CN112288594A - Data quality transaction processing method and system based on real-time event triggering - Google Patents
Data quality transaction processing method and system based on real-time event triggering Download PDFInfo
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Abstract
The application provides a data quality transaction processing method and a system based on real-time event triggering, wherein the data quality transaction processing method comprises the following steps: acquiring and monitoring the electric quantity related data of the special transformer user in real time by using a special transformer user electric quantity monitoring system; preliminarily judging whether the data related to the electric quantity is abnormal or not and judging the abnormal type based on the acquired electric quantity data; finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program; and receiving field electric quantity data abnormal processing data related to the work order information. The invention can effectively realize the high-efficiency processing of various data transaction.
Description
Technical Field
The present disclosure relates to the field of power information processing, and in particular, to a method and a system for processing data quality transaction based on real-time event triggering.
Background
In the prior art, in the power field, along with the increase of the amount of users and the diversification of power equipment, multiple types of data in the power field often have abnormal situations, for example, the power consumption of the users increases sharply. In the prior art, when data transaction is faced, the data transaction is often difficult to process quickly and efficiently.
Disclosure of Invention
One of the objectives of the present disclosure is to provide a data quality transaction processing method and system based on real-time event triggering, so as to effectively handle the problem of data quality transaction in the power domain.
In order to achieve the above object, according to an embodiment of the present disclosure, a method for processing data quality transaction based on real-time event triggering is provided, including: acquiring and monitoring the electric quantity related data of the special transformer user in real time by using a special transformer user electric quantity monitoring system; preliminarily judging whether the data related to the electric quantity is abnormal or not and judging the abnormal type based on the acquired electric quantity data; finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program; and receiving field electric quantity data abnormal processing data related to the work order information.
Optionally, the step of preliminarily determining whether the data related to the electric quantity is abnormal or not and the type of the abnormality based on the acquired data of the electric quantity includes at least one of: judging whether the three-phase voltage is abnormal or not according to the three-phase voltage data of the primary meter of the special transformer user acquired by the electric quantity monitoring system and different wiring modes of a three-phase three-wire or a three-phase four-wire, based on the numerical relation between the normal numerical value of the three-phase voltage and the three-phase voltage or/and the numerical relation between a current curve and the current voltage formed by the historical current data of the special transformer user acquired by the electric quantity monitoring system; calculating the deviation of three-phase current according to the three-phase current data of the primary meter of the special transformer user, which is acquired by the electric quantity monitoring system, and judging whether CT cutoff abnormality exists according to different wiring modes of three-phase three-wire or three-phase four-wire and the numerical relation of the three-phase current; calculating an over capacity rate according to daily electricity consumption, daily valley electricity consumption and daily maximum demand of a primary meter of a special transformer user, which are acquired by an electricity monitoring system, and determining whether daily over capacity abnormality exists or not based on a preset abnormality judgment rule of the maximum demand over capacity; according to the electric quantity and three-phase current data of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, the user with the daily electric quantity being zero but the current value being not zero is initially judged as an abnormal zero-degree user, and whether the current abnormality of the zero-degree user exists is determined by eliminating the conditions of abnormal measurement acquisition and measurement point types.
Optionally, the step of completing the work order information input or/and approval of the data related to the electric quantity based on the work order processing and approval program includes: presetting a plurality of work order processing templates; receiving a work order processing type input or selected by a work order processing personnel or/and an abnormal type of electric power related data, automatically screening or matching a work order processing template corresponding to the input or selected content from a plurality of preset work order processing templates according to the input or selected content, and presenting the work order processing template to the work order processing personnel so that the work order processing personnel can fill in related information of work order processing based on the work order processing template; and analyzing the work order information filled by the work order processing personnel, and determining whether to automatically send the work order information to a system of a second-level processing personnel corresponding to the work order information or to automatically approve the work order information by a computer system based on the judgment of whether one or more items of data in the analysis exceed a preset threshold value.
