CN110083640B - Power outage data-based distribution room identification method and device - Google Patents
Power outage data-based distribution room identification method and device Download PDFInfo
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- CN110083640B CN110083640B CN201910339507.2A CN201910339507A CN110083640B CN 110083640 B CN110083640 B CN 110083640B CN 201910339507 A CN201910339507 A CN 201910339507A CN 110083640 B CN110083640 B CN 110083640B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a power failure data-based station area identification method and a power failure data-based station area identification device, wherein the method comprises the following steps: s1, when power failure occurs in a power failure area, acquiring an adjacent area within a specified range of the power failure area, and determining to obtain an associated area associated with the power failure area; s2, respectively acquiring power failure record data of the power failure platform area and power failure record data of each electric energy meter subordinate to the power failure platform area and the related platform area; and S3, matching and comparing the power failure recorded data of the power failure zone with the power failure recorded data of each electric energy meter under the power failure zone and the power failure recorded data of each electric energy meter under the associated zone respectively, and determining whether the household change relations of the power failure zone and each electric energy meter under the associated zone are normal or not according to the comparison result. The invention has the advantages of simple realization method, low cost, high identification efficiency, high identification precision and the like.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a power outage data-based distribution room identification method and device.
Background
The line interweaving of the transformer areas in the power system is complex, the user electric meters are distributed irregularly, the situation that two or more transformer areas are together or nearby and the like often exists, currently, the attribution of the transformer areas of the electric energy meters is usually recorded manually, the attribution of the transformer areas of the intelligent electric meters is recorded only manually, and file making errors are easily caused, for example, some nodes (such as nodes shown by circles in the drawing) of the transformer areas 1 are easily made into files of the transformer areas 2, so that the user variable relation of the electric energy meters in the transformer areas 1 and 2 is abnormal, and the management and planning of electricity utilization by an electricity utilization manager cannot be implemented accurately and reasonably.
The accurate establishment of the station area subscriber relationship is the key point for ensuring the accurate calculation of the line loss of the station area, and the station area identification method is adopted to identify the working station areas of different carrier networks, so that the accuracy of the judgment of the subscriber relationship is improved, and the management of the line loss of the station area is facilitated. For the identification of the station area, the following two methods are mainly adopted in the prior art:
the first is to adopt the mode of manual line splitting power failure before hand, and then line inspection one by one to realize, and this kind of mode is wasted time and energy and can cause inconveniently for the user.
And secondly, station area automatic identification is realized by installing a carrier generator, namely, a power line sends carrier signals containing station area numbers and phase sequence numbers to each terminal device in the station area at preset time intervals, and each power line carrier terminal device determines the station area and the phase sequence of each power line carrier terminal device according to the received carrier signals. The method is complex to realize and operate, a carrier generator is required to be additionally arranged, hardware cost is increased, and the method can only be applied to a station area provided with a power line carrier terminal.
The above-mentioned platform region identification method is not only complicated in implementation operation and long in time consumption, but also not suitable for occasions with high adaptability requirements, and the implementation cost is high, and hardware devices such as a carrier wave generator need to be additionally added, so that it is urgently needed to provide a platform region identification method to reduce the implementation complexity and implementation cost of platform region identification, and meanwhile, the identification efficiency and identification precision can be ensured.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides the power failure data-based station area identification method and device which are simple in implementation method, low in cost, high in identification efficiency and identification precision.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a power outage data-based transformer area identification method comprises the following steps:
s1, when power failure occurs in a power failure area, acquiring an adjacent area within a specified range of the power failure area, and determining to obtain an associated area associated with the power failure area;
s2, respectively acquiring power failure record data of the power failure region and power failure record data of each electric energy meter subordinate to the power failure region and the associated region;
and S3, matching and comparing the power failure record data of the power failure zone with the power failure record data of each electric energy meter under the power failure zone and the power failure record data of each electric energy meter under the associated zone respectively, and determining whether the household change relationship of the power failure zone and each electric energy meter under the associated zone is normal or not according to the comparison result.
As a further improvement of the invention: in step S3, when the power outage record data of the power outage region is compared with the power outage record data of each electric energy meter under the power outage region in a matching manner, whether the household variation relationship of each electric energy meter under the power outage region is normal is determined according to the matching comparison result, if the household variation relationship of the target electric energy meter is determined to be normal, it is determined that the target electric energy meter belongs to the power outage region, if the household variation relationship of the target electric energy meter is determined to be abnormal, the power outage record data of each associated region is obtained, and the region to which the target electric energy meter belongs is searched from the associated regions according to the power outage record data of each associated region.
As a further improvement of the invention: the step of finding out the distribution area to which the target electric energy meter belongs from the associated distribution areas comprises the following steps: and matching and comparing the power failure record data of the target electric energy meter with the power failure record data of each associated station area, and judging that the target electric energy meter belongs to the target associated station area if the power failure record data of the target electric energy meter is matched with the power failure record data of the target associated station area consistently or the deviation is within a preset range.
