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CN113821540A - A method and device for realizing abnormal power consumption judgment based on rule engine - Google Patents

A method and device for realizing abnormal power consumption judgment based on rule engine Download PDF

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CN113821540A
CN113821540A CN202111113299.8A CN202111113299A CN113821540A CN 113821540 A CN113821540 A CN 113821540A CN 202111113299 A CN202111113299 A CN 202111113299A CN 113821540 A CN113821540 A CN 113821540A
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李剑
祝永晋
曹卫青
孔峥
朱霖
于广荣
邵俊
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Jiangsu Fangtian Power Technology Co Ltd
Jiangsu Frontier Electric Power Technology Co Ltd
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Abstract

本发明公开一种基于规则引擎用电异常研判的实现方法和装置,方法包括以下步骤:获取目标信息;分析目标信息的特征,梳理出目标信息之间的数据流向及计算层次;根据数据流向及计算层次,抽取目标信息,建立多层次的数据仓库;从低到高逐层使用规则引擎对多层次的数据仓库进行研判计算,查找出用电异常数据。本发明的方法和装置能够降低用电异常诊断使用的门槛,可快速实现异常诊断逻辑新增或变更,同时减少风险和降低成本,支撑异常诊断持续优化工作,提升电力计量业务精益化管理水平。

Figure 202111113299

The invention discloses a method and device for realizing the judgment of abnormal electricity consumption based on a rule engine. The method comprises the following steps: acquiring target information; analyzing the characteristics of the target information, and sorting out the data flow and calculation level between the target information; Calculate the level, extract the target information, and establish a multi-level data warehouse; use the rule engine to conduct research and calculation on the multi-level data warehouse layer by layer from low to high, and find out abnormal electricity consumption data. The method and device of the present invention can lower the threshold for the use of abnormal power consumption diagnosis, can quickly realize the addition or modification of abnormal diagnosis logic, reduce risks and costs, support the continuous optimization of abnormal diagnosis, and improve the lean management level of power metering business.

Figure 202111113299

Description

Method and device for implementing electricity utilization abnormity study and judgment based on rule engine
Technical Field
The invention relates to the technical field of electric power metering, in particular to a method and a device for researching and judging electricity utilization abnormity based on a rule engine.
Background
With the popularization of the electricity utilization information acquisition system, massive electricity utilization data can be acquired, and a solid data foundation is provided for large data analysis in an electricity utilization link. However, in the face of the increase of massive power consumption data, most power departments only use the traditional statistical method to perform anomaly analysis at present, and the event information hidden behind the anomaly data cannot be effectively extracted. The power utilization abnormity research and judgment is to analyze and judge target information such as collected data, user power utilization working conditions, power supply equipment working conditions, collecting device working conditions and the like reasonably and try to find out the problems such as user power utilization abnormity, power supply equipment abnormity, collecting device abnormity and the like. In order to reduce the operation and maintenance cost and continuously improve the accuracy of studying and judging the abnormal events, the abnormal studying and judging method needs to be continuously optimized. How to rapidly diagnose and logically judge the abnormal events, reduce the power utilization risk and reduce the cost of studying and judging the abnormal events is a problem to be solved urgently.
Through search, the Chinese special benefit 2019, 8, 12 and the like with the publication number of CN110531305A disclose a power abnormity monitoring system, a platform and a method thereof, wherein the monitored objects are all levels of metering gateways, and the monitoring system comprises the following steps: the system comprises a plurality of acquisition terminals, a monitoring platform and a monitoring server, wherein the acquisition terminals are used for acquiring power consumption data of each level of metering gateway in real time and uploading the data to the monitoring platform, and the monitoring platform comprises a rule module, a calculation analysis module and an abnormality judgment output module; the rule module is used for storing a parameter threshold value of the electricity utilization data during abnormal judgment; the calculation analysis module is used for analyzing whether abnormal conditions exist in each level of metering gateway or not according to the parameter threshold and the power consumption data uploaded by each acquisition terminal; and the abnormity judgment output module is used for outputting the metering gateway information corresponding to the abnormal condition if the abnormal condition exists in the analysis result of the calculation analysis module. Through the real-time acquisition of the power consumption data of the metering gateways at all levels and uploading to the monitoring platform for real-time monitoring, the method is more reliable and more efficient than the conventional power system abnormity monitoring mode. However, the logic for abnormality diagnosis can be completed only by matching the rule module, the calculation analysis module and the abnormality judgment output module, and the implementation mode is complex; in addition, for different types of power utilization terminals, the abnormal conditions are complex and variable, the method for setting the threshold parameters through the rule module cannot meet the power utilization abnormality existing in the existing power utilization conditions, and the best matching judgment logic cannot be set to study and judge the data.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method and a device for studying and judging electricity utilization abnormity based on a rule engine, and solves the technical problems of low analysis accuracy, too long diagnosis time and high operation and maintenance cost of electricity utilization abnormity events in the prior art.
