences the rest candidate pictures from small to large according to the sequence of the comprehensive indexes and then displays the main picture.
Further, the association index obtaining module calculates an association index of a candidate frameWherein S is the total number of all monitoring pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j And C is the number of times of abnormality occurrence of the history of the j-th observation data in the candidate picture.
A comprehensive management method for intelligent power grid monitoring based on datamation comprises the following steps:
acquiring power data in each monitoring picture, if certain power data exist in a certain monitoring picture and are in an abnormal range,
then a duration of time that the power data is within the anomaly range is acquired, and if the duration of time is greater than a duration threshold, the power data is observed,
the monitoring picture containing the observed data is set as a candidate picture,
if there is only one candidate picture in each monitoring picture, 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:
pre-establishing an expert database for storing power data abnormal set information and a corresponding main picture,
acquiring the set of the observation data in all candidate pictures as a monitoring set, comparing the monitoring set with the information of the abnormal set of the electric power data in the patent database,
if the similarity between the abnormal set information of a certain group of power data and the monitoring set is greater than a similarity threshold, directly acquiring a main picture corresponding to the abnormal set information of the group of power data;
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 includes:
acquiring a reference item for a composition item of observation data in a candidate picture and a composition item of observation data each time when the observation data appears in the history in the candidate picture, then the item index p=ns/Nd of the candidate picture, where Ns is the number of times the reference item is the composition item of observation data when the observation data appears in the history in the candidate picture, nd is the number of times the observation data appears in the history in the candidate picture,
then the picture index of the candidate pictureWhere 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,
collecting the association condition of each monitoring picture of the history, calculating the association index V of a certain candidate picture,
then the composite index z=0.6 x u+0.4 x v for each candidate frame,
and sequencing the comprehensive indexes of the candidate pictures in the order from small to large, and selecting the picture with the first sequence as a main picture.
Further, the calculating the association index V of a certain candidate frame includes:
association index of the candidate pictureWherein S is the total number of all monitoring pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j And C is the number of times of abnormality occurrence of the history of the j-th observation data in the candidate picture.
Further, the ranking the composite indexes of the candidate pictures in order from small to large further includes:
and sequencing the rest candidate pictures in the order of the comprehensive indexes from small to large after the main picture is displayed.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, when the data in the monitoring pictures are abnormal, the priority ranking is carried out on the presentation of the monitoring pictures according to the abnormal data item condition and the historical power abnormal condition on the monitoring pictures, so that a monitor can discover the sign point of the power abnormality more quickly 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 are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic block diagram of a smart grid monitoring integrated management system based on datamation.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: the utility model provides a smart power grid monitoring integrated management system based on data, integrated management system includes electric power data monitoring module, duration judging module, candidate picture selection module, main picture selection module and main picture control module, electric power data monitoring module obtains the electric power data in each monitored picture, if there is certain electric power data in a certain monitored picture in the unusual scope, make duration judging module obtain the duration that this electric power data is in the unusual scope, if duration is longer than duration threshold value, this electric power data is observed data, candidate picture selection module selects the monitored picture that contains observed data as candidate picture, if the number of candidate picture in each monitored picture is only one, select this candidate picture as main picture, if the number of candidate picture is greater than one, main picture selection module analyzes the data information of each candidate picture, select main picture from the candidate picture, main picture control module amplifies main picture to the monitor.
The main picture selection module comprises an expert database, a set comparison module and a history exception analysis module, wherein the expert database is used for storing power data exception set information and corresponding main pictures, the set comparison module obtains the set of observation data in all candidate pictures as a monitoring set, compares the monitoring set with the power data exception set information in the patent database, and directly obtains the main pictures corresponding to the power data exception set information if the similarity between a certain group of power data exception set information and the monitoring set is greater than a similarity threshold value, otherwise, the history exception analysis module selects the main pictures according to the history exception condition of the candidate pictures.
The history 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 sequencing module, wherein the item index calculation module acquires the composition item of the observation data in a certain candidate picture as a reference item and the composition item of each observation data when the observation data appears in the history in the candidate picture, then the item index P=Ns/Nd of the candidate picture, wherein Ns is the number of times that the composition item of the observation data is the reference item when the observation data appears in the history in the candidate picture, nd is the number of times that the observation data appears in the history in the candidate picture, and the picture index acquisition module obtains the picture index of the candidate pictureThe method comprises the steps of selecting a first picture to be a main picture, and sequencing the rest candidate pictures from small to large according to the sequence of the comprehensive indexes of the candidate pictures, wherein m is the item number of the observed data in the candidate pictures, b is the item number of all the electric power data in the candidate pictures, the correlation index acquisition module acquires the correlation condition of each monitoring picture of history, calculates the correlation index V of a certain candidate picture, the comprehensive index calculation module calculates the comprehensive index Z=0.6XU+0.4XV of each candidate picture, and the comprehensive index sequencing module sequences the comprehensive indexes of each candidate picture from small to large, selects the first picture to be the main picture, and sequences the rest candidate pictures from small to large according to the sequence of the comprehensive indexes and then displays the main picture.
