A method, device and equipment for searching a power stealing metering device

Abstract

The application discloses a power stealing metering device searching method, device and equipment, the method comprises the following steps: screening a typical transformer area and a transformer area to be searched from a plurality of low-voltage transformer areas according to transformer area basic data; calculating the actual line loss rate of the transformer area to be searched; calculating the theoretical line loss rate of the transformer area to be searched by using the average power loss rate of the typical transformer area; further determining the power stealing transformer area by comparing the theoretical line loss rate and the actual line loss rate of the transformer area to be searched; calculating the multivariate correlation between the time series data of each power metering device in the power stealing transformer area and the actual line loss value of the power stealing transformer area; and screening the power metering device with a multivariate correlation higher than a preset correlation index as a power stealing metering device. The technical scheme of the application locates the power stealing transformer area through transformer area basic data, and then determines the power stealing metering device by calculating the multivariate correlation between the time series data of the power metering device in the power stealing transformer area and the actual line loss value of the transformer area, thereby improving the searching accuracy of the power stealing metering device.

Description

Technical Field

[0001] This application relates to the field of power system engineering technology, and in particular to a method, apparatus and equipment for locating electricity theft metering devices. Background Technology

[0002] Existing technologies sometimes employ methods that combine line loss and abnormal events to locate metering devices for electricity theft, identifying suspected users through K-means clustering, support vector machine, and Bayesian algorithms. However, these methods fail to clarify the relationships between anti-theft indicator systems, resulting in low accuracy in locating metering devices for electricity theft. Other methods use the relationship between line loss and user electricity consumption changes to locate metering devices for electricity theft. This involves calculating the electricity consumption potential of all users within each transformer area, then filtering out users with high potential, and subsequently calculating the user's anomaly suspicion level to determine the electricity thief. This method involves filtering a portion of users' electricity consumption data over a long period and performing extensive function calculations, leading to a large calculation error range and low accuracy in locating metering devices for electricity theft. Summary of the Invention

[0003] This application provides a method, apparatus, and equipment for locating electricity theft metering devices, which solves the technical problem of low accuracy in locating electricity theft metering devices in the prior art.

[0004] The first aspect of this application provides a method for locating electricity theft metering devices, the method comprising:

[0005] Obtain basic data of multiple low-voltage distribution areas;

[0006] Based on the basic data of the low-voltage distribution area, select the distribution area to be investigated and typical distribution areas from the low-voltage distribution area;

[0007] Calculate the corresponding average power loss rate based on the basic data of the typical transformer area.

[0008] Based on the average power loss rate and the basic data of the transformer area to be inspected, calculate the actual line loss value, actual line loss rate and theoretical line loss rate of the transformer area to be inspected.

[0009] Select the electricity metering areas to be investigated where the actual line loss rate is greater than the theoretical line loss rate as the electricity theft areas, and obtain the time series data corresponding to each electricity metering device in the electricity theft areas;

[0010] Calculate the multivariate correlation between the time series data and the actual line loss value, and select electricity metering devices whose multivariate correlation is higher than a preset correlation index as electricity theft metering devices.

[0011] Optionally, the basic data of the distribution area includes electricity theft event markers and transformer operating parameters; the step of screening the distribution areas to be investigated and typical distribution areas from the low-voltage distribution areas according to the basic data of the distribution area includes:

[0012] The low-voltage distribution area corresponding to the electricity theft event marker is used as the initial distribution area;

[0013] The remaining low-voltage distribution areas, excluding the initial distribution area, are identified as typical distribution areas;

[0014] Determine whether there are any abnormalities in the transformer operating parameters corresponding to each initial distribution area;

[0015] If the transformer operating parameters are abnormal, the corresponding initial transformer area will be designated as the transformer area to be investigated.

[0016] Optionally, the basic data of the distribution area includes transformer capacity, electricity sales, and electricity supply. The step of calculating the corresponding average power loss rate based on the basic data of the typical distribution area includes:

[0017] The difference between the power supply and the power sales of the typical distribution area are calculated as the power loss value of the typical distribution area.

[0018] Calculate the sum of all the energy loss values ​​and the sum of the transformer capacities of all the typical distribution areas;

[0019] The average power loss rate of multiple typical transformer substations is obtained by calculating the ratio between the power loss value and the capacity value.

