CN112347089B - Method for checking power supply reliability data quality of multiple systems - Google Patents
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Abstract
The invention discloses a method for checking the quality of power supply reliability data of multiple systems, which comprises the following steps: establishing a data checking and analyzing database; collecting power failure events; and (3) power failure event collection to be verified: acquiring a power failure event within a required time period or a required power supply range from a power supply reliability system, extracting required key fields for combination, and putting the key fields into a power failure event database to be verified; establishing a data checking algorithm rule; data quality verification and feedback: and automatically comparing the power failure event source database data with the data of the power failure event database to be verified by using the data verification algorithm base, automatically generating a data quality verification feedback report, and putting the data quality verification feedback report into a checking result feedback base. The method for checking the quality of the power supply reliability data of the multiple systems can be oriented to power supply enterprises of different levels, and has a beneficial promoting effect on improving the management level of the quality of the power supply reliability data.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method for checking the quality of power supply reliability data of multiple systems.
Background
The power supply reliability index is an important index for assessing the power quality of a power supply system of a power grid enterprise, reflects the satisfaction degree of the power industry on national economic power requirements, and is also an important assessment index for optimizing the power obtained by the operator environment. The quality management of power supply reliability data is an important foundation for digital transformation of power grid enterprises, the data quality level determines the value of big data analysis and application, and the high-quality data has important effects on distribution network management decision and production service support. Therefore, the accuracy, timeliness, consistency and integrity of the power supply reliability data are comprehensively improved, and the basic management work is of great importance. At present, more information systems related to production, management and power supply services are provided for each power grid enterprise, higher management requirements are provided for data quality managers, and the challenges and the problems faced by the data quality managers are how to meet the working requirements of wider checking range, shorter checking time and stricter checking requirements.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a method for checking the quality of power supply reliability data of multiple systems, which can be oriented to power supply enterprises of different levels and has a beneficial promoting effect on improving the management level of the quality of the power supply reliability data.
In order to solve the above technical problem, an embodiment of the present invention provides a method for checking quality of power supply reliability data of multiple systems, where the method includes the following steps:
establishing a data checking and analyzing database: the data checking analysis database comprises a power failure event source database, a power failure event database to be checked, a data checking algorithm database and a checking result feedback database;
power failure event acquisition: collecting power failure events in a required time period or a required power supply range from the power dispatching automation system, collecting power failure events in the required time period or the required power supply range from the metering automation system, extracting required key fields, merging the key fields, and putting the key fields into a power failure event source database;
and (3) power failure event collection to be verified: acquiring a power failure event within a required time period or a required power supply range from a power supply reliability system, extracting required key fields for combination, and putting the key fields into a power failure event database to be verified;
establishing a data checking algorithm rule: based on a python language, adopting a reading function, a circulation function and a comparison function to realize automatic comparison of the power failure event source database data and the power failure event database to be verified, and putting algorithm rules into a data verification algorithm library;
data quality verification and feedback: and automatically comparing the power failure event source database data with the data of the power failure event database to be verified by using the data verification algorithm base, automatically generating a data quality verification feedback report, and putting the data quality verification feedback report into a verification result feedback base.
The collecting of the power failure event in the demand time period or the demand power supply range from the power dispatching automation system comprises:
and acquiring power failure data of a main network and/or a distribution network of the power dispatching automation system in a demand time period, and acquiring system power failure user data of the metering automation system.
The collecting of the power failure event within the demand time period or the demand power supply range from the power supply reliability system includes:
and power supply reliability system power failure data and/or distribution network line property data in a demand time period are/is acquired.
The extracting the required key fields for merging, and the placing into the power failure event source database comprises the following steps:
extracting power failure data key fields of the power dispatching automation system in a demand time period, wherein the key fields comprise names of power failure lines of 10kV or more, power failure date data of the lines of 10kV or more, power restoration date data of 10kV or more and affiliated operation and maintenance units;
and extracting a power failure data key field of the metering automation system, wherein the key field comprises a 10kV medium-voltage power failure user code, a 10kV medium-voltage power failure user name, power failure date data of a 10kV medium-voltage power failure user, power restoration date data of a 10kV medium-voltage power failure user, 10kV medium-voltage power failure user belonging 10kV medium-voltage line data and a belonging operation and maintenance unit.
The extracting required key fields for combination and putting the key fields into a power failure event database to be verified comprises the following steps:
extracting power failure data key fields of the power supply reliability system, wherein the key fields comprise names of 10kV and above power failure lines, power failure date data of 10kV and above lines, power restoration date data of 10kV and above lines, belonging operation and maintenance unit data and power supply reliability system event numbers related to the power supply reliability system.
The data checking algorithm rule establishment comprises the following steps:
extracting and combining key fields of power failure data of the power dispatching automation system, sequentially combining name data of lines of 10kV and above, power failure date data of lines of 10kV and above, power restoration date data of lines of 10kV and above and belonging operation and maintenance unit data in each power failure event of the main network and the distribution network in sequence, naming a formed power failure event data set, and placing the named power failure event data set into a power failure event source database.
The data checking algorithm rule establishment comprises the following steps:
analyzing and merging key fields of the power failure data of the metering automation system, taking power failure events of 10kV medium-voltage users with the same power failure date, the same power restoration date and the same affiliated 10kV medium-voltage line as one power failure event, sequentially merging the power failure date data of the 10kV medium-voltage power failure users, the power restoration date data of the 10kV medium-voltage power failure users, the 10kV medium-voltage line data of the 10kV medium-voltage power failure users and the affiliated operation and maintenance unit data of each power failure event in sequence, naming a formed power failure event data set, and putting the named power failure event data set into a power failure event source database.
The data checking algorithm rule establishment comprises the following steps:
extracting and merging key fields of power failure data of a power supply reliability system, sequentially merging the power failure date data of 10kV and above lines, the power restoration date data of 10kV and above lines, the name data of 10kV and above power failure lines and the belonged operation and maintenance unit data of each distribution network power failure event, naming a formed power failure event data set, and putting the power failure event data set into a power failure event database to be verified.
The method further comprises the following steps:
and triggering power failure event acquisition based on the quality requirement of the user, and feeding back a feedback checking result to the user based on a checking result feedback library.
According to the embodiment of the invention, a plurality of databases are constructed to meet the requirements of different data storage and data processing, and the results processing and triggering functions of different stages can be realized facing different stages, so that different data acquisition can be realized facing different levels of power supply enterprises, the quality management of power supply reliability data is improved, the data verification is more convenient for users, the Python language is established as a basic data verification algorithm rule, the whole power data verification is realized automatically, and the overall efficiency is higher.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for checking quality of power supply reliability data of multiple systems in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be 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 invention.
The embodiment of the invention relates to a method for checking the quality of power supply reliability data of multiple systems, which needs to establish a power supply reliability data quality checking analysis library: the system comprises a power failure event source database, a power failure event database to be verified, a data verification algorithm database and a verification result feedback database. The power failure event source database is used for storing power failure data of the power dispatching automation system and power failure data of the metering automation system; the power failure event database to be verified is used for storing power failure data of the power supply reliability system; the data checking algorithm base is used for storing a comparison algorithm which can realize automatic comparison of the power failure event source database data and the power failure event database data to be checked; and the checking result feedback library is used for storing comparison analysis tables. The embodiment of the invention can automatically generate the data quality check analysis table and meet the user requirements.
The database according to the embodiment of the present invention includes: and the power failure event source database is used for storing key merging fields extracted by power failure events in the power dispatching automation system and the metering automation system. And the power failure event database to be verified is used for storing key merging fields extracted from the power failure events in the power supply reliability system. And the data checking algorithm library is used for storing a comparison algorithm based on python language, which can realize automatic comparison between the power failure event source database data and the power failure event database data to be checked. And the checking result feedback library is used for storing the automatically generated comparison analysis result.
Specifically, the method for checking the quality of the power supply reliability data of the multiple systems comprises the following steps:
establishing a data checking and analyzing database: the database comprises a power failure event source database, a power failure event database to be verified, a data verification algorithm database and a verification result feedback database.
Power failure event acquisition: and collecting power failure events in a required time period and a required power supply range from the power dispatching automation system and the metering automation system, extracting required key fields, merging the key fields, and putting the key fields into a power failure event source database.
Power failure event collection to be verified: and acquiring the power failure events in the required time period and the required power supply range from the power supply reliability system, extracting required key fields, merging the key fields, and putting the key fields into a power failure event database to be verified.
Establishing a data checking algorithm rule: based on a python language, functions such as a reading function, a circulation function, a comparison function and the like are adopted to realize automatic comparison of the power failure event source database data and the power failure event database to be verified, and algorithm rules are put into a data verification algorithm library.
Data quality check and feedback: and automatically comparing the power failure event source database data with the data of the power failure event database to be verified by using the data verification algorithm base, automatically generating a data quality verification feedback report, and putting the data quality verification feedback report into a verification result feedback base.
The method provided by the embodiment of the invention can be oriented to power supply enterprises of different levels, and has a beneficial promoting effect on improving the quality management level of power supply reliability data.
Specifically, fig. 1 shows a flowchart of a method for checking quality of power supply reliability data of multiple systems in an embodiment of the present invention, including the following steps:
s101, a data checking analysis database is required to be established, and the database is divided into a power failure event source database, a to-be-checked power failure event database, a data checking algorithm database and a checking result feedback database.
S102, power failure data of a main network and a distribution network of the power dispatching automation system in a demand time period are obtained, and system power failure user data of the metering automation system are obtained.
S103, power failure data of the power supply reliability system and property data of the distribution network line in the demand time period are obtained.
And S104, extracting power failure data key fields of the power dispatching automation system in the required time period, wherein the key fields comprise names of power failure lines of 10kV or more, power failure date data of the lines of 10kV or more, power restoration date data of 10kV or more and operation and maintenance units to which the key fields belong. Examples are shown in table 1 below:
TABLE 1 Power outage data for power dispatching automation systems
And S105, extracting a key field of the power failure data of the automatic metering system, wherein the key field comprises a 10kV medium-voltage power failure user code, a 10kV medium-voltage power failure user name, power failure date data of a 10kV medium-voltage power failure user, power restoration date data of a 10kV medium-voltage power failure user, 10kV medium-voltage power failure user data of a 10kV medium-voltage line to which the 10kV medium-voltage power failure user belongs, and an operation and maintenance unit to which the 10kV medium-voltage line belongs. Examples are shown in table 2 below:
TABLE 2 metering automation system outage data
S106, extracting a power failure data key field of the power supply reliability system, wherein the key field comprises the name of a power failure line of 10kV or more, power failure date data of the line of 10kV or more, power restoration date data of the line of 10kV or more, operation and maintenance unit data of the line, and an event number of the power supply reliability system, which are related in the power supply reliability system. Examples are shown in table 3 below:
TABLE 3 Power supply reliability System Power outage data
And S107, extracting and combining the key fields of the power failure data of the power dispatching automation system, sequentially combining the name data of lines of 10kV or more, the power failure date data of lines of 10kV or more, the power restoration date data of lines of 10kV or more and the operation and maintenance unit data of the lines in each main network power failure event and each distribution network power failure event, and putting the formed power failure event data set named as '01-dispatching power failure data source' into a power failure event source database. Examples are shown in tables 4 and 5 below:
TABLE 4 Power outage data for power dispatching automation system
TABLE 5 merged "01-Schedule blackout data Source"
And S108, analyzing and combining the key fields of the power failure data of the metering automation system, taking the power failure events of 10kV medium-voltage users with the same power failure date, the same power restoration date and the same belonging 10kV medium-voltage line as one power failure event, sequentially combining the power failure date data of the 10kV medium-voltage power failure users, the power restoration date data of the 10kV medium-voltage power failure users, the 10kV medium-voltage line data of the 10kV medium-voltage power failure users and the belonging operation and maintenance unit data of each power failure event in sequence, and putting a formed power failure event data set named as '02-metering power failure data source' into a power failure event source database. The data are shown in tables 6, 7 and 8 below.
TABLE 6 metering Automation System outage data Key fields
TABLE 7 metering automation system Power outage event Classification
TABLE 8 merged "02-metering blackout data Source"
S109, extracting and combining key fields of power failure data of the power supply reliability system, sequentially combining power failure date data of lines of 10kV and above, power restoration date data of lines of 10kV and above, power failure line name data of 10kV and above and affiliated operation and maintenance unit data of each distribution network power failure event in sequence, and putting a formed power failure event data set named '03-power supply reliability system power failure data source to be verified' into a power failure event database to be verified. The data combinations are shown in tables 9 and 10 below, for example.
TABLE 9 Power supply reliability System Power failure data
Table 10 merged "03-power supply reliability system blackout data source to be verified"
S110, establishing a data checking algorithm rule based on Python language in a data checking algorithm library, wherein the algorithm rule comprises a reading function, a circulation function and a comparison function. The data checking algorithm library takes the power failure data in the power failure event source database as a checking standard, consistency comparison is carried out on the power failure data in the power failure event database to be checked, if key fields of a 01-dispatching power failure data source, a 02-metering power failure data source and a 03-power supply reliability system for checking the power failure data source data, such as power failure date, power restoration date, power failure lines and affiliated operation and maintenance units, are consistent, yes is returned, if the key fields are inconsistent, no is returned, an automatic comparison analysis report is finally generated, and automatic comparison of the power failure event source database and the power failure data source of the power failure event database to be checked is achieved. The data quality check feedback results are shown in table 11 below, for example.
TABLE 11 Power supply reliability data quality verification feedback results
It should be noted that, here, the power-off event collection may be triggered based on the user quality requirement, and the feedback check result is fed back to the user based on the check result feedback library.
According to the embodiment of the invention, a plurality of databases are constructed to meet the requirements of different data storage and data processing, and the results processing and triggering functions of different stages can be realized for different stages, so that different data acquisition can be realized for power supply enterprises of different levels, the power supply reliability data quality management is improved, the data verification can be more conveniently carried out by a user, the Python language is established as a basic data verification algorithm rule, the whole power data quality verification is realized automatically, and the overall efficiency is higher.
The above embodiments of the present invention are described in detail, and the principle and the implementation manner of the present invention should be described by using specific embodiments, and the description of the above embodiments is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (6)
1. A method for checking the quality of power supply reliability data of multiple systems is characterized by comprising the following steps:
establishing a data checking and analyzing database: the data checking analysis database comprises a power failure event source database, a power failure event database to be checked, a data checking algorithm database and a checking result feedback database;
power failure event acquisition: collecting power failure events in a required time period or a required power supply range from the power dispatching automation system, collecting power failure events in the required time period or the required power supply range from the metering automation system, extracting required key fields, merging the key fields, and putting the key fields into a power failure event source database;
power failure event collection to be verified: acquiring a power failure event within a required time period or a required power supply range from a power supply reliability system, extracting required key fields for combination, and putting the key fields into a power failure event database to be verified;
establishing a data checking algorithm rule: based on a python language, adopting a reading function, a cyclic function and a comparison function to realize automatic comparison of the power failure event source database data and the power failure event database to be verified, and putting algorithm rules into a data verification algorithm library;
data quality verification and feedback: automatically comparing the source database data of the power failure event with the data of the power failure event database to be verified by using a data verification algorithm library, automatically generating a data quality verification feedback report, and putting the data quality verification feedback report into a verification result feedback library;
the data checking algorithm rule establishment comprises the following steps:
extracting and combining key fields of power failure data of the power dispatching automation system, sequentially combining name data of lines of 10kV and above, power failure date data of lines of 10kV and above, power restoration date data of lines of 10kV and above and operation and maintenance unit data of the lines in each main network power failure event and each distribution network power failure event in sequence, naming a formed power failure event data set and placing the power failure event data set into a power failure event source database;
analyzing and merging key fields of the power failure data of the metering automation system, taking power failure events of 10kV medium-voltage users with the same power failure date, the same power restoration date and the same belonging 10kV medium-voltage line as one power failure event, sequentially merging the power failure date data of the 10kV medium-voltage power failure users, the power restoration date data of the 10kV medium-voltage power failure users, the belonging 10kV medium-voltage line data of the 10kV medium-voltage power failure users and the belonging operation and maintenance unit data of each power failure event, naming a formed power failure event data set, and putting the named power failure event data set into a power failure event source database;
extracting and combining key fields of power failure data of a power supply reliability system, sequentially combining the power failure date data of 10kV and above lines, the power restoration date data of 10kV and above lines, the name data of 10kV and above power failure lines and the belonging operation and maintenance unit data of each distribution network power failure event in sequence, naming a formed power failure event data set, and placing the named power failure event data set into a power failure event database to be verified.
2. The method for verifying power supply reliability data quality for multiple systems as claimed in claim 1, wherein said collecting power outage events from the power dispatching automation system within a demand time period or demand power supply range comprises:
and acquiring main network and/or distribution network power failure data of the power dispatching automation system in a demand time period, and acquiring system power failure user data of the metering automation system.
3. The method for checking the quality of reliability data for power supply to multiple systems according to claim 2, wherein collecting the blackout event within the required time period or the required power supply range from the reliability data for power supply system comprises:
and power supply reliability system power failure data and/or distribution network line property data in a demand time period are/is acquired.
4. The method for checking quality of reliability data for power supply to multiple systems according to claim 3, wherein extracting the required key fields for merging and placing into the source database of blackout events comprises:
extracting power failure data key fields of the power dispatching automation system in a demand time period, wherein the key fields comprise names of power failure lines of 10kV or more, power failure date data of the lines of 10kV or more, power restoration date data of 10kV or more and affiliated operation and maintenance units;
and extracting a power failure data key field of the metering automation system, wherein the key field comprises a 10kV medium-voltage power failure user code, a 10kV medium-voltage power failure user name, power failure date data of a 10kV medium-voltage power failure user, power restoration date data of a 10kV medium-voltage power failure user, 10kV medium-voltage power failure user belonging 10kV medium-voltage line data and a belonging operation and maintenance unit.
5. The method of claim 4, wherein extracting required key fields for merging and placing into a to-be-verified outage event database comprises:
extracting power failure data key fields of the power supply reliability system, wherein the key fields comprise names of 10kV and above power failure lines, power failure date data of 10kV and above lines, power restoration date data of 10kV and above lines, affiliated operation and maintenance unit data and power supply reliability system event numbers related to the power supply reliability system.
6. The method for checking the quality of power supply reliability data for multiple systems according to any one of claims 1 to 5, wherein the method further comprises:
and triggering power failure event collection based on the quality requirement of the user, and feeding back a feedback checking result to the user based on a checking result feedback library.
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US9383795B2 (en) * | 2013-03-10 | 2016-07-05 | Seagate Technololgy Llc | Storage device power failure infrastructure |
CN105843883A (en) * | 2016-03-21 | 2016-08-10 | 国家电网公司 | Data quality check method and apparatus |
CN106786596A (en) * | 2016-11-28 | 2017-05-31 | 国家电网公司 | Transmission and distribution network combines the out-of-limit processing method of trend and system |
CN108647328B (en) * | 2018-05-11 | 2022-04-01 | 国网安徽省电力有限公司淮南供电公司 | Reliability power failure event acquisition integrity analysis and automatic completion method |
CN109919406A (en) * | 2018-12-18 | 2019-06-21 | 国网浙江桐乡市供电有限公司 | The intelligent housekeeping arrangement method of the power distribution network method of operation |
CN111047188A (en) * | 2019-12-12 | 2020-04-21 | 深圳供电局有限公司 | Power failure plan generation method and system, computer equipment and storage medium |
CN111553603A (en) * | 2020-04-30 | 2020-08-18 | 深圳供电局有限公司 | Method and device for evaluating power supply reliability of low-voltage user and computer readable storage medium |
-
2020
- 2020-10-29 CN CN202011180400.7A patent/CN112347089B/en active Active
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102254091A (en) * | 2011-06-10 | 2011-11-23 | 华北电力大学 | Method for estimating 20-kilovolt medium-voltage distribution scheme |
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