阅读说明：本技术 一种基于电能表采集信息的计量异常分析处理系统 (Metering abnormity analysis and processing system based on electric energy meter acquisition information ) 是由 乔文俞 陈昊 刘婧 张密 谭煌 苏良立 李媛 李刚 李野 乔亚男 刘浩宇 卢静 于 2019-09-10 设计创作，主要内容包括：本发明涉及一种基于电能表采集信息的计量异常分析处理系统,其特征在于：包括数据治理模块、建立计量异常分析模型、计量异常工单的生成管理模块以及现场移动作业处理模块。本发明实现计量异常的自动诊断、生成工单、工单处理的线上全流程闭环管理；实现计量异常原因的精准分析,减少无效工单和现场排查次数,节约大量的人力物力成本；线上全流程的处理方式提高了管理的精细化水平,创新工作模式,有效规范工作流程和质量管控。(The invention relates to a metering abnormity analysis processing system based on electric energy meter collected information, which is characterized in that: the system comprises a data management module, a generation management module for establishing a metering abnormity analysis model and a metering abnormity work order, and a field mobile operation processing module. The invention realizes the online full-flow closed-loop management of automatic diagnosis of metering abnormity, generation of work orders and work order processing; the method has the advantages that accurate analysis of the reasons of the metering abnormality is realized, invalid work orders and on-site troubleshooting times are reduced, and a large amount of manpower and material resource cost is saved; the online full-flow processing mode improves the refinement level of management, creates a working mode, and effectively standardizes the working flow and quality control.)

1. The utility model provides a measurement anomaly analysis processing system based on electric energy meter information collection which characterized in that: the system comprises a data management module, a generation management module for establishing a metering abnormity analysis model and a metering abnormity work order, and a field mobile operation processing module;

the data management module comprises traceability management of historical electric quantity data and data management of a marketing business application system;

establishing a measurement anomaly analysis model, and automatically diagnosing measurement anomaly of the treated data;

the abnormal metering work order generation management module generates an abnormal metering work order according to the diagnosis result and carries out closed-loop management on the abnormal metering work order;

the field mobile operation processing module uses a mobile operation terminal APP to realize field order receiving, work order downloading and abnormal feedback of the intelligent meter operation error abnormity, supports the input of error measurement data of a field general meter and a user meter and the condition of the user power consumption load, supports field shooting and uploading, supports the initiation of power consumption inspection and the fault flow of a metering device, and supports the feedback of the measurement result of a metering peripheral.

2. The metering anomaly analysis and processing system based on the electric energy meter collected information according to claim 1, characterized in that: the traceability of the historical electric quantity data is controlled by aiming at the conditions of user form change, file change, station-to-station relation change and the like, the system can record the data before and after change at the same time, thereby realizing the traceability of the historical electric quantity data before and after change and supporting the abnormal metering analysis.

3. The metering anomaly analysis and processing system based on the electric energy meter collected information according to claim 1, characterized in that: the data governance of the marketing business application system is as follows: firstly, historical archive integrity management of a transformer area, a metering point, a metering device, an acquisition terminal and the like is carried out; secondly, the relevance of historical archive information such as a disassembled and replaced meter, a sales counter and the like and the station area information is ensured, the reduction of the electric quantity data information of the disassembled and replaced meter is supported, and the traceability of the station area information of the electric energy meter before and after the change of the gear of the electric energy meter user is realized; and thirdly, continuously promoting the treatment work of the indoor variable relationship of the transformer area.

4. The metering anomaly analysis and processing system based on the electric energy meter collected information according to claim 1, characterized in that: the establishment of the abnormal metering analysis model comprises the following steps:

(1) optimizing an electric energy representation value unevenness analysis model:

adding an abnormal processing importance grade diagnosis model, eliminating the turning condition of the electric energy representation value, further combing the abnormal reasons of the uneven electric energy representation value, adding into a metering abnormal knowledge base, supporting abnormal analysis application,

the anomaly handling importance level diagnosis model is as follows:

(forward/reverse active total electric energy indicating value-sigma (forward/reverse active each rate electric energy indicating value) | > rate number K

The K value in the formula is subjected to hierarchical management according to different threshold values and can be dynamically adjusted;

(2) optimizing a flying analysis model of the electric energy meter:

increasing the importance level of exception handling, and establishing a diagnosis model of electric energy meter flying:

daily electric quantity/daily maximum theoretical electric quantity > K

The K value in the formula is subjected to hierarchical management according to different threshold values and can be dynamically adjusted;