As a further improvement of the invention: and when the power failure record data of each associated station area is obtained, the power-on time of each associated station area is obtained by performing cluster analysis on the power-on time of all electric energy meters under each associated station area.
As a further improvement of the invention: the step of judging whether the household variation relations of the electric energy meters under the power outage platform area are normal or not comprises the following steps: the method comprises the steps of firstly obtaining power failure record data of a target electric energy meter for specified times, comparing the power failure record data with power failure record data of a power failure platform area, judging that a household change relationship is normal if matching is consistent or deviation is within a preset range, otherwise judging the size relationship between the obtained power failure record data of each electric energy meter and the power failure record data of the power failure platform area, judging that the household change relationship of the target electric energy meter is abnormal if all the obtained power failure record data are smaller than all the obtained power failure record data of each electric energy meter, comparing the obtained power failure record data of the target electric energy meter for the specified times with the obtained power failure record data of the power failure platform area if all the obtained power failure record data are larger than all the obtained power failure record data of the target electric energy meter, and judging whether the household change relationship of the target electric energy meter is normal or not according to a comparison result.
As a further improvement of the present invention, the specific step of determining whether the household variation relationship of each electric energy meter under the blackout platform area is normal includes:
s31, acquiring the power failure recorded data of the target electric energy meter for the previous n times, wherein n =1,2,3 … …, comparing the power failure recorded data with the power failure recorded data of the power failure platform area respectively, if the matching is consistent or the deviation is within a preset range, judging that the household variable relation is normal, and otherwise, executing the step S32;
s32, judging the size relation between the power failure recorded data of the target electric energy meter for the previous n times and the power failure recorded data of the power failure platform area, and if the size relation is smaller than the size relation, judging that the household change relation is abnormal; if all the values are greater than the preset value, the step S33 is executed;
s33, acquiring the power failure record data N + N times before the target electric energy meter, wherein N =1,2,3 … …, comparing the power failure record data with the power failure record data of the power failure platform area respectively, if the power failure record data are matched consistently or the deviation is within a preset range, judging that the user variable relation is normal, and otherwise, executing a step S34;
and S34, judging the size relationship between the power failure recorded data N + N times before the target electric energy meter and the power failure recorded data of the power failure platform area, and if all the power failure recorded data are smaller than the power failure recorded data of the power failure platform area, judging that the household change relationship is abnormal.
As a further improvement of the invention: in step S3, when the power outage record data of the power outage region is compared with the power outage record data of each electric energy meter under the associated region, if the power outage record data of the power outage region is consistent with or within a preset range of the power outage record data of the target electric energy meter under the target associated region, it is determined that the household variation relationship of the target electric energy meter under the target associated region is abnormal, and it is determined that the target electric energy meter under the target associated region is under the power outage region.
As a further improvement of the invention: after the step S2 and before the step S3, the method further includes a step of compensating the power failure data clock of the electric energy meter, and the step includes: comparing the power failure event recording time of each electric energy meter acquired in the step S1 with a standard GPS clock, calculating the clock deviation value of each electric energy meter, and correcting the power failure time and the power on time of each electric energy meter according to the calculated clock deviation value.
A station area identification device based on power outage data comprises:
the association station area determining module is used for acquiring adjacent station areas within the specified range of the power failure station area when the power failure occurs to the station areas, and determining to obtain the association station area associated with the power failure station area;
the data acquisition module is used for respectively acquiring power failure record data of the power failure region and power failure record data of each electric energy meter under the power failure region and the associated region;
and the station area identification module is used for respectively matching and comparing the power failure record data of the power failure station area with the power failure record data of each electric energy meter subordinate to the power failure station area and the power failure record data of each electric energy meter subordinate to the associated station area, and determining whether the household change relationship of the power failure station area and each electric energy meter subordinate to the associated station area is normal or not according to the comparison result.
A computer-readable storage medium having stored thereon a computer program which, when executed, implements the method as described above.
Compared with the prior art, the invention has the advantages that:
1. according to the method, the associated areas within the specified range of the power failure areas are determined, the power failure record data of the power failure areas, the power failure record data of the electric energy meters under the power failure areas and the number of the power failure event records of the electric energy meters under the associated areas are respectively collected to be matched and compared, and the power failure data of the power failure areas, the electric energy meters under the power failure areas and the power failure event records of the electric energy meters under the associated areas are synthesized to identify the areas to which the electric energy meters belong, so that the power failure data of the areas can be fully utilized to realize quick and efficient area identification, the operation is simple and efficient, additional hardware equipment is not needed, and the implementation cost can be greatly reduced.
