CN112821566A - Intelligent statistical method and device for remote control intervention processing of distribution network faults - Google Patents
Intelligent statistical method and device for remote control intervention processing of distribution network faults Download PDFInfo
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Abstract
The application discloses an intelligent statistical method and device for remote control intervention processing of distribution network faults, comprising the following steps of: firstly, acquiring a relation table related to remote control failure of an automatic switch; extracting key information of the distribution network equipment fault tripping transaction list in the relation table, and storing a distribution network equipment fault tripping record matched with the key information into a new database; then, associating a new database with the distribution network equipment fault tripping transaction list, performing association matching on the distribution network equipment fault tripping transaction list, the distribution network automatic switch remote control list and the distribution network automatic switch ledger table, and outputting a result after the association matching; and finally, carrying out statistics and classification on the results after correlation matching, and classifying the results into fault work order remote control processing statistics, fault remote control execution result statistics and fault remote control processing process statistics. Therefore, intelligent analysis and statistics of the remote control intervention processing conditions of the distribution network faults are realized, and the technical problems that the workload of the existing manual statistics and analysis means is large and errors are easy to occur are solved.
Description
Technical Field
The application relates to the technical field of power grid operation and maintenance, in particular to an intelligent statistical method and device for remote control intervention processing of distribution network faults.
Background
The distribution network remote control switch is an important ring for the development of the whole distribution network, and the coverage rate and the distribution rationality of the distribution network remote control switch directly influence the condition that a dispatching desk can transfer users and loads when a 10kV line of the whole distribution network breaks down.
At present, the situation of intervention processing of fault isolation and power transmission recovery through remote control when a fault occurs in a distribution network still remains depending on message analysis, the remote control isolation and remote control power restoration situation of the fault and the related success rate still remain in manual analysis, an effective intelligent analysis means is lacked, the statistical analysis of the access rate and the access situation of a remote control switch after the fault occurs in the whole 10kV line of the distribution network still remains to be promoted, obviously, the means of traditional manual statistics and manual analysis has larger workload and is easy to cause errors.
Therefore, an intelligent statistical method and an intelligent statistical device for remote intervention processing of distribution network faults are needed to intelligently count the remote intervention processing conditions when the distribution network fails so as to improve the level of distribution network management.
Disclosure of Invention
The embodiment of the application provides an intelligent statistical method and device for remote control intervention processing of distribution network faults, and the method and device are used for solving the technical problems that the existing manual statistical analysis means is large in workload and prone to errors.
In view of the above, a first aspect of the present application provides an intelligent statistics for remote intervention processing of distribution network faults, where the method includes:
s1, obtaining a relation table related to the remote control failure of the automatic switch, wherein the relation table comprises: the distribution network equipment fault tripping abnormal operation list, the distribution network automatic switch remote control list and the distribution network automatic ledger table;
s2, storing the tripping records of the distribution network equipment matched with the key information of the fault tripping transaction list of the distribution network equipment into a first database;
s3, matching the distribution network equipment trip record in the first database with the distribution network equipment fault trip transaction list to obtain a distribution network equipment fault trip transaction record, and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the distribution network equipment fault trip transaction record;
s4, judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list exist between the power failure time and the power restoration time, and if so, associating the distribution network automatic switch remote control record with the distribution network equipment fault tripping abnormal operation record;
s5, matching the remote control records of the distribution network automatic switch with the distribution network automatic standing book table, saving the successfully matched distribution network automatic standing book data as effective automatic standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automatic standing book data;
and S6, performing fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, performing fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and performing fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
Optionally, after step S6, the method further includes:
and respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
Optionally, the first statistical rule specifically includes:
and judging whether the distribution network automation switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record or not in the effective automatic ledger data, if so, counting as remote control processing, and otherwise, counting as non-remote control processing.
Optionally, the second statistical rule specifically includes:
and judging whether the remote control results recorded by the distribution network automation switch in the effective automatic standing book data are all remote control failures or not, if so, counting as fault remote control failures, and otherwise, counting as fault remote control successes.