(3) optimizing a backward walking analysis model of the electric energy meter:

according to different daily maximum theoretical electric quantity calculation methods of different meter types and different user types, different meter types are distinguished, an electric energy expression value overturning and meter changing judgment method is designed in a calculation model, the conditions of electric energy expression value overturning and meter changing are eliminated in an abnormal diagnosis method, the generation reason of the electric energy meter falling abnormality is combed, and support is provided for the construction of a metering abnormality knowledge base;

(4) optimizing an electric energy meter stop analysis model:

increasing an electric energy meter stop-go diagnosis method according to different users and combing the reasons of the electric energy meter stop-go abnormality:

the diagnosis method for the special transformer user comprises the following steps: adopting a diagnostic method that the difference value of forward/reverse active total electric energy indication values of the electric energy meter for 3 continuous days is equal to 0, and 3 continuous integral point values of total active power greater than K are monitored in the time period;

the low-voltage user diagnosis method of the object-oriented protocol comprises the following steps: adopting 1) the difference values of the daily positive/reverse active total electric energy indication values of the electric energy meter within N days to be equal to 0; 2) when the active power is monitored to have 3 continuous integer values greater than K in the time period meeting the condition 1, the active power is used as a diagnosis method;

the low-voltage user diagnosis method with four-point acquisition comprises the following steps: 1) the difference values of the daily positive/negative active total electric energy indication values of the electric energy meter within N days are all equal to 0; 2) when the condition 1 is met, 3 values of the active power are monitored to be larger than K, and the active power is used as a diagnosis method;

(5) optimizing a reverse electric quantity abnormity analysis model:

setting a reverse electric quantity threshold value of the electric energy meter, judging the importance level of the abnormal handling, and designing a reverse electric quantity abnormal diagnosis method according to different task configuration conditions, wherein the method specifically comprises the following steps:

aiming at a low-voltage user with a configured reverse electric quantity acquisition task, judging according to the condition that the reverse active total electric quantity indication value of the electric energy meter is greater than 0, the reverse electric quantity of the electric energy meter is greater than a threshold value K on the same day, and the reverse active total electric quantity of the low-voltage user is greater than the forward active total electric quantity Q3;

for low-voltage users without configured reverse electric quantity acquisition tasks, reverse active total electric energy indication values of the electric energy meter are recalled twice per month for judgment, and recall operation is initiated for judgment on the 2 nd day after the normal reporting of the forward active total electric energy indication values within 7 days after the meter is replaced;

designing a power generation user judgment method in a calculation model, and excluding the condition that the power utilization property is a power generation user; and (4) combing the generation reason of the abnormal reverse electric quantity, bringing the generation reason into an algorithm model, and providing support for the construction of a metering abnormal knowledge base.

5. The metering anomaly analysis and processing system based on the electric energy meter acquisition information is characterized in that: according to the electricity utilization characteristics of low-voltage users, the stop-off judgment period of the electric energy meter is properly widened, and the electric energy meter can be dynamically adjusted; aiming at the phenomenon that a low-voltage user is easy to stop running after a new meter is installed or replaced, a judgment method for stopping running of an electric energy meter is triggered after the new meter is installed or replaced in a diagnosis method of the low-voltage user, so that abnormal running can be found in time, and the condition of missing report can be reduced.

6. The metering anomaly analysis and processing system based on the electric energy meter collected information according to claim 1, characterized in that: the metering anomaly automatic diagnosis module comprises:

(1) automatically diagnosing the unevenness abnormality of the electric energy representation value:

on the basis of an abnormal algorithm model with uneven electric energy representation values, after the master station finds that the measured data is abnormal, the master station introduces the automatic diagnosis of the master station, through recalling the daily frozen positive/reverse active electric energy representation values of the electric energy meter every day, the data is compared with the daily frozen positive/reverse active electric energy representation value data stored by the master station, primary diagnosis is completed, errors in collected data are preliminarily eliminated, and secondary diagnosis is carried out through the abnormal algorithm model again according to the recalling the electric energy meter data;

(2) automatically diagnosing the flying abnormality of the electric energy meter:

based on the electric energy meter flying abnormal algorithm model, the main station introduces the main station for automatic diagnosis after finding the abnormal phenomenon of the metering data, completes primary diagnosis and preliminarily eliminates data acquisition errors by comparing daily frozen forward/reverse active total electric energy indication values of the electric energy meter with daily frozen forward/reverse active total electric energy indication values stored by the main station, and performs secondary diagnosis through the abnormal algorithm model again according to the data of the electric energy meter recalled;

(3) automatically diagnosing the backward walking abnormality of the electric energy meter:

based on the electric energy meter backward walking abnormal algorithm model, the main station introduces the main station for automatic diagnosis after finding the abnormal phenomenon of the metering data, completes primary diagnosis and preliminarily eliminates data acquisition errors by comparing daily frozen forward/reverse active total electric energy indication values of the thoroughly-called electric energy meter with daily frozen forward/reverse active total electric energy indication values stored by the main station, and performs secondary diagnosis through the abnormal algorithm model again according to the thoroughly-called electric energy meter data;

(4) automatically diagnosing the stop and go abnormity of the electric energy meter:

based on the electric energy meter stop-and-go abnormal algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, completes the primary diagnosis and preliminarily eliminates the data acquisition error by comparing the daily frozen forward/reverse active total electric energy indication value of the electric energy meter with the daily frozen forward/reverse active total electric energy indication value stored by the main station through the recall of the electric energy meter every day, and performs the secondary diagnosis through the abnormal algorithm model again according to the data of the electric energy meter through the recall;

(5) automatic diagnosis of reverse electric quantity abnormality:

based on the reverse electric quantity abnormity algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormity phenomenon of the metering data, the daily frozen forward/reverse active total electric energy indication value of the electric energy meter is recalled thoroughly every day and is compared with the daily frozen forward/reverse active total electric energy indication value stored by the main station, the primary diagnosis is completed, the error of the collected data is eliminated preliminarily, and the secondary diagnosis is carried out through the abnormity algorithm model again according to the data recalled thoroughly.

7. The metering anomaly analysis and processing system based on the electric energy meter acquisition information is characterized in that: the indication value of the reverse active electric energy is daily freezing positive/reverse active total, peak, flat and valley.

8. The metering anomaly analysis and processing system based on the electric energy meter collected information according to claim 1, characterized in that: the closed-loop management module of the abnormal work order comprises:

(1) error early warning:

checking an error analysis result calculated by the intelligent electric energy meter operation error diagnosis analysis model, supporting statistics according to conditions such as a power supply unit, a statistics period, an error range and the like, displaying the operation error quantity of each unit intelligent meter in a chart mode, supporting a power supply unit to drill down, and enabling the quantity to be linked to details for checking;

(2) and (3) generating a work order:

according to the statistical analysis result of the intelligent meter operation error diagnosis model, a work order generation algorithm for abnormal operation errors of the electric energy meter is designed, a threshold value and a generation frequency of abnormal work orders are defined, automatic generation of the abnormal work orders is achieved, and meanwhile manual work order generation through early warning detail is supported;

(3) closed-loop work order processing:

bringing the running error abnormity of the intelligent meter into a remote analysis guide, and analyzing and positioning the reason of the abnormity; when the work order is dispatched to the platform area manager, the automatic triggering of the on-site inspection process is supported; the method supports the input feedback of field measurement data and the user power load condition and the submission of a white list; the work order is to be filed, and auditing and manual filing of the field feedback information of the abnormal operation error of the intelligent meter are realized; and the handling of the abnormal operation errors of the intelligent meter in the non-filed and filed links, such as inquiry, recall and the like is realized based on different post roles.

9. The metering anomaly analysis and processing system based on the electric energy meter acquisition information is characterized in that: the work order types include: the electric energy indicating value is not a smooth work order, the electric energy meter flying work order, the electric energy meter reversing work order, the electric energy meter stopping work order and the reverse electric quantity work order.

Technical Field

The invention belongs to the field of electric energy meter data acquisition and analysis, and relates to a metering abnormity analysis processing system based on electric energy meter acquisition information.

Background

The electricity utilization information acquisition system covered by the national network at the end of 2014 has realized the comprehensive coverage of all power users and gateways, realizes the online monitoring of metering devices and the real-time acquisition of important information such as user load, electric quantity, voltage and the like, can timely, completely and accurately provide basic data for advanced analysis and assistant decision research of related systems, and provides a solid information foundation for realizing intelligent bidirectional interaction of electric energy meters.

The current situation that the number of low-voltage transformer areas is large and the construction conditions are uneven causes a plurality of problems to be solved urgently in the process of improving the management level of the transformer areas, and the problems are mainly reflected in the following 3 aspects.

(1) Due to the dual influences of the energy supply side and the energy utilization side, a scientific and comprehensive evaluation means for the actual running state of the intelligent electric energy meter in the low-voltage transformer area is lacked;

(2) the current measurement abnormity on-line monitoring function has insufficient analysis accuracy, and still generates a large amount of work orders.

(3) The operation and maintenance dispatching of the intelligent electric energy meter in the low-voltage distribution area mainly depends on manual work, and contradiction exists between operation and maintenance resources and operation and maintenance requirements.

The above problems directly relate to the actual interests of the users and the operational benefits of the national network companies. Taking the electric power company of Tianjin city of the national grid as an example, the current access users of the low-voltage transformer area reach more than 580 thousands. The problem of metering abnormality is checked on site, which means huge workload and causes serious waste to power resources.

Through a search for a patent publication, no patent publication that is the same as the present patent application is found.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides a metering abnormity analysis processing system based on information collected by an electric energy meter.

The technical problem to be solved by the invention is realized by the following technical scheme:

the utility model provides a measurement anomaly analysis processing system based on electric energy meter information collection which characterized in that: the system comprises a data management module, a generation management module for establishing a metering abnormity analysis model and a metering abnormity work order, and a field mobile operation processing module;

the data management module comprises traceability management of historical electric quantity data and data management of a marketing business application system;

establishing a measurement anomaly analysis model, and automatically diagnosing measurement anomaly of the treated data;

the abnormal metering work order generation management module generates an abnormal metering work order according to the diagnosis result and carries out closed-loop management on the abnormal metering work order;

the field mobile operation processing module: the mobile operation terminal APP is used for realizing field order receiving, work order downloading and abnormal feedback of the running error abnormality of the intelligent meter, supporting the input of the error measurement data of a field general meter and a user meter and the condition of the user power load, supporting the field shooting and uploading, supporting the initiation of the power utilization inspection and the fault flow of the metering device and supporting the feedback of the measurement result of the metering peripheral.

The traceability of the historical electric quantity data is controlled by simultaneously recording data before and after change aiming at the conditions of user form change, file change, station-to-station relation change and the like, so that the traceability of the historical electric quantity data before and after change is realized, and abnormal metering analysis is supported.

Moreover, the data governance of the marketing business application system is as follows: firstly, historical archive integrity management of a transformer area, a metering point, a metering device, an acquisition terminal and the like is carried out; secondly, the relevance of historical archive information such as a disassembled and replaced meter, a sales counter and the like and the station area information is ensured, the reduction of the electric quantity data information of the disassembled and replaced meter is supported, and the traceability of the station area information of the electric energy meter before and after the change of the gear of the electric energy meter user is realized; and thirdly, continuously promoting the treatment work of the indoor variable relationship of the transformer area.

Moreover, the establishing of the abnormal metering analysis model comprises the following steps:

(1) optimizing an electric energy representation value unevenness analysis model:

adding an abnormal processing importance grade diagnosis model, eliminating the turning condition of the electric energy representation value, further combing the abnormal reasons of the uneven electric energy representation value, adding into a metering abnormal knowledge base, supporting abnormal analysis application,

the anomaly handling importance level diagnosis model is as follows:

(forward/reverse active total electric energy indicating value-sigma (forward/reverse active each rate electric energy indicating value) | > rate number K

The K value in the formula is subjected to hierarchical management according to different threshold values and can be dynamically adjusted;

(2) optimizing a flying analysis model of the electric energy meter:

increasing the importance level of exception handling, and establishing a diagnosis model of electric energy meter flying:

daily electric quantity/daily maximum theoretical electric quantity > K

The K value in the formula is subjected to hierarchical management according to different threshold values and can be dynamically adjusted;

(3) optimizing a backward walking analysis model of the electric energy meter:

according to different daily maximum theoretical electric quantity calculation methods of different meter types and different user types, different meter types are distinguished, an electric energy expression value overturning and meter changing judgment method is designed in a calculation model, the conditions of electric energy expression value overturning and meter changing are eliminated in an abnormal diagnosis method, the generation reason of the electric energy meter falling abnormality is combed, and support is provided for the construction of a metering abnormality knowledge base;

(4) optimizing an electric energy meter stop analysis model:

increasing an electric energy meter stop-go diagnosis method according to different users and combing the reasons of the electric energy meter stop-go abnormality:

the diagnosis method for the special transformer user comprises the following steps: the method comprises the steps that the difference value of forward/reverse active total electric energy indication values of an electric energy meter for 3 continuous days is equal to 0, and 3 continuous integral point values (any three points) of total active power are monitored to be larger than K in the period, so that the method is used as a diagnosis method;

the low-voltage user diagnosis method of the object-oriented protocol comprises the following steps: adopting 1) the difference values of the daily positive/reverse active total electric energy indication values of the electric energy meter within N days to be equal to 0; 2) when the active power is monitored to have 3 continuous integer values greater than K in the time period meeting the condition 1, the active power is used as a diagnosis method;

the low-voltage user diagnosis method with four-point acquisition comprises the following steps: 1) the difference values of the daily positive/negative active total electric energy indication values of the electric energy meter within N days are all equal to 0; 2) when the condition 1 is met, 3 values of the active power are monitored to be larger than K, and the active power is used as a diagnosis method;

(5) optimizing a reverse electric quantity abnormity analysis model:

setting a reverse electric quantity threshold value of the electric energy meter, judging the importance level of the abnormal handling, and designing a reverse electric quantity abnormal diagnosis method according to different task configuration conditions, wherein the method specifically comprises the following steps:

aiming at a low-voltage user with a configured reverse electric quantity acquisition task, judging according to the condition that the reverse active total electric quantity indication value of the electric energy meter is greater than 0, the reverse electric quantity of the electric energy meter is greater than a threshold value K on the same day, and the reverse active total electric quantity of the low-voltage user is greater than the forward active total electric quantity Q3;

for low-voltage users without configured reverse electric quantity acquisition tasks, reverse active total electric energy indication values of the electric energy meter are recalled twice per month for judgment, and recall operation is initiated for judgment on the 2 nd day after the normal reporting of the forward active total electric energy indication values within 7 days after the meter is replaced;

designing a power generation user judgment method in a calculation model, and excluding the condition that the power utilization property is a power generation user; and (4) combing the generation reason of the abnormal reverse electric quantity, bringing the generation reason into an algorithm model, and providing support for the construction of a metering abnormal knowledge base.

Moreover, the judgment period of stopping the electric energy meter is properly widened according to the electricity utilization characteristics of the low-voltage users, and the electric energy meter can be dynamically adjusted; aiming at the phenomenon that a low-voltage user is easy to stop running after a new meter is installed or replaced, a judgment method for stopping running of an electric energy meter is triggered after the new meter is installed or replaced in a diagnosis method of the low-voltage user, so that abnormal running can be found in time, and the condition of missing report can be reduced.

The metering anomaly automatic diagnosis module comprises:

(1) automatically diagnosing the unevenness abnormality of the electric energy representation value:

on the basis of an abnormal algorithm model with uneven electric energy representation values, after the master station finds that the measured data is abnormal, the master station introduces the automatic diagnosis of the master station, through recalling the daily frozen positive/reverse active electric energy representation values of the electric energy meter every day, the data is compared with the daily frozen positive/reverse active electric energy representation value data stored by the master station, primary diagnosis is completed, errors in collected data are preliminarily eliminated, and secondary diagnosis is carried out through the abnormal algorithm model again according to the recalling the electric energy meter data;

(2) automatically diagnosing the flying abnormality of the electric energy meter:

based on the electric energy meter flying abnormal algorithm model, the main station introduces the main station for automatic diagnosis after finding the abnormal phenomenon of the metering data, completes primary diagnosis and preliminarily eliminates data acquisition errors by comparing daily frozen forward/reverse active total electric energy indication values of the electric energy meter with daily frozen forward/reverse active total electric energy indication values stored by the main station, and performs secondary diagnosis through the abnormal algorithm model again according to the data of the electric energy meter recalled;

(3) automatically diagnosing the backward walking abnormality of the electric energy meter:

based on the electric energy meter backward walking abnormal algorithm model, the main station introduces the main station for automatic diagnosis after finding the abnormal phenomenon of the metering data, completes primary diagnosis and preliminarily eliminates data acquisition errors by comparing daily frozen forward/reverse active total electric energy indication values of the thoroughly-called electric energy meter with daily frozen forward/reverse active total electric energy indication values stored by the main station, and performs secondary diagnosis through the abnormal algorithm model again according to the thoroughly-called electric energy meter data;

(4) automatically diagnosing the stop and go abnormity of the electric energy meter:

based on the electric energy meter stop-and-go abnormal algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, completes the primary diagnosis and preliminarily eliminates the data acquisition error by comparing the daily frozen forward/reverse active total electric energy indication value of the electric energy meter with the daily frozen forward/reverse active total electric energy indication value stored by the main station through the recall of the electric energy meter every day, and performs the secondary diagnosis through the abnormal algorithm model again according to the data of the electric energy meter through the recall;

(5) automatic diagnosis of reverse electric quantity abnormality:

based on the reverse electric quantity abnormity algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormity phenomenon of the metering data, the daily frozen forward/reverse active total electric energy indication value of the electric energy meter is recalled thoroughly every day and is compared with the daily frozen forward/reverse active total electric energy indication value stored by the main station, the primary diagnosis is completed, the error of the collected data is eliminated preliminarily, and the secondary diagnosis is carried out through the abnormity algorithm model again according to the data recalled thoroughly.

And the indication value of the reverse active electric energy is daily freezing positive/reverse active total, peak, flat and valley.

Furthermore, the closed-loop management module for the abnormal work order includes:

(1) error early warning:

checking an error analysis result calculated by the intelligent electric energy meter operation error diagnosis analysis model, supporting statistics according to conditions such as a power supply unit, a statistics period, an error range and the like, displaying the operation error quantity of each unit intelligent meter in a chart mode, supporting a power supply unit to drill down, and enabling the quantity to be linked to details for checking;

(2) and (3) generating a work order:

according to the statistical analysis result of the intelligent meter operation error diagnosis model, a work order generation algorithm for abnormal operation errors of the electric energy meter is designed, a threshold value and a generation frequency of abnormal work orders are defined, automatic generation of the abnormal work orders is achieved, and meanwhile manual work order generation through early warning detail is supported;

(3) closed-loop work order processing:

bringing the running error abnormity of the intelligent meter into a remote analysis guide, and analyzing and positioning the reason of the abnormity; when the work order is dispatched to the platform area manager, the automatic triggering of the on-site inspection process is supported; the method supports the input feedback of field measurement data and the user power load condition and the submission of a white list; the work order is to be filed, and auditing and manual filing of the field feedback information of the abnormal operation error of the intelligent meter are realized; and the handling of the abnormal operation errors of the intelligent meter in the non-filed and filed links, such as inquiry, recall and the like is realized based on different post roles.

Moreover, the types of work orders include: the electric energy indicating value is not a smooth work order, the electric energy meter flying work order, the electric energy meter reversing work order, the electric energy meter stopping work order and the reverse electric quantity work order.

The invention has the advantages and beneficial effects that:

according to the invention, the original metering anomaly analysis model is optimized, functions of anomaly grade analysis, anomaly reason combing, interference factor elimination and the like are added, and the accuracy of anomaly analysis is improved. And developing measurement anomaly analysis and processing functions based on the measurement online monitoring model. The optimization of the abnormal metering analysis model in the aspects of abnormal grade, abnormal reason combing, interference factor elimination and the like is realized; the online full-flow closed-loop management of automatic diagnosis of metering abnormity, generation of work orders and work order processing is realized; the application transformation, on-site order receiving, feedback and the like of the mobile operation terminal are realized.

Drawings

Fig. 1 is an overall system architecture diagram of the present invention.

Detailed Description

The present invention is further illustrated by the following specific examples, which are intended to be illustrative, not limiting and are not intended to limit the scope of the invention.

A metering abnormity analysis and processing system based on electric energy meter acquisition information is innovative in that: the system comprises a data management module, a generation management module for establishing a metering abnormity analysis model and a metering abnormity work order, and a field mobile operation processing module;

the data management module comprises traceability management of historical electric quantity data and data management of a marketing business application system;

establishing a measurement anomaly analysis model, and automatically diagnosing measurement anomaly of the treated data;

the abnormal metering work order generation management module generates an abnormal metering work order according to the diagnosis result and carries out closed-loop management on the abnormal metering work order;

the field mobile operation processing module: the mobile operation terminal APP is used for realizing field order receiving, work order downloading and abnormal feedback of the running error abnormality of the intelligent meter, supporting the input of the error measurement data of a field general meter and a user meter and the condition of the user power load, supporting the field shooting and uploading, supporting the initiation of the power utilization inspection and the fault flow of the metering device and supporting the feedback of the measurement result of the metering peripheral.

The traceability of the historical electric quantity data is controlled by aiming at the conditions of user form change, file change, station-to-station relation change and the like, and the system can record the data before and after change at the same time, so that the traceability of the historical electric quantity data before and after change is realized, and abnormal metering analysis is supported.

The marketing business application system data governance comprises historical archive integrity governance of a developing platform area, a metering point, a metering device, an acquisition terminal and the like. And secondly, the relevance between the historical archive information of the disassembled and replaced meter, the sales counter and the like and the station area information is ensured, the reduction of the electric quantity data information of the disassembled and replaced meter is supported, and the traceability of the station area information of the electric energy meter before and after the change of the gear of the electric energy meter user is realized. And thirdly, continuously promoting the treatment work of the indoor variable relationship of the transformer area.

The construction of the abnormal metering analysis model comprises the following steps:

(1) optimization electric energy representation value unevenness analysis model

In order to deepen the treatment efficiency and the management level of the uneven data of the electric energy representation value, improve the accuracy of abnormal reason analysis, increase the importance level of abnormal treatment, eliminate the overturning condition of the electric energy representation value, further sort out the abnormal reasons of the uneven electric energy representation value, add a metering abnormal knowledge base and support abnormal analysis application.

The anomaly handling importance level diagnosis model is as follows: the K value in | (positive/reverse active total electric energy indicating value-sigma (positive/reverse active each rate electric energy indicating value) | > rate number K is managed in a grading way according to different threshold values and can be dynamically adjusted.

(2) Optimization electric energy meter flying analysis model

Increasing the importance level of exception handling, and according to a diagnosis model of electric energy meter flying: and carrying out hierarchical management on the K values in the daily electric quantity/daily maximum theoretical electric quantity > K according to different thresholds, and dynamically adjusting. According to different daily maximum theoretical electric quantity calculation methods of different meter types, and in combination with different user types, a model is created to distinguish different meter types. The method for calculating the maximum theoretical electric quantity is adjusted, a plurality of threshold value intervals are designed aiming at various conditions of the ratio of the forward/reverse daily electric quantity (not multiplied by the transformation ratio) of the electric energy meter to the daily maximum theoretical electric quantity of the electric energy meter, and the threshold value can be dynamically adjusted. And (4) adding a turnover judgment method, designing the electric energy expression value turnover judgment method in the calculation model, and eliminating the condition of electric energy expression value turnover in abnormal diagnosis and recovery algorithms. The method and the device can be used for solving the generation reasons of the abnormal flying away of the electric energy meter, such as the faults of acquisition equipment, the faults of the electric energy meter, the daily electric quantity of a user exceeding the receiving capacity and the like, and provide support for the construction of the abnormal metering knowledge base.

(3) Optimization electric energy meter backward walking analysis model

According to different daily maximum theoretical electric quantity calculation methods of different meter types, different meter types are distinguished by combining different user types. And designing an electric energy representation value overturning and meter changing judgment method in the calculation model, and eliminating the electric energy representation value overturning and meter changing in the abnormal diagnosis method. The method and the device can be used for combing the generation reasons of the backward walking abnormity of the electric energy meter, such as acquisition equipment meter reading parameter errors, acquisition equipment faults, electric energy meter faults and the like, and provide support for the construction of a metering abnormity knowledge base.

(4) Optimization electric energy meter stop-go analysis model

And adding an electric energy meter stop diagnosis method according to different users and combing the reasons of the abnormal stop of the electric energy meter.

The diagnosis method for the special transformer user comprises the following steps: the difference value of forward/reverse active total electric energy indication values of the electric energy meter for 3 continuous days is equal to 0, and 3 continuous integral point values (any three points) of the total active power are monitored to be greater than K in the period, so that the diagnosis method is adopted.

The low-voltage user diagnosis method of the object-oriented protocol comprises the following steps: adopting 1) the difference values of the daily positive/reverse active total electric energy indication values of the electric energy meter within N days to be equal to 0; 2) and 3 continuous integer values of active power greater than K are monitored in the time period meeting the condition 1, and the method is used as a diagnosis method.

The low-voltage user diagnosis method with four-point acquisition comprises the following steps: 1) the difference values of the daily positive/negative active total electric energy indication values of the electric energy meter within N days are all equal to 0; 2) and 3 values of the active power which is monitored to be more than K in the time period which meets the condition 1 are used as a diagnosis method.

According to the electricity utilization characteristics of low-voltage users, the stop-off judgment period of the electric energy meter is properly widened, and the electric energy meter can be dynamically adjusted. Aiming at the phenomenon that a low-voltage user is easy to stop running after a new meter is installed or replaced, a judgment method for stopping running of an electric energy meter is triggered after the new meter is installed or replaced in a diagnosis method of the low-voltage user, so that abnormal running can be found in time, and the condition of missing report can be reduced.

(5) Optimized reverse electric quantity abnormity analysis model

Setting a reverse electric quantity threshold value of the electric energy meter, judging the importance level of the abnormal handling, and designing a reverse electric quantity abnormal diagnosis method according to different task configuration conditions.

And aiming at the low-voltage users with the configured reverse electric quantity acquisition task, judging according to the condition that the reverse active total electric quantity indication value of the electric energy meter is greater than 0, the reverse electric quantity of the electric energy meter is greater than a threshold value K on the same day, and the condition that the reverse active total electric quantity of the low-voltage users > the forward active total electric quantity Q3 is met. And for low-voltage users without a configured reverse electric quantity acquisition task, increasing reverse active total electric energy indication values of the electric energy meter to be recalled twice per month for judgment, and initiating recall operation for judgment on the 2 nd day after the normal reporting of the forward active total electric energy indication values within 7 days after the meter is changed. A power generation user judgment method is designed in a calculation model, and the condition that the power utilization property is a power generation user is eliminated. And (4) combing the generation reason of the abnormal reverse electric quantity, bringing the generation reason into an algorithm model, and providing support for the construction of a metering abnormal knowledge base.

The automatic diagnosis of the metering abnormality comprises the following contents:

(1) automatic diagnosis of unevenness abnormality of electric energy representation value

Based on the abnormal algorithm model of the uneven electric energy representation value, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, compares the daily frozen forward/reverse active electric energy representation value (daily frozen forward/reverse active total, peak, flat and valley) data of the electric energy meter with the daily frozen forward/reverse active electric energy representation value (daily frozen forward/reverse active total, peak, flat and valley) data stored by the main station to complete the primary diagnosis and primarily eliminate the data acquisition error, and carries out the secondary diagnosis through the abnormal algorithm model again according to the data of the electric energy meter.

(2) Automatic diagnosis for abnormal flying of electric energy meter

Based on the electric energy meter flying abnormal algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, the main station thoroughly calls the daily frozen forward/reverse active total electric energy indicating value of the electric energy meter every day to be compared with the daily frozen forward/reverse active total electric energy indicating value stored by the main station, completes the primary diagnosis and preliminarily eliminates the data acquisition error, and carries out the secondary diagnosis through the abnormal algorithm model according to the thoroughly called electric energy meter data again

(3) Automatic diagnosis for backward walking abnormity of electric energy meter

Based on the electric energy meter backward walking abnormal algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, the daily frozen forward/backward active total electric energy indication value of the electric energy meter is thoroughly called every day to be compared with the daily frozen forward/backward active total electric energy indication value stored by the main station, the primary diagnosis is completed, the data acquisition error is preliminarily eliminated, and the secondary diagnosis is carried out through the abnormal algorithm model according to the data of the electric energy meter thoroughly called again.

(4) Automatic diagnosis for stop and go abnormity of electric energy meter

Based on the electric energy meter stop-go abnormal algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormal phenomenon of the metering data, the daily frozen forward/reverse active total electric energy indication value of the electric energy meter is thoroughly called every day to be compared with the daily frozen forward/reverse active total electric energy indication value stored by the main station, the primary diagnosis is completed, the data acquisition error is preliminarily eliminated, and the secondary diagnosis is carried out through the abnormal algorithm model according to the data of the electric energy meter thoroughly called again.

(5) Automatic diagnosis of reverse electric quantity abnormality

Based on the reverse electric quantity abnormity algorithm model, the main station introduces the automatic diagnosis of the main station after finding the abnormity phenomenon of the metering data, the daily frozen forward/reverse active total electric energy indication value of the electric energy meter is recalled thoroughly every day and is compared with the daily frozen forward/reverse active total electric energy indication value stored by the main station, the primary diagnosis is completed, the error of the collected data is eliminated preliminarily, and the secondary diagnosis is carried out through the abnormity algorithm model again according to the data recalled thoroughly.

The closed-loop management of the abnormal early warning work order comprises the following contents:

(1) error early warning

Checking error analysis results calculated by the intelligent electric energy meter operation error diagnosis analysis model, supporting statistics according to conditions such as power supply units, statistics periods, error ranges and the like, displaying the operation error quantity of each unit intelligent meter in a chart mode, supporting drilling of the power supply units, and enabling the quantity to be linked to details for checking

(2) Work order generation

According to the statistical analysis result of the intelligent meter operation error diagnosis model, a work order generation algorithm for abnormal operation errors of the electric energy meter is designed, a threshold value and a generation frequency of abnormal work orders are defined, automatic generation of the abnormal work orders is achieved, and meanwhile manual work order generation through early warning detail is supported. The work order types include: the electric energy indicating value is not a smooth work order, the electric energy meter flying work order, the electric energy meter reversing work order, the electric energy meter stopping work order and the reverse electric quantity work order.

(3) Closed loop work order processing

Bringing the running error abnormity of the intelligent meter into a remote analysis guide, and analyzing and positioning the reason of the abnormity; when the work order is dispatched to the platform area manager, the automatic triggering of the on-site inspection process is supported; the method supports the input feedback of field measurement data and the user power load condition and the submission of a white list; the work order is to be filed, and auditing and manual filing of the field feedback information of the abnormal operation error of the intelligent meter are realized; and the handling of the abnormal operation errors of the intelligent meter in the non-filed and filed links, such as inquiry, recall and the like is realized based on different post roles.

The invention provides a metering anomaly analysis processing system based on electric energy meter collected information, which increases the contents of traceability management and the like of historical data, continuously optimizes a metering online monitoring model from the aspects of anomaly level, anomaly reason combing, interference factor elimination and the like, and increases the accuracy of anomaly analysis. And on-line full-flow closed-loop management of automatic diagnosis of metering abnormity, generation of work orders and work order processing is realized based on a metering on-line monitoring model. The method has the advantages of realizing accurate analysis of the reasons of metering abnormality, reducing invalid work orders and on-site troubleshooting times, and saving a large amount of manpower and material cost. The online full-flow processing mode improves the refinement level of management, creates a working mode, and effectively standardizes the working flow and quality control.

Although the embodiments of the present invention and the accompanying drawings are disclosed for illustrative purposes, those skilled in the art will appreciate that: various substitutions, changes and modifications are possible without departing from the spirit and scope of the invention and the appended claims, and therefore the scope of the invention is not limited to the disclosure of the embodiments and the accompanying drawings.