Optionally, the data quality adopts four types of indexes including data integrity, data accuracy, data consistency and data timeliness as data quality indexes.
Optionally, the following steps are used to preprocess the data quality: selecting the ith data in the set of data operations DOProcessing operation PiUsing PiTo perform data processing operations, the resulting data quality is denoted as Qi(ii) a Calculating data quality gain Δ Q ═ Qi-Qi-1If Δ Q > 0, the data is processed by operation PiPut in SjI is i +1, and returning to the first step until i is n, wherein n is a positive integer; let j equal j +1 and go back to the first step until j equal n.
According to another embodiment of the present disclosure, there is provided a data quality transaction processing system based on real-time event triggering, the data quality transaction processing system including: the data acquisition and monitoring module is used for acquiring and monitoring the electric quantity related data of the special transformer user in real time by using the special transformer user electric quantity monitoring system; the abnormality judgment module is used for preliminarily judging whether the data related to the electric quantity is abnormal or not and the type of the abnormality based on the acquired electric quantity data; the input or/and approval module is used for finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program; and the data receiving module is used for receiving the field electric quantity data abnormal processing data related to the work order information.
The embodiment of the present disclosure can achieve the following advantageous effects: the invention can effectively realize the high-efficiency processing of various data transaction.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a schematic diagram of naming rules of data quality in the power domain according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating an existing greedy algorithm for determining a data processing sequence according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a data quality transaction processing method based on real-time event triggering according to an embodiment of the present application;
FIG. 4 is a schematic block diagram of a real-time event trigger based data quality transaction processing system according to an embodiment of the present application;
the same or similar reference numbers in the drawings identify the same or similar structures.
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 terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.
According to one aspect of the application, a data quality transaction processing method based on real-time event triggering is provided.
The real-time event mainly refers to an electric power real-time event occurring in the field of electric power, and includes but is not limited to an electric power failure, an electric power early warning and the like.
The data quality of the application mainly refers to the data quality of the power big data. High quality data is a prerequisite for efficient data analysis and mining. Data quality is typically expressed using a set of data quality indicators, and data quality may be improved by improving one or more of the indicators. In order to evaluate the data quality more scientifically, the data quality evaluation method and the data quality evaluation system establish a data quality evaluation index and a data quality evaluation model according to the data consistency, accuracy, integrity and timeliness of the data quality so as to evaluate the data quality of the power big data scientifically and conveniently perform more efficient post-processing on the data quality.
The data quality evaluation model includes a data quality evaluation index, a weight of each quality evaluation index, a score of each quality evaluation index, and the like.
In order to better match the data quality in the power domain, the naming rule shown in fig. 1 is adopted in the present application, so as to better define the data quality index, and the naming rule includes the named contents of the sampling interval, the average sampling interval, and the like.
Although there are many types of data quality indexes in the prior art, the inventor of the present application adopts four types of indexes, namely, data integrity, data accuracy, data consistency and data timeliness, as data quality indexes according to characteristics of power field data and various practical application scenarios in reality related to power data.