The association index obtaining module calculates an association index of a candidate pictureWherein S is allMonitor the total number of pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j And C is the number of times of abnormality occurrence of the history of the j-th observation data in the candidate picture.
A comprehensive management method for intelligent power grid monitoring based on datamation comprises the following steps:
acquiring power data in each monitoring picture, if certain power data exist in a certain monitoring picture and are in an abnormal range,
then a duration of time that the power data is within the anomaly range is acquired, and if the duration of time is greater than a duration threshold, the power data is observed,
the monitoring picture containing the observed data is set as a candidate picture,
if there is only one candidate picture in each monitoring picture, then that candidate picture is the home picture,
otherwise, analyzing the data information of each candidate picture, and selecting a main picture from each candidate picture; when only the data in one monitoring picture is abnormal, the position of the abnormal power sign 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:
an expert database is pre-established, the expert database is used for storing the power data abnormal set information and the corresponding main picture, the expert database is established according to the historical experience of a monitor,
acquiring a set of observation data in all candidate pictures as a monitoring set, and comparing the monitoring set with the power data abnormal set information in the patent database, for example, 2 monitoring pictures in all the monitoring pictures belong to the candidate pictures: monitoring a picture 1 and a monitoring picture 2, wherein the observed data in the monitoring picture 1 are data items a1 and a data item a4, and the observed data in the monitoring picture 2 are data items b2 and b3, then the monitoring set is data items a1, a data item a4, a data item b2 and a data item b3, and if the expert database has power data abnormal set information, the main picture corresponding to the power data abnormal set information is acquired;
if the similarity between the abnormal set information of a certain group of power data and the monitoring set is greater than a similarity threshold, directly acquiring a main picture corresponding to the abnormal set information of the group of power data;
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:
acquiring a composition item of observation data in a candidate picture as a reference item and a composition item of observation data each time when the observation data appears in the history in the candidate picture, wherein Ns is the number of times that the composition item of the observation data is the reference item when the observation data appears in the history in the candidate picture, and Nd is the number of times that the observation data appears in the history in the candidate picture; for example, if the observation data of a certain time in the monitor screen 1 is the data item a1 and the data item a4, the data item a1 and the data item a4 constitute the constituent items of the observation data of the time;
then the picture index of the candidate pictureWherein 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, and the power data displayed in the monitoring picture is differentThe more the data items, the more the monitor can judge the power abnormality;
collecting the association condition of each monitoring picture of the history, and calculating the association index of a certain candidate pictureWherein S is the total number of all monitoring pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j For the number of abnormal occurrence of the history of the jth observation data in the candidate frame, C is the number of abnormal occurrence in the history monitoring frame, for example, 1 item of observation data in a candidate frame is 1, d1 is data item, then m=2, then the average number of monitoring frames with other abnormal data is obtained for each abnormal occurrence of the history of the data item d1, assuming that 3 abnormal occurrences of the history of the data item d1 are present, 1 monitoring frame with other observed data is present for the first time, 3 monitoring frames with other observed data is present for the second time, 2 monitoring frames with other observed data is present for the third time, then T corresponding to the data item d1 j 2, when a certain candidate picture is abnormal in data item, the other monitoring pictures with abnormal data item are relatively small, so that the stronger the characteristics of the candidate picture are, the more the characteristic of the candidate picture is, the more the candidate picture has the representativeness of the sign of the abnormal power, and the judgment of a monitor on the abnormal power is facilitated; if the number of times of abnormality occurrence of one power data item in the history abnormality occurrence process is smaller, the more characteristic of the power data item is strong, the more favorable the power data item is for judging the power abnormality node;
when the comprehensive index Z=0.6XU+0.4XV of a certain candidate picture is smaller, the specificity in the data information in the candidate picture is stronger, and the monitor can be helped to perform abnormal analysis, so that the first candidate picture in sequence is placed in a main picture, and other candidate pictures are placed behind the main picture for display, thereby being convenient for the monitor to perform rapid analysis and improving the working efficiency of the monitor;
and sequencing the comprehensive indexes of the candidate pictures in the order from small to large, selecting the picture with the first sequencing as a main picture, sequencing the rest candidate pictures in the order from small to large in the main picture, and displaying.