[0020] Optionally, the step of calculating the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer substation to be inspected based on the average power loss rate and the basic data of the substation to be inspected includes:

[0021] The difference between the power supply of the area to be inspected and the electricity sales of the area to be inspected is calculated as the actual line loss value of the area to be inspected.

[0022] The ratio between the actual line loss value and the power supply of the transformer substation to be inspected is calculated as the actual line loss rate of the transformer substation to be inspected.

[0023] The product of the average power loss rate of the typical distribution area and the transformer capacity of the distribution area to be investigated is used as the theoretical line loss value of the distribution area to be investigated.

[0024] The theoretical line loss value is calculated as the ratio between the theoretical line loss value and the power supply of the transformer area to be inspected, which is then used as the theoretical line loss rate of the transformer area to be inspected.

[0025] Optionally, the step of obtaining time-series data corresponding to each electricity metering device within the stolen electricity zone and calculating the multivariate correlation between the time-series data and the actual line loss value includes:

[0026] Obtain electricity consumption data recorded by each electricity metering device in the theft radio zone at fixed time intervals, and generate one or more time series data groups under the time intervals;

[0027] Calculate the first correlation between the voltage time series data set of the metering device and the actual line loss value data set;

[0028] Calculate the second correlation between the current time series data set of the metering device and the actual line loss value data set;

[0029] Calculate the third correlation between the time series data set of the metering device readings and the data set of actual line loss values;

[0030] The multiplication of the first correlation, the second correlation, and the third correlation is calculated as the multivariate correlation between the time series data and the actual line loss value.

[0031] Optionally, the formula for calculating the first correlation between the voltage time series data set of the metering device and the actual line loss value data set is as follows:

[0032]

[0033] In the formula, R um (S um ,Y m S represents the first correlation between the voltage time series data set of the metering device and the actual line loss value data set. um This refers to the m-th group of voltage time series data from the metering device. Y is the median of the voltage time series data set. m This represents the actual line loss value of the m-th group of the metering device. This is the median of the actual line loss data set of the metering device.

[0034] Optionally, the formula for calculating the second correlation between the current time series data set of the metering device and the actual line loss value data set is as follows:

[0035]

[0036] In the formula, R im (S im ,Y m S represents the second correlation between the current time series data set of the metering device and the actual line loss value data set.im This refers to the m-th set of current time series data from the metering device. Y is the mode of the current time series data set. m This represents the actual line loss value of the m-th group of the metering device. The mode of the actual line loss data set of the metering device.

[0037] Optionally, the formula for calculating the third correlation between the time series data set of the metering device's readings and the data set of actual line loss values ​​is as follows:

[0038]

[0039] In the formula, R sm (S sm ,Y m S represents the third correlation between the time series data set of the metering device readings and the data set of actual line loss values. sm This refers to the time series data of the m-th group of metering readings from the metering device. Y is the mean of the time series data set of the measurement readings. m This represents the actual line loss value of the m-th group of the metering device. This is the average of the actual line loss data set of the metering device.

[0040] A second aspect of this application provides a device for detecting electricity theft metering devices, the device comprising:

[0041] The basic data acquisition module is used to acquire basic data of multiple low-voltage distribution areas;

[0042] The transformer area screening module is used to screen transformer areas to be inspected and typical transformer areas from the low-voltage transformer areas according to the basic transformer area data.

[0043] The average power loss rate calculation module is used to calculate the corresponding average power loss rate based on the basic data of the typical transformer area.

[0044] The line loss calculation module is used to calculate the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer substation to be inspected based on the average power loss rate and the basic data of the transformer substation to be inspected.

[0045] The tapping area screening module is used to screen tapping areas whose actual line loss rate is greater than the theoretical line loss rate as tapping areas.

[0046] The time series acquisition module is used to acquire time series data corresponding to each electricity metering device in the theft radio zone;

[0047] The multivariate correlation calculation module is used to calculate the multivariate correlation between the time series data and the actual line loss value;

[0048] The electricity theft metering device screening module is used to screen electricity metering devices whose multivariate correlation is higher than a preset correlation index as electricity theft metering devices.