Wherein, data integrity DintegrityThe method is used for measuring the integrity degree of data, including the content of scale integrity, attribute integrity, content integrity and the like, and the data integrity can be measured by the data scale, the data amount, the data coverage degree and the like. In order to simplify the data quality evaluation model, the data integrity is defined as the data missing degree, and according to fig. 1, the following is the accurate definition of the data integrity, as shown in formulas (1) and (2):
wherein, data accuracy DaccuracyThe method is used for measuring the data accuracy by measuring the capability of accurate description of data to the physical world, illegal values, invalid data types, low data accuracy and the like, and the method is used for simplifying a data quality evaluation model, defining the data accuracy as the data abnormal degree, and according to the figure 1, accurately defining the data accuracyAs shown in formulas (3) and (4):
wherein, data consistency DconsistencyThe method is used for measuring the consistency of different data formats, contents, value ranges and the like of a single or a plurality of data sources, and the data consistency comprises the aspects of concept consistency, format consistency, value range consistency, time consistency and the like. Different constraint conditions are determined according to data contents, data violating the constraint conditions are considered to have consistency conflicts, and the more complex the constraint conditions are, the more complex the consistency judgment is. In order to simplify a data quality evaluation model, only one constraint condition is established: the sampling value ranges of the same node on the same attribute should be consistent. Data consistency is defined as the degree to which the data violates the constraint, and according to fig. 1, the following is the exact definition of data consistency, as shown in equations (5), (6):
wherein, data timeliness DtimelinessIs an important criterion for measuring the freshness and availability of data, and the timeliness refers to the time interval after receiving, processing, transmitting and utilizing information sent from an information source and the efficiency of the time interval. The shorter the time interval is, the more timely the information is updated, and the stronger the timeliness of the data is. In order to simplify the data quality evaluation model, the data timeliness is defined as the data updating degree, and according to fig. 1, the following is the precise definition of the data timeliness, as shown in formulas (7) and (8):
according to the above definition of the data quality index, the overall quality of the data is recorded as Q, the measurement value of the data quality index X is X, and the weight of the data quality index X is recorded as wXThen, the overall quality of the data is precisely defined as shown in equation (9):
according to the above definitions of data integrity, accuracy, consistency and timeliness of data quality, in order to make the scheme proposed by the present application clearer and easier to compare, the present application uses the following data quality index promotion method:
operations to improve data integrity are denoted as pintegrityFor the operation of improving the data integrity, methods such as mean interpolation, similar mean interpolation, modeling prediction, high-dimensional mapping, multiple interpolation and the like are available, and the integrity improving method based on the mean interpolation is used in the application.
The operation to improve the data accuracy is recorded as paccuracyThe abnormal data in the data set are the main reasons for low data accuracy, the abnormal data can be identified by using a data statistics technology and data visualization, common methods include a box separation method, a regression method, a clustering method and the like, and the abnormal data are identified and then filled by using a mean value to improve the data accuracy.
The operation to improve data consistency is denoted as pconsistencyAnd when the data violates the constraint condition, the data is considered as abnormal data, and the abnormal data is filled according to the constraint rule so as to improve the data consistency.
The operation of improving the timeliness of the data is denoted as ptimelinessFor time in data setAnd (4) judging the intermediate items, and deleting or filling data with low timeliness.
In addition, before data processing, the influence of the data quality promotion sequence on the overall data quality needs to be clarified, which specifically includes:
first, a certain data quality indicator is improved, which does not mean an improvement in the overall quality of the data. For example, the data consistency is DconsistencyThe overall quality of the data is Q, and the operation p is carried out by improving the data consistencyconsistencyThen, the data consistency is D'consistencyData Total Mass is Q ', then D'consistency>DconsistencyHowever, Q' is not necessarily larger than Q, i.e. the overall quality of the data may be degraded after a certain data processing operation.
Second, the impact of different data processing operations on data quality cannot be directly accumulated. For example, data integrity is DintegrityData consistency is DconsistencyThe data quality is Q, and the data integrity improving operation p is respectively carried out on the dataintegrityAnd improve data consistency operation pconsistencyThe obtained data quality is Q ' and Q ", respectively, and the data quality gain is denoted as Δ Q ' ═ Q-Q ', and Δ Q ″ ═ Q-Q", respectively. Sequentially carrying out data integrity improving operation p on original dataintegrityAnd improve data consistency operation pconsistencyThe obtained data quality result is denoted as Q ' ", and the data quality gain is Δ Q '" Q-Q ' ", where Δ Q '" Δ Q ' + Δ Q ", that is, the data quality gain cannot be directly accumulated.