2. The invention can quickly and accurately find out the electric energy meters with abnormal household variation relations in the power failure area and the associated area by fully utilizing the power failure record data of the power failure area and the associated area and the power failure data of each electric energy meter in the area for matching and comparing, and simultaneously identify the correct affiliated area of the abnormal electric energy meter.
3. The invention further compares and judges the power failure record data of the power failure area with the power failure record data of each electric energy meter in the area, can quickly find out the electric energy meter with abnormal household transformation relation in the power failure area, and can quickly find out the correct affiliated area of the abnormal electric energy meter from the associated area by combining the power failure record data of the associated area to carry out supplementary matching comparison.
4. The invention further collects the power failure record data of the collection terminal of the power failure zone when the target zone, the planned or fault power failure zone and the operation zone are newly added or modified respectively, compares the power failure record data with the power failure record of each electric energy meter penetrating the subordinated zone of the power failure zone and each electric energy meter of the subordinated zone of the associated zone, can carry out the user-to-user relationship check when the target zone is newly added or modified, and realizes the user-to-user relationship check by utilizing the power failure event in the process of the planned or fault power failure of the zone and the operation of the zone.
Drawings
Fig. 1 is a schematic diagram illustrating the principle of abnormal subscriber relationship in a distribution room.
Fig. 2 is a schematic flow chart illustrating an implementation of the power outage data-based station area identification method according to the embodiment.
Fig. 3 is a schematic diagram of an execution flow between systems for implementing user-variant relationship verification in an embodiment of the present invention.
Fig. 4 is a detailed flowchart illustrating the implementation of the platform area identification in the embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and specific preferred embodiments of the description, without thereby limiting the scope of protection of the invention.
As shown in fig. 2, the method for identifying a distribution area based on blackout data according to this embodiment includes the steps of:
s1, determining a relevant station area: when power failure occurs in the power failure area, acquiring an adjacent power failure area within an appointed range of the power failure area, and determining to obtain an associated area associated with the power failure area;
s2, data acquisition: respectively acquiring power failure record data of a power failure platform area and power failure record data of each electric energy meter under the power failure platform area and the associated platform area;
s3, identifying the transformer area: and respectively matching and comparing the power failure record data of the power failure district with the power failure record data of each electric energy meter under the power failure district and the power failure record data of each electric energy meter under the associated district, and determining whether the household transformation relation of the power failure district and each electric energy meter under the associated district is normal or not according to the comparison result.
If the outdoor transformer relationship in the power distribution area is normal, the records of the power failure events in the power distribution area and the power meters under the power distribution area are consistent, and the power meters with abnormal outdoor transformer relationship in the power distribution area are more likely to belong to adjacent power distribution areas.
In this embodiment, the blackout recording data is specifically blackout recording time, which includes blackout time and power-on time, and of course, other blackout recording parameters may be set according to actual requirements, so as to further improve the calibration accuracy.
In the embodiment, adjacent power distribution areas within a specified distance of a power failure power distribution area are firstly obtained to obtain an associated power distribution area, power failure record data of the power failure power distribution area are acquired through a power distribution area terminal, power failure records of the power failure power distribution area and electric energy meters under the associated power distribution area are automatically penetrated through by a power utilization information acquisition system, power failure record data of each electric energy meter are acquired, and the power failure record data acquired are used for identifying the power distribution area, so that the power failure/power up event recording functions of the acquisition terminal, the intelligent electric energy meter and the TTU in the power distribution area are utilized to quickly judge the household-to-transformer corresponding relation of the electric energy meters in the power distribution area.
In this embodiment, when a target platform area is newly added or modified, the method further includes performing power outage/transmission operation for a specified duration by the console area, recording time points of the power outage/transmission operation, and performing steps S1 to S3 to perform user-to-user relationship verification on the newly added or modified target platform area. When a target platform area is newly added or modified, the power cut/power transmission operation is actively controlled for a short time, the user change relationship of the platform area can be updated according to the method after the power cut time at the moment is recorded, the complex platform area identification process does not need to be executed again, and the checking of the user change relationship of the newly added or modified platform area can be efficiently completed.
In a specific application embodiment, when a target station area is newly added or modified, after the station area has power transmission conditions, short-time power cut/transmission operation of user change checking is added, power cut and transmission time are recorded after power transmission is stopped for a specified short time, and the station area needing to be checked and a checking time interval are transmitted; after receiving the checking task, acquiring power failure record data according to the checking method, finishing the judgment and checking of the user variation relationship, generating a user variation relationship corresponding table and a user variation dynamic table, and synchronously feeding back related information to the PMS production system.
