CN114689916A - Intelligent electric energy meter metering error analysis system - Google Patents
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Abstract
The invention provides an intelligent electric energy meter metering error analysis system, which belongs to the technical field of electric energy meters and comprises a collecting device, a rejecting device, an error data operation device, a mean value operation device and a coefficient operation device; the collecting device collects the effective power of the sub-meters and the total power of the general meter, the removing device removes the data of the sub-meters with the effective power lower than a fixed value, the error data operation device calculates the error value of a meter box before removal and the error value of the meter box after removal, the mean value operation device is used for calculating the effective power average value of the sub-meters before removal of the sub-meters and calculating the effective power mean value of the sub-meters after removal, and the coefficient operation device is used for calculating the Pearson correlation coefficient before removal between the effective power of the sub-meters before removal and the error value of the meter box before removal. The intelligent electric energy meter metering error analysis system provided by the invention can accurately obtain the running condition of each sub-meter, can judge the metering error condition of the sub-meter in time, is convenient to realize and saves the labor cost.
Description
Technical Field
The invention belongs to the technical field of electric energy meters, and particularly relates to an intelligent electric energy meter metering error analysis system.
Background
The electric energy meter is used as a terminal product of the smart power grid, is the basis of the construction of the smart power grid, is also the key support of policies of the smart power grid of each country, has constantly increased novel and practical functions, and has obvious development trend of modularization, networking and systematization. The intelligent electric meter is one of basic devices for acquiring data of an intelligent power grid, undertakes tasks including two aspects of acquisition, metering and transmission of original electric energy data, and is also the basis for realizing information integration, information analysis optimization and display. The metering error of the electric energy meter is directly related to the economic benefits of both the power supply and the power utilization, so that both the power supply and the power utilization put forward higher requirements on the accuracy of electric energy metering, and the metering precision of the intelligent electric energy meter has important significance. At present, the method has great effect on the metering error analysis of the electric energy meter, and is related to the running condition and the electricity utilization safety of the electric energy meter.
Disclosure of Invention
The invention aims to provide an intelligent electric energy meter metering error analysis system to solve the technical problems that the accuracy of electric energy metering is low and the use of human resources is high in the prior art.
In order to achieve the purpose, the invention adopts the technical scheme that: the system comprises a collecting device, a rejecting device, an error data operation device, a mean value operation device and a coefficient operation device which are sequentially arranged; the collecting device is used for collecting the effective power of each sub-meter in the meter box and the total power of the total meter input into the meter box; the removing device is used for removing the data of the sub-table with the effective power lower than a fixed value; the error data arithmetic device is used for calculating the error value of the meter box before rejection and calculating the error value of the meter box after rejection; the mean value operation device is used for calculating the effective power average value of the sub-tables before the elimination of the sub-tables and the effective power mean value of the sub-tables after the elimination; and the coefficient operation device is used for calculating a pre-rejection Pearson correlation coefficient between the effective power of the sub-table before rejection and the error value of the meter box before rejection.
In a possible implementation manner, the acquisition device is used for recording the number of the sub-tables and the number of the acquisition points.
In a possible implementation manner, the removing device removes data of the sub-tables with effective power lower than a set value, and records the number of the remaining sub-tables as the number of corresponding acquisition points.
In one possible implementation, the pre-culling meter box error value and the post-culling meter box error value are calculated for the effective power and the total power of the culling sub-meters.
In a possible implementation manner, the total power of the meter box after being rejected is the sum of the total power minus the rated power of the rejected sub-meter.
In a possible implementation manner, the mean value operation device is used for calculating a mean value of the effective power of the meter box before elimination of the error value of the meter box before elimination and calculating a mean value of the effective power of the meter box after elimination of the error value of the meter box after elimination.
In a possible implementation manner, the coefficient operation device is configured to calculate a post-rejection pearson correlation coefficient between the effective power of the sub-table after rejection and the error value of the post-rejection meter box.
In a possible implementation manner, the acquisition device is provided with a monitoring module for eliminating the abnormal sub-table.
In one possible implementation, the coefficient calculation device calculates an error coefficient to be uploaded to a server for monitoring the error of the sub-table in the meter box.
In one possible implementation, the absolute values of the pre-culling pearson correlation coefficients are ordered from small to large, and the remaining pre-culling pearson correlation coefficients are averaged with the post-culling pearson correlation coefficients.
The intelligent electric energy meter metering error analysis system provided by the invention has the beneficial effects that: compared with the prior art, the system for analyzing the metering error of the intelligent electric energy meter acquires the effective power of each sub-meter and the total power of the total meter in the meter box by virtue of the acquisition device, the rejection device rejects the data of the sub-meters with the effective power lower than a fixed value, the error data operation device calculates the error value of the meter box, the mean value operation device calculates the effective power average value and the effective power mean value of the sub-meters, and the coefficient operation device calculates the effective power and the Pearson correlation coefficient of the sub-meters before rejection, so that the operation condition of each sub-meter can be accurately acquired, the metering error condition of the sub-meters can be timely judged, the system is convenient to realize, and the labor cost is saved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of a system for analyzing a measurement error of an intelligent electric energy meter according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
It will be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like, as used herein, refer to an orientation or positional relationship indicated in the drawings that is solely for the purpose of facilitating the description and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and is therefore not to be construed as limiting the invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
Referring to fig. 1, a description will now be given of a metering error analysis system of an intelligent electric energy meter according to the present invention. An intelligent electric energy meter metering error analysis system comprises a collecting device, a rejecting device, an error data operation device, a mean value operation device and a coefficient operation device which are sequentially arranged; the collecting device is used for collecting the effective power of each sub-meter in the meter box and the total power of the general meter input into the meter box; the removing device is used for removing the data of the sub-table with the effective power lower than a fixed value; the error data arithmetic device is used for calculating the error value of the meter box before rejection and calculating the error value of the meter box after rejection; the mean value operation device is used for calculating the effective power mean value of the sub-tables before the sub-tables are removed and the effective power mean value of the sub-tables after the sub-tables are removed; and the coefficient operation device is used for calculating a pre-rejection Pearson correlation coefficient between the effective power of the pre-rejection sub-table and the error value of the meter box before rejection.
Compared with the prior art, the system for analyzing the metering error of the intelligent electric energy meter acquires the effective power of each sub-meter and the total power of a total meter in a meter box by virtue of the acquisition device, the rejection device rejects the data of the sub-meters with the effective power lower than a fixed value, the error data operation device calculates the error value of the meter box, the mean value operation device calculates the effective power average value and the effective power mean value of the sub-meters, and the coefficient operation device calculates the effective power and the Pearson correlation coefficient of the sub-meters before rejection, so that the operation condition of each sub-meter can be accurately acquired, the metering error condition of the sub-meters can be timely judged, the system is convenient to realize, and the labor cost is saved.
Specifically, the method comprises the following steps: the collecting device is used for collecting the effective power of each sub-meter in the meter box and collecting the total power of the total meter input into the meter box, the number of the sub-meters is recorded as m1, and the number of the collecting points is recorded as n 1. A plurality of sub-tables are arranged in one meter box, and the number of the sub-tables is recorded as m 1.
The removing device is used for removing the data of the sub-tables with the effective power lower than the set value, the number of the remaining sub-tables is recorded as m2, and the number of the acquisition points corresponding to m2 is n 2; because many sub-tables in the meter box can not guarantee that all sub-tables of the detection time point are normally operated, therefore, the abnormal sub-tables are firstly discarded, and the discarding mode is as follows: if the effective power of a sub-table is less than an error floor, the sub-table is discarded. The minimum value of the error is data which can be known during production, and of course, the minimum value of the error can be artificially defined during detection, and the minimum value of the error is a sub-table which needs to be rejected if the power of the sub-table cannot normally work at the moment only by comparing the power of the sub-table which normally works. According to the method, all abnormal sub-tables are removed, and the number of the remaining effective sub-tables is recorded as m2, namely m2-m1 sub-tables are removed.
The error data operation device is used for calculating an error value of a meter box before the elimination according to the effective power and the total power of the m1 sub-meters before the elimination, and calculating an error value of a meter box after the elimination according to the effective power of the m2 sub-meters after the elimination and the total power of the meter box after the elimination, wherein the total power of the meter box after the elimination is the sum of the total power minus the rated power of the eliminated sub-meters; before the elimination, an abnormal sub-table may exist, but the abnormal sub-table may or may not affect the final error, so as to avoid the accuracy of blind elimination and subsequent errors, the data before and after the elimination are calculated uniformly, and then the subsequent processing is performed.
After the elimination, the number of the sub-tables is small, but the supply power of the whole meter box is not small, so that the rated power corresponding to the sub-tables needs to be subtracted, and the supply power of the meter box is matched with the rest normal sub-tables.
Wherein the calculation formula of the meter box error value before elimination is the sum of the total power minus the effective power of m1 sub-tables,
the calculation formula is as follows:
wherein S is1jRepresenting the meter box power deviation value of the jth data acquisition point, m1 is the number of sub-meters before removal, n1 is the number of acquisition points before removal, PijRepresents the power reading, T, of the ith sub-table of the jth data acquisition pointjRepresenting the total power reading for the jth data acquisition point.
The calculation formula of the eliminated meter box error value is the sum of the total power minus the effective power of m2 sub-tables,
the calculation formula is as follows:
wherein S is2jRepresenting the meter box power deviation value of the jth data acquisition point, m2 is the number of rejected sub-meters, n2 is the number of rejected acquisition points, PijRepresents the power reading, T, of the ith sub-table of the jth data acquisition pointjRepresenting the total power reading for the jth data acquisition point.
(4) The mean value operation device is used for calculating the mean value of the effective power of the sub-tables before the elimination of the m1 sub-tables, the mean value of the effective power of the sub-tables after the elimination of the m2 sub-tables, the mean value of the effective power of the meter box before the elimination of the error value of the meter box before the elimination of the meter box, and the mean value of the effective power of the meter box after the elimination of the error value of the meter box after the elimination of the meter box;
the calculation formula of the effective power mean value of the sub-table before elimination is as follows:
wherein,
represents the average of the i-th sub-table n1 power data.
The calculation formula of the effective power mean value of the rejected sub-tables is as follows:
wherein,
represents the mean of the ith sub-table n2 power data.
The calculation formula of the effective power mean value of the meter box before the elimination of the error value of the meter box before the elimination is as follows:
the calculation formula of the effective power mean value of the eliminated meter boxes of the eliminated meter box error value is as follows:
the coefficient operation device is used for calculating a pre-rejection Pearson correlation coefficient between the effective power of the m1 sub-tables before rejection and the error value of the meter box before rejection, and calculating a post-rejection Pearson correlation coefficient between the effective power of the m2 sub-tables after rejection and the error value of the meter box after rejection; and calculating the Pearson correlation coefficients before and after the elimination to obtain a group of m1 coefficient data and a group of m2 coefficient data.
The calculation formula of the correlation coefficient of the pearson before elimination is as follows:
the calculation formula of the correlation coefficient of the removed Pearson is as follows:
sorting the absolute values of the correlation coefficients before elimination from small to large, deleting the correlation coefficients before elimination of m1-m2, and taking the average value of the correlation coefficients before elimination and the correlation coefficients after elimination. That is, the data of the first group of m1 coefficients are sorted into smaller to larger absolute values, and if the number of the culled sub-tables is 1, the smallest data is deleted, so that the number of the remaining data is the same as that of the second group, that is, the culled data, that is, m1 is m2, at this time, two groups of coefficient data with the same number are obtained, and the two groups of coefficient data are subjected to an average processing, so that an average value is the final error coefficient.
And uploading the calculated error coefficient to a server for a worker to monitor the error of the sub-meter in the meter box. In order to enable the staff to monitor the error in real time, a real-time monitoring mode is further provided in the embodiment: the collecting device collects the total power of the meter box within 30 minutes and the effective power of each sub-meter, and the final error coefficient within 30 minutes is calculated after the elimination, the error value calculation, the average value calculation and the coefficient operation; the acquisition device is also used for dividing 24 hours into 48 meters for 30 minutes, acquiring the total power of the meter boxes in 48 minutes and the effective power of each sub-meter, calculating the final error coefficient in each 30 minutes after removing, error value calculation, mean value calculation and coefficient operation to obtain a group of data, drawing the reorganized data on a curve, if the curve is similar to a straight line, the error is proved to be normal, and if the curve fluctuates greatly, the sub-meter abnormality is proved to occur at the fluctuation position; meanwhile, if the sub-table is abnormal, the abnormal sub-table is automatically removed in the next 30 minutes, and then the final error coefficient of the next 30 minutes is calculated. The curve when the abnormity occurs and the curve redrawn after the abnormity is removed are both displayed, so that the working personnel can know the conditions before and after the time period when the abnormity occurs. The drawn curve and the fluctuation point are automatically stored and displayed, and in addition, the device also comprises an abnormality recording device which is used for recording the information of the abnormality sub-table. The information comprises the number of the abnormal sub-meter, the effective power, the total power of the meter box and the time period in which the abnormal sub-meter is positioned, and the abnormal sub-meter refers to the shifting point in the curve.
Further, the error analysis method comprises the following steps:
s10: and collecting the effective power of each sub-meter in the meter box and the total power of the total meter input into the meter box, wherein the number of the sub-meters is recorded as m1, and the number of the collection points is recorded as n 1.
S20: and eliminating data of the sub-tables with the effective power lower than the set value, and recording the number of the remaining sub-tables as m2, wherein the number of acquisition points corresponding to m2 is n 2.
S30: calculating an error value of a meter box before the elimination according to the effective power and the total power of the m1 sub-meters before the elimination, and calculating an error value of a meter box after the elimination according to the effective power of the m2 sub-meters after the elimination and the total power of the meter box after the elimination, wherein the total power of the meter box after the elimination is the sum of the total power minus the rated power of the eliminated sub-meters;
the calculation formula for the pre-culling meter box error value is the sum of the total power minus the effective power of the m1 sub-tables,
the calculation formula is as follows:
wherein S is1jRepresenting the meter box power deviation value of the j-th data acquisition point, m1 is the number of sub-meters before removal, n1 is the number of acquisition points before removal, PijRepresents the power reading, T, of the ith sub-table of the jth data acquisition pointjRepresenting the total power reading for the jth data acquisition point.
The calculation formula of the eliminated meter box error value is the sum of the total power minus the effective power of m2 sub-tables,
the calculation formula is as follows:
wherein S is2jRepresenting the meter box power deviation value of the jth data acquisition point, m2 is the number of rejected sub-meters, n2 is the number of rejected acquisition points, PijRepresents the power reading, T, of the ith sub-table of the jth data acquisition pointjRepresenting the total power reading for the jth data acquisition point.
S40: calculating the effective power average value of the sub-tables before the elimination of the m1 sub-tables before the elimination, the effective power average value of the sub-tables after the elimination of the m2 sub-tables after the elimination, the effective power average value of the meter box before the elimination for calculating the error value of the meter box before the elimination, and the effective power average value of the meter box after the elimination for calculating the error value of the meter box after the elimination;
the calculation formula of the effective power mean value of the sub-table before elimination is as follows:
wherein,
represents the mean of the ith sub-table n1 power data.
The calculation formula of the effective power mean value of the rejected sub-tables is as follows:
wherein,
represents the average of the i-th sub-table n2 power data.
The calculation formula of the effective power mean value of the meter box before the elimination of the error value of the meter box is as follows:
the calculation formula of the effective power mean value of the eliminated meter box after the error value of the meter box is eliminated is as follows:
s50: calculating pre-rejection Pearson correlation coefficients between the effective powers of the m1 sub-tables before rejection and the error values of the meter box before rejection, and calculating post-rejection Pearson correlation coefficients between the effective powers of the m2 sub-tables after rejection and the error values of the meter box after rejection;
the calculation formula of the correlation coefficient of the pearson before elimination is as follows:
the calculation formula of the correlation coefficient of the removed Pearson is as follows:
s60: sorting the absolute values of the correlation coefficients before elimination from small to large, deleting the correlation coefficients before elimination of m1-m2, and taking the average value of the correlation coefficients before elimination and the correlation coefficients after elimination.
S70: and uploading the calculated error coefficient to a server for a worker to monitor the error of the sub-meter in the meter box. In order to enable the staff to monitor the error in real time, a real-time monitoring mode is further provided in the embodiment: the collecting device collects the total power of the meter box within 30 minutes and the effective power of each sub-meter, and the final error coefficient within 30 minutes is calculated after the elimination, the error value calculation, the average value calculation and the coefficient operation; the acquisition device is also used for dividing 24 hours into 48 meters for 30 minutes, acquiring the total power of the meter boxes in 48 minutes and the effective power of each sub-meter, calculating the final error coefficient in each 30 minutes after removing, error value calculation, mean value calculation and coefficient operation to obtain a group of data, drawing the reorganized data on a curve, if the curve is similar to a straight line, the error is proved to be normal, and if the curve fluctuates greatly, the sub-meter abnormality is proved to occur at the fluctuation position; meanwhile, if the sub-table is abnormal, the abnormal sub-table is automatically removed in the next 30 minutes, and then the final error coefficient of the next 30 minutes is calculated.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An intelligent electric energy meter metering error analysis system is characterized by comprising a collecting device, a rejecting device, an error data operation device, a mean value operation device and a coefficient operation device which are sequentially arranged; the collecting device is used for collecting the effective power of each sub-meter in the meter box and the total power of the general meter input into the meter box; the removing device is used for removing the data of the sub-table with the effective power lower than a fixed value; the error data arithmetic device is used for calculating the error value of the meter box before rejection and calculating the error value of the meter box after rejection; the mean value operation device is used for calculating the effective power average value of the sub-tables before the elimination of the sub-tables and the effective power mean value of the sub-tables after the elimination; and the coefficient operation device is used for calculating a pre-rejection Pearson correlation coefficient between the effective power of the sub-table before rejection and the error value of the meter box before rejection.
2. The system for analyzing the metering error of the intelligent electric energy meter according to claim 1, wherein the collecting device is used for recording the number of the sub-meters and the number of collecting points.
3. The system for analyzing the metering error of the intelligent electric energy meter according to claim 2, wherein the rejecting device rejects the data of the sub-meter with the effective power lower than the set value, and records the number of the remaining sub-meters as the number of corresponding collection points.
4. The system of claim 1, wherein the pre-culling meter box error values and post-culling meter box error values are calculated for the effective power and total power of the culling of the sub-meters.
5. The system for analyzing the metering error of the intelligent electric energy meter according to claim 4, wherein the total power of the meter boxes after being rejected is the sum of the total power minus the rated power of the rejected sub-meters.
6. The system for analyzing the metering error of the intelligent electric energy meter according to claim 1, wherein the mean value operation device is used for calculating a mean value of the effective power of the meter box before elimination of the error value of the meter box and calculating a mean value of the effective power of the meter box after elimination of the error value of the meter box after elimination.
7. The system of claim 1, wherein the coefficient computing device is configured to compute a post-culling pearson correlation coefficient between the culled effective power of the sub-meter and the culled meter box error value.
8. The system for analyzing the metering error of the intelligent electric energy meter according to claim 1, wherein the acquisition device is provided with a monitoring module for rejecting abnormal sub-meters.
9. The system for analyzing the metering error of the intelligent electric energy meter according to claim 1, wherein the coefficient operation device calculates the error coefficient to be uploaded to a server for monitoring the error of the sub-meter in the meter box.
10. The system of claim 1, wherein the pre-culling pearson correlation coefficients are ordered from small to large in absolute value, and the remaining pre-culling pearson correlation coefficients are averaged with the post-culling pearson correlation coefficients.
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| CN115542236A (en) * | 2022-11-24 | 2022-12-30 | 北京志翔科技股份有限公司 | Method and device for estimating running error of electric energy meter |
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| CN115542236A (en) * | 2022-11-24 | 2022-12-30 | 北京志翔科技股份有限公司 | Method and device for estimating running error of electric energy meter |
| CN115542236B (en) * | 2022-11-24 | 2023-06-06 | 北京志翔科技股份有限公司 | Electric energy meter operation error estimation method and device |
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