Thirdly, the data processing operations are the same, the data processing operation sequences are different, and the data quality gains are different. For example, the data consistency is DconsistencyData integrity of DintegrityThe data quality is Q, and the data consistency improving operation p is carried out on the data in sequenceconsistencyAnd improve data integrity operation pintegrityThe obtained data quality is recorded as Q ', and the data quality gain is delta Q'; data integrity improving operation p is carried out on data in sequenceintegrityAnd improve data coherency operationspconsistencyThe resulting data quality is denoted as Q ", and the data quality is denoted as Δ Q"; in this case, Δ Q' ≠ Δ Q ″, i.e., the data processing sequence is different and the data quality gain is different.
Fourth, the greater the number of data processing operations, the greater the data quality gain is not necessarily. For example, the data timeliness is DtimelinessData consistency is DconsistencyQ, improving data timeliness operation P on datatimelinessThe obtained data quality is recorded as Q ', and the data quality gain is recorded as Δ Q ' ═ Q-Q '; performing an increase data timeliness operation P on datatimelinessAnd improve data consistency operation pconsistencyThe obtained data quality is denoted as Q ", and the data quality gain is denoted as Δ Q ″, which is not necessarily larger than Δ Q', that is, the data quality gain is not necessarily increased as the number of data processing operations increases.
Assuming that each data quality index corresponds to a data processing method below, and each data processing method is not repeatedly used, and n data processing methods are provided in total, all data processing sequences are as follows:
for example, when there are four data quality indexes, 64 data processing sequences can be selected, when there are five data quality indexes, 325 data processing sequences can be selected, when the dimension of the data quality indexes is increased, the situation becomes more complicated, and when an optimal data processing strategy is sought, all data processing strategies are traversed.
In order to save time and calculation cost, the application uses the existing greedy algorithm to determine the data processing sequence, and the specific flow is shown in fig. 2.
Assuming that there are n data processing operations in the data set and the data operation set is DO, according to fig. 2, the determining the data processing flow includes:
step 1: selecting among a set of data operations DOSelecting the ith data processing operation PiUsing PiTo perform data processing operations, the resulting data quality is denoted as QiWherein i is a positive integer.
Step 2: calculating data quality gain Δ Q ═ Qi-Qi-1If Δ Q > 0, the data is processed by operation PiPut in SjI +1, and returning to the first step until i is n, wherein n is a positive integer.
And step 3: j equals j +1, and the first step is returned until j equals n, where j is a positive integer.
After the definition and the processing flow of the data quality are clearly set forth above, please refer to fig. 3, which details the flow of the real-time event trigger-based data quality transaction processing method of the present application. As shown in fig. 3, the data quality transaction processing method includes:
and S101, acquiring and monitoring the electric quantity related data of the special transformer user in real time by using the special transformer user electric quantity monitoring system.
Specifically, the power monitoring system may adopt any device in the prior art that can obtain the data related to the power, including but not limited to the power consumption or/and the power consumption rate of the power-dedicated user, the name of the user, the number of the user, the power supply unit, etc. In a power grid system, a distribution transformer is used for supplying power to users, the distribution transformer specially used for supplying power to a certain user is a special transformer, a special transformer power supply mode is adopted for supplying power to the users, for example, a special transformer is used as a power supply mode, after being sold, a house is used as a public facility inside a community, an owner entrusts an intermediary organization such as a property company to manage and maintain the power supply mode, and charges for electricity are collected, namely, the user supplying power through the special transformer is a special transformer power user. Each distribution transformer has its corresponding capacity, which is the apparent power of the distribution transformer. Through the electric quantity monitoring system, the electricity consumption cost and the like of a special transformer user in a preset time period can be acquired in real time.
The electric quantity monitoring system adopts a preset abnormal change judgment rule to judge whether the acquired electric quantity related data is abnormal or not, and generates data related to abnormal indexes based on a judgment result, for example, data including abnormal index names, numerical values corresponding to the abnormal indexes and the like.
Step S102, based on the acquired electric quantity data, preliminarily judging whether the electric quantity related data is abnormal or not and judging the abnormal type.
The method comprises the steps of obtaining electric quantity data, judging the abnormal reason of the electric quantity data in a preliminary step based on the obtained electric quantity data, automatically judging the abnormal reason by a computer based on a preset abnormal reason judgment rule, providing manual downloading and judgment for electric quantity related data which cannot be judged by the preset abnormal reason judgment rule after the electric quantity related data is indexed by the computer, and further receiving a judgment result uploaded manually.
For the special transformer users judged to be abnormal by the electric quantity monitoring system, the information of the special transformer users is screened out from the information of all the special transformer users to carry out preliminary analysis on abnormal reasons, and then the types of the abnormal reasons are obtained, wherein the abnormal reasons comprise PT (high-voltage transformer) voltage loss abnormity, CT (high-voltage current transformer) current cutoff abnormity, daily capacity exceeding abnormity, zero-degree household current abnormity and the like.
Specifically, the PT voltage loss abnormality may be determined whether the three-phase voltage is abnormal based on a numerical relationship between a normal numerical value of the three-phase voltage and the three-phase voltage, or/and a numerical relationship between a current curve and a current voltage formed by historical current data of the special transformer user acquired by the electric quantity monitoring system, and the like, according to three-phase voltage data of the special transformer user primary meter acquired by the electric quantity monitoring system, and according to different wiring modes of the three-phase three-wire or three-phase four-wire.
The CT cutoff abnormality can calculate the deviation of three-phase current according to the three-phase current data of the primary meter of the special transformer user, which is acquired by the electric quantity monitoring system, and judge whether the CT cutoff abnormality exists according to the numerical relation between different wiring modes of three-phase three-wire or three-phase four-wire and the three-phase current.
The daily capacity exceeding abnormity can calculate the capacity exceeding rate according to daily electric quantity, daily low-valley electric quantity, daily maximum demand and the like of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, and determine whether the daily capacity exceeding abnormity exists or not based on a preset abnormity judgment rule of the maximum demand capacity exceeding.
The zero-degree household current abnormity can be judged as an abnormal zero-degree household for the first time according to the electric quantity and three-phase current data of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, and the conditions of measurement acquisition abnormity, measurement point types and the like are eliminated through the prior art or manual work and the like, so that whether the zero-degree household current abnormity exists is determined.
And step S103, finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program.
Specifically, the work order processing and approval process may include the following steps:
the method comprises the steps that firstly, a plurality of work order processing templates are preset, the work order processing templates can be classified according to the abnormal type of the electric quantity related data, and the work order processing templates can comprise the abnormal place, time, equipment and other contents of the electric quantity related data.
And secondly, receiving the work order processing type input or selected by the work order processing personnel or/and the abnormal type of the electric power related data, automatically screening or matching the work order processing template corresponding to the input or selected content from a plurality of preset work order processing templates according to the input or selected content, and presenting the work order processing template to the work order processing personnel, so that the work order processing personnel can fill the related information of the work order processing based on the work order processing template, wherein the related information comprises information of filling personnel information, abnormal place, time, equipment, abnormal grade and the like of the electric quantity related data.
And step three, analyzing the work order information filled by the work order processing personnel, and determining whether to automatically send the work order information to a system of a second-level processing personnel corresponding to the work order information or automatically pass the examination and approval by a computer system based on the judgment of whether one or more items of data in the analysis exceed a preset threshold value. For example, if the abnormal level is higher than the nth level in the analysis, wherein N is an integer greater than 1, the work order information is automatically sent to a system of a second-level processing personnel corresponding to the work order information, so that the second-level processing personnel can look up and approve the work order information; and if the number of the work orders is lower than or equal to the Nth level, the work order processing personnel completes the work order information and submits the information to the computer system, and the computer system automatically displays that the examination and approval is passed.