In this embodiment, when the target block area stops/powers or fails according to a designated schedule, recording the time point of the stop/power operation after the stop/power operation is completed, and executing steps S1 to S3 to perform the user-to-user relationship check on the target block area by using the block area schedule or the failure power failure data, so as to implement the passive power failure check of the operating block area, and the user-to-user relationship check can be implemented by fully using the schedule and the failure power failure data in the block area operating process.
In the passive power outage verification of this embodiment, a distribution area in which only one distribution transformer has power outage at the same time on the same line and the power outage duration reaches a preset interval (for example, 8 minutes, which can be configured according to time requirements) is brought into the area range to be verified.
In the embodiment, the method further comprises the steps of identifying the power failure event of the electric energy meter/acquisition terminal at each gateway in the target area in the operation process of the target area, and when the power failure event is identified, turning to the steps S1 to S3 to actively check the household-to-household relation of the target area, so that the active power failure check of the operation area is realized, and the real-time power failure data of the meters and the terminals at each gateway in the operation process of the area can be fully utilized to actively check the household-to-household relation, so that the change can be timely discovered when the household-to-household relation changes, and the real-time accuracy of the household-to-household relation of the area is ensured.
In a specific application embodiment, when various plans or fault power cut/transmission events occur in the operation process of a station area, the recorded data of the plans and the fault power cut/transmission events are fully utilized, user change checking is added by combining the plans and the fault power cut events, after power cut and transmission operation is completed, power cut and transmission time points are recorded after power transmission is stopped for a specified short time, and the station area needing to be checked and a checking time interval are transmitted; and collecting power failure record data according to the checking method, finishing the judgment and checking of the user variation relationship, generating a user variation relationship corresponding table and a user variation dynamic table, and synchronously feeding back related information to the PMS production system.
In a specific application embodiment, the power consumption information acquisition system actively identifies a power failure event of a gateway table/terminal of a platform area, the power failure event acquisition task of the intelligent electric meter of the platform area is triggered after the power failure event is identified, the household variation relation is judged and checked according to the checking method, a household variation relation corresponding table and a household variation dynamic table are generated, and the household variation relation corresponding table and the household variation dynamic table are pushed to an application system and a PMS production system.
In the embodiment, when a target platform area, a platform area plan or fault power failure and operation platform area are newly added or modified, power failure record data of the acquisition terminal of the power failure platform area is acquired and compared with power failure records of electric energy meters penetrating through subordinates of the power failure platform area and electric energy meters subordinates of the associated platform area, so that the user-to-user relationship verification can be performed when the target platform area is newly added or modified, and the user-to-user relationship verification can be realized by utilizing power failure events in the platform area plan or fault power failure and operation process of the platform area.
In a specific application embodiment, the power consumption information acquisition system, the application system and the PMS system cooperate to complete verification of the household-to-maintenance relationship, as shown in fig. 3, the PMS system generates power failure information of a daily operation and maintenance plan, the power failure information acquisition system sends the power failure information of the daily operation and maintenance plan to the power consumption information acquisition system through the application system, the power consumption information acquisition system starts to check the household-to-maintenance relationship, generates a platform area directional power failure application worksheet, and transmits the worksheet to the PMS system through the application system, the PMS system combines power failure planning and arranges special power failure, after power failure operation is executed, the application system receives platform area power failure application feedback and sends the platform area power failure application feedback to the user information acquisition system, the power consumption information acquisition system monitors power failure data of the platform area planning power failure, unplanned power failure, directional power failure and the like, acquires power failure records of related terminals and the electric energy meter, after platform area identification is performed according to the steps S1 to S3, whether the household-to-change relationship abnormality exists is judged, and if the household-to-change relationship abnormality file is generated, the household-to-change relationship abnormality file is changed based on the household-change relationship abnormality table.
In step S2, when the collected power failure record data of the electric energy meter and the clock collection success rate of the electric energy meter reach the corresponding preset threshold simultaneously, step S3 is executed. If the success rate of acquiring the clock of the electric meter and the power failure record of the electric meter is too low, the user change file check analysis result is influenced, the electric meter which fails to acquire is subjected to complementary acquisition according to a preset complementary acquisition period, the success rate of acquiring the power failure event of the electric meter is improved as much as possible through field data acquisition, and the subsequent user change check step is carried out only when the power failure record and the clock acquisition success rate of the electric meter reach certain preset standards simultaneously, so that the accuracy of the user change check is further ensured.
The clock of the electric energy meter may have a deviation, in this embodiment, after step S2 and before step S3, the clock compensation step of the power failure data of the electric energy meter is further included to compensate and correct the power failure record data of the electric energy meter, so as to ensure the reliable validity of the power failure event data of the electric energy meter, and the clock compensation step of the power failure data of the electric energy meter specifically includes: comparing the recorded time of the power failure events of the electric energy meters acquired in the step S1 with a standard GPS clock, calculating the clock deviation value of each electric energy meter, and correcting the power failure time and the power-on time of each electric energy meter according to the calculated clock deviation value.
