Electric energy meter and method for judging electricity stealing before using acquisition terminal meter

Abstract

The invention discloses an electric energy meter and a method for judging electricity stealing before using an acquisition terminal, and belongs to the technical field of electric digital data processing. The method comprises the following steps: calculating a sub-meter metering error vector of each time period in real time, storing electric energy data contained in the time period when the sub-meter metering error vector exceeds tolerance in an out-of-tolerance electric energy data matrix, monitoring the out-of-tolerance electric energy data matrix in real time, and when new electric energy data is added into the out-of-tolerance electric energy data matrix every time, determining that the out-of-tolerance electric energy data matrix exists. And judging whether the current out-of-tolerance electric energy data matrix contains periodic electric quantity data or not, and if so, further judging whether electricity stealing exists before the meter. According to the method, the characteristics of periodicity and regularity of electricity utilization of actual users are utilized, the electric quantity data with stable load of electricity stealing before the meter is screened out to be matched with the historical empirical data, and effective and accurate judgment of electricity stealing before the meter is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of electric digital data processing, and in particular relates to a method for judging electricity theft. Background Art

[0002] Among the acts of electricity theft, pre-meter theft is a special case, which refers to illegally drawing additional lines from the power supply line to supply power to other devices before the power supply line passes through the power meter or the terminal equipment. In essence, this method of electricity theft introduces an unknown power-consuming device into the power supply system, and its power consumption is highly random.

[0003] The traditional electricity theft analysis method is based on the energy conservation model, that is, the total power of the total metering device should be equal to the sum of the power of each branch metering device. By establishing a linear equation system, the accuracy data of each metering device can be solved. If the calculated accuracy error value of a device deviates significantly from the ideal value, it may indicate that the device is inaccurate or has stolen electricity.

[0004] However, since electricity theft before the meter is equivalent to the existence of unknown electrical equipment, this will introduce random interference when solving the linear equations, causing the calculated accuracy data to also show randomness. Therefore, it is difficult for traditional methods to accurately determine electricity theft before the meter. Summary of the invention

[0005] The present invention proposes an electric energy meter and a method for determining electricity theft before the meter using a terminal, the purpose of which is to solve the problem that the traditional method cannot accurately determine whether there is electricity theft before the meter.

[0006] The technical solution of the present invention is as follows:

[0007] A method for judging electricity theft in front of an electric energy meter and a terminal meter, wherein the metering topology structure in which the electric energy meter and the terminal meter are located includes a master meter and a plurality of sub-meters, and the method comprises the following steps:

[0008] Step 1: Calculate the sub-meter measurement error vector of each time period in real time, wherein the sub-meter measurement error vector includes the error of each sub-meter in the time period, and save the electric energy data included in the time period when the sub-meter measurement error vector exceeds the tolerance into the out-of-tolerance electric energy data matrix;

[0009] Step 2: monitor the out-of-tolerance electric energy data matrix in real time. Whenever new electric energy data is added to the out-of-tolerance electric energy data matrix, execute step 3;

[0010] Step 1 and step 2 are performed simultaneously;

[0011] Step 3: determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data. If so, execute step 4; otherwise, return to step 2 to continue monitoring.

[0012] Step 4: Calculate the sub-meter electric energy error vector according to the periodic electric energy data. The sub-meter electric energy error vector includes the recalculated error of each sub-meter. Determine whether there is pre-meter electricity theft according to the sub-meter electric energy error vector.

[0013] As a further improvement of the electric energy meter and the method for determining electricity theft before the terminal meter, the process of calculating the sub-meter measurement error vector for a certain time period in step 1 is:

[0014] Assume that the number of sub-meters is M, a time period includes N time intervals, and the error of the i-th sub-meter in the time period is E i , the energy increment of the ith submeter in the nth time interval is X ni , the total energy increment is Y n , then the sub-meter measurement error vector for this time period is:

[0015] E=1 M×1 -(X T X) -1 X T Y;

[0016] in:

[0017]

[0018]

[0019]

[0020] (·) T represents the matrix transpose operation, (·) -1 Represents a matrix inversion operation.