The invention provides a method for judging electricity utilization abnormity based on a rule engine on one hand, which comprises the following steps:
acquiring target information;
analyzing the characteristics of the target information, and combing the data flow direction and the calculation level among the target information;
extracting target information according to the data flow direction and the calculation level, and establishing a multi-level data warehouse;
and (4) carrying out research and calculation on the multi-level data warehouse by using a rule engine layer by layer from low to high, and finding out abnormal electricity utilization data.
In the technical scheme, firstly, data acquisition is carried out on equipment such as an electric energy meter, a terminal and a secondary circuit polling instrument through an electricity information acquisition system, and the acquired data is analyzed and calculated to obtain target information; secondly, analyzing the characteristics of the target information, and combing the data flow direction and the calculation level among the target information; thirdly, extracting target information according to the data flow direction and the calculation level, and establishing a multi-level data warehouse; providing a data base for subsequent study and judgment of data; and finally, carrying out study calculation on the multi-level data warehouse by using a rule engine layer by layer from low to high, and finding out abnormal power utilization data. According to the invention, the target information is researched, judged and calculated through the rule engine, the power utilization abnormity meeting the query condition is found out, the use threshold of abnormity diagnosis is reduced, the increment and change of abnormity diagnosis logic can be rapidly realized, the risk and the cost are reduced, the continuous optimization work of abnormity diagnosis is supported, and the lean management level of the power metering service is improved.
Further, the target information comprises a user power utilization working condition, a power supply equipment working condition and an acquisition device working condition.
Further, the data flow direction comprises a client flow direction, a power supply flow direction, a collection flow direction and a time flow direction.
Further, the client flow direction refers to the data flow direction of the user power utilization working condition, and the calculation levels of the user power utilization working condition sequentially comprise an electric energy meter, a metering point, a user and an industry from low to high;
the power supply flow direction refers to the data flow direction of the working condition of the power supply equipment, and the calculation level of the working condition of the power supply equipment sequentially comprises an electric energy meter, a transformer area, a line and a transformer substation from low to high;
the acquisition flow direction refers to the data flow direction of the working condition of the acquisition device, and the calculation levels of the working condition of the acquisition device are respectively an electric energy meter, a terminal, a channel and a master station from low to high;
the time flow direction is the data flow direction of the time dimension, and the calculation levels of the time dimension are respectively minutes, days, nearly 15 days and months from low to high.
Further, the step of establishing a multi-level data warehouse further comprises: counting layer by layer according to the client flow direction to obtain a client flow direction data table; carrying out step-by-step statistics according to the power supply flow direction to obtain a power supply flow direction data table; counting layer by layer according to the flow direction of the collected data to obtain a collected flow direction data table; and carrying out layer-by-layer statistics according to the time flow to obtain a time flow data table.
Further, the step of using the rule engine to perform the studying and judging calculation further comprises:
establishing a research and judgment rule database, and registering the research and judgment rule database in a rule engine;
inputting the data tables in the data warehouse into a rule engine layer by layer to form a data stream;
and the rule engine performs rule calculation on the data stream according to the study and judgment rule database to obtain a study and judgment result.
Further, if the studying and judging result is data abnormity, recording the abnormal data flow to an abnormity database; and if the judging result is not abnormal, recording the data stream to the operation database.
Further, the abnormal electricity consumption data includes abnormal backward movement of the electric energy meter, and the abnormal backward movement determination mode of the electric energy meter is as follows: the data of the electric energy meter is reduced compared with the data of the last time.
In another aspect, the present invention provides an apparatus for implementing rules engine-based power consumption anomaly study, including:
a collecting unit: the analysis unit is used for acquiring target information and sending the acquired target information to the analysis unit;
an analysis unit: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for receiving target information, performing characteristic analysis on the received target information and combing data flow direction and calculation level among the target information;
a processing unit: the analysis unit is connected with the storage unit and used for extracting target information according to the data flow direction and the calculation level and establishing a multi-level data warehouse;
a judging unit: and the processing unit is connected with the data warehouse and is used for receiving the multi-level data warehouse, conducting research and calculation on the multi-level data warehouse by using the rule engine layer by layer from low to high, and finding out abnormal power utilization data.
Compared with the prior art, the invention has the beneficial effects that:
(1) the method provided by the invention combs out the data flow direction and the calculation level among the target information by carrying out characteristic analysis on the target information, extracts the target information according to the data flow direction and the calculation level, establishes a multi-level data warehouse, and finally carries out judging calculation on the multi-level data warehouse by using a rule engine layer by layer from low to high to find out abnormal power utilization data. The method reduces the use threshold of the abnormity diagnosis, can quickly realize the addition and change of the abnormity diagnosis logic, supports the continuous optimization work of the abnormity diagnosis, and improves the lean management level of the electric power metering service.
(2) The method provided by the invention improves the accuracy of studying and judging the electricity utilization abnormal events and reduces the electricity utilization risk; and the abnormity studying and judging cost and the operation and maintenance cost are reduced.
(3) The device provided by the invention acquires target information through the acquisition unit and sends the acquired target information to the analysis unit; the analysis unit analyzes the characteristics of the received target information and combs out the data flow direction and the calculation level among the target information; the processing unit extracts target information according to the data flow direction and the calculation level and establishes a multi-level data warehouse; the judging unit receives the multi-level data warehouse, and the rule engine is used for studying, judging and calculating the multi-level data warehouse layer by layer from low to high to find out abnormal electricity utilization data. The device provided by the invention reduces the threshold of abnormality diagnosis, can quickly realize addition and change of abnormality diagnosis logic, supports continuous optimization work of abnormality diagnosis, and improves the lean management level of electric power metering service.
Drawings
FIG. 1 is a flowchart of an implementation method for rule engine power consumption anomaly-based evaluation according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an implementation apparatus for studying and determining an electrical anomaly based on a rule engine according to an embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood 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 of the present invention without any inventive step, are within the scope of the present invention.
Example one
Referring to fig. 1, the present embodiment provides a method for studying and judging power consumption anomalies based on a rule engine, including the following steps:
step 1: acquiring target information; the power consumption information acquisition system acquires data of the electric energy meter, the terminal, the secondary circuit polling instrument and other equipment, analyzes and calculates the acquired data, and generates target information of a user power consumption working condition, a power supply equipment working condition, an acquisition device, a working condition and the like.
Step 2: analyzing the characteristics of the target information, and combing the data flow direction and the calculation level among the target information; the data flow direction comprises a client flow direction, a power supply flow direction, a collection flow direction and a time flow direction, wherein:
1) the client flow direction refers to the data flow direction of the information related to the electricity utilization working condition of the user, and the calculation levels from low to high are respectively an electric energy meter, a metering point, the user and the industry;
2) the power supply flow direction refers to the data flow direction of the information related to the working condition of the power supply equipment, and the calculation levels from low to high are respectively an electric energy meter, a transformer area, a line and a transformer substation;
3) the acquisition flow direction refers to the data flow direction of the working condition of the acquisition device, and the calculation levels from low to high are respectively an electric energy meter and a terminal;
4) the time flow direction is the data flow direction of the time dimension, and the calculation levels are minutes, 1 day, nearly 15 days and months from low to high respectively.
And step 3: extracting target information according to the data flow direction and the calculation level, and establishing a multi-level data warehouse;
and extracting target information such as collected data, working condition data and the like according to the definition of the data flow direction and the calculation level, and establishing a multi-level data warehouse. The method specifically comprises the following steps:
1) the method is characterized in that collected data such as a voltage curve, a current curve, a power curve, a voltage phase angle curve, a current phase angle curve or a minute-level electric quantity and an indication value of the electric energy meter are fused, minute-level data containing voltage, current, power, a voltage phase angle, a current phase angle and an indication value are generated according to time alignment of each collecting point, and the minute-level data are stored in an electric energy meter-minute-level data meter of a data warehouse.
2) The daily freezing indication value, the electric quantity, the demand and other data of the electric energy meter are fused, daily data are generated according to the extreme value, the average value and other pre-aggregated values of the minute-level data, and the daily data are stored in a data warehouse electric energy meter-daily data meter.
3) And according to the flow direction of the client, carrying out summary statistics layer by layer and storing the pre-aggregated extreme values and average values of each layer into a metering point-daily data table, a user-daily data table and an industry-daily data table respectively.
4) And according to the power supply flow direction, carrying out summary statistics layer by layer and storing the pre-aggregated extreme values and average values of each layer into a transformer area-daily data table, a line-daily data table and a transformer substation-daily data table respectively.
5) And summarizing statistics layer by layer and pre-aggregated extreme values and average values of each layer according to the flow direction of the acquired data, and respectively storing the extreme values and the average values into a terminal-daily data table.
6) According to the time flow direction, the extreme values and the average values of layer-by-layer summary statistics and each layer pre-aggregation are respectively stored in a metering point-near 15 day data table, a user-near 15 day data table, an industry-near 15 day data table, a platform area-near 15 day data table, a line-near 15 day data table, a transformer substation-near 15 day data table, a terminal-near 15 day data table, a metering point-month data table, a user-month data table, an industry-month data table, a platform area-month data table, a line-month data table, a transformer substation-month data table and a terminal-month data table.
And 4, step 4: using a rule engine to study, judge and calculate the multi-level data warehouse layer by layer from low to high, and finding out the power utilization abnormity meeting the conditions; the method specifically comprises the following steps:
establishing a basic function, a power utilization abnormity studying and judging method, a definition studying and judging rule database and registering in a rule engine;
data are pulled from each layer of data table to form data flow;
using a rule engine to perform rule calculation on the data stream to form a judging result;
and recording the found abnormality in a warehouse.
In this embodiment, the step of performing the studying and calculating on the multi-level data warehouse by using the rule engine layer by layer from low to high specifically includes: defining a study and judgment rule to adapt to data flow according to a study and judgment method of electricity utilization abnormity; the electricity utilization abnormity studying and judging rule comprises the following steps:
1) the method is suitable for the power supply to the hierarchy of the electric energy meter and the time to day hierarchy, and the definition rule is that the electric energy meter falls down abnormally, the data of the electric energy meter read at this time is reduced compared with the data at the last time, and the research and judgment method is suitable for the power supply to the hierarchy of the electric energy meter and the time to day hierarchy, and the definition rule is
value(‘meter’,‘today’,‘pap’)-value(’meter’,‘yesterday’,’rap’)<0||
value(‘meter’,‘today’,‘rap’)-value(‘meter’,‘yesterday’,‘rap’)<0
2) The abnormal phase failure of voltage is the disconnection of one or more phases of voltage of a user power supply, the method is used for the power supply to flow to the level of an electric energy meter and the time to flow to the level of minutes, and the definition rule is that
count(value(‘meter’,‘minute’,‘Ua’)<0.78*param(‘Un’))>3||
count(value(‘meter’,‘minute’,‘Ub’)<0.78*param(‘Un’))>3||
count(value(‘meter’,‘minute’,‘Uc’)<0.78*param(‘Un’))>3
3) The study and judgment method is used for the level of customer flow direction 'user' and the level of time flow direction 'nearly 15 days' and the definition rule is that electricity quantity fluctuation abnormity is caused by meter change or occurrence of an event of opening a cover of an electric energy meter and the electricity quantity of a metering cabinet after opening the door obviously exceeds the electricity consumption before, and the study and judgment method is used for the level of customer flow direction 'user' and the level of time flow direction 'nearly 15 days' and has the following rule
TRIMMEAN(‘cons’,‘d15’,‘pap_e’,1,7,2)<TRIMMEAN(‘cons’,‘d15’,‘pap_e’,8,15,2)*0.5||
TRIMMEAN(‘cons’,‘d15’,‘pap_e’,1,7,2)>TRIMMEAN(‘cons’,‘d15’,‘pap_e’,8,15,2)*2
In this embodiment, the judging rule may be added or changed according to the diagnosis requirement.