In a specific application embodiment, the master station processes the power-off event data of the user electric energy meter to ensure that the successfully collected electric energy meter event data is processed into effective data which can participate in the checking of the user variable relationship, specifically, after the power-off event on the electric energy meter in the transformer area is penetrated, the clock deviation of the electric energy meter is calculated by comparing the time of the penetrated electric energy meter with a standard GPS clock, the power-off time and the power-on time of the power-off event of the electric energy meter are corrected according to the deviation value, and the correction expression is as follows:
corrected blackout time = original blackout time + clock offset value (1)
Corrected power-on time = original power-on time + clock deviation value (2)
The terminal also has clock deviation when reporting the power failure event, in this embodiment, specifically, if the terminal clock deviation does not exceed the preset K minutes, the user variable relationship check is started, and if the terminal clock deviation exceeds the preset K minutes, it is determined that the user variable relationship check service condition is not met, the user variable relationship check is not executed, and the reliability and the effectiveness of the user variable relationship check are further ensured.
In step S3 in this embodiment, when the power outage record data of the power outage region is compared with the power outage record data of each electric energy meter under the power outage region in a matching manner, it is specifically determined whether the household variation relationship of each electric energy meter is normal according to the matching comparison result, if the household variation relationship of the target electric energy meter is determined to be normal, it is determined that the target electric energy meter belongs to the power outage region, if the household variation relationship of the target electric energy meter is determined to be abnormal, the power outage record data of each associated region is obtained, and the region to which the target electric energy meter belongs is found from the associated regions according to the power outage record data of each associated region. The power failure record data of the power failure region is compared with the power failure record data of each electric energy meter in the region for judgment, the electric energy meter with abnormal household variation relation in the power failure region can be found out, the power failure record data of the associated region is combined to determine the region to which the abnormal electric energy meter belongs, the electric energy meter with abnormal household variation relation in the power failure region can be rapidly identified, and meanwhile, the correct region to which the abnormal electric energy meter belongs can be rapidly found out.
In this embodiment, the step of finding the distribution area to which the target electric energy meter belongs from the associated distribution areas includes: and matching and comparing the power failure record data of the target electric energy meter with the power failure record data of each associated station area, and judging that the target electric energy meter belongs to the target associated station area if the power failure record data of the target electric energy meter is matched with the power failure record data of the target associated station area consistently or the deviation is within a preset range. If the abnormal electric energy meter with abnormal household change relationship in the power failure distribution area is matched with the power failure record data of a certain associated distribution area consistently, it is indicated that the abnormal electric energy meter belongs to the associated distribution area.
In this embodiment, when the power outage recorded data of each associated station area is obtained, specifically, the power outage recorded data of each associated station area is obtained by performing cluster analysis on the power-on time of all electric energy meters belonging to each associated station area, and the power outage recorded data of each associated station area can be obtained.
In this embodiment, the step of determining whether the user variation relationship of each electric energy meter is normal includes: the method comprises the steps of firstly obtaining power failure record data of a target electric energy meter for specified times and comparing the power failure record data with power failure record data of a power failure platform area, judging that a household change relationship is normal if matching is consistent or deviation is within a preset range, otherwise judging the size relationship between the obtained power failure record data of each electric energy meter and the power failure record data of the power failure platform area, judging that the household change relationship of the target electric energy meter is abnormal if all the obtained power failure record data of each electric energy meter are smaller than all the obtained power failure record data of the power failure platform area, re-obtaining the power failure record data of the target electric energy meter for the specified times and comparing the power failure record data of the power failure platform area, and judging whether the household change relationship of the target electric energy meter is normal or not according to a comparison result. If the recording time of each power failure of the electric energy meter is consistent with the recording time of the power failure of the transformer area, the relationship of the household transformer is normal, if the recording time of each power failure of the electric energy meter is less than the recording time of the power failure of the transformer area, the relationship of the household transformer is abnormal, if the recording time of each power failure of the electric energy meter is greater than the recording time of the power failure of the transformer area, the relationship of the household transformer may be normal or abnormal due to the reporting time difference of the power failure time.
In this embodiment, the specific step of determining whether the household variable relationship of each electric energy meter is normal includes:
s31, acquiring power failure record data of the target electric energy meter for the previous n times, wherein n =1,2,3 … …, comparing the power failure record data with the power failure record data of the power failure area respectively, if the power failure record data are matched consistently or the deviation is within a preset range, judging that the household change relation is normal, and otherwise, executing a step S32;
s32, judging the size relationship between the previous n times of power failure recorded data of the target electric energy meter and the power failure recorded data of the power failure platform area, and if all the power failure recorded data are smaller than the power failure recorded data of the power failure platform area, judging that the household change relationship is abnormal; if all the values are greater than the preset value, the step S33 is executed;
s33, acquiring power failure recorded data N + N times before the target electric energy meter, wherein N =1,2,3 … …, comparing the power failure recorded data with the power failure recorded data of the power failure platform area respectively, if the power failure recorded data are matched consistently or the deviation is within a preset range, judging that the household variable relation is normal, and otherwise, executing a step S34;
and S34, judging the size relation between the power failure recorded data of the target electric energy meter for the first N + N times and the power failure recorded data of the power failure area, and if all the power failure recorded data are smaller than all the power failure recorded data of the power failure area, judging that the household change relation is abnormal.