Optionally, the third statistical rule specifically includes:
when the switch position type in the effective automation account data is a contact switch, judging whether the effective automation account data contains a record of successful remote control closing, if so, defining that the remote control is successful and the power transfer is successful, otherwise, defining that the remote control power transfer is failed;
when the effective automatic account data is successfully matched with the fault equipment ID of the tripping record of the distribution network equipment and the switch position type is a non-contact switch, judging whether the effective automatic account data contains a record of successful remote control closing, if so, defining the effective automatic account data as successful trial delivery, otherwise, defining the effective automatic account data as failed trial delivery;
and when the effective automatic account data fails to be matched with the fault equipment ID of the distribution network equipment trip record and the switch position type is a non-contact switch, judging whether the effective automatic account data contains the record of the success of remote control switching-off, if so, defining that the fault is successfully isolated, otherwise, defining that the remote control isolation fails.
Optionally, the key information is: permanently faulted and non-dedicated lines.
The second aspect of the present application provides an intelligent statistical device for remote intervention processing of distribution network faults, the device includes:
an obtaining module, configured to obtain a relationship table related to a remote control failure of an automation switch, where the relationship table includes: the distribution network equipment fault tripping abnormal operation list, the distribution network automatic switch remote control list and the distribution network automatic ledger table;
the first matching module is used for storing the tripping records of the distribution network equipment matched with the key information of the fault tripping transaction list of the distribution network equipment to a first database;
the extraction module is used for matching the tripping records of the distribution network equipment in the first database with the fault tripping transaction list of the distribution network equipment to obtain fault tripping transaction records of the distribution network equipment and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the fault tripping transaction records of the distribution network equipment;
the judging module is used for judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list have the same transformer substation name and the same line name between the power failure time and the power restoration time, and if so, the distribution network automatic switch remote control record and the distribution network equipment fault tripping abnormal operation record are associated;
the second matching module is used for matching the remote control records of the distribution network automatic switch with the distribution network automatic standing book table, saving the successfully matched distribution network automatic standing book data as effective automatic standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automatic standing book data;
and the counting module is used for performing fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, performing fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and performing fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
Optionally, the method further comprises: a generation module;
and the generating module is used for respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
Optionally, the first statistical rule specifically includes:
and judging whether the distribution network automation switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record or not in the effective automatic ledger data, if so, counting as remote control processing, and otherwise, counting as non-remote control processing.
Optionally, the second statistical rule specifically includes:
and judging whether the remote control results recorded by the distribution network automation switch in the effective automatic standing book data are all remote control failures or not, if so, counting as fault remote control failures, and otherwise, counting as fault remote control successes.
According to the technical scheme, the method has the following advantages:
the application provides an intelligent statistical method for remote control intervention processing of distribution network faults, which comprises the steps of firstly, obtaining a relational table related to remote control failure of an automatic switch; extracting key information of the distribution network equipment fault tripping transaction list in the relation table, and storing a distribution network equipment fault tripping record matched with the key information into a new database; then, associating a new database with the distribution network equipment fault tripping transaction list, sequentially associating and matching the distribution network equipment fault tripping transaction list, the distribution network automatic switch remote control list and the distribution network automatic switch ledger table, and outputting a result after association and matching; and finally, carrying out statistical classification on the result after the correlation matching, wherein the classification is as follows: fault work order remote control processing statistics, fault remote control execution result statistics and fault remote control processing process statistics. The intelligent statistical method can realize intelligent analysis and statistics on the remote control intervention processing condition of the distribution network fault, thereby solving the technical problems that the existing manual statistical analysis means has large workload and is easy to generate errors.
Drawings
Fig. 1 is a schematic flowchart of a first embodiment of an intelligent statistical method for remote control intervention processing of a distribution network fault according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a second embodiment of an intelligent statistical method for remote control intervention processing of a distribution network fault according to the present application;
fig. 3 is a structural diagram of an embodiment of an intelligent statistics apparatus for remote control intervention processing of a distribution network fault provided in an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a schematic flowchart of a first embodiment of an intelligent statistical method for remote intervention processing of a distribution network fault according to an embodiment of the present application.
The intelligent statistical method for remote control intervention processing of distribution network faults, provided by the embodiment of the application, comprises the following steps:
It should be noted that, in the present embodiment, the relational table related to the remote control failure of the automation switch is obtained through the underlying multi-metadata database. It can be understood that the distribution network equipment fault tripping transaction list is the condition that equipment moves when the equipment fails to trip; the distribution network automation switch remote control list is the condition that a distribution network automation system sends a remote control instruction; the distribution network automation ledger table is various instruction sets of the distribution network automation system.
And 102, storing the tripping records of the distribution network equipment matched with the key information of the fault tripping transaction list of the distribution network equipment into a first database.