In the embodiment, by analyzing the characteristics of the target information, the data flow direction/level is sorted, the studying and judging method is regularized, and the rule engine is used for studying and judging layer by layer, so that the exception diagnosis logic adjustment can be quickly realized, and meanwhile, the risk is reduced and the cost is reduced.
Example two:
referring to fig. 2, the present embodiment provides an implementation apparatus for studying and judging power consumption anomaly based on a rule engine, including:
a collecting unit: the analysis unit is used for acquiring target information and sending the acquired target information to the analysis unit;
an analysis unit: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for receiving target information, performing characteristic analysis on the received target information and combing data flow direction and calculation level among the target information;
a processing unit: the analysis unit is connected with the storage unit and used for extracting target information according to the data flow direction and the calculation level and establishing a multi-level data warehouse;
a judging unit: and the processing unit is connected with the data warehouse and is used for receiving the multi-level data warehouse, conducting research and calculation on the multi-level data warehouse by using the rule engine layer by layer from low to high, and finding out abnormal power utilization data.
The working principle is as follows:
the acquisition unit acquires data of equipment such as an electric energy meter, a terminal and a secondary circuit polling instrument, generates target information such as a user electricity utilization working condition, a power supply equipment working condition and an acquisition device working condition after preprocessing the acquired data, and sends the target information to the analysis unit;
after receiving the target data, the analysis unit analyzes the characteristics of the target information and combs the data flow direction and calculation level among the target information; the method specifically comprises the steps of customer flow direction, power supply flow direction, collection flow direction, time flow direction and the like; the client flow direction refers to the data flow direction of information related to the power utilization condition of a user, and the calculation levels from low to high are respectively an electric energy meter, a metering point, a user and an industry; the power supply flow direction refers to the data flow direction of the information related to the working condition of the power supply equipment, and the calculation levels from low to high are respectively an electric energy meter, a transformer area, a line and a transformer substation; the acquisition flow direction refers to the data flow direction of the working condition of the acquisition device, and the calculation levels from low to high are respectively an electric energy meter and a terminal; the time flow direction is the data flow direction of the time dimension, and the calculation levels are minutes, 1 day, nearly 15 days and months from low to high respectively. The analysis unit sends the sorted data flow direction and the calculation level to the processing unit;
the processing unit extracts target information according to the definition of the data flow direction and the calculation level and establishes a multi-level data warehouse; the process of establishing a data warehouse further comprises:
1) the method comprises the steps that collected data such as a voltage curve, a current curve, a power curve, a voltage phase angle curve, a current phase angle curve or a minute-level electric quantity and an indication value of the electric energy meter are fused, minute-level data containing voltage, current, power, a voltage phase angle, a current phase angle and an indication value are generated according to time alignment of each collecting point, and the minute-level data are stored in an electric energy meter-minute-level data meter of a data warehouse;
2) fusing data such as daily freezing indication values, electric quantity and demand of the electric energy meter, generating daily data by combining extreme values, average values and other pre-aggregated values of minute-level data according to days, and storing the daily data into a data warehouse electric energy meter-daily data meter;
3) according to the flow direction of a client, carrying out summary statistics layer by layer and storing the pre-aggregated extreme values and average values of each layer into a metering point-daily data table, a user-daily data table and an industry-daily data table respectively;