In a specific application embodiment, the value of N can be 3,N to 6, that is, the blackout recording times 1,2, and 3 times before the electric energy meter are firstly obtained for comparison, if the blackout recording times 1,2, and 3 times before the electric energy meter are all greater than the blackout recording time of the platform area, the blackout recording times 4-10 times before the electric energy meter are obtained again for comparison, and the values of N and N can be specifically configured according to actual requirements.
In this embodiment, when the household variable relationship is determined to be waiting, the power outage record data of the target electric energy meter in the specified times is further obtained and compared with the power outage record data of the target station area, if the power outage record data is consistent with or smaller than the power outage record data, the household variable relationship is determined to be abnormal, if the power outage record data is larger than the power outage record data, the steps are executed again until the household variable relationship is determined to be normal or abnormal, the checking is quitted, and the household variable relationship can be finally determined by using the power outage record data of the electric energy meter for multiple times.
In step S3 in this embodiment, when the blackout record data of the blackout area is compared with the blackout record data of each electric energy meter under the associated area in a matching manner, if the blackout record data of the blackout area is consistent with or has a deviation within a preset range with the blackout record data of the target electric energy meter under the associated area, it is determined that the target electric energy meter under the associated area belongs to the blackout area, and the electric energy meter incorrectly divided into the associated area in the blackout area can be quickly found out.
Through the steps, all the electric energy meters with abnormal household variation relations in the power failure distribution area and the associated distribution area can be quickly and accurately found, and meanwhile, the correct affiliated distribution area of the abnormal electric energy meters is identified.
In a specific application embodiment of the present invention, unplanned power outage and directional power outage such as planned power outage and fault power outage in a daily operation and maintenance plan of a transformer area are utilized to collect power outage events of a collection terminal of a relevant transformer area and power outage records of a relevant electric energy meter, as shown in fig. 4, detailed steps for realizing transformer area identification are as follows:
step 1: obtaining a household transformer checking correlation zone
And the power utilization information acquisition system senses power failure of the power distribution area by using the acquisition terminal, and then the adjacent power distribution area within the specified distance of the power failure power distribution area is taken, so that the associated power distribution area is obtained.
Step 2: power failure record acquisition of electric energy meter
The power utilization information acquisition system automatically penetrates through the power failure zone and the power failure record data of the subordinate electric energy meters of the associated zone.
And step 3: clock compensation for power-off event of electric energy meter
And comparing the time of the electric energy meter which penetrates back with the standard GPS clock to calculate the clock deviation of the electric energy meter, and correcting the power failure time and the power-on time recorded by the electric energy meter by using the clock deviation.
And 4, step 4: matching of collection terminal power failure event and electric energy meter power failure record
(1) Power failure area acquisition terminal and electric energy meter power failure event matching
Matching the collection terminal of the power failure area with the recording time of the power stop events of the electric energy meters, comparing the power stop events with the power up time of all the electric energy meters under the same area by taking the power up time of the collection terminal of the area as a reference, and judging that the household variation relation is normal if the power stop time of the collection terminal and the power up time deviation of the electric energy meters (1, 2 and 3 times) in the same area are within a preset range; if the power-on time of the electric energy meter (1, 2 and 3 times) is less than the power-off time of the acquisition terminal, judging that the household variable relation is abnormal; if the power-on time of the electric energy meter (1, 2 and 3 times) is all longer than the power-on time of the acquisition terminal, automatically penetrating the power-on time of the electric energy meter (4, 5, … and 10 times), after penetrating, continuously comparing the power-off time of the acquisition terminal with the power-on time of the electric energy meter, and if the power-on time deviation of the electric energy meter (4, 5, … and 10 times) is within a preset range, judging that the user variation relationship is normal; if the power-on time of the electric energy meters in the electric energy meters (4, 5, … and 10 times) is all longer than the power-on time of the acquisition terminal, the user variable relationship is determined to be undetermined, and further determination is needed.
(2) Power-off event supplementary matching of electric energy meter associated with distribution area
Comparing the power-on time of the power-off area acquisition terminal with the power-on time of all the electric energy meters under the associated area by taking the power-on time of the power-off area acquisition terminal as a reference, and judging that the household transformer relationship is abnormal if the power-on time of the electric energy meters under the associated area is within a preset range of the power-on time deviation of the power-off record of the power-off area acquisition terminal, namely the electric energy meters belong to the power-off area; and for the household-variant relation abnormal electric energy meters, performing cluster analysis on the power-on time of all the electric energy meters in the associated distribution areas to obtain the power-on time of the associated distribution areas, respectively comparing the household-variant relation abnormal electric energy meters with the power-on time of each associated distribution area, and if the deviation of the power-on time of the household-variant relation abnormal electric energy meters and the power-on time of a certain associated distribution area is within a preset range, judging that the household-variant relation abnormal electric energy meters belong to the corresponding associated distribution areas.
In this embodiment, after step S3, a user variation relationship validity filtering step is further included, and the step includes: if the user variable relation abnormal ratio is smaller than the preset threshold, the user variable checking result is judged to be valid, if the user variable relation abnormal ratio is larger than the preset threshold, a large number of suspected user variable relation abnormalities are judged to occur, the user variable checking result is doubtful, secondary checking needs to be executed, the steps S1 and S2 are executed again to perform secondary checking, and the user variable relation abnormal ratio can be calculated according to the following formula:
abnormal rate of outdoor variation relationship = abnormal constant of outdoor variation relationship/number of users involved in outdoor variation verification (3)
In the embodiment, the table area is used as a statistical dimension to perform validity filtering on the checking result of the user variable relationship, when the checking result of the user variable relationship reaches a certain value, it is indicated that a large number of suspected abnormalities of the user variable relationship exist, and then secondary checking is further performed for further verification.
This embodiment platform district recognition device based on power failure data includes:
the association station area determining module is used for acquiring adjacent station areas within the specified range of the power failure station area when the power failure occurs to the station areas, and determining to obtain the association station area associated with the power failure station area;
the data acquisition module is used for respectively acquiring power failure record data of the power failure platform area and power failure record data of each electric energy meter under the power failure platform area and the associated platform area;
and the station area identification module is used for respectively matching and comparing the power failure record data of the power failure station area with the power failure record data of each electric energy meter under the power failure station area and the power failure record data of each electric energy meter under the associated station area, and determining whether the household change relationship of the power failure station area and each electric energy meter under the associated station area is normal or not according to the comparison result.
In this embodiment, the station area identification device based on the outage data corresponds to the station area identification method based on the outage data one to one, and is not described herein any more.
The present embodiment provides a computer-readable storage medium storing a computer program, which when executed implements the method described above.
The foregoing is considered as illustrative of the preferred embodiments of the invention and is not to be construed as limiting the invention in any way. Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical spirit of the present invention should fall within the protection scope of the technical scheme of the present invention, unless the technical spirit of the present invention departs from the content of the technical scheme of the present invention.
Claims (10)
1. A power outage data-based distribution room identification method is characterized by comprising the following steps:
s1, when power failure occurs in a power failure area, acquiring an adjacent area within a specified range of the power failure area, and determining to obtain an associated area associated with the power failure area;
s2, respectively acquiring power failure record data of the power failure region and power failure record data of each electric energy meter subordinate to the power failure region and the associated region;
and S3, matching and comparing the power failure record data of the power failure area with the power failure record data of each electric energy meter under the power failure area and the power failure record data of each electric energy meter under the associated area respectively, and determining whether the household transformation relation of the power failure area and each electric energy meter under the associated area is normal or not according to the comparison result.
2. The power outage data-based station area identification method according to claim 1, wherein in step S3, when the power outage record data of the power outage station area is compared with the power outage record data of each energy meter under the power outage station area in a matching manner, whether the household variation relationship of each energy meter under the power outage station area is normal is determined according to the comparison result, if the household variation relationship of the target energy meter is determined to be normal, the target energy meter is determined to belong to the power outage station area, if the household variation relationship of the target energy meter is determined to be abnormal, the power outage record data of each associated station area is obtained, and the station area to which the target energy meter belongs is searched from the associated station areas according to the power outage record data of each associated station area.
3. The method as claimed in claim 2, wherein the step of finding the power distribution area to which the target power meter belongs in the associated power distribution areas comprises: and matching and comparing the power failure record data of the target electric energy meter with the power failure record data of each associated station area, and judging that the target electric energy meter belongs to the target associated station area if the power failure record data of the target electric energy meter is matched with the power failure record data of the target associated station area consistently or the deviation is within a preset range.
4. The power outage data-based distribution room identification method according to claim 2, wherein when the power outage record data of each associated distribution room is obtained, the power-on time of each associated distribution room is obtained by performing cluster analysis on the power-on time of all electric energy meters under each associated distribution room.