It should be noted that, in this embodiment, first, by extracting the key information of the fault trip transaction list of the distribution network device, it can be understood that the key information is, for example: the fault type in the distribution network equipment fault tripping transaction list is a permanent fault or a non-permanent fault, for example, the fault type is key information of a non-private line or a private line, and the key information selected by the implementation comprises the following steps: the fault type is "permanent fault" and is "non-dedicated line"; and then, matching the distribution network equipment trip records by taking the key information as a matching condition to obtain the distribution network equipment trip records with the key information and storing the distribution network equipment trip records in a new database.
And 103, matching the distribution network equipment trip record in the first database with the distribution network equipment fault trip transaction list to obtain a distribution network equipment fault trip transaction record, and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the distribution network equipment fault trip transaction record.
It can be understood that, in the embodiment, the fault trip transaction record of the distribution network equipment, which matches the trip record of the distribution network equipment in the first database, is first obtained, and then the blackout time, the power restoration time, the transformer substation name and the line name of the record are extracted. It should be noted that, when the power failure occurs, that is, when the distribution network fails, the power failure of the distribution network line is caused by remote intervention processing; similarly, the power restoration time is the time for restoring the power supply of the distribution network line through remote intervention; and the name of the transformer substation and the name of the line, namely the name of the transformer substation and the name of the line with tripping abnormality, appear when the distribution network equipment fails.
And 104, judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list have the same transformer substation name and line name between the power failure time and the power restoration time, and if so, associating the distribution network automatic switch remote control record with the distribution network equipment fault tripping abnormal operation record.
It can be understood that, in this embodiment, the distribution network automatic switch remote control list and the distribution network equipment fault trip transaction list are matched, the power failure time and the power restoration time obtained in step 103 are used as the judgment conditions, that is, whether the same records of the transformer substation name and the line name exist in the two lists is judged between the power failure time and the power restoration time, if yes, the records in the two lists, that is, the distribution network automatic switch remote control record and the distribution network equipment fault trip transaction record, are recorded, and the two records are associated.
And 105, matching the remote control records of the distribution network automatic switch with the distribution network automatic standing book table, saving the successfully matched distribution network automatic standing book data as effective automatic standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automatic standing book data.
It can be understood that, in this embodiment, the distribution network automation switch remote control record is matched with the distribution network automation account table, the automation account data matched with the distribution network automation switch remote control record is stored, and the distribution network automation switch remote control record corresponding to the distribution network automation account data that is not matched is deleted.
It should be noted that, in steps 103, 104, and 105, correlation matching is performed on multi-source data, and data that is successfully matched is output, and in the following step 106, classification statistics is performed on the successfully matched data.
And 106, respectively carrying out fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, carrying out fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and carrying out fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
It can be understood that, in this embodiment, the effective automated ledger data is classified according to the preset statistical rules, and the classification is: the statistics of fault work order remote control processing, fault remote control execution result statistics and fault remote control processing process statistics, and those skilled in the art can set statistical rules according to actual needs to classify effective automatic ledger data, for example: the statistical logic of the remote control processing statistics of the fault work order is as follows: in the data after the multi-source data association matching is successful, if the distribution network equipment fault tripping abnormal operation record has a record corresponding to the distribution network automatic switch remote control detailed list, the record is remote control processing, and if the distribution network equipment fault tripping abnormal operation record does not have a record corresponding to the distribution network automatic switch remote control detailed list, the record is non-remote control processing, and for the examples of fault remote control execution result statistics and fault remote control processing process statistics, the description is omitted here.
The intelligent statistical method for remote control intervention processing of the distribution network faults comprises the steps of firstly obtaining a relation table related to remote control failures of an automatic switch; extracting key information of the distribution network equipment fault tripping transaction list in the relation table, and storing a distribution network equipment fault tripping record matched with the key information into a new database; then, associating a new database with the distribution network equipment fault tripping transaction list, sequentially associating and matching the distribution network equipment fault tripping transaction list, the distribution network automatic switch remote control list and the distribution network automatic switch ledger table, and outputting a result after association and matching; and finally, carrying out statistical classification on the result after the correlation matching, wherein the classification is as follows: fault work order remote control processing statistics, fault remote control execution result statistics and fault remote control processing process statistics. The intelligent statistical method can realize intelligent analysis and statistics on the remote control intervention processing condition of the distribution network fault, thereby solving the technical problems that the existing manual statistical analysis means has large workload and is easy to generate errors.