It is noted that relational terms such as first and second, and the like are 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. Moreover, 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: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. The utility model provides a smart power grid monitoring integrated management system based on data, which is characterized in that 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, wherein the power data monitoring module acquires power data in each monitoring picture, if 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 longer 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 candidate pictures in each monitoring picture is only one, the candidate picture is selected as a main picture, if the number of the candidate pictures is greater than one, the main picture selecting module analyzes data information of each candidate picture, the main picture is selected from the candidate pictures, and the main picture control module amplifies the main picture to a monitor;
the main picture selection module comprises an expert database, a set comparison module and a history exception analysis module, wherein the expert database is used for storing power data exception set information and corresponding main pictures, the set comparison module obtains the set of observation data in all candidate pictures as a monitoring set, compares the monitoring set with the power data exception set information in the patent database, and directly obtains the main pictures corresponding to the power data exception set information if the similarity between a certain group of power data exception set information and the monitoring set is greater than a similarity threshold value, otherwise, the history exception analysis module selects the main pictures according to the history exception condition of the candidate pictures;
the history 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 sequencing module, wherein the item index calculation module acquires the composition item of the observation data in a certain candidate picture as a reference item and the composition item of each observation data when the observation data appears in the history in the candidate picture, then the item index P=Ns/Nd of the candidate picture, wherein Ns is the number of times that the composition item of the observation data is the reference item when the observation data appears in the history in the candidate picture, nd is the number of times that the observation data appears in the history in the candidate picture, and the picture index acquisition module obtains the picture index of the candidate pictureWherein m is the candidate pictureThe method comprises the steps that b is the item number of all electric power data in a candidate picture, the association index acquisition module acquires the association condition of each monitoring picture of history, the association index V of a certain candidate picture is calculated, the comprehensive index calculation module calculates the comprehensive index Z=0.6XU+0.4XV of each candidate picture, the comprehensive index ordering module orders the comprehensive indexes of each candidate picture according to the order from small to large, the picture with the first order is selected as a main picture, and the rest candidate pictures are ordered in the order from small to large according to the comprehensive index and then displayed.
2. The intelligent power grid monitoring integrated management system based on data according to claim 1, wherein: the association index obtaining module calculates an association index of a candidate pictureWherein S is the total number of all monitoring pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j And C is the number of times of abnormality occurrence of the history of the j-th observation data in the candidate picture.
3. A method for comprehensively managing intelligent power grid monitoring based on datamation is characterized in that: the integrated management method comprises the following steps:
acquiring power data in each monitoring picture, if certain power data exist in a certain monitoring picture and are in an abnormal range,
then a duration of time that the power data is within the anomaly range is acquired, and if the duration of time is greater than a duration threshold, the power data is observed,
the monitoring picture containing the observed data is set as a candidate picture,
if there is only one candidate picture in each monitoring picture, 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;
amplifying the main picture to a monitor;
the selecting the main picture from the candidate pictures comprises:
pre-establishing an expert database for storing power data abnormal set information and a corresponding main picture,
acquiring the set of the observation data in all candidate pictures as a monitoring set, comparing the monitoring set with the information of the abnormal set of the electric power data in the patent database,
if the similarity between the abnormal set information of a certain group of power data and the monitoring set is greater than a similarity threshold, directly acquiring a main picture corresponding to the abnormal set information of the group of power data;
otherwise, selecting a 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:
acquiring a reference item for a composition item of observation data in a candidate picture and a composition item of observation data each time when the observation data appears in the history in the candidate picture, then the item index p=ns/Nd of the candidate picture, where Ns is the number of times the reference item is the composition item of observation data when the observation data appears in the history in the candidate picture, nd is the number of times the observation data appears in the history in the candidate picture,
then the picture index of the candidate pictureWhere 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,
collecting the association condition of each monitoring picture of the history, calculating the association index V of a certain candidate picture,
then the composite index z=0.6 x u+0.4 x v for each candidate frame,
and sequencing the comprehensive indexes of the candidate pictures in the order from small to large, and selecting the picture with the first sequence as a main picture.
4. The intelligent power grid monitoring integrated management method based on data according to claim 3, wherein the intelligent power grid monitoring integrated management method based on data is characterized by comprising the following steps of: the calculating the association index V of a certain candidate picture includes:
association index of the candidate pictureWherein S is the total number of all monitoring pictures, T j A is the average value of the number of other monitoring pictures with the observation data when the j-th observation data history of the candidate picture becomes the observation data j And C is the number of times of abnormality occurrence of the history of the j-th observation data in the candidate picture.
5. The intelligent power grid monitoring integrated management method based on the data according to claim 4, wherein the intelligent power grid monitoring integrated management method based on the data is characterized by comprising the following steps: the step of sequencing the comprehensive indexes of the candidate pictures from small to large further comprises the following steps:
and sequencing the rest candidate pictures in the order of the comprehensive indexes from small to large after the main picture is displayed.
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