[0021] As a further improvement of the electric energy meter and the method for determining electricity theft before the terminal meter, the method for determining whether the sub-meter measurement error vector exceeds the tolerance in step 1 is:

[0022] For a sub-meter measurement error vector E in a certain time period, calculate the average vector of the sub-meter measurement error vectors of L time periods before this time period Then determine whether the following conditions are met:

[0023]

[0024] Among them, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold;

[0025] If the above conditions are not met, the electric energy data contained in the time period is added to the out-of-tolerance electric energy data matrix by adding rows in the following matrix form:

[0026]

[0027] As a further improvement of the electric energy meter and the method for determining electricity theft in front of the terminal meter, the value of the tolerance threshold ε is: ε=1.5×M×δ, where δ is the upper limit of the accuracy error of the sub-meter.

[0028] As a further improvement of the electric energy meter and the method for determining electricity theft before the terminal meter, the process of determining whether periodic electricity data is included in step 3 is as follows:

[0029] Step 3-1: Assume that the out-of-tolerance electric energy data matrix includes metering data of T time intervals:

[0030]

[0031] Among them, X ti is the electric energy increment of the ith sub-meter in the tth time interval in the out-of-tolerance electric energy data matrix, Y t is the electric energy increment of the total meter in the tth time interval;

[0032] Traverse each row in the out-of-tolerance electric energy data matrix and calculate the electric energy difference between the ideal electric energy and the actual electric energy in each time interval. For the tth row, the electric energy difference Δ t for:

[0033]

[0034] in is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1 The average error corresponding to the i-th sub-table in;

[0035] Step 3-2: According to the electric energy difference Δ t The maximum value of Δ max and the minimum value Δ min Establish the electric energy difference range and divide the electric energy difference range into K difference intervals on average, where the value range of the kth difference interval is:

[0036]

[0037] Step 3-3: Count the electric energy difference values ​​Δ falling into different difference intervals t , calculate the probability P of each difference interval k :

[0038]

[0039] Among them C k is the number of electric energy differences falling into the kth difference interval;

[0040] Step 3-4, find the Q difference intervals with the largest probability as the target difference interval;

[0041] Step 3-5: For each target difference interval, calculate the electric energy difference Δ that falls into it t The variance of is used to determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data.

[0042] As a further improvement of the method for determining electricity theft in front of the electricity meter and the terminal, the specific determination method in step 3-5 is: if the variance of any target difference interval is greater than the threshold, it is determined that it does not contain periodic electricity data; otherwise, it is determined that it contains periodic electricity data.

[0043] As a further improvement of the electric energy meter and the method for determining electricity theft before the terminal meter is used, step 4 specifically includes:

[0044] Step 4-1, respectively calculating the corresponding sub-meter electric energy error vector E′ for each target difference interval selected in step 3;

[0045] Step 4-2: Determine whether the electric energy error vector of each sub-meter meets the following conditions:

[0046]

[0047] in, is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold;

[0048] If the sub-meter electric energy error vectors corresponding to all target difference intervals meet the condition, it is determined that there is pre-meter electricity theft; otherwise, it is determined that there is no pre-meter electricity theft.

[0049] As a further improvement of the electric energy meter and the method for determining electricity theft before using the terminal meter, the method for calculating the sub-meter electric energy error vector T' in step 4-1 is:

[0050] For a certain target difference interval, the rows corresponding to the electric energy differences falling within it in the out-of-tolerance electric energy data matrix are extracted to form an electric energy matrix:

[0051]

[0052] Among them, X ci is the electric energy increment of the ith submeter in the cth time interval, Y c is the electric energy increment of the total meter in the cth time interval, C is the number of rows of the electric energy matrix, that is, the number of electric energy differences in the target difference interval;

[0053] Calculate the average value of the electric energy difference in the target difference interval and record it as

[0054] Then the corresponding sub-meter electric energy error vector E′ is calculated by the following formula:

[0055] E'=1 M×1 -(X′ T X′) -1 x′ T Y';

[0056] Among them, X' and Y' are based on the average value of the above power matrix and power difference Build:

[0057]

[0058]

[0059] Compared with the prior art, the present invention has the following positive effects:

[0060] The present invention utilizes the periodicity and regularity of actual user electricity consumption to perform statistical analysis on electric energy, screens out relatively stable electricity data for pre-meter electricity theft loads, then uses these stable electricity data to recalculate errors, and makes a judgment on pre-meter electricity theft based on the degree of matching between the calculated accuracy data and historical experience data, thereby achieving effective and accurate judgment on pre-meter electricity theft. DETAILED DESCRIPTION

[0061] The technical solution of the present invention is described in detail below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0062] The present invention is based on the following assumptions: the accuracy of the electric energy meter and the user terminal are tested and qualified at the initial stage of equipment installation, the line is normal, and the abnormal condition of electricity theft before the meter occurs after the line has been running for a period of time.

[0063] To simplify the description, in the metering topology, the main metering equipment (electricity meter, user and procurement terminal) is referred to as the main meter; the branch metering equipment (electricity meter, user and procurement terminal) is referred to as the sub-meter.

[0064] An electric energy meter and a method for determining electricity theft before using a terminal meter, the steps comprising:

[0065] Step 1: Calculate the sub-meter measurement error vector of each time period in real time, and save the electric energy data included in the time period where the sub-meter measurement error vector exceeds the tolerance into the out-of-tolerance electric energy data matrix.

[0066] The process of calculating the sub-meter measurement error vector for a certain period of time is as follows:

[0067] Assume that the number of sub-meters is M, a time period includes N time intervals, and the error of the i-th sub-meter in the time period is Ei , the energy increment of the ith submeter in the nth time interval is X ni , the total energy increment is Y n , then the sub-meter measurement error vector for this time period is:

[0068] E=1 M×1 -(X T X) -1 X T Y;

[0069] in:

[0070]

[0071]

[0072]

[0073] (·) T represents the matrix transpose operation, (·)- 1 Represents a matrix inversion operation.

[0074] Furthermore, the method for judging whether the sub-meter measurement error vector exceeds the tolerance is:

[0075] For a sub-meter measurement error vector E in a certain time period, calculate the average vector of the sub-meter measurement error vectors of L time periods before this time period L is preferably 5, and then determine whether the following conditions are met:

[0076]

[0077] Among them, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold.

[0078] Further, the value of the tolerance threshold ε is preferably: ε=1.5×M×δ. δ is the upper limit of the accuracy error of the sub-meter, for example, δ=0.02 for an active level 2 electric energy meter.

[0079] If the above conditions are not met, the electric energy data contained in the time period is added to the out-of-tolerance electric energy data matrix by adding rows in the following matrix form:

[0080]

[0081] Step 2: monitor the out-of-tolerance power data matrix in real time. Whenever new power data is added to the out-of-tolerance power data matrix, execute step 3.

[0082] Step 1 and step 2 are performed simultaneously.

[0083] Step 3: Determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data. If so, execute step 4; otherwise, return to step 2 to continue monitoring.

[0084] The process of determining whether periodic power data is included is as follows:

[0085] Step 3-1: Assume that the out-of-tolerance electric energy data matrix includes metering data of T time intervals:

[0086]

[0087] Among them, X ti is the electric energy increment of the ith sub-meter in the tth time interval in the out-of-tolerance electric energy data matrix, Y t is the electric energy increment of the total meter in the tth time interval. In general, the number of rows T of the out-of-tolerance electric energy data matrix should be greater than 20×N, where N is the number of time intervals contained in a time period.

[0088] Traverse each row in the out-of-tolerance electric energy data matrix and calculate the electric energy difference between the ideal electric energy and the actual electric energy in each time interval. For the tth row, the electric energy difference Δ t for:

[0089]

[0090] in is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1 The average error corresponding to the i-th subtable in .

[0091] Step 3-2: According to the electric energy difference Δ t The maximum value of Δ max and the minimum value Δ min Establish the electric energy difference range and divide the electric energy difference range into K difference intervals on average, where the value range of the kth difference interval is:

[0092]

[0093] Step 3-3: Count the electric energy difference values ​​Δ falling into different difference intervals t , calculate the probability P of each difference interval k :

[0094]

[0095] Among them C k is the number of electric energy differences falling into the kth difference interval.

[0096] Step 3-4: Find the Q difference intervals with the largest probability as the target difference interval. In this embodiment, Q=3.

[0097] Step 3-5: For each target difference interval, calculate the electric energy difference Δ that falls into it t The variance of is used to determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data.

[0098] The specific judgment method is: if the variance of any target difference interval is greater than the threshold (0.1), it means that the dispersion of the electric energy difference is large and does not contain periodic electric energy data; otherwise, it is determined to contain periodic electric energy data.

[0099] The actual user's electricity consumption has a certain periodicity and regularity. From the perspective of electricity consumption, there is an unknown user in the pre-meter electricity theft, so the obtained electric energy difference will also show periodicity and regularity. When the amount of data is large enough, the variance of all target difference intervals will be less than the threshold. If there is a situation greater than the threshold, it means that more data needs to be saved.

[0100] Step 4: Calculate the sub-meter electric energy error vector according to the periodic electric energy data, and determine whether there is pre-meter electricity theft according to the sub-meter electric energy error vector.

[0101] Specifically include:

[0102] Step 4-1: Calculate the corresponding sub-meter electric energy error vector for each target difference interval selected in step 3.

[0103] For a certain target difference interval, the rows corresponding to the electric energy differences falling within it in the out-of-tolerance electric energy data matrix are extracted to form an electric energy matrix:

[0104]

[0105] Among them, X ci is the electric energy increment of the ith submeter in the cth time interval, Y c is the electric energy increment of the total meter in the cth time interval, and C is the number of rows of the electric energy matrix, that is, the number of electric energy differences in the target difference interval.

[0106] Calculate the average value of the electric energy difference in the target difference interval and record it as

[0107] Then the corresponding sub-meter electric energy error vector E′ is calculated by the following formula:

[0108] E′=1 M×1 -(X′ T X′) -1 x′ T Y′;

[0109] Among them, X' and Y' are based on the average value of the above power matrix and power difference Build:

[0110]

[0111]

[0112] Step 4-2: Determine whether the electric energy error vector of each sub-meter meets the following conditions:

[0113]

[0114] in, is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold. The value of the tolerance threshold ε is preferably: v = 1.5×M×δ, where δ is the upper limit of the precision error of the sub-meter.

[0115] If the sub-meter electric energy error vectors corresponding to all target difference intervals meet the condition, it is determined that there is pre-meter electricity theft; otherwise, it is determined that there is no pre-meter electricity theft.

[0116] It should be noted that it is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. The scope of the present invention is defined by the claims rather than the above description.

Claims

1. A method for judging electricity theft before an electric energy meter and a terminal meter, wherein the metering topology structure in which the electric energy meter and the terminal meter are located includes a master meter and a plurality of sub-meters, characterized in that The method steps include: Step 1: Calculate the sub-meter measurement error vector of each time period in real time, wherein the sub-meter measurement error vector includes the error of each sub-meter in the time period, and save the electric energy data included in the time period when the sub-meter measurement error vector exceeds the tolerance into the out-of-tolerance electric energy data matrix; Step 2: monitor the out-of-tolerance electric energy data matrix in real time. Whenever new electric energy data is added to the out-of-tolerance electric energy data matrix, execute step 3; Step 1 and step 2 are performed simultaneously; Step 3: determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data. If so, execute step 4; otherwise, return to step 2 to continue monitoring. Step 4: Calculate the sub-meter electric energy error vector according to the periodic electric energy data. The sub-meter electric energy error vector includes the recalculated error of each sub-meter. Determine whether there is pre-meter electricity theft according to the sub-meter electric energy error vector.

2. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 1, characterized in that: The process of calculating the sub-meter measurement error vector for a certain period of time in step 1 is: Assume that the number of sub-meters is M, a time period includes N time intervals, and the error of the i-th sub-meter in the time period is E i , the energy increment of the ith submeter in the nth time interval is X ni , the total energy increment is Y n , then the sub-meter measurement error vector for this time period is: E=1 M×1 -(X T X) -1 X T Y; in: (·) T represents the matrix transpose operation, (·) -1 Represents a matrix inversion operation.

3. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 2, characterized in that: In step 1, the method for judging whether the sub-meter measurement error vector exceeds the tolerance is: For a sub-meter measurement error vector E in a certain time period, calculate the average vector of the sub-meter measurement error vectors of L time periods before this time period Then determine whether the following conditions are met: Among them, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold; If the above conditions are not met, the electric energy data contained in the time period is added to the out-of-tolerance electric energy data matrix by adding rows in the following matrix form:

4. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 3 are characterized by: The value of the tolerance threshold ε is: ε = 1.5 × M × δ, where δ is the upper limit of the accuracy error of the sub-table.

5. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 1, characterized in that: The process of determining whether periodic power data is included in step 3 is as follows: Step 3-1: Assume that the out-of-tolerance electric energy data matrix includes metering data of T time intervals: Among them, X ti is the electric energy increment of the ith sub-meter in the tth time interval in the out-of-tolerance electric energy data matrix, Y t is the electric energy increment of the total meter in the tth time interval; Traverse each row in the out-of-tolerance electric energy data matrix and calculate the electric energy difference between the ideal electric energy and the actual electric energy in each time interval. For the tth row, the electric energy difference Δ t for: in is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1 The average error corresponding to the i-th sub-table in; Step 3-2: According to the electric energy difference Δ t The maximum value of Δ max and the minimum value Δ min Establish the electric energy difference range and divide the electric energy difference range into K difference intervals on average, where the value range of the kth difference interval is: Step 3-3: Count the electric energy difference values ​​Δ falling into different difference intervals t , calculate the probability P of each difference interval k : Among them C k is the number of electric energy differences falling into the kth difference interval; Step 3-4, find the Q difference intervals with the largest probability as the target difference interval; Step 3-5: For each target difference interval, calculate the electric energy difference Δ that falls into it t The variance of is used to determine whether the current out-of-tolerance electric energy data matrix contains periodic electric energy data.

6. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 5, characterized in that: The specific judgment method in step 3-5 is: if the variance of any target difference interval is greater than the threshold, it is determined that it does not contain periodic power data; otherwise, it is determined that it contains periodic power data.

7. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 5, characterized in that: Step 4 specifically includes: Step 4-1, respectively calculating the corresponding sub-meter electric energy error vector E′ for each target difference interval selected in step 3; Step 4-2: Determine whether the electric energy error vector of each sub-meter meets the following conditions: in, is the average vector of the sub-meter measurement error vectors of the most recent L time periods obtained in step 1, ‖·‖2 represents the 2-norm operation of the calculation vector, and ε represents the tolerance threshold; if the sub-meter electric energy error vectors corresponding to all target difference intervals meet this condition, it is determined that there is pre-meter electricity theft, otherwise it is determined that there is no pre-meter electricity theft.

8. The electric energy meter and the method for determining electricity theft before using the terminal meter as claimed in claim 7, characterized in that: Calculate the sub-meter electric energy error vector E in step 4-1 ′ The method is: For a certain target difference interval, the rows corresponding to the electric energy differences falling within it in the out-of-tolerance electric energy data matrix are extracted to form an electric energy matrix: Among them, X ci is the electric energy increment of the ith submeter in the cth time interval, Y c is the electric energy increment of the total meter in the cth time interval, C is the number of rows of the electric energy matrix, that is, the number of electric energy differences in the target difference interval; Calculate the average value of the electric energy difference in the target difference interval and record it as Then the corresponding sub-meter electric energy error vector E′ is calculated by the following formula: E′=1 M×1 -(X ′T X ′ ) -1 X ′T Y′; Among them, X ′ and Y′ are based on the average value of the above power matrix and power difference Build:

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