The foregoing is an embodiment one of the intelligent statistical methods for remote control intervention processing of a distribution network fault provided in the embodiments of the present application, and the following is an embodiment two of the intelligent statistical methods for remote control intervention processing of a distribution network fault provided in the embodiments of the present application.
Referring to fig. 2, fig. 2 is a schematic flowchart of a second embodiment of an intelligent statistical method for remote intervention processing of a distribution network fault according to the present application.
The intelligent statistical method for remote control intervention processing of distribution network faults provided by the embodiment comprises the following steps:
Step 201 of this embodiment is the same as step 101 of this embodiment, please refer to step 101 for description, and will not be described herein again.
Step 202 of this embodiment is the same as step 102 of this embodiment, please refer to step 102 for description, and will not be described herein again.
And step 203, matching the distribution network equipment trip record in the first database with the distribution network equipment fault trip transaction list to obtain a distribution network equipment fault trip transaction record, and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the distribution network equipment fault trip transaction record.
Step 203 of this embodiment is the same as step 103 of this embodiment, please refer to step 103 for description, and will not be described herein again.
And 204, judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list have the same transformer substation name and line name between the power failure time and the power restoration time, and if so, associating the distribution network automatic switch remote control record with the distribution network equipment fault tripping abnormal operation record.
Step 204 of this embodiment is the same as step 104 of this embodiment, please refer to step 104 for description, and will not be described herein again.
And step 205, matching the remote control records of the distribution network automation switch with the distribution network automation standing book table, saving the successfully matched distribution network automation standing book data as effective automation standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automation standing book data.
Step 205 of this embodiment is the same as the description of step 105 of this embodiment, please refer to step 105 for description, and further description is omitted here.
And step 206, judging whether the distribution network automation switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record in the effective automatic ledger data, if so, counting as remote control processing, and otherwise, counting as non-remote control processing.
It should be noted that, the statistical rule for remote control processing of the fault work order in this embodiment is as follows: firstly, defining remote control processing and non-remote control processing, and counting as remote control processing if the distribution network automatic switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record; and if the distribution network automatic switch remote control record does not have the corresponding distribution network equipment fault tripping abnormal operation record, counting as non-remote control processing.
And step 207, in the effective automatic ledger data, judging whether the remote control results recorded by the distribution network automation switch remote control are all remote control failures, if so, counting as fault remote control failures, otherwise, counting as fault remote control successes.
It should be noted that, the statistical rule of the fault remote control execution result in this embodiment is: firstly, defining failure remote control success and failure remote control failure, counting failure remote control failure if all remote control results in the remote control records of the distribution network automatic switch are remote control failure, and counting failure remote control success if one remote control result in the remote control records of the distribution network automatic switch is remote control success.
And 208, when the switch position type in the effective automatic account data is a contact switch, judging whether the effective automatic account data contains a record of successful remote control closing, if so, defining that the remote control is successful and the power transfer is successful, otherwise, defining that the remote control power transfer is failed.
It should be noted that, the statistical rule of the fault remote control processing process in this embodiment is as follows: firstly, defining remote control isolation, remote control trial transmission and remote control power conversion, wherein a step 208 is a statistical rule of remote control isolation, a step 209 is a statistical rule of remote control trial transmission, and a step 210 is a statistical rule of remote control power conversion.
The statistical rule of remote control isolation is as follows: when the switch position type in the effective automation standing book data is a tie switch, if the record in the effective automation standing book data contains a record of successful remote control closing, the definition is as follows: if the record contains remote control closing failure, the definition is as follows: the remote power transfer fails.
And 209, when the effective automatic account data is successfully matched with the fault equipment ID of the trip record of the distribution network equipment and the switch position type is a non-contact switch, judging whether the effective automatic account data contains the record of successful remote control closing, if so, defining the result as successful trial delivery, and otherwise, defining the result as failed trial delivery.
The statistical rule of remote control trial delivery is as follows: when the effective automatic account data is successfully matched with the ID of the fault equipment of the trip record of the distribution network equipment and the type of the switch position is a non-contact switch, if the record in the effective automatic account data contains the record of the successful remote control closing, the definition is as follows: and if the trial delivery is successful, if the record contains the record of the remote control closing failure, defining as follows: the trial delivery fails.
And step 210, when the effective automatic account data fails to be matched with the fault equipment ID of the distribution network equipment trip record and the switch position type is a non-contact switch, judging whether the effective automatic account data contains the record of the success of remote control brake opening, if so, defining that the fault is successfully isolated, otherwise, defining that the remote control isolation fails.
The statistical rule of remote control power conversion is as follows: when the effective automatic ledger data fails to be matched with the ID of the fault equipment of the trip record of the distribution network equipment and the type of the switch position is a non-contact switch, if the record in the effective automatic ledger data contains the record of the success of the remote control switching-off, the definition is as follows: and if the fault is successfully isolated and the record contains the remote control brake-separating failure, defining as follows: the isolation failure fails.
And step 211, respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
It should be noted that, in this embodiment, a corresponding report is automatically generated for the counted effective automated ledger data according to the category of the power grid department, for example: and generating a city fault remote control processing operation condition report, a district fault remote control processing operation condition report and a power supply station fault remote control processing operation condition report, and further generating and reporting an accessory statistical list.
The intelligent statistical method for remote control intervention processing of the distribution network faults comprises the steps of firstly obtaining a relation table related to remote control failures of an automatic switch; extracting key information of which the fault type is a permanent fault and is a non-private line in a distribution network equipment fault tripping transaction list in the relation table, and storing a distribution network equipment fault tripping record matched with the key information into a new database; then, associating a new database with the distribution network equipment fault tripping transaction list, sequentially associating and matching the distribution network equipment fault tripping transaction list, the distribution network automatic switch remote control list and the distribution network automatic switch ledger table, and outputting a result after association and matching; and finally, carrying out statistical classification on the result after the correlation matching, wherein the classification is as follows: the fault work order remote control processing statistics, the fault remote control execution result statistics and the fault remote control processing process statistics solve the technical problems that the existing manual statistical analysis means has large workload and is easy to generate errors.
Further, the embodiment also automatically generates a corresponding fault remote control processing operation condition report and list statistics output according to the classification of the power grid department for the results of the statistics classification.
The second embodiment of the intelligent statistical method for remote control intervention processing of distribution network faults provided in the embodiment of the present application is as follows.
Referring to fig. 3, fig. 3 is a structural diagram of an embodiment of an intelligent statistical apparatus for remote control intervention processing of a distribution network fault according to the embodiment of the present application.
The embodiment of the intelligent statistical device for remote control intervention processing of distribution network faults provided by the embodiment of the application comprises the following steps:
an obtaining module 301, configured to obtain a relationship table related to a remote control failure of an automation switch, where the relationship table includes: the system comprises a distribution network equipment fault tripping transaction list, a distribution network automatic switch remote control list and a distribution network automatic ledger table.
The first matching module 302 is configured to store the distribution network device trip record matched with the key information of the distribution network device fault trip transaction list in a first database.
The extracting module 303 is configured to match the distribution network device trip record in the first database with the distribution network device fault trip transaction list to obtain a distribution network device fault trip transaction record, and extract the power failure time, the power restoration time, the transformer substation name, and the line name of the distribution network device fault trip transaction record.
The determining module 304 is configured to determine whether the distribution network automation switch remote control list and the distribution network equipment fault trip transaction list have the same substation name and line name between the power failure time and the power restoration time, and if so, associate the distribution network automation switch remote control record with the distribution network equipment fault trip transaction record.
And a second matching module 305, configured to match the distribution network automation switch remote control record with the distribution network automation ledger table, store the successfully matched distribution network automation ledger data as effective automation ledger data, and delete the unsuccessfully matched remote control record corresponding to the distribution network automation ledger data.
And the counting module 306 is used for performing fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, performing fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and performing fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
The intelligent statistical device for remote control intervention processing of the distribution network faults of the embodiment firstly obtains a relational table related to the remote control failure of an automatic switch; extracting key information of the distribution network equipment fault tripping transaction list in the relation table, and storing a distribution network equipment fault tripping record matched with the key information into a new database; then, associating a new database with the distribution network equipment fault tripping transaction list, sequentially associating and matching the distribution network equipment fault tripping transaction list, the distribution network automatic switch remote control list and the distribution network automatic switch ledger table, and outputting a result after association and matching; and finally, carrying out statistical classification on the result after the correlation matching, wherein the classification is as follows: fault work order remote control processing statistics, fault remote control execution result statistics and fault remote control processing process statistics. The intelligent statistical method can realize intelligent analysis and statistics on the remote control intervention processing condition of the distribution network fault, thereby solving the technical problems that the existing manual statistical analysis means has large workload and is easy to generate errors.
Further, in a specific embodiment, the method further comprises: a generation module;
and the generating module is used for respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The terms "first," "second," "third," "fourth," and the like in the description of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. An intelligent statistical method for remote control intervention processing of distribution network faults is characterized by comprising the following steps:
s1, obtaining a relation table related to the remote control failure of the automatic switch, wherein the relation table comprises: the distribution network equipment fault tripping abnormal operation list, the distribution network automatic switch remote control list and the distribution network automatic ledger table;
s2, storing the tripping records of the distribution network equipment matched with the key information of the fault tripping transaction list of the distribution network equipment into a first database;
s3, matching the distribution network equipment trip record in the first database with the distribution network equipment fault trip transaction list to obtain a distribution network equipment fault trip transaction record, and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the distribution network equipment fault trip transaction record;
s4, judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list exist between the power failure time and the power restoration time, and if so, associating the distribution network automatic switch remote control record with the distribution network equipment fault tripping abnormal operation record;
s5, matching the remote control records of the distribution network automatic switch with the distribution network automatic standing book table, saving the successfully matched distribution network automatic standing book data as effective automatic standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automatic standing book data;
and S6, performing fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, performing fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and performing fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
2. The intelligent statistical method for remote intervention processing of distribution network failures according to claim 1, further comprising, after step S6:
and respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
3. The intelligent statistical method for remote intervention processing of distribution network faults as recited in claim 1, wherein the first statistical rule specifically includes:
and judging whether the distribution network automation switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record or not in the effective automatic ledger data, if so, counting as remote control processing, and otherwise, counting as non-remote control processing.
4. The intelligent statistical method for remote intervention processing of distribution network faults as recited in claim 1, wherein the second statistical rule specifically includes:
and judging whether the remote control results recorded by the distribution network automation switch in the effective automatic standing book data are all remote control failures or not, if so, counting as fault remote control failures, and otherwise, counting as fault remote control successes.
5. The intelligent statistical method for remote intervention processing of distribution network faults as recited in claim 1, wherein the third statistical rule specifically includes:
when the switch position type in the effective automation account data is a contact switch, judging whether the effective automation account data contains a record of successful remote control closing, if so, defining that the remote control is successful and the power transfer is successful, otherwise, defining that the remote control power transfer is failed;
when the effective automatic account data is successfully matched with the fault equipment ID of the tripping record of the distribution network equipment and the switch position type is a non-contact switch, judging whether the effective automatic account data contains a record of successful remote control closing, if so, defining the effective automatic account data as successful trial delivery, otherwise, defining the effective automatic account data as failed trial delivery;
and when the effective automatic account data fails to be matched with the fault equipment ID of the distribution network equipment trip record and the switch position type is a non-contact switch, judging whether the effective automatic account data contains the record of the success of remote control switching-off, if so, defining that the fault is successfully isolated, otherwise, defining that the remote control isolation fails.
6. The intelligent statistical method for remote intervention processing of distribution network faults as recited in claim 1, wherein the key information is: permanently faulted and non-dedicated lines.
7. The utility model provides a join in marriage intelligent statistics device that net trouble remote control intervenes processing which characterized in that includes:
an obtaining module, configured to obtain a relationship table related to a remote control failure of an automation switch, where the relationship table includes: the distribution network equipment fault tripping abnormal operation list, the distribution network automatic switch remote control list and the distribution network automatic ledger table;
the first matching module is used for storing the tripping records of the distribution network equipment matched with the key information of the fault tripping transaction list of the distribution network equipment to a first database;
the extraction module is used for matching the tripping records of the distribution network equipment in the first database with the fault tripping transaction list of the distribution network equipment to obtain fault tripping transaction records of the distribution network equipment and extracting the power failure time, the power restoration time, the transformer substation name and the line name of the fault tripping transaction records of the distribution network equipment;
the judging module is used for judging whether the distribution network automatic switch remote control list and the distribution network equipment fault tripping abnormal operation list have the same transformer substation name and the same line name between the power failure time and the power restoration time, and if so, the distribution network automatic switch remote control record and the distribution network equipment fault tripping abnormal operation record are associated;
the second matching module is used for matching the remote control records of the distribution network automatic switch with the distribution network automatic standing book table, saving the successfully matched distribution network automatic standing book data as effective automatic standing book data, and deleting the remote control records corresponding to the unsuccessfully matched distribution network automatic standing book data;
and the counting module is used for performing fault work order remote control processing statistics on the effective automatic account data according to a first statistical rule, performing fault remote control execution result statistics on the effective automatic account data according to a second statistical rule, and performing fault remote control processing process statistics on the effective automatic account data according to a third statistical rule.
8. The intelligent statistics apparatus for remote intervention processing of distribution network failures according to claim 7, further comprising: a generation module;
and the generating module is used for respectively generating corresponding remote control processing condition reports for the counted effective automatic ledger data according to the categories of the power grid departments.
9. The intelligent statistical device for remote intervention processing of distribution network failures according to claim 7, wherein the first statistical rule specifically comprises:
and judging whether the distribution network automation switch remote control record has a corresponding distribution network equipment fault tripping abnormal operation record or not in the effective automatic ledger data, if so, counting as remote control processing, and otherwise, counting as non-remote control processing.
10. The intelligent statistical device for remote intervention processing of distribution network failures according to claim 7, wherein the second statistical rule specifically comprises:
and judging whether the remote control results recorded by the distribution network automation switch in the effective automatic standing book data are all remote control failures or not, if so, counting as fault remote control failures, and otherwise, counting as fault remote control successes.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113407592A (en) * | 2021-06-07 | 2021-09-17 | 深圳明锐理想科技有限公司 | PCB production line fault positioning method and device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0599606A2 (en) * | 1992-11-24 | 1994-06-01 | Xerox Corporation | Interactive diagnostic data transfer system for remote diagnostics |
| US20100174945A1 (en) * | 2007-06-06 | 2010-07-08 | Nec Corporation | Communication network failure cause analysis system, failure cause analysis method, and failure cause analysis program |
| CN103514516A (en) * | 2013-09-27 | 2014-01-15 | 国家电网公司 | Method for obtaining power grid device failure information based on calculation of multi-source redundant information |
| CN104459474A (en) * | 2014-12-22 | 2015-03-25 | 国网上海市电力公司 | Intelligent distribution network fault recognition method |
| CN104463712A (en) * | 2014-12-22 | 2015-03-25 | 国网上海市电力公司 | Intelligent distribution network fault information statistical analysis system |
| CN107230160A (en) * | 2017-05-08 | 2017-10-03 | 国网江西省电力公司电力科学研究院 | A kind of 10kV line trippings wrong report is intelligent to judge implementation method |
| CN108734418A (en) * | 2018-06-13 | 2018-11-02 | 国网山东省电力公司蓬莱市供电公司 | A kind of electric network fault statistical analysis system and its analysis method |
-
2021
- 2021-03-18 CN CN202110290174.6A patent/CN112821566B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0599606A2 (en) * | 1992-11-24 | 1994-06-01 | Xerox Corporation | Interactive diagnostic data transfer system for remote diagnostics |
| US20100174945A1 (en) * | 2007-06-06 | 2010-07-08 | Nec Corporation | Communication network failure cause analysis system, failure cause analysis method, and failure cause analysis program |
| CN103514516A (en) * | 2013-09-27 | 2014-01-15 | 国家电网公司 | Method for obtaining power grid device failure information based on calculation of multi-source redundant information |
| CN104459474A (en) * | 2014-12-22 | 2015-03-25 | 国网上海市电力公司 | Intelligent distribution network fault recognition method |
| CN104463712A (en) * | 2014-12-22 | 2015-03-25 | 国网上海市电力公司 | Intelligent distribution network fault information statistical analysis system |
| CN107230160A (en) * | 2017-05-08 | 2017-10-03 | 国网江西省电力公司电力科学研究院 | A kind of 10kV line trippings wrong report is intelligent to judge implementation method |
| CN108734418A (en) * | 2018-06-13 | 2018-11-02 | 国网山东省电力公司蓬莱市供电公司 | A kind of electric network fault statistical analysis system and its analysis method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113407592A (en) * | 2021-06-07 | 2021-09-17 | 深圳明锐理想科技有限公司 | PCB production line fault positioning method and device |
| CN113407592B (en) * | 2021-06-07 | 2023-11-03 | 深圳明锐理想科技有限公司 | PCB production line fault positioning method and equipment |
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