CN114415101A - Intelligent electric meter operation error diagnosis and analysis method and system - Google Patents
Intelligent electric meter operation error diagnosis and analysis method and system Download PDFInfo
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- CN114415101A CN114415101A CN202111648199.5A CN202111648199A CN114415101A CN 114415101 A CN114415101 A CN 114415101A CN 202111648199 A CN202111648199 A CN 202111648199A CN 114415101 A CN114415101 A CN 114415101A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- G01R35/04—Testing or calibrating of apparatus covered by the other groups of this subclass of instruments for measuring time integral of power or current
Abstract
The invention discloses a method and a system for diagnosing and analyzing an operating error of an intelligent electric meter, wherein the system for diagnosing and analyzing the operating error of the intelligent electric meter comprises a data acquisition unit, a data processing unit, a database for diagnosing the operating error of the intelligent electric meter, an operation management database of the intelligent electric meter and a data storage unit, wherein the data acquisition unit is in communication connection with the data storage unit, the data storage unit is in communication connection with the data processing unit, and the data processing unit is respectively in communication connection with the database for diagnosing the operating error of the intelligent electric meter and the operation management database of the intelligent electric meter. According to the invention, the life cycle of the intelligent electric meter is divided into different periods, and different data acquisition strategies are adopted in different periods, so that the operation burden of the power supply management system is reduced, and meanwhile, the operation fault of the intelligent electric meter can be discovered in time or early.
Description
Technical Field
The invention relates to the technical field of power grids. In particular to a method and a system for diagnosing and analyzing the operation error of an intelligent electric meter.
Background
No matter the smart meter or the traditional meter, operation errors can occur during operation and use. When the operation error exceeds a certain range, the electric meter needs to be corrected or replaced so as to avoid the avoidable loss of power supply enterprises or power consumers. The existing method for diagnosing the operation error of the intelligent electric meter generally detects the operation condition of the intelligent electric meter by regularly acquiring power consumption data or irregularly acquiring data, and the method ignores that the internal electronic elements of the intelligent electric meter are aged to an extent that the intelligent electric meter is not damaged along with the increase of the service time of the intelligent electric meter, and the aged electronic components can bring certain influence on the operation condition of the intelligent electric meter. The same data acquisition strategy is adopted in the whole life cycle of the intelligent electric meter, so that the operation burden of a power supply management system is overweight, and the operation fault of the intelligent electric meter cannot be found timely or early.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to provide a method and a system for diagnosing and analyzing the operation error of the smart meter, wherein the life cycle of the smart meter is divided into different periods, and different data acquisition strategies are adopted in different periods, so that the operation burden of the power supply management system is reduced, and meanwhile, the operation fault of the smart meter can be discovered in time or earlier.
In order to solve the technical problems, the invention provides the following technical scheme:
the intelligent electric meter operation error diagnosis and analysis method comprises the following steps:
s1) acquiring the product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter of the user through a data acquisition unit and storing the acquired product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter under a data directory of the user;
s2) the data processing unit sets a data acquisition strategy for the intelligent electric meter according to the intelligent electric meter operation state historical data prestored in the database for intelligent electric meter operation error diagnosis and the intelligent electric meter product information acquired in the step S1) and the intelligent electric meter internet surfing time, and the data acquisition strategy specifically comprises the following operations:
s2-1) calling, by the data processing unit, historical data of the running state of the intelligent electric meter, which is pre-stored in the database for running error diagnosis of the intelligent electric meter and is a product with the same brand and the same model as the intelligent electric meter, according to the product information of the intelligent electric meter collected in the step S1);
s2-2) dividing the life cycle of the intelligent electric meter into a running stable period, a performance aging period and a standby period according to the online time of the intelligent electric meter and the historical data of the running state of the intelligent electric meter prestored in the database for diagnosing the running errors of the intelligent electric meter, wherein the running stable period is a period in which the factors other than the running errors of the intelligent electric meter are dominant, the performance aging period is a period in which the factors of the running errors of the intelligent electric meter are equivalent to internal factors and external factors, and the standby period is a period in which the running errors of the intelligent electric meter frequently occur and the expected time for replacing a new intelligent electric meter is reached;
s2-3) setting data acquisition strategies of the intelligent electric meter in a stable operation period, a performance aging period and a standby machine changing period;
s3) collecting the electricity data of the user according to the data collection strategy in the step S2-3), wherein the electricity data comprises electricity consumption, voltage and current;
s4) carrying out operation error judgment on the intelligent electric meter according to the electricity utilization data collected in the step S3).