4) according to the power supply flow direction, carrying out summary statistics layer by layer and storing the pre-aggregated extreme values and average values of each layer into a transformer area-daily data table, a line-daily data table and a transformer substation-daily data table respectively;
5) according to the flow direction of the collected data, carrying out summary statistics layer by layer and storing the pre-aggregated extreme values and average values of each layer into a terminal-daily data table respectively;
6) according to the time flow direction, carrying out summary statistics layer by layer and storing the extreme values and average values of each layer pre-aggregation into a metering point-near 15 day data table, a user-near 15 day data table, an industry-near 15 day data table, a station area-near 15 day data table, a line-near 15 day data table, a transformer station-near 15 day data table, a terminal-near 15 day data table, a metering point-month data table, a user-month data table, an industry-month data table, a station area-month data table, a line-month data table, a transformer station-month data table and a terminal monthly data table;
the judgment unit is connected with the processing unit, and the rule engines are used for conducting research and calculation layer by layer from low to high to find out power utilization abnormity meeting the conditions. The process of judging calculation further comprises:
(1) creating a basic function and registering in a rule engine;
(2) pulling data from each layer of data table to form a data stream;
(3) the rule engine carries out rule calculation aiming at the data stream to form a judging result;
(4) and recording the found abnormality in a warehouse.
The implementation device for studying and judging the electricity consumption abnormity of the rule engine reduces the abnormity diagnosis threshold, can rapidly realize the addition and change of abnormity diagnosis logic, supports the continuous optimization work of abnormity diagnosis, and improves the lean management level of the electricity metering service.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
In the description herein, references to the description of the terms "one embodiment," "certain embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will 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 or all of the technical features may be equivalently replaced; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the present embodiments.

Claims (9)

1.一种基于规则引擎用电异常研判的实现方法,其特征在于,包括以下步骤:1. a realization method based on rule engine power consumption abnormal research and judgment, is characterized in that, comprises the following steps: 获取目标信息;Get target information; 分析目标信息的特征,梳理出目标信息之间的数据流向及计算层次;Analyze the characteristics of target information, and sort out the data flow and calculation level between target information; 根据数据流向及计算层次,抽取目标信息,建立多层次的数据仓库;According to the data flow and calculation level, extract the target information and establish a multi-level data warehouse; 从低到高逐层使用规则引擎对多层次的数据仓库进行研判计算,查找出用电异常数据。From low to high, the rule engine is used to analyze and calculate the multi-level data warehouse to find out abnormal electricity consumption data. 2.根据权利要求1所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,所述目标信息包括用户用电工况、供电设备工况、采集装置工况。2 . The method for realizing power consumption abnormality judgment based on a rule engine according to claim 1 , wherein the target information includes a user power consumption condition, a power supply equipment condition, and a collection device condition. 3 . 3.根据权利要求1所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,所述数据流向包括客户流向、供电流向、采集流向和时间流向。3 . The method for realizing power consumption abnormality judgment based on a rule engine according to claim 1 , wherein the data flow direction includes a customer flow direction, a power supply direction, a collection flow direction, and a time flow direction. 4 . 4.