[0049] A third aspect of this application provides a device for detecting electricity theft metering devices, the device comprising a processor and a memory:

[0050] The memory is used to store program code and transmit the program code to the processor;

[0051] The processor is used to execute any of the methods for locating electricity theft metering devices according to the instructions in the program code.

[0052] As can be seen from the above technical solutions, this application has the following advantages:

[0053] In this application, typical and untapped transformer substations are selected from multiple low-voltage substations using basic substation data. After calculating the actual line loss rate of the untapped substation, the theoretical line loss rate of the untapped substation is calculated using the average power loss rate of the typical substation. By comparing the theoretical and actual line loss rates of the untapped substation, the area where electricity theft occurs is further identified. This solves the technical problem in existing technologies that require data calculations on the electricity metering devices of all users in a large number of substations, resulting in a large range of calculation errors. By calculating the multivariate correlation between the time series data of each electricity metering device in the untapped substation and the actual line loss value of the untapped substation, electricity metering devices with a multivariate correlation higher than the preset correlation index are selected as electricity theft metering devices. The correlation between the electricity metering device and the actual line loss value of the untapped substation is calculated from multiple aspects, avoiding the influence of single-dimensional abnormal data on the correlation calculation results and improving the accuracy of locating electricity theft metering devices. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart illustrating an embodiment of a method for locating electricity theft metering devices according to this application.

[0056] Figure 2 This is a flowchart illustrating another embodiment of a method for locating electricity theft metering devices according to this application.

[0057] Figure 3 This is a schematic diagram illustrating the relationship between the line loss value of a transformer substation and multi-dimensional data in another embodiment of the method for locating electricity theft metering devices according to this application.

[0058] Figure 4 This is a schematic diagram of the device structure of one embodiment of the electricity theft metering device locator of this application. Detailed Implementation

[0059] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] Please see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of a method for locating electricity theft metering devices according to this application.

[0061] The present invention provides a method for locating electricity theft metering devices, comprising:

[0062] Step 101: Obtain basic data of multiple low-voltage distribution areas.

[0063] A low-voltage distribution area refers to an area supplied with electricity at low voltage by a particular transformer. Specifically, low voltage refers to the 380V system. The basic data of the distribution area includes the nameplate information of a particular transformer and statistical data of the distribution area, including transformer capacity, supply voltage, supply frequency, electricity theft event markers in the area supplied by the transformer in the past, the amount of electricity supplied to the area during a certain period, and the electricity sales volume formed by the electricity consumption data returned by the electricity metering devices in the area.

[0064] In this embodiment of the invention, basic data of multiple low-voltage distribution areas are obtained, including transformer capacity, power supply, electricity sales, electricity theft event markers, and transformer operating parameters.

[0065] Step 102: Select the transformer substations to be investigated and typical transformer substations from the low-voltage transformer substations based on the basic data of the transformer substations.

[0066] The area to be investigated refers to a low-voltage area that contains electricity theft incident markers or has abnormal operating parameters. The operating parameters include data such as the voltage, current, and frequency of the transformer. A typical area refers to an area where no electricity theft incident has occurred in the power supply area of ​​the transformer and where the transformer's operating parameters, power grid structure, and other indicators are normal.

[0067] In this embodiment of the invention, after obtaining the basic data of multiple low-voltage distribution areas, the multiple distribution areas are divided into distribution areas to be investigated that contain electricity theft event markers or abnormal transformer operating parameters, and typical distribution areas that do not contain electricity theft event markers and whose transformer operating parameters are normal, according to the basic data of the distribution areas.

[0068] Step 103: Calculate the corresponding average power loss rate based on the basic data of typical transformer substations.

[0069] The average power loss rate refers to the ratio of the sum of line losses in multiple typical distribution areas to the sum of transformer capacities in multiple typical distribution areas.

[0070] In this embodiment of the invention, after selecting typical transformer substations, the average power loss value of the selected typical transformer substations is calculated based on the basic data of the typical transformer substations.

[0071] Step 104: Calculate the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer substation to be inspected based on the average power loss rate and the basic data of the substation to be inspected.

[0072] Actual line loss refers to the difference between the power supply and the electricity sold in a distribution area, reflecting the amount of electrical energy lost in that area. Actual line loss rate refers to the ratio of the actual line loss to the power supply in a distribution area, reflecting the degree of electrical energy loss in that area. Theoretical line loss rate refers to the theoretical degree of electrical energy loss in a distribution area under the conditions that the transformer operating parameters are normal, there are no electricity theft incidents in the area, and the grid structure and other indicators are normal.

[0073] In this embodiment of the invention, after calculating the average power loss rate of a typical transformer substation, the actual line loss value and the actual line loss rate are calculated according to the basic data of the transformer substation to be investigated. The theoretical line loss rate of the transformer substation to be investigated is calculated based on the average power loss rate of the typical transformer substation and the basic data of the transformer substation to be investigated.

[0074] Step 105: Select the areas to be investigated where the actual line loss rate is greater than the theoretical line loss rate as the theft area, and obtain the time series data corresponding to each electricity metering device in the theft area.

[0075] A "stealing electricity area" refers to a low-voltage distribution area where there are suspected electricity theft metering devices. Its actual line loss value and actual line loss rate will exceed those of other normally operating distribution areas. Time series data refers to the electricity consumption data collected by the electricity metering device within a certain period of time and reported to the next higher level electricity metering system.

[0076] In this embodiment of the invention, after calculating the actual line loss rate and the theoretical line loss rate of the area to be inspected, the areas to be inspected with an actual line loss rate greater than the theoretical line loss rate are selected as the theft areas. At the same time, the time series data of each electricity metering device in the theft area are obtained.

[0077] It is worth mentioning that a percentage threshold can be set as a standard for judging radio stations that are being burglarized. For example, if the absolute value of the difference between the theoretical line loss rate and the actual line loss rate of the radio station to be investigated is greater than the ratio of the actual line loss rate (or theoretical line loss rate) to the set percentage threshold, the radio station to be investigated can also be considered as a radio station that is being burglarized.

[0078] Step 106: Calculate the multivariate correlation between time series data and actual line loss values, and select electricity metering devices with multivariate correlation higher than the preset correlation index as electricity theft metering devices.

[0079] Electricity metering devices can acquire multi-dimensional electricity consumption data. However, using only one dimension of electricity consumption data to calculate the correlation between the data and the line loss value of the transformer area to determine whether the electricity metering device is a theft metering device is easily influenced by one-sided data.

[0080] To this end, data from multiple aspects can be collected, the correlation between each aspect of data and the line loss value can be calculated, and finally the multidimensional correlation between the multidimensional data and the line loss value can be calculated to reduce calculation errors.

[0081] In this embodiment of the invention, the multivariate correlation between the time series data of the electricity metering device and the actual line loss value of the transformer area is used as the basis for judging the electricity theft metering device, and the electricity metering device with a multivariate correlation higher than the preset correlation index is selected as the electricity theft metering device.

[0082] It is worth mentioning that the preset correlation index can be adjusted according to the electricity theft phenomenon in the area to be investigated, and there is no limitation here;

[0083] When the multivariate correlation index of an electricity metering device is close to the preset correlation index (e.g., the absolute value of the difference between the preset correlation index and the multivariate correlation index is less than 1%), the electricity metering device can be considered a suspected electricity theft metering device that requires close attention.

[0084] In this embodiment of the invention, typical and untapped transformer substations are selected from multiple low-voltage substations using basic substation data. After calculating the actual line loss rate of the untapped substation, the theoretical line loss rate of the untapped substation is calculated using the average power loss rate of the typical substation. By comparing the theoretical and actual line loss rates of the untapped substation, the electricity theft substation is further identified. This solves the technical problem in the prior art that data calculations are required for all users' electricity metering devices in a large number of substations, resulting in a large range of calculation errors. By calculating the multivariate correlation between the time series data of each electricity metering device in the electricity theft substation and the actual line loss value of the electricity theft substation, electricity metering devices with a multivariate correlation higher than a preset correlation index are selected as electricity theft metering devices. The correlation between the electricity metering device and the actual line loss value of the electricity theft substation is calculated from multiple aspects, avoiding the influence of single-dimensional abnormal data on the correlation calculation results and improving the accuracy of electricity theft metering device location.

[0085] Please see Figure 2 , Figure 2 This is a flowchart illustrating another embodiment of a method for locating electricity theft metering devices according to this application.

[0086] The present invention provides a method for locating electricity theft metering devices, comprising:

[0087] Step 201: Obtain the electricity theft event markers, transformer operating parameters, transformer capacity, electricity sales, and electricity supply for multiple low-voltage distribution areas.

[0088] In this embodiment of the invention, the specific implementation process of step 201 is similar to that of step 101, and will not be repeated here.

[0089] Step 202: Select the areas to be investigated and typical areas from the low-voltage distribution areas according to the electricity theft event markers and transformer operating parameters.

[0090] Optionally, step 202 may include the following sub-steps:

[0091] The low-voltage transformer area corresponding to the electricity theft event is matched as the initial transformer area;

[0092] The remaining low-voltage distribution areas, excluding the initial distribution area, are identified as typical distribution areas;

[0093] Determine if there are any abnormalities in the transformer operating parameters corresponding to each initial distribution area;

[0094] If there are abnormalities in the transformer operating parameters, the corresponding initial transformer area will be designated as the transformer area to be investigated.

[0095] In this embodiment of the invention, after obtaining the electricity theft event marker, the low-voltage distribution area that also contains the electricity theft event marker is selected as the initial distribution area, and the remaining distribution areas other than the electricity theft event marker are selected as typical distribution areas. It is determined whether there are any abnormalities in the transformer operating parameters corresponding to each initial distribution area. The abnormal operating parameters may be abnormalities in voltage operating parameters, current operating parameters, frequency changes, etc. If it is determined that there are abnormalities in the transformer operating parameters of each initial distribution area, the initial distribution area corresponding to the abnormal operating parameters is determined as the distribution area to be investigated.

[0096] Step 203: Calculate the difference between the power supply and the power sales of a typical distribution area as the power loss value of the typical distribution area.

[0097] It is worth mentioning that the calculation process for the power loss value of a typical transformer substation in step 203 is as follows:

[0098] △AT i =G di -S di

[0099] Among them, △A Ti Let Gdi be the power loss value of the i-th typical transformer substation, Gdi be the power supply of the i-th typical transformer substation, and Sdi be the power sales of the i-th typical transformer substation.

[0100] Step 204: Calculate the sum of all power loss values ​​and the sum of all transformer capacities in all typical distribution areas.

[0101] It is worth mentioning that the calculation process for the sum of all power loss values ​​in step 204 is as follows:

[0102]

[0103] Where △A represents the sum of power losses for m typical transformer substations, △A Ti Let m be the power loss value of the i-th typical transformer substation, and m be the number of typical transformer substations.

[0104] The calculation process for the sum of the transformer capacities across all typical distribution areas is as follows:

[0105]

[0106] Among them, S T Let m be the transformer capacities and values ​​for typical distribution areas. Let m be the transformer capacity of the i-th typical distribution area, and m be the number of typical distribution areas.

[0107] Step 205: Calculate the ratio between the sum of power loss values ​​and the sum of capacity values ​​to obtain the average power loss rate of multiple typical transformer substations.

[0108] It is worth mentioning that the calculation process for the ratio between the sum of power loss values ​​and the sum of capacity values ​​in step 205 is as follows:

[0109]

[0110] Among them, L ave Let S be the average power loss rate of m typical transformer substations, ΔA be the sum of power loss values ​​of m typical transformer substations, and S be the sum of power loss values ​​of m typical transformer substations. T Let m be the transformer capacities and values ​​for typical distribution areas.

[0111] Step 206: Calculate the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer area to be inspected, based on the average power loss rate and the transformer capacity, electricity sales, and power supply of the area to be inspected.

[0112] Optionally, step 206 may include the following sub-steps:

[0113] The difference between the power supply and the electricity sales of the transformer substation to be inspected is calculated as the actual line loss value of the transformer substation to be inspected.

[0114] The ratio between the actual line loss value and the power supply of the transformer substation to be inspected is used as the actual line loss rate of the transformer substation to be inspected.

[0115] The product of the average power loss rate of a typical distribution area and the transformer capacