CN112684397B - Electric energy meter operation error monitoring method and system based on high-frequency HPLC (high Performance liquid chromatography) data - Google Patents

Abstract

The present application provides a method and system for monitoring the running error of an electric energy meter based on high-frequency data collected by HPLC, and relates to the technical field of electric power. In the present application, firstly, the total meter electricity consumption and the sub-meter electricity consumption obtained by multiple HPLC equipments in the current period respectively collecting the total electricity meter of the target station area and the electricity meter of the station area; secondly, for each meter Sub-meter power consumption, based on the pre-determined power correspondence relationship and sub-meter power consumption, to obtain the line power consumption corresponding to the sub-meter power consumption; Calculate the total operating error data of the electric energy meters of multiple stations according to the power loss; finally, based on the total operation error data and the pre-determined error ratio information, determine the operation error data of the electric energy meters of each station. Based on the above method, the problem in the prior art that it is difficult to effectively monitor the operation error of the station-distinguished electric energy meter can be improved.

Description

Method and system for monitoring operation error of electric energy meter based on high-frequency data acquisition by HPLC

technical field

The present application relates to the field of electric power technology, and in particular, to a method and system for monitoring the running error of an electric energy meter based on high-frequency data collected by HPLC.

Background technique

In the field of electric power technology, the station area refers to the power supply range or area of a transformer in the power system, wherein the electric energy meter used to measure the total electricity consumption within the power supply range can be called the station area total electric energy meter, and a The station area may include a plurality of electric energy meters for measuring the electricity consumption of each user, which may be referred to as station-specific electric energy meters.

The inventor's research finds that each discriminative electric energy meter will generate a certain operating error after it is put into use, therefore, the operating error needs to be monitored. However, in the prior art, there is a problem that it is difficult to effectively monitor the operation error of the station-distinguished electric energy meter.

SUMMARY OF THE INVENTION

In view of this, the purpose of this application is to provide a method and system for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data, so as to improve the problem that it is difficult to effectively monitor the operation error of the electric energy meter in the prior art. .

To achieve the above purpose, the embodiment of the present application adopts the following technical solutions:

A method and system for monitoring the operation error of an electric energy meter based on high-frequency data collected by HPLC, which is applied to a computing platform in the operation error monitoring system of an electric energy meter, wherein the monitoring system further includes an HPLC device that is communicatively connected to the computing platform. include:

Obtain the total meter electricity consumption and sub-meter electricity consumption obtained by multiple HPLC equipments in the target station area respectively collecting the total electricity meter of the station area and the electricity meter of the station area. The station distinguishes the electric energy meter into multiple;

Distinguish the sub-meter power consumption of the electric energy meter for each of the stations, and obtain the line power consumption corresponding to the sub-meter power consumption based on the predetermined power correspondence relationship and the sub-meter power consumption;

Based on the electricity consumption of the total meter in the station area, the electricity consumption of the sub-meters and the power consumption of the line, the total operation error data of a plurality of the station-specific electric energy meters are calculated and obtained;

Based on the total operation error data and the error ratio information determined in advance for each station-distinguished electric energy meter, the operation error data of each of the station-distinguished electric energy meters is determined.

On the basis of the above-mentioned embodiment, the present application also provides an electric energy meter operation error monitoring system, including HPLC equipment and a computing platform connected in communication with the HPLC;

Wherein, the computing platform includes:

memory for storing computer programs;

The processor connected with the memory is used for executing the computer program to realize the above-mentioned method for monitoring the running error of the electric energy meter based on the high-frequency data collected by the HPLC.

The method and system for monitoring the operation error of electric energy meters based on HPLC high-frequency acquisition data provided in this application, through HPLC equipment to collect the total electric energy meter of the station area and the electric energy meter of the station area respectively, and the corresponding total meter electricity consumption and sub-meters can be obtained. Electricity consumption, and then, based on the predetermined electric power correspondence and the sub-meter electric power consumption, the line loss power corresponding to the sub-meter electric power consumption can be obtained, so that the total operation of the station-distinguished electric energy meter can be obtained in combination with the total meter electric power consumption The error data makes it possible to determine the operation error data of the electric energy meter for each station based on the determined error ratio information. In this way, the operation error of the electric energy meter in the station area can be effectively monitored, thereby improving the problem in the prior art that it is difficult to effectively monitor the operation error of the electric energy meter in the station area.

In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the preferred embodiments are exemplified below, and are described in detail as follows in conjunction with the accompanying drawings.

Description of drawings

FIG. 1 is a structural block diagram of a computing platform in a system for monitoring operating errors of an electric energy meter provided by an embodiment of the present application.

FIG. 2 is a schematic flowchart of each step included in the method for monitoring the running error of an electric energy meter based on high-frequency HPLC data collected according to an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments It is only a part of the embodiments of the present application, but not all of the embodiments. The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations.

Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

Embodiments of the present application provide a system for monitoring running error of an electric energy meter, and the system for monitoring running error of an electric energy meter may include a plurality of HPLC (high-speed power line carrier) devices and a computing platform connected in communication with each HPLC.

Wherein, the HPLC equipment has a carrier chip and a main control chip, which can be installed in the total energy meter of the station area and the station-specific energy meter, and can operate independently of the station-area total energy meter and the station-differentiated energy meter.

Also, as shown in FIG. 1, a computing platform may include a memory and a processor.

Specifically, the memory and the processor are directly or indirectly electrically connected to realize data transmission or interaction. For example, they can be electrically connected to each other through one or more communication buses or signal lines. The memory may store at least one software function module (computer program) that may exist in the form of software or firmware (firmware). The processor may be configured to execute the executable computer program stored in the memory, thereby implementing the method for monitoring the running error of the electric energy meter based on the high-frequency HPLC data collected in the embodiment of the present application.

Optionally, the memory may be, but not limited to, random access memory (Random Access Memory, RAM), read only memory (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only Memory, PROM) , Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Read-Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

In addition, the processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), a system on chip (System on Chip, SoC), etc.; it may also be a digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

With reference to FIG. 2 , an embodiment of the present application further provides a method for monitoring the running error of an electric energy meter based on high-frequency data collected by HPLC, which can be applied to the computing platform of the above-mentioned system for monitoring the running error of an electric energy meter. Wherein, the method steps defined in the process related to the method for monitoring the running error of the electric energy meter based on the high-frequency data collected by HPLC can be realized by the computing platform of the electric energy meter running error monitoring system.

The specific flow shown in FIG. 2 will be described in detail below.

In step S110, the total meter electricity consumption and the sub-meter electricity consumption obtained by the multiple HPLC devices in the current period respectively collecting the station area total energy meter and the station area electricity energy meter of the target station area.

In this embodiment, the computing platform can obtain the target station area (station area refers to the target station area in the power system) collected by multiple HPLC devices in the current time period (that is, the target time period from the current moment onward, such as one day or one month, etc.) The power supply range or area of a transformer, the electric energy meter used to measure the total electricity consumption within the power supply range can be called the total energy meter of the station area, and a station area can also include multiple energy meters in addition to the total energy meter of the station area. The total electric energy meter of the station area (the total electric energy meter of the station area can be regularly calibrated or replaced to ensure that the measured data has high accuracy) and the station-divisional electric energy meter are obtained. The total meter electricity consumption (that is, the electricity consumption increment of the station's total electricity meter in the current period) and the sub-meter electricity consumption (that is, the electricity consumption increment of the station's differentiated electricity meter in the current period).

Wherein, there is one total electric energy meter in the station area, and there are multiple electric energy meters in the station area.

In step S120, the sub-meter power consumption of the electric energy meter is distinguished for each station, and the line power consumption corresponding to the sub-meter power consumption is obtained based on the predetermined power correspondence relationship and the sub-meter power consumption.

In this embodiment, after obtaining the sub-meter power consumption based on step S110, the computing platform may distinguish the sub-meter power consumption of the electric energy meter for each of the stations, based on the predetermined power corresponding relationship and the The power consumption of the sub-meter is obtained, and the power consumption of the line corresponding to the power consumption of the sub-meter is obtained (considering that the line lengths between the power meters of different stations and the total power meters of the station area are different, so that even under the same power consumption , the power consumption of the line will also be different, therefore, it needs to be calculated in combination with the corresponding line length).

Wherein, the corresponding relationship of electric quantity may be calculated based on simulating the target station area (simulating the operating environment of the target station area).

Step S130, based on the power consumption of the total meter in the station area, the power consumption of the sub-meters, and the power consumption of the line, calculate and obtain the total operation error data of the plurality of the station-specific electric energy meters.

In this embodiment, after obtaining the power consumption of the line based on step S120, the computing platform may calculate the power consumption of the total meter of the station area and the power consumption of the sub-meter based on the power consumption of the line and the power consumption of the sub-meter. The total running error data of the plurality of said station-distinguished electric energy meters are obtained.

That is to say, the electricity consumption of the total meter in the station area - the sum of the electricity consumption of a plurality of the sub-meters - minus the power consumption of a plurality of lines = the total operation error data of the plurality of the station-specific electric energy meters.

Step S140, based on the total operation error data and the error ratio information determined in advance for each station-specific electric energy meter, determine the operation error data of each of the station-specific electric energy meters.

In this embodiment, after obtaining the total operating error data based on step S130, the computing platform may, on the basis of the total operating error data and in combination with the error ratio information determined in advance for each station differentiated electric energy meters, determine each One of the stations distinguishes the operating error data of the electric energy meter.

Based on the above method, the operation error of the electric energy meter can also be effectively monitored on the basis of not relying on the actual detection of the inspection personnel, thereby improving the problems caused by the actual detection of the operation error of the electric energy meter in the prior art by the inspection personnel. difficult to monitor effectively.

It should be noted for step S140 that the specific manner of determining the operation error data of the electric energy meter for each of the stations is not limited, and can be selected according to actual application requirements.

For example, in an alternative example, in order to improve the accuracy of the determined running error data, step S140 may include the following steps:

The first step is to obtain each historical period adjacent to the current period (for example, if the current period is April 18, 2020, the adjacent historical period is April 17, 2020). The station distinguishes the historical information of the error ratio of the electric energy meter, where the historical period is the same as the current period, and the end point of the historical period is the starting point of the current period, and if the historical period is the first historical period, the corresponding The historical information of the error ratio of is obtained based on the measurement;

Step 2: Divide the current time period according to a preset time length (such as one hour) to obtain multiple time segments, and form a time segment sequence based on the multiple time segments according to the time sequence, wherein two adjacent time segments are In each time segment, the end point of the previous time segment coincides with the start point of the next time segment;

The third step, for each of the time segments in the sequence of time segments, obtain the sub-meter sub-meter power consumption of each of the station-distinguished electric energy meters in the time segment;

The fourth step is to distinguish the electric energy meter for each of the stations, and form the sub-electrical consumption sequence of the electric energy meter of the station based on the sub-meter power consumption corresponding to the electric energy meter of the station in chronological order (such as 0. -1 hour of sub-meter power consumption, 1-2 hours of sub-meter power consumption, 2-3 hours of sub-meter power consumption, 3-4 hours of sub-meter power consumption.... ..);

Step 5: For each sub-sequence of electricity consumption, screen each sub-meter and sub-consumption of electricity in the sub-sequence of electricity consumption based on the preset abnormal data screening rules (in this way, abnormal data can be avoided. interference), and replace the screened sub-meter sub-power consumption with the sub-meter preset sub-power consumption to form the sub-power consumption target sequence corresponding to the sub-power consumption sequence;

The sixth step is to update the historical information of the error ratio based on each of the sub-consumption target sequences (for example, based on the average value of the sub-meter sub-consumption included in each of the sub-consumption target sequences. For example, the ratio information between the four average values is 5%, 30%, 40%, and 25%, and the historical information of the four error ratios is 25%. %, 25%, 25%, and 25%, and the corresponding 4 error proportions are 15%, 27.5%, 32.5%, and 25%, respectively, that is, the update processing is realized through mean calculation), and each of the said station-specific electric energy meters is obtained. The error ratio information of ;

In the seventh step, based on the error ratio information and the total running error data, determine the running error data of each of the station-distinguished electric energy meters.

Optionally, in the above example, the specific manner of performing the screening process is not limited, and can be selected according to actual application requirements.

For example, in an alternative example, the filtering process may be based on the following steps:

In the first step, from the sub-consumption sequence, screening and exclusion processing is performed on sub-meters with preset identifiers to obtain the sub-meters to be interpolated, wherein the preset identifiers are based on the corresponding sub-meters. In the time segment where the sub-power consumption is located, it is generated after the operation error correction of the station-specific energy meter is performed (if there is no sub-meter sub-power consumption with a preset identifier, the sub-power consumption sequence can be directly used as a sub-use power target sequence);

The second step is to determine the relationship between the power consumption of the sub-meter and the (adjacent) previous sub-meter, and the (adjacent) after The relationship between the electricity consumption of a sub-meter;

In the third step, for each sub-meter sub-meter power consumption that is screened and excluded, if the difference between the sub-meter sub-meter sub-meter sub-meter power consumption and the previous sub-meter sub-meter power consumption is not greater than the preset threshold (according to accuracy requirements Set, the higher the accuracy requirement, the smaller the preset threshold), or the difference between the power consumption of this sub-meter and the next sub-meter is not greater than the preset threshold, then based on the first preset The rule determines a sub-meter preset sub-power consumption to replace the sub-meter sub-power consumption;

The fourth step, for each screened and excluded sub-meter sub-meter power consumption, if the difference between the sub-meter sub-meter sub-meter sub-meter power consumption and the previous sub-meter sub-meter power consumption is greater than the preset threshold, and the sub-meter sub-meter power consumption The difference between the power consumption of a sub-meter and the power consumption of the next sub-meter is greater than the preset threshold, then a preset sub-meter power consumption of one sub-meter is determined based on the second preset rule. carry out replacement processing;

The fifth step is to form a corresponding sub-meter power consumption target sequence based on each sub-meter sub-power consumption that is not screened and excluded in the sub-meter power consumption sequence and each sub-meter preset sub-power consumption determined.

It can be understood that, in the above example, the specific method for determining a sub-meter preset sub-power consumption to replace the sub-meter sub-power consumption based on the first preset rule is not limited, and can be based on actual application requirements. to make a selection.

For example, in an alternative example, a sub-meter preset sub-power consumption can be determined based on the following steps to perform replacement processing on the sub-meter sub-power consumption:

First, the average power consumption of the previous sub-meter sub-meter and the latter sub-meter sub-sub-meter power consumption of the sub-meter sub-meter power consumption excluded by the screening can be calculated; secondly, the average power consumption can be used as a Sub-meter preset sub-power consumption, and the sub-meter sub-power consumption that has been screened and excluded is replaced by the sub-meter preset sub-power consumption.

It can be understood that, in the above example, the specific method for determining a sub-meter preset sub-power consumption to replace the sub-meter sub-power consumption based on the second preset rule is not limited, and can be based on actual application requirements. to make a selection.

For example, in an alternative example, in particular, in order to ensure the validity of the replacement, the sub-meter preset sub-power consumption can be determined based on the following steps to perform replacement processing on the sub-meter sub-power consumption:

The first step is to determine a sequence segment including the sub-meter electricity consumption in the sub-meter electricity consumption sequence where the sub-meter electricity consumption that is excluded from the screening is located, wherein the sequence segment includes the first quantity ( It can be configured based on the accuracy requirement, the higher the accuracy requirement, the larger the value of the first number of sub-meter sub-meters, and the first number of sub-meter sub-meter power consumption is continuous in time;

The second step is to acquire the sub-meter power consumption history sequence formed by the sub-meter and sub-power consumption corresponding to the sub-meter and the sub-meter that has been screened out in the adjacent historical period, wherein the historical period is based on the preset The time length is divided into a plurality of historical time segments, and the sub-power consumption history sequence is formed based on the historical sub-table sub-power consumption of the multiple historical time segments;

The third step is to perform sliding window processing on the historical sub-sequence of electricity consumption according to the first quantity to obtain a plurality of historical sub-sequences, wherein each historical sub-sequence includes a the quantity is the first quantity;

The fourth step, in the multiple historical sub-sequences, based on the similarity with the sequence segment (such as first calculating the similarity between the sub-meter power consumption of the corresponding position and the historical sub-meter sub-power consumption, For example, the reciprocal of the difference is used as the similarity, and then the average similarity is calculated), and the second quantity with the largest similarity is determined (it can be configured based on the accuracy requirement, the higher the accuracy requirement, the larger the value of the second quantity can be) target history subsequence;