根据权利要求3所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,4. a kind of realization method based on rule engine power abnormality judgment according to claim 3, is characterized in that, 所述客户流向是指用户用电工况的数据流向,用户用电工况的计算层次由低到高依次包括电能表、计量点、用户、行业;The customer flow direction refers to the data flow direction of the user's electricity consumption condition, and the calculation level of the user's electricity consumption condition includes the electric energy meter, the metering point, the user, and the industry in order from low to high; 所述供电流向是指供电设备工况的数据流向,供电设备工况的计算层次由低到高依次包括电能表、台区、线路、变电站;The power supply current direction refers to the data flow direction of the power supply equipment operating conditions, and the calculation level of the power supply equipment operating conditions includes the electric energy meter, the station area, the line, and the substation in order from low to high; 所述采集流向是指采集装置工况的数据流向,采集装置工况的计算层次由低到高分别为电能表、终端、通道、主站;The collection flow direction refers to the data flow direction of the working condition of the collection device, and the calculation level of the working condition of the collection device from low to high is the electric energy meter, the terminal, the channel, and the main station; 所述时间流向是指时间维度的数据流向,时间维度的计算层次由低到高分别为分钟、日、近15日、月。The time flow refers to the data flow of the time dimension, and the calculation levels of the time dimension from low to high are minutes, days, the last 15 days, and months, respectively. 5.根据权利要求3所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,建立多层次的数据仓库的步骤进一步包括:根据客户流向逐层统计得到客户流向数据表;根据供电流向逐级统计得到供电流向数据表;根据采集数据流向逐层统计得到采集流向数据表;根据时间流向逐层统计得到时间流向数据表。5. a kind of realization method based on rule engine electricity abnormality research and judgment according to claim 3, is characterized in that, the step of establishing multi-level data warehouse further comprises: according to customer flow direction statistics layer by layer obtains customer flow direction data table; The supply current direction data table is obtained by the statistics of the current supply direction step by step; the acquisition flow direction data table is obtained according to the layer by layer statistics of the collected data flow direction; the time flow direction data table is obtained by the layer by layer statistics of the time flow direction. 6.根据权利要求1所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,使用规则引擎进行研判计算的步骤进一步包括:6. a kind of realization method based on rule engine power consumption abnormality research and judgment according to claim 1, is characterized in that, the step of using rule engine to carry out research and judgment calculation further comprises: 创建研判规则数据库,将研判规则数据库在规则引擎内注册;Create a research and judgment rule database, and register the research and judgment rule database in the rule engine; 将数据仓库中的数据表逐层输入规则引擎,形成数据流;Input the data tables in the data warehouse into the rule engine layer by layer to form a data flow; 规则引擎根据研判规则数据库对数据流进行规则计算,得到研判结果。The rule engine performs rule calculation on the data stream according to the judgment rule database, and obtains the judgment result. 7.根据权利要求6所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,若研判结果为数据异常,则将异常的数据流记录至异常数据库;若研判结果无异常,则将数据流记录至运行数据库。7. A kind of realization method based on rule engine power consumption abnormal research and judgment according to claim 6, is characterized in that, if the research and judgment result is data abnormality, then the abnormal data flow is recorded to the abnormal database; if the research and judgment result is not abnormal, The data flow is then logged to the operational database. 8.根据权利要求1所述的一种基于规则引擎用电异常研判的实现方法,其特征在于,所述用电异常数据包括电能表倒走异常,电能表倒走异常判定方式为:电能表本次数据比上次数据减少。8 . The method for realizing power consumption abnormality research and judgment based on a rule engine according to claim 1 , wherein the power consumption abnormality data includes the abnormality of reverse running of the electric energy meter, and the judgment method of the abnormal running of the electric energy meter is: the electric energy meter The data this time is lower than the previous data. 9.一种基于规则引擎用电异常研判的实现装置,其特征在于,包括:9. A realization device based on rule engine power consumption abnormality research and judgment, is characterized in that, comprises: 采集单元:用于获取目标信息,将获取的目标信息发送给分析单元;Acquisition unit: used to acquire target information, and send the acquired target information to the analysis unit; 分析单元:用于接收目标信息,并对接收的目标信息进行特征分析,梳理出目标信息之间的数据流向及计算层次;Analysis unit: used to receive target information, analyze the characteristics of the received target information, and sort out the data flow and calculation level between the target information; 处理单元:与所述分析单元连接,用于根据数据流向及计算层次,抽取目标信息,建立多层次的数据仓库;Processing unit: connected with the analysis unit, used for extracting target information according to the data flow direction and calculation level, and establishing a multi-level data warehouse; 判断单元:与所述处理单元连接,用于接收多层次的数据仓库,从低到高逐层使用规则引擎对多层次的数据仓库进行研判计算,查找出用电异常数据。Judging unit: connected with the processing unit, used for receiving multi-level data warehouses, using the rule engine to conduct research and calculation on the multi-level data warehouses layer by layer from low to high, and find out abnormal electricity consumption data.
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Application publication date: 20211221