In this embodiment, after the monitoring personnel of the electric quantity data knows the abnormal problem and the preliminary reason, the related abnormal data is filled and submitted through the work order processing and approval program, so that the related monitoring departments can conveniently look up or/and approve the abnormal data, and the work orders with related abnormal data can be further transmitted to the related power supply units through the work order processing and approval program, so that a plurality of departments or units can conveniently know and process the related abnormal conditions in time.
And step S104, receiving field electric quantity data abnormal processing data related to the work order information.
Specifically, after the work order information input or/and approval of the electric quantity-related data is completed based on step S103, in order to further solve the abnormality, the staff who consults or/and approves the work order information organizes the professional to perform the on-site investigation and verification work and the on-site processing work according to the information such as the abnormality level, etc., so as to solve the abnormality of the electric quantity data as soon as possible. In order to facilitate relevant personnel of the work order information to know information such as the progress and the verification condition of field processing in time, personnel who carry out field investigation and verification work and field processing work can input and upload the progress and the verification condition information of the field processing through an app which can carry out data interaction with a computer system applied by a work order processing and approval program, so that relevant monitoring departments can know the processing progress of each work order information in time through the computer system and follow up and track the processing condition of abnormal problems in time.
In practical cases, in addition to data quality transaction, the case of interface transaction is also included.
It should be noted that while the operations of the disclosed methods are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Rather, the steps depicted in the flowcharts may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Based on the same inventive concept of the invention, the invention also provides a data quality transaction processing system based on real-time event triggering. Referring to fig. 4, fig. 4 is a schematic block diagram illustrating a real-time event trigger-based data quality transaction processing system according to an embodiment of the present application.
According to fig. 4, the data quality transaction processing system includes:
the data acquisition and monitoring module 101 is used for acquiring and monitoring the electric quantity related data of the special transformer user in real time by using the special transformer user electric quantity monitoring system;
an abnormality determining module 102, configured to preliminarily determine whether the data related to the electric quantity is abnormal and an abnormal type based on the acquired electric quantity data;
the input or/and approval module 103 is used for finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program;
and the data receiving module 104 is configured to receive field electric quantity data exception handling data related to the work order information.
Optionally, the abnormality determining module 102 is configured to perform at least one of the following operations:
judging whether the three-phase voltage is abnormal or not according to the three-phase voltage data of the primary meter of the special transformer user acquired by the electric quantity monitoring system and different wiring modes of a three-phase three-wire or a three-phase four-wire, based on the numerical relation between the normal numerical value of the three-phase voltage and the three-phase voltage or/and the numerical relation between a current curve and the current voltage formed by the historical current data of the special transformer user acquired by the electric quantity monitoring system;
calculating the deviation of three-phase current according to the three-phase current data of the primary meter of the special transformer user, which is acquired by the electric quantity monitoring system, and judging whether CT cutoff abnormality exists according to different wiring modes of three-phase three-wire or three-phase four-wire and the numerical relation of the three-phase current;
calculating an over capacity rate according to daily electricity consumption, daily valley electricity consumption and daily maximum demand of a primary meter of a special transformer user, which are acquired by an electricity monitoring system, and determining whether daily over capacity abnormality exists or not based on a preset abnormality judgment rule of the maximum demand over capacity;
according to the electric quantity and three-phase current data of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, the user with the daily electric quantity being zero but the current value being not zero is initially judged as an abnormal zero-degree user, and whether the current abnormality of the zero-degree user exists is determined by eliminating the conditions of abnormal measurement acquisition and measurement point types.
Optionally, the input or/and approval module 103 is specifically configured to perform the following operations:
presetting a plurality of work order processing templates;
receiving a work order processing type input or selected by a work order processing personnel or/and an abnormal type of electric power related data, automatically screening or matching a work order processing template corresponding to the input or selected content from a plurality of preset work order processing templates according to the input or selected content, and presenting the work order processing template to the work order processing personnel so that the work order processing personnel can fill in related information of work order processing based on the work order processing template;
and analyzing the work order information filled by the work order processing personnel, and determining whether to automatically send the work order information to a system of a second-level processing personnel corresponding to the work order information or to automatically approve the work order information by a computer system based on the judgment of whether one or more items of data in the analysis exceed a preset threshold value.