5. The method for identifying a distribution area based on blackout data according to claim 2,3 or 4, wherein the step of determining whether the user-to-user relationship of each electric energy meter under the blackout distribution area is normal comprises the steps of: the method comprises the steps of firstly obtaining power failure record data of a target electric energy meter for specified times, comparing the power failure record data with power failure record data of a power failure platform area, judging that a household change relationship is normal if matching is consistent or deviation is within a preset range, otherwise judging the size relationship between the obtained power failure record data of each electric energy meter and the power failure record data of the power failure platform area, judging that the household change relationship of the target electric energy meter is abnormal if all the obtained power failure record data are smaller than all the obtained power failure record data of each electric energy meter, comparing the obtained power failure record data of the target electric energy meter for the specified times with the obtained power failure record data of the power failure platform area if all the obtained power failure record data are larger than all the obtained power failure record data of the target electric energy meter, and judging whether the household change relationship of the target electric energy meter is normal or not according to a comparison result.
6. The method according to claim 5, wherein the step of determining whether the household variation relationship of the electric energy meters under the blackout distribution area is normal comprises:
s31, acquiring the power failure recorded data of the target electric energy meter for the previous n times, wherein n =1,2,3 … …, comparing the power failure recorded data with the power failure recorded data of the power failure platform area respectively, if the matching is consistent or the deviation is within a preset range, judging that the household variable relation is normal, and otherwise, executing the step S32;
s32, judging the size relation between the power failure recorded data of the target electric energy meter for the previous n times and the power failure recorded data of the power failure platform area, and if the size relation is smaller than the size relation, judging that the household change relation is abnormal; if all the values are greater than the preset value, the step S33 is executed;
s33, acquiring the power failure record data N + N times before the target electric energy meter, wherein N =1,2,3 … …, comparing the power failure record data with the power failure record data of the power failure platform area respectively, if the power failure record data are matched consistently or the deviation is within a preset range, judging that the user variable relation is normal, and otherwise, executing a step S34;
and S34, judging the size relationship between the power failure recorded data N + N times before the target electric energy meter and the power failure recorded data of the power failure platform area, and if all the power failure recorded data are smaller than the power failure recorded data of the power failure platform area, judging that the household change relationship is abnormal.
7. The method according to any one of claims 1 to 4, wherein in step S3, when the blackout record data of the blackout area is compared with the blackout record data of the electric energy meters under the associated area, if the blackout record data of the blackout area matches or deviates within a predetermined range with the blackout record data of the target electric energy meter under the target associated area, it is determined that the household-to-household relationship of the target electric energy meter under the target associated area is abnormal, and it is determined that the target electric energy meter under the target associated area is affiliated to the blackout area.
8. The method for identifying a distribution room based on blackout data according to any one of claims 1 to 4, wherein after the step S2 and before the step S3, the method further comprises a step of clock compensation of blackout data of the electric energy meter, and the step comprises the following steps: comparing the recorded time of the power failure events of the electric energy meters acquired in the step S1 with a standard GPS clock, calculating the clock deviation value of each electric energy meter, and correcting the power failure time and the power-on time of each electric energy meter according to the calculated clock deviation value.
9. The utility model provides a platform district recognition device based on outage data which characterized in that includes:
the association station area determining module is used for acquiring an adjacent station area within the specified range of the power failure station area when the power failure occurs in the station area, and determining to obtain an association station area associated with the power failure station area;
the data acquisition module is used for respectively acquiring power failure record data of the power failure region and power failure record data of each electric energy meter under the power failure region and the associated region;
and the station area identification module is used for respectively matching and comparing the power failure record data of the power failure station area with the power failure record data of each electric energy meter subordinate to the power failure station area and the power failure record data of each electric energy meter subordinate to the associated station area, and determining whether the household change relationship of the power failure station area and each electric energy meter subordinate to the associated station area is normal or not according to the comparison result.
10. A computer-readable storage medium storing a computer program which, when executed, implements the method of any one of claims 1 to 8.
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| CN112444687A (en) * | 2019-08-29 | 2021-03-05 | 北京科东电力控制系统有限责任公司 | Effective power failure event studying and judging method and device |
| CN110456206A (en) * | 2019-09-09 | 2019-11-15 | 广东电网有限责任公司 | A kind of family becomes the judgment method of relationship and judges system |
| CN110942236B (en) * | 2019-11-14 | 2023-05-09 | 国网浙江海宁市供电有限公司 | Abnormal user identification method for comprehensive power failure record and power consumption data |
| CN113447882B (en) * | 2021-06-01 | 2022-09-09 | 国网河北省电力有限公司营销服务中心 | Fault processing method based on electric energy meter, server and terminal |
| CN115061013B (en) * | 2022-08-17 | 2022-12-30 | 国网江西省电力有限公司电力科学研究院 | Low-voltage common fault studying and judging method and system based on power failure event big data analysis |
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