According to the method for diagnosing and analyzing the operation errors of the intelligent electric meter, the operation stable period data acquisition strategy is an acquisition strategy combining regular acquisition and random acquisition, wherein in the regular acquisition, the nth time data acquisition time is tn＝tn-1+ Δ t, n is a natural number greater than or equal to 2, Δ t is 0 to 600 seconds.
According to the intelligent electric meter operation error diagnosis and analysis method, the data acquisition strategy in the performance aging period is an acquisition strategy combining regular acquisition and random acquisition, and a random data acquisition point is arranged between two adjacent regular data acquisition points.
According to the intelligent electric meter operation error diagnosis and analysis method, the data acquisition strategy of the standby machine-changing period is random acquisition, and the time interval between two adjacent random data acquisition points is 120-300 seconds.
In the method for diagnosing and analyzing the operation errors of the intelligent electric meters, in step S4), when an operation error difference occurs in one intelligent electric meter, one or more intelligent electric meters of the same type in the same region are selected as a reference system for verification.
In step S4), the method for diagnosing and analyzing the operation error of the smart meter specifically includes the following steps:
s4-1) calculating to obtain an operation error xi of the intelligent electric meter by using the power utilization data collected in the step S3);
s4-2) calculating the running error xi of the intelligent electric meter and the mark running error xi of the intelligent electric meter of the type obtained in the step S4-10When the degree of deviation sigma is greater than the desired degree of deviation sigmaPeriod of timeIf so, determining that the intelligent electric meter has a fault, otherwise, determining that the intelligent electric meter normally operates; desired degree of deviation σPeriod of timeAnd the degree of deviation σ is calculated by the following formula:
σ＝ξ/ξ0；
σperiod of time＝ξDetection of/ξ0；
Wherein ξDetection ofAnd verifying the operation error for the intelligent electric meter laboratory of the model.
In the method for diagnosing and analyzing the operation errors of the intelligent electric meter, in the step S4-2), the expected deviation sigma for diagnosing the operation errors of the intelligent electric meter in the standby machine changing periodPeriod of timeCalculated by the following formula:
σperiod of time＝k*ξDetection of/ξ0；
Wherein k is a tolerance coefficient, and the value range of k is [1.01,1.1 ].
The system for diagnosing and analyzing the operation errors of the intelligent electric meter by using the intelligent electric meter operation error diagnosing and analyzing method comprises the following steps:
the data acquisition unit is used for acquiring product information of the intelligent ammeter, internet surfing time and user electricity utilization data;
the data processing unit is used for setting a strategy for acquiring data of the intelligent electric meter according to product information of the intelligent electric meter and internet surfing time, processing user electricity utilization data and diagnosing operation errors of the intelligent electric meter;
the intelligent electric meter operation error diagnosis database is used for prestoring historical data of the intelligent electric meter operation condition;
the intelligent electric meter operation management database is used for storing the operation condition records of the intelligent electric meters of users;
the data storage unit is used for storing the data acquired by the data acquisition unit;
the data acquisition unit is in communication connection with the data storage unit, the data storage unit is in communication connection with the data processing unit, and the data processing unit is in communication connection with the intelligent electric meter operation error diagnosis database and the intelligent electric meter operation management database respectively.
In the system, the data processing unit is in communication connection with the information issuing unit.
The technical scheme of the invention achieves the following beneficial technical effects:
1. according to the invention, the life cycle of the intelligent electric meter is divided into three periods, different data acquisition strategies are adopted in different periods, and then the operation error of the intelligent electric meter is calculated, so that the phenomenon that the data acquisition amount is too large in a period with good performance of the intelligent electric meter is avoided, and meanwhile, the operation fault of the intelligent electric meter can be timely found.
2. A tolerance coefficient is introduced into the intelligent electric meter greatly influenced by the aging of electronic components, and frequent alarm of the system is avoided.
Drawings
FIG. 1 is a schematic diagram of the working principle of an intelligent electric meter operation error diagnosis and analysis system;
fig. 2 is a flow chart of the intelligent electric meter operation error diagnosis and analysis method.
Detailed Description
As shown in fig. 1, the system for diagnosing and analyzing the operation error of the smart meter according to the present invention includes:
the data acquisition unit is used for acquiring product information of the intelligent ammeter, internet surfing time and user electricity utilization data;
the data processing unit is used for setting a strategy for acquiring data of the intelligent electric meter according to product information of the intelligent electric meter and internet surfing time, processing user electricity utilization data and diagnosing operation errors of the intelligent electric meter;
the intelligent electric meter operation error diagnosis database is used for prestoring historical data of the intelligent electric meter operation condition;
the intelligent electric meter operation management database is used for storing the operation condition records of the intelligent electric meters of users;
the data storage unit is used for storing the data acquired by the data acquisition unit;
the data acquisition unit is in communication connection with the data storage unit, the data storage unit is in communication connection with the data processing unit, and the data processing unit is in communication connection with the intelligent electric meter operation error diagnosis database and the intelligent electric meter operation management database respectively.
In order to facilitate managers of the power supply management system to know the operation fault of the intelligent electric meter in time, in the embodiment, the data processing unit is in communication connection with the information issuing unit, and the information issuing unit can select system broadcast or system mail of the power supply management system.
The method for diagnosing the operation error of the intelligent electric meter by using the intelligent electric meter operation error diagnosing system is shown in a specific flow chart in figure 2 and comprises the following steps:
s1) acquiring the product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter of the user through a data acquisition unit and storing the acquired product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter under a data directory of the user;
s2) the data processing unit sets a data acquisition strategy for the intelligent electric meter according to the intelligent electric meter operation state historical data prestored in the database for intelligent electric meter operation error diagnosis and the intelligent electric meter product information acquired in the step S1) and the intelligent electric meter internet surfing time, and the data acquisition strategy specifically comprises the following operations:
s2-1) calling, by the data processing unit, historical data of the running state of the intelligent electric meter, which is pre-stored in the database for running error diagnosis of the intelligent electric meter and is a product with the same brand and the same model as the intelligent electric meter, according to the product information of the intelligent electric meter collected in the step S1);
s2-2) dividing the life cycle of the intelligent electric meter into a running stable period, a performance aging period and a standby period according to the online time of the intelligent electric meter and the historical data of the running state of the intelligent electric meter prestored in the database for diagnosing the running errors of the intelligent electric meter, wherein the running stable period is a period in which the factors other than the running errors of the intelligent electric meter are dominant, the performance aging period is a period in which the factors of the running errors of the intelligent electric meter are equivalent to internal factors and external factors, and the standby period is a period in which the running errors of the intelligent electric meter frequently occur and the expected time for replacing a new intelligent electric meter is reached;
s2-3) setting data acquisition strategies of the intelligent electric meter in a stable operation period, a performance aging period and a standby machine changing period; in this embodiment, the operation stabilization period data acquisition strategy is an acquisition strategy combining regular acquisition and random acquisition, where in the regular acquisition, the nth data acquisition time is tn＝tn-1+ Δ t, n being a natural number greater than or equal to 2, Δ t being 70 seconds; the data acquisition strategy of the performance aging period is an acquisition strategy combining regular acquisition and random acquisition, and a random data acquisition point is arranged between two adjacent regular data acquisition points; the data acquisition strategy of the machine waiting period is random acquisition, and the time interval between two adjacent random data acquisition points is 120-300 seconds;
s3) collecting the electricity data of the user according to the data collection strategy in the step S2-3), wherein the electricity data comprises electricity consumption, voltage and current;
s4) carrying out operation error judgment on the intelligent electric meter according to the electricity utilization data collected in the step S3), and specifically comprising the following steps:
s4-1) calculating to obtain an operation error xi of the intelligent electric meter by using the power utilization data collected in the step S3);
s4-2) calculating the running error xi of the intelligent electric meter and the mark running error xi of the intelligent electric meter of the type obtained in the step S4-10When the degree of deviation sigma is greater than the desired degree of deviation sigmaPeriod of timeIf so, determining that the intelligent electric meter has a fault, otherwise, determining that the intelligent electric meter normally operates; desired degree of deviation σPeriod of timeAnd the degree of deviation σ is calculated by the following formula:
σ＝ξ/ξ0；
σperiod of time＝ξDetection of/ξ0；
Wherein ξDetection ofAnd verifying the operation error for the intelligent electric meter laboratory of the model.
Since the internal electronic components of the smart meter are aged after the smart meter is used for a long time and the aged electronic components have certain influence on the operation error of the smart meter, the influence is not caused by faults of the smart meter and the like, and the operation error of the smart meter needs to be subjected to tolerance processing during the standby switch period, in step S4-2), the expected deviation sigma for diagnosing the operation error of the smart meter during the standby switch period is determinedPeriod of timeCalculated by the following formula:
σperiod of time＝k*ξDetection of/ξ0；
Wherein k is a tolerance coefficient, and the value range of k is [1.01,1.1 ].
The tolerance coefficient k is set according to the environmental conditions of each region, and can also be set through reinforcement learning training. For example, for the nanning area, the tolerance factor k may be set to 1.05.
In order to avoid that the power supply system fault is mistaken as the fault of the intelligent electric meter, in step S4), when the operation of one intelligent electric meter is mistakenly different, one or more intelligent electric meters with the same model in the same region are selected as a reference system for verification. The abnormal operation error of the smart meter in the embodiment refers to a situation that the deviation degree sigma of the operation error of the smart meter is greater than or equal to 2.
When the operation monitoring is carried out on the three intelligent electric meters of the same type in the operation stable period, the performance aging period and the standby machine period, the operation error diagnosis analysis method of the intelligent electric meters is utilized to carry out operation error diagnosis on the three intelligent electric meters of the same type, the existing intelligent electric meter operation error diagnosis method is utilized to carry out operation error diagnosis on the three intelligent electric meters of the same type, and the diagnosis result is displayed: the method comprises the steps that the results of diagnosis of the operation errors of the intelligent electric meter in the operation stable period are the same, but the data are collected more than 20 times every day by the conventional intelligent electric meter operation error diagnosis method; for the intelligent electric meter in the performance aging period, the operation fault detection rate of the intelligent electric meter is 99% when the intelligent electric meter operation error diagnosis method is used for diagnosis, while the operation fault detection rate of the intelligent electric meter is 94% and 17% of false picking and missed picking exist when the existing intelligent electric meter operation error diagnosis method is used for diagnosis, and the data collected by the two methods every day are equivalent; for the intelligent electric meters in the standby period and the intelligent electric meters in the performance aging period, the operation fault detection rate of the intelligent electric meters is 98% when the intelligent electric meter operation error diagnosis method is used for diagnosis, while the operation fault detection rate of the intelligent electric meters is 91% and 23% of false detection and missed detection exist when the existing intelligent electric meter operation error diagnosis method is used for diagnosis, and the data acquired by the two methods every day are equivalent. When the intelligent electric meter in the period of waiting for replacement is subjected to intelligent electric meter operation error diagnosis, the error picking in the diagnosis result obtained by using the conventional intelligent electric meter operation error diagnosis method is caused by aging of the electronic components of the intelligent electric meter, and after the aged electronic components are replaced, the operation error of the intelligent electric meter is normal. The intelligent electric meter running error diagnosis method provided by the invention is used for diagnosing the intelligent electric meter in the period of waiting for replacement, and because the electricity consumption data is randomly acquired, the influence of regular fluctuation of voltage and current on the running error of the intelligent electric meter can be effectively avoided, and the influence of similar factors can also be avoided, so that the false detection and the missed detection are reduced, and the tolerance coefficient is introduced, so that the misguidance of the running error change of the intelligent electric meter on the running error diagnosis of the intelligent electric meter caused by the aging of electronic components in the intelligent electric meter is reduced.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications are possible which remain within the scope of the appended claims.
Claims (9)
1. The intelligent electric meter operation error diagnosis and analysis method is characterized by comprising the following steps:
s1) acquiring the product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter of the user through a data acquisition unit and storing the acquired product information of the intelligent electric meter and the internet surfing time of the intelligent electric meter under a data directory of the user;
s2) the data processing unit sets a data acquisition strategy for the intelligent electric meter according to the intelligent electric meter operation state historical data prestored in the database for intelligent electric meter operation error diagnosis and the intelligent electric meter product information acquired in the step S1) and the intelligent electric meter internet surfing time, and the data acquisition strategy specifically comprises the following operations:
s2-1) calling, by the data processing unit, historical data of the running state of the intelligent electric meter, which is pre-stored in the database for running error diagnosis of the intelligent electric meter and is a product with the same brand and the same model as the intelligent electric meter, according to the product information of the intelligent electric meter collected in the step S1);
s2-2) dividing the life cycle of the intelligent electric meter into a running stable period, a performance aging period and a standby period according to the online time of the intelligent electric meter and the historical data of the running state of the intelligent electric meter prestored in the database for diagnosing the running errors of the intelligent electric meter, wherein the running stable period is a period in which the factors other than the running errors of the intelligent electric meter are dominant, the performance aging period is a period in which the factors of the running errors of the intelligent electric meter are equivalent to internal factors and external factors, and the standby period is a period in which the running errors of the intelligent electric meter frequently occur and the expected time for replacing a new intelligent electric meter is reached;
s2-3) setting data acquisition strategies of the intelligent electric meter in a stable operation period, a performance aging period and a standby machine changing period;
s3) collecting the electricity data of the user according to the data collection strategy in the step S2-3), wherein the electricity data comprises electricity consumption, voltage and current;
s4) carrying out operation error judgment on the intelligent electric meter according to the electricity utilization data collected in the step S3).
2. The method for diagnosing and analyzing the operation errors of the smart meter according to claim 1, wherein the operation stabilization period data acquisition strategy is an acquisition strategy combining regular acquisition and random acquisition, wherein in the regular acquisition, the nth time is carried outThe data acquisition time is tn＝tn-1+ Δ t, n is a natural number greater than or equal to 2, Δ t is 0 to 600 seconds.
3. The method for diagnosing and analyzing the operation errors of the smart meter according to claim 1, wherein the data acquisition strategy of the performance aging period is an acquisition strategy combining regular acquisition and random acquisition, and a random data acquisition point is arranged between two adjacent regular data acquisition points.
4. The method for diagnosing and analyzing the running error of the smart meter according to claim 1, wherein a data acquisition strategy of a machine waiting period is random acquisition, and a time interval between two adjacent random data acquisition points is 120-300 seconds.
5. The method for diagnosing and analyzing the operating errors of the smart meters of claim 1, wherein in step S4), when an operating error occurs in one smart meter, one or more smart meters of the same type in the same area are selected as a reference system for verification.
6. The method for diagnosing and analyzing the operation errors of the smart meter according to any one of claims 1 to 5, wherein in the step S4), the method specifically comprises the following steps:
s4-1) calculating to obtain an operation error xi of the intelligent electric meter by using the power utilization data collected in the step S3);
s4-2) calculating the running error xi of the intelligent electric meter and the mark running error xi of the intelligent electric meter of the type obtained in the step S4-10When the degree of deviation sigma is greater than the desired degree of deviation sigmaPeriod of timeIf so, determining that the intelligent electric meter has a fault, otherwise, determining that the intelligent electric meter normally operates; desired degree of deviation σPeriod of timeAnd the degree of deviation σ is calculated by the following formula:
σ＝ξ/ξ0；
σperiod of time＝ξDetection of/ξ0；
Wherein the content of the first and second substances,ξdetection ofAnd verifying the operation error for the intelligent electric meter laboratory of the model.
7. The method for diagnosing and analyzing the operating errors of the smart meter according to claim 6, wherein in step S4-2), the expected deviation σ for diagnosing the operating errors of the smart meter in the standby period isPeriod of timeCalculated by the following formula:
σperiod of time＝k*ξDetection of/ξ0；
Wherein k is a tolerance coefficient, and the value range of k is [1.01,1.1 ].
8. The system for diagnosing and analyzing the operation errors of the intelligent electric meter by using the method for diagnosing and analyzing the operation errors of the intelligent electric meter according to any one of claims 1 to 7 is characterized by comprising the following steps:
the data acquisition unit is used for acquiring product information of the intelligent ammeter, internet surfing time and user electricity utilization data;
the data processing unit is used for setting a strategy for acquiring data of the intelligent electric meter according to product information of the intelligent electric meter and internet surfing time, processing user electricity utilization data and diagnosing operation errors of the intelligent electric meter;
the intelligent electric meter operation error diagnosis database is used for prestoring historical data of the intelligent electric meter operation condition;
the intelligent electric meter operation management database is used for storing the operation condition records of the intelligent electric meters of users;
the data storage unit is used for storing the data acquired by the data acquisition unit;
the data acquisition unit is in communication connection with the data storage unit, the data storage unit is in communication connection with the data processing unit, and the data processing unit is in communication connection with the intelligent electric meter operation error diagnosis database and the intelligent electric meter operation management database respectively.
9. The system of claim 8, wherein the data processing unit is communicatively coupled to the information distribution unit.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115567899A (en) * | 2022-08-23 | 2023-01-03 | 浙江晨泰科技股份有限公司 | Error analysis method and device for intelligent electric meter |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115567899A (en) * | 2022-08-23 | 2023-01-03 | 浙江晨泰科技股份有限公司 | Error analysis method and device for intelligent electric meter |
| CN115567899B (en) * | 2022-08-23 | 2023-10-03 | 浙江晨泰科技股份有限公司 | Error analysis method and device for intelligent ammeter |
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