Optionally, the data quality adopts four types of indexes including data integrity, data accuracy, data consistency and data timeliness as data quality indexes.
Optionally, the data quality transaction processing system further includes a preprocessing module 105, where the preprocessing module performs the following operations to preprocess the data quality:
selecting an ith data processing operation P in a set of data operations DOiUsing PiTo perform data processing operations, the resulting data quality is denoted as Qi；
Calculating data quality gain Δ Q ═ Qi-Qi-1If Δ Q > 0, the data is processed by operation PiPut in SjI is i +1, and returning to the first step until i is n, wherein n is a positive integer;
let j equal j +1 and go back to the first step until j equal n.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A data quality transaction processing method based on real-time event triggering is characterized by comprising the following steps:
acquiring and monitoring the electric quantity related data of the special transformer user in real time by using a special transformer user electric quantity monitoring system;
preliminarily judging whether the data related to the electric quantity is abnormal or not and judging the abnormal type based on the acquired electric quantity data;
finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program;
and receiving field electric quantity data abnormal processing data related to the work order information.
2. The data quality transaction processing method according to claim 1, wherein the step of preliminarily determining whether the data related to the electric quantity is abnormal and the type of the abnormality based on the acquired data of the electric quantity includes at least one of:
judging whether the three-phase voltage is abnormal or not according to the three-phase voltage data of the primary meter of the special transformer user acquired by the electric quantity monitoring system and different wiring modes of a three-phase three-wire or a three-phase four-wire, based on the numerical relation between the normal numerical value of the three-phase voltage and the three-phase voltage or/and the numerical relation between a current curve and the current voltage formed by the historical current data of the special transformer user acquired by the electric quantity monitoring system;
calculating the deviation of three-phase current according to the three-phase current data of the primary meter of the special transformer user, which is acquired by the electric quantity monitoring system, and judging whether CT cutoff abnormality exists according to different wiring modes of three-phase three-wire or three-phase four-wire and the numerical relation of the three-phase current;
calculating an over capacity rate according to daily electricity consumption, daily valley electricity consumption and daily maximum demand of a primary meter of a special transformer user, which are acquired by an electricity monitoring system, and determining whether daily over capacity abnormality exists or not based on a preset abnormality judgment rule of the maximum demand over capacity;
according to the electric quantity and three-phase current data of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, the user with the daily electric quantity being zero but the current value being not zero is initially judged as an abnormal zero-degree user, and whether the current abnormality of the zero-degree user exists is determined by eliminating the conditions of abnormal measurement acquisition and measurement point types.
3. The data quality transaction processing method according to claim 1, wherein the step of completing the work order information input or/and approval of the data related to the electric quantity based on the work order processing and approval process comprises:
presetting a plurality of work order processing templates;
receiving a work order processing type input or selected by a work order processing personnel or/and an abnormal type of electric power related data, automatically screening or matching a work order processing template corresponding to the input or selected content from a plurality of preset work order processing templates according to the input or selected content, and presenting the work order processing template to the work order processing personnel so that the work order processing personnel can fill in related information of work order processing based on the work order processing template;
and analyzing the work order information filled by the work order processing personnel, and determining whether to automatically send the work order information to a system of a second-level processing personnel corresponding to the work order information or to automatically approve the work order information by a computer system based on the judgment of whether one or more items of data in the analysis exceed a preset threshold value.
4. The data quality transaction processing method according to claim 1, wherein the data quality adopts four types of indicators, namely data integrity, data accuracy, data consistency and data timeliness, as data quality indicators.
5. The data quality transaction processing method according to claim 1, wherein the data quality is preprocessed by the following steps:
selecting an ith data processing operation P in a set of data operations DOiUsing PiTo perform data processing operations, the resulting data quality is denoted as Qi；
Calculating data quality gain Δ Q ═ Qi-Qi-1If Δ Q > 0, the data is processed by operation PiPut in SjI is i +1, and returning to the first step until i is n, wherein n is a positive integer;
let j equal j +1 and go back to the first step until j equal n.
6. A data quality transaction processing system based on real-time event triggering, the data quality transaction processing system comprising:
the data acquisition and monitoring module is used for acquiring and monitoring the electric quantity related data of the special transformer user in real time by using the special transformer user electric quantity monitoring system;
the abnormality judgment module is used for preliminarily judging whether the data related to the electric quantity is abnormal or not and the type of the abnormality based on the acquired electric quantity data;
the input or/and approval module is used for finishing work order information input or/and approval of the electric quantity related data based on the work order processing and approval program;
and the data receiving module is used for receiving the field electric quantity data abnormal processing data related to the work order information.
7. The data quality transaction processing system of claim 6, wherein the anomaly determination module is configured to perform at least one of:
judging whether the three-phase voltage is abnormal or not according to the three-phase voltage data of the primary meter of the special transformer user acquired by the electric quantity monitoring system and different wiring modes of a three-phase three-wire or a three-phase four-wire, based on the numerical relation between the normal numerical value of the three-phase voltage and the three-phase voltage or/and the numerical relation between a current curve and the current voltage formed by the historical current data of the special transformer user acquired by the electric quantity monitoring system;
calculating the deviation of three-phase current according to the three-phase current data of the primary meter of the special transformer user, which is acquired by the electric quantity monitoring system, and judging whether CT cutoff abnormality exists according to different wiring modes of three-phase three-wire or three-phase four-wire and the numerical relation of the three-phase current;
calculating an over capacity rate according to daily electricity consumption, daily valley electricity consumption and daily maximum demand of a primary meter of a special transformer user, which are acquired by an electricity monitoring system, and determining whether daily over capacity abnormality exists or not based on a preset abnormality judgment rule of the maximum demand over capacity;
according to the electric quantity and three-phase current data of the primary meter of the special transformer user, which are acquired by the electric quantity monitoring system, the user with the daily electric quantity being zero but the current value being not zero is initially judged as an abnormal zero-degree user, and whether the current abnormality of the zero-degree user exists is determined by eliminating the conditions of abnormal measurement acquisition and measurement point types.
8. The data quality transaction processing system of claim 6, wherein the input or/and approval module is specifically configured to perform the following operations:
presetting a plurality of work order processing templates;
receiving a work order processing type input or selected by a work order processing personnel or/and an abnormal type of electric power related data, automatically screening or matching a work order processing template corresponding to the input or selected content from a plurality of preset work order processing templates according to the input or selected content, and presenting the work order processing template to the work order processing personnel so that the work order processing personnel can fill in related information of work order processing based on the work order processing template;
and analyzing the work order information filled by the work order processing personnel, and determining whether to automatically send the work order information to a system of a second-level processing personnel corresponding to the work order information or to automatically approve the work order information by a computer system based on the judgment of whether one or more items of data in the analysis exceed a preset threshold value.
9. The data quality transaction system of claim 6, wherein the data quality adopts four types of indicators, namely data integrity, data accuracy, data consistency and data timeliness, as data quality indicators.
10. The data quality transaction processing system of claim 6, further comprising a pre-processing module that pre-processes data quality by:
selecting an ith data processing operation P in a set of data operations DOiUsing PiTo perform data processing operations, the resulting data quality is denoted as QiWherein i is a positive integer;
calculating data quality gain Δ Q ═ Qi-Qi-1If Δ Q > 0, the data is processed by operation PiPut in SjI is i +1, and returning to the first step until i is n, wherein n is a positive integer;
and j is enabled to be j +1, and the first step is returned until j is enabled to be n, wherein j is a positive integer.
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