The fifth step, for each of the target historical sub-sequences, based on the historical average power consumption of the historical sub-meter sub-sequence included in the target historical sub-sequence, each historical sub-meter sub-sequence included in the target historical sub-sequence The power is mapped to obtain a plurality of historical power consumption identification values included in the target historical subsequence, which have the same relationship with the historical average power consumption (for example, both are greater than the historical average power consumption) Any two historical sub-meter sub-meter power consumption corresponding to the historical power consumption identification value is the same, and has a different relationship with the historical average power consumption (for example, one is greater than the historical average power consumption, and the other is not greater than all the historical average power consumption. The historical power consumption identifier values corresponding to any two historical sub-meter sub-consumption power consumption are different;

The sixth step, for each of the target historical subsequences, sort the multiple historical power consumption identification values corresponding to the target historical subsequence according to the time sequence relationship of the corresponding historical sub-tables of power consumption to obtain the target. The historical identification value sequence corresponding to the historical subsequence;

The seventh step, for each of the historical identification value sequences, calculate the number of target sequence bits between the historical identification value sequence and each other historical identification value sequence, wherein, the number of target sequence bits is two The number of sequence bits that have the same historical power consumption identification value on the corresponding sequence bits between the historical identification value sequences (that is, it is necessary to determine the historical power consumption identification value of the first place in every two historical identification value sequences. Whether it is the same, whether the historical power consumption identification value of the second digit is the same, whether the historical power consumption identification value of the third digit is the same...);

The eighth step, for each of the historical identification value sequences, based on the discrete degree value of each of the target sequence bits corresponding to the historical identification value sequence (for example, the three target sequence bits are 2, 2 , 2, the corresponding mean value is 2, and the corresponding discrete degree value is (|2-2|+|2-2|+|2-2|)/3=0; the three target sequence bits are 1 respectively , 2, 9, the corresponding average value is 4, and the corresponding discrete degree value is (|1-4|+|2-4|+|9-4|)/3=3.33);

The ninth step, based on the magnitude relationship of the discrete degree values, determines a target historical identification value sequence in a plurality of the historical identification value sequences, wherein the target historical identification value sequence is one of the multiple historical identification value sequences. The sequence of historical identification values with the smallest discrete degree value;

The tenth step, based on the position (position in chronological order) of the sub-meter power consumption of the sub-meters excluded by the screening, in the target historical sub-sequence corresponding to the target historical identification value sequence, determine the corresponding The historical sub-meter power consumption of the location;

The eleventh step is to use the historical sub-meter power consumption of the corresponding location as the sub-meter preset sub-power consumption, and based on the sub-meter preset sub-meter power consumption, the screened and excluded sub-meter sub-consumption is used. Replace the battery.

For another example, in an alternative example, in order to ensure the validity of the replacement and take into account the efficiency of the overall calculation, the sub-meter preset sub-power consumption can be determined based on the following steps to sub-meter sub-power consumption: Perform replacement processing:

Sub-step 1: Obtain a plurality of sub-power consumption history sequences formed by the station-specific electric energy meters corresponding to the sub-meter sub-power consumption that have been screened and excluded in multiple historical periods (which may be multiple adjacent historical periods), wherein, Each of the historical time periods is divided into a plurality of historical time segments based on the preset time length, and each of the sub-power consumption historical sequences is formed based on the historical sub-table sub-power consumption of the corresponding multiple historical time segments;

Sub-step 2, in the plurality of sub-power consumption historical sequences, determine the target sub-power consumption historical sequence that has the greatest similarity with the sub-power consumption sequence in which the sub-table sub-power consumption that has been screened and excluded is located ;

Sub-step 3, based on a plurality of historical sub-meter sub-consumptions included in the target sub-meter power consumption history sequence, determine a historical sub-meter sub-meter power consumption as a sub-meter preset sub-meter power consumption, and based on the sub-meter sub-meter power consumption The preset sub-meter power consumption performs replacement processing on the screened and excluded sub-meter sub-power consumption.

Wherein, in the above example, the specific manner of determining the historical sub-meter sub-power consumption as the sub-meter preset sub-power consumption based on sub-step 3 is not limited, and can be selected according to actual application requirements.

For example, in an alternative example, in order to ensure the efficiency of the overall calculation, sub-step 3 may include the following steps:

First, determine the time segment corresponding to the power consumption of the sub-meters excluded by the screening;

Next, determine the corresponding historical time segment based on the time segment (for example, the time segment is 9-10 o'clock on May 8, 2020, and the historical time segment may be 9-10 o'clock on May 7, 2020) , and obtains a historical sub-meter sub-meter power consumption corresponding to the historical time segment from a plurality of historical sub-meter sub-meter sub-power consumptions included in the target sub-meter power consumption historical sequence;

Then, use the acquired historical sub-meter sub-power consumption as the sub-meter preset sub-power consumption, and perform replacement processing on the screened and excluded sub-meter sub-power consumption based on the sub-meter preset sub-power consumption .

For another example, in another alternative example, in order to ensure the validity of the replacement, sub-step 3 may include the following steps:

First, according to the order from largest to smallest, re-order the multiple historical sub-table sub-power consumption included in the target sub-sub-power consumption historical sequence;

Secondly, according to the order from largest to smallest, re-order the multiple sub-meter sub-power consumptions included in the sub-meter sub-power consumption sequence where the sub-meter sub-power consumption that has been screened and excluded is located;

Then, based on the reordered positions of the sub-meter sub-meter power consumption that have been screened out, the historical sub-meter sub-meter power consumption of the corresponding position is determined in the reordered historical sequence of the target sub-meter sub-meter power consumption (as shown in If the reordered position of the sub-meter sub-meter power consumption that has been screened out is the fifth, then the fifth historical sub-meter sub-meter sub-meter power consumption in the reordered historical sub-meter sub-meter power consumption sequence is performed. Sure);

Finally, the historical sub-meter sub-power consumption of the corresponding location is used as the sub-meter preset sub-power consumption, and the screened and excluded sub-meter sub-power consumption is replaced based on the sub-meter preset sub-power consumption .

Further, considering that in the above example, the maximum similarity needs to be determined when sub-step 2 is executed, therefore, it may also include calculating the relationship between the historical sequence of sub-power consumption and the sub-table sub-power consumption that has been screened and excluded. Steps for similarity between sub-consumption sequences. Wherein, based on different requirements, this step may include different examples, and in this embodiment, the following three examples are provided.

In the first example, the following sub-steps can be included:

Sub-step 11: For each sub-meter sub-consumption in the sub-meter sub-consumption sequence where the sub-meter sub-consumption that has been screened and excluded is located, the sub-meter sub-consumption and the sub-meter sub-consumption The electricity consumption of each sub-meter after the measurement is used as the target comparison sequence of the electricity consumption of the sub-meter (multiple target comparison sequences can be obtained, and each target comparison sequence includes different amounts of sub-meter electricity consumption );

Sub-step 12, for each target comparison sequence corresponding to the sub-power consumption sequence, calculate the score between the target comparison sequence and the corresponding position in the sub-power consumption historical sequence (the position is the position in the sequence); The electricity ratio between the electricity consumption of the meter sub-meter and the historical sub-meter electricity consumption is obtained, and the set of electricity ratio values corresponding to the target comparison sequence is obtained;

Sub-step 13, for each power ratio in each of the power ratio sets, the power ratio and each power ratio before the power ratio in the corresponding power ratio set are taken as the ratio sequence corresponding to the power ratio ( Each of the power ratio sets corresponds to at least one of the ratio sequences);

Sub-step 14, calculate the average value of the electric quantity ratio in each described ratio sequence respectively, and obtain the ratio average value corresponding to each ratio sequence;

Sub-step 15, for each of the power ratio sets, determine the maximum ratio average value among the ratio average values of each ratio sequence corresponding to the power ratio set, and use the maximum ratio average as the target ratio of the power ratio set average value;

Sub-step 16, sort the average value of the target ratios according to the order of the largest and the smallest to obtain an average value sequence, and obtain the pre-set number in the average value sequence (which can be configured according to the accuracy requirement, the higher the accuracy is) , the preset number can be larger) the average value of target ratios;

Sub-step 17, for each target ratio average value in the preset number of target ratio average values, determine the number of power ratio values in the power ratio set corresponding to the target ratio average value (such as 2, 3, 8 etc.), and determine the first weighting coefficient of the average value of the target ratio based on the quantity, wherein the quantity has a positive correlation with the first weighting coefficient (that is, the more the quantity of electricity ratios in a set of electricity ratios, the The larger the corresponding first weight coefficient);

Sub-step 18: For each of the first weight coefficients, calculate the product of the first weight coefficient and the target ratio average value corresponding to the first weight coefficient, and use the product as the target comparison sequence corresponding to the target ratio average value the similarity with the sub-power consumption history sequence;

Sub-step 19: Determine the target comparison sequence with the greatest similarity, and use the similarity of the target comparison sequence as the similarity between the sub-electricity consumption sequence and the sub-electricity consumption history sequence.

In the second example, the following sub-steps can be included:

Sub-step 21, for each sub-meter sub-consumption in the sub-meter sub-consumption sequence where the sub-meter sub-consumption that has been screened out is located, the sub-meter sub-consumption and the sub-meter sub-consumption The electricity consumption of each sub-meter after the measurement is used as the target comparison sequence of the electricity consumption of the sub-meter;

Sub-step 22, for each target comparison sequence corresponding to the sub-power consumption sequence, calculate the sub-meter sub-meter sub-meter power consumption and historical sub-meter sub-meter corresponding position in the target comparison sequence and the sub-meter power consumption historical sequence. The power ratio between the powers is obtained, and the set of power ratios corresponding to the target comparison sequence is obtained;

Sub-step 23, for each power ratio in each of the power ratio sets, use the power ratio and each power ratio before the power ratio in the corresponding power ratio set as the ratio sequence corresponding to the power ratio;

Sub-step 24, calculate the average value of the electric quantity ratio in each described ratio sequence respectively, and obtain the ratio average value corresponding to each ratio sequence;

Sub-step 25, for each of the power ratio sets, determine the maximum ratio average value in the ratio average values of each ratio sequence corresponding to the power ratio set, and use the maximum ratio average as the target ratio of the power ratio set average value;

Sub-step 26, for each adjacent (in time) two target comparison sequences, compare the two target ratio average values corresponding to the two target comparison sequences respectively;

Sub-step 27, if the average difference between the average values of the two target ratios is less than the target difference (configured based on the accuracy requirement, for example, the higher the accuracy requirement, the larger the target difference), then the two A second weight coefficient is set for the larger one of the target ratio averages, wherein the second weight coefficient is less than 1 and has a negative correlation with the target difference (that is, the target difference The larger the value, the smaller the second weight coefficient);

Sub-step 28, for each of the second weight coefficients, update the corresponding target ratio average value based on the second weight coefficient (that is, multiply the second weight coefficient and the corresponding target ratio average value to realize the update process. ) to get the updated average target ratio;

Sub-step 29: Determine the maximum average value of the target ratio, and use the maximum average value of the target ratio as the similarity between the sub-power consumption sequence and the sub-power consumption historical sequence.

In the third example, in particular, in order to fully ensure that the calculated similarity has a high degree of reliability, the following sub-steps may be included:

Sub-step 30, for each sub-meter sub-consumption in the sub-meter sub-consumption sequence where the sub-meter sub-consumption that has been screened out is located, the sub-meter sub-consumption and the sub-meter sub-consumption The electricity consumption of each sub-meter after the measurement is taken as the target comparison sequence of the electricity consumption of the sub-meter;

Sub-step 31, for each target comparison sequence corresponding to the sub-power consumption sequence, calculate the sub-meter sub-meter sub-meter power consumption and historical sub-meter sub-meter of the corresponding position in the target comparison sequence and the sub-meter power consumption historical sequence. The power ratio between the powers is obtained, and the set of power ratios corresponding to the target comparison sequence is obtained;

Sub-step 32, for each power ratio in each of the power ratio sets, use the power ratio and each power ratio before the power ratio in the corresponding power ratio set as the ratio sequence corresponding to the power ratio;

Sub-step 33, calculate the average value of the electric quantity ratio in each described ratio sequence respectively, and obtain the ratio average value corresponding to each ratio sequence;

Sub-step 34, for each of the power ratio sets, determine the maximum ratio average value among the ratio average values of each ratio sequence corresponding to the power ratio set, and use the maximum ratio average value as the target ratio of the power ratio set average value;

Sub-step 35, sorting and processing the average value of the target ratios according to the order of the largest and the smallest, to obtain an average value sequence, and obtain the average value of the target ratio values located in the front preset number in the average value sequence;

Sub-step 36, for each target ratio average in the preset number of target ratio averages, determine the number of power ratios in the set of power ratios corresponding to the target ratio average, and determine the target ratio average based on the number a first weighting factor of the value, wherein the quantity has a positive correlation with the first weighting factor;

Sub-step 37, for each of the first weight coefficients, calculate the product of the first weight coefficient and the target ratio average value corresponding to the first weight coefficient, and use the product as the target comparison sequence corresponding to the target ratio average value the similarity with the sub-power consumption history sequence;

Sub-step 38, determining the target number of target comparison sequences with the largest similarity;

Sub-step 39: Determine the target comparison sequence with the largest number of sub-meter electricity consumption included in the target number of target comparison sequences, and use the similarity of the target comparison sequence as the sub- electricity consumption sequence and the The similarity between the sub-power consumption history series.

To sum up, the method and system for monitoring the operation error of electric energy meters based on HPLC high-frequency data collection provided by the present application can collect the total electric energy meter of the station area and the electric energy meter of the station area respectively through the HPLC equipment, and the corresponding total electric energy meter can be obtained. Then, based on the predetermined power correspondence relationship and the power consumption of the sub-meter, the power consumption of the line corresponding to the power consumption of the sub-meter can be obtained, so that the station distinction can be obtained in combination with the power consumption of the total meter. The total operation error data of the electric energy meter makes it possible to determine the operation error data of the electric energy meter for each station based on the determined error ratio information. In this way, the operation error of the electric energy meter in the station area can be effectively monitored, thereby improving the problem in the prior art that it is difficult to effectively monitor the operation error of the electric energy meter in the station area.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims (9)

1. a kind of electric energy meter operating error monitoring method based on HPLC high frequency acquisition data, it is characterized in that, be applied to the computing platform in the electric energy meter operating error monitoring system, wherein, this monitoring system also comprises the HPLC that is communicatively connected with this computing platform device, the method includes: Obtain the total meter electricity consumption and sub-meter electricity consumption obtained by multiple HPLC equipments in the target station area respectively collecting the total electricity meter of the station area and the electricity meter of the station area. The station distinguishes the electric energy meter into multiple; Distinguish the sub-meter power consumption of the electric energy meter for each of the stations, and obtain the line power consumption corresponding to the sub-meter power consumption based on the predetermined power correspondence relationship and the sub-meter power consumption; Based on the electricity consumption of the total meter in the station area, the electricity consumption of the sub-meters and the power consumption of the line, the total operation error data of a plurality of the station-specific electric energy meters are calculated and obtained; Based on the total operation error data and the error ratio information determined in advance for each station-distinguished electric energy meter, determining the operation error data of each of the station-distinguished electric energy meters; Wherein, the step of determining the operation error data of each of the station-distinguished electric energy meters based on the total operating error data and the error ratio information determined for each station-distinguished electric energy meter in advance includes: Acquire the historical information of the error ratio of each of the station-distinguished electric energy meters in a historical period adjacent to the current period, wherein the historical period is the same as the current period, and the end point of the historical period is the current period The starting point of , and if the historical period is the first historical period, the corresponding historical information of the error ratio is obtained based on the measurement; The current time period is divided according to the preset time length to obtain multiple time segments, and a time segment sequence is formed based on the multiple time segments according to the time sequence, wherein the time segment of the previous time segment in the two adjacent time segments is The end point coincides with the start point of the next time segment; For each time segment in the time segment sequence, obtain the sub-meter sub-meter power consumption of each of the station-distinguished electric energy meters in the time segment; For each of the station-distinguished electric energy meters, the sub-meter electricity consumption sequence of the station-distinguished electric energy meter is formed in a chronological order based on the plurality of sub-meter sub-electrical power consumption corresponding to the station-distinguished electric energy meter; For each sub-sequence of electricity consumption, screen each sub-meter sub-electricity consumption in the sub-electricity consumption sequence based on a preset abnormal data screening rule, and screen out the sub-meter sub-consumption of electricity. After the sub-meter preset sub-power consumption is replaced by the sub-meter, the sub-power consumption target sequence corresponding to the sub-power consumption sequence is formed; updating the error ratio history information based on each of the sub-electricity consumption target sequences, to obtain error ratio information of each of the station-distinguished electric energy meters; Based on the error ratio information and the total operating error data, operating error data for each of the station-distinguished electric energy meters is determined. 2. the electric energy meter operation error monitoring method based on HPLC high-frequency acquisition data according to claim 1, is characterized in that, described based on preset abnormal data screening rule each sub-meter in this sub-electricity consumption sequence The sub-meter electricity consumption is screened, and after the sub-meter sub-meter electricity consumption screened out is replaced by the sub-meter preset sub-meter electricity consumption, the steps of forming the sub-meter electricity consumption target sequence corresponding to the sub-meter electricity consumption sequence, include: From the sub-power consumption sequence, the sub-meter sub-power consumption with a preset identifier is screened and excluded to obtain a sub-meter power consumption sequence to be interpolated, wherein the preset identifier is based on the corresponding sub-meter sub-power consumption Generated after performing running error correction processing on the station-distinguished electric energy meter within the time segment; For each sub-meter sub-meter power consumption that is screened and excluded, determine the relationship between the sub-meter sub-meter sub-meter sub-meter power consumption and the previous sub-meter sub-sub-meter power consumption, and the relationship with the next sub-meter sub-sub-meter power consumption; For each sub-meter sub-meter power consumption that is screened out, if the difference between the sub-meter sub-meter sub-meter sub-meter power consumption and the previous sub-meter sub-meter sub-power consumption is not greater than the preset threshold, or the sub-meter sub-meter sub-meter power consumption If the difference between the power consumption of the next sub-meter and the sub-meter is not greater than the preset threshold, then determine a sub-meter preset sub-power consumption based on the first preset rule to perform replacement processing on the sub-meter sub-power consumption; For each sub-meter sub-meter power consumption that is screened and excluded, if the difference between the sub-meter sub-meter sub-meter power consumption and the previous sub-meter sub-meter sub-power consumption value is greater than the preset threshold, and the sub-meter sub-meter power consumption If the difference between the power consumption of the next sub-meter and the sub-meter is greater than the preset threshold, then determine a sub-meter preset sub-power consumption based on the second preset rule to perform replacement processing on the sub-meter sub-power consumption; Based on each sub-meter sub-consumption that is not screened and excluded in the sub-consumption sequence and each sub-meter preset sub-consumption determined, a corresponding sub-consumption target sequence is formed. 3. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 2, wherein the described power consumption of a sub-meter preset sub-meter is determined based on the first preset rule to this sub-meter sub-meter. The steps of using electricity for replacement processing include: Calculate the average electricity consumption of the electricity consumption of the former sub-meter and the latter sub-meter of the electricity consumption of the excluded sub-meter; The average power consumption is used as a sub-meter preset sub-power consumption, and the screened and excluded sub-meter sub-power consumption is replaced by the sub-meter preset sub-power consumption. 4. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 2, wherein the described power consumption of a sub-meter preset sub-meter is determined based on the second preset rule to this sub-meter sub-meter. The steps of using electricity for replacement processing include: Obtain a plurality of sub-power consumption history sequences formed by the sub-meter and sub-power consumption corresponding to the sub-meters that are excluded from the screening and formed in a plurality of historical periods, wherein each historical period is divided based on the preset time length is a plurality of historical time segments, each of the sub-power consumption history sequences is formed based on the historical sub-table sub-power consumption of the corresponding multiple historical time segments; From the plurality of sub-meter power consumption history sequences, determine the target sub-meter power consumption history sequence that has the greatest similarity with the sub-meter power consumption sequence where the screened and excluded sub-meter power consumption is located; Based on a plurality of historical sub-meter sub-consumptions included in the target sub-meter power consumption history sequence, one historical sub-meter sub-consumption is determined as the sub-meter preset sub-consumption, and the sub-meter preset sub-consumption is based on the sub-meter The power consumption is to replace the power consumption of the sub-meters excluded by the screening. 5. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 4, wherein the described power consumption of a sub-meter preset sub-meter is determined based on the second preset rule to this sub-meter sub-meter. The steps of using electricity for replacement processing also include: The step of calculating the similarity between the sub-consumption historical sequence and the sub-consumption sequence where the sub-meter sub-consumption that has been screened and excluded is located, the step includes: For each sub-meter sub-power consumption in the sub-meter sub-power consumption sequence where the sub-meter sub-power consumption that has been screened and excluded is located, the sub-meter sub-meter power consumption and each subsequent sub-meter sub-power consumption of the sub-meter sub-consumption The electricity consumption of a sub-meter is used as the target comparison sequence of the electricity consumption of the sub-meter; For each target comparison sequence corresponding to the sub-power consumption sequence, calculate the difference between the target comparison sequence and the sub-meter sub-power consumption and historical sub-meter sub-power consumption at the corresponding position in the sub-power consumption historical sequence to obtain the set of power ratios corresponding to the target comparison sequence; For each power ratio in each of the power ratio sets, the power ratio and each power ratio before the power ratio in the corresponding power ratio set are used as the ratio sequence corresponding to the power ratio; Calculate the average value of the electricity ratio in each of the ratio series respectively, and obtain the average value of the ratio corresponding to each ratio series; For each of the power ratio sets, determine the maximum ratio average value in the ratio average values of each ratio sequence corresponding to the power ratio set, and use the maximum ratio average value as the target ratio average value of the power ratio set; Sorting the average value of the target ratios in the order of the largest and the smallest to obtain an average value sequence, and obtain the average value of the target ratios located in the first preset number in the average value sequence; For each target ratio average value in the preset number of target ratio average values, determine the number of power ratio values in the power ratio value set corresponding to the target ratio average value, and determine the first average value of the target ratio value based on the number. a weight coefficient, wherein the quantity has a positive correlation with the first weight coefficient; For each of the first weight coefficients, calculate the product of the first weight coefficient and the target ratio average value corresponding to the first weight coefficient, and use the product as the target comparison sequence corresponding to the target ratio average value and the sub- Similarity between historical series of electricity consumption; Determine the target comparison sequence with the largest similarity, and use the similarity of the target comparison sequence as the similarity between the sub-electricity consumption sequence and the sub-electricity consumption history sequence. 6. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 4, wherein the described power consumption of a sub-meter preset sub-meter is determined based on the second preset rule to this sub-meter sub-meter. The steps of using electricity for replacement processing also include: The step of calculating the similarity between the sub-consumption historical sequence and the sub-consumption sequence where the sub-meter sub-consumption that has been screened and excluded is located, the step includes: For each sub-meter sub-power consumption in the sub-meter sub-power consumption sequence where the sub-meter sub-power consumption that has been screened and excluded is located, the sub-meter sub-meter power consumption and each subsequent sub-meter sub-power consumption of the sub-meter sub-consumption The electricity consumption of a sub-meter is used as the target comparison sequence of the electricity consumption of the sub-meter; For each target comparison sequence corresponding to the sub-power consumption sequence, calculate the difference between the target comparison sequence and the sub-meter sub-power consumption and historical sub-meter sub-power consumption at the corresponding position in the sub-power consumption historical sequence to obtain the set of power ratios corresponding to the target comparison sequence; For each power ratio in each of the power ratio sets, the power ratio and each power ratio before the power ratio in the corresponding power ratio set are used as the ratio sequence corresponding to the power ratio; Calculate the average value of the electricity ratio in each of the ratio series respectively, and obtain the average value of the ratio corresponding to each ratio series; For each of the power ratio sets, determine the maximum ratio average value in the ratio average values of each ratio sequence corresponding to the power ratio set, and use the maximum ratio average value as the target ratio average value of the power ratio set; For each adjacent two target comparison sequences, compare the average value of the two target ratios corresponding to the two target comparison sequences respectively; If the average difference between the two target ratio averages is smaller than the target difference, a second weight coefficient is set for the larger one of the two target ratio averages, wherein the The second weight coefficient is less than 1 and has a negative correlation with the target difference; For each of the second weight coefficients, update the corresponding target ratio average value based on the second weight coefficient to obtain an updated target ratio average value; The maximum average value of target ratio is determined, and the maximum average value of target ratio is used as the similarity between the sub-electricity consumption sequence and the sub-electricity consumption historical sequence. 7. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 4, wherein the multiple historical sub-meter sub-meter power consumption included in the target sub-meter power consumption historical sequence Steps of determining a historical sub-meter sub-power consumption as a sub-meter preset sub-power consumption, and performing replacement processing on the screened and excluded sub-meter sub-power consumption based on the sub-meter preset sub-power consumption, include: Determine the time segment corresponding to the sub-meter power consumption that is excluded from the screening; Determine the corresponding historical time segment based on the time segment, and obtain a historical sub-meter sub-meter power consumption corresponding to the historical time segment from the multiple historical sub-meter sub-meter power consumption included in the target sub-meter power consumption history sequence quantity; Taking the acquired historical sub-meter sub-power consumption as sub-meter preset sub-power consumption, and performing replacement processing on the screened and excluded sub-meter sub-power consumption based on the sub-meter preset sub-power consumption . 8. The method for monitoring the operation error of an electric energy meter based on HPLC high-frequency acquisition data according to claim 4, wherein the multiple historical sub-meter sub-meter power consumption included in the target sub-meter power consumption historical sequence Steps of determining a historical sub-meter sub-power consumption as a sub-meter preset sub-power consumption, and performing replacement processing on the screened and excluded sub-meter sub-power consumption based on the sub-meter preset sub-power consumption, include: Reordering the multiple historical sub-meter sub-power consumption included in the target sub-sub-power consumption historical sequence in descending order; Re-ordering the multiple sub-meter sub-power consumptions included in the sub-meter sub-power consumption sequence where the sub-meter sub-power consumption that has been screened and excluded is located in descending order; Based on the reordered positions of the sub-meter sub-meter power consumption that have been screened out, determine the historical sub-meter sub-meter sub-power consumption of the corresponding position in the reordered historical sequence of the target sub-meter power consumption; Taking the historical sub-meter sub-power consumption of the corresponding location as the sub-meter preset sub-power consumption, and performing replacement processing on the screened and excluded sub-meter sub-power consumption based on the sub-meter preset sub-power consumption . 9. An electric energy meter operation error monitoring system is characterized in that, comprises HPLC equipment and the computing platform that is connected with this HPLC communication, wherein, described computing platform comprises: memory for storing computer programs; A processor connected with the memory is used to execute a computer program to implement the method for monitoring the running error of an electric energy meter based on high-frequency HPLC data collected in any one of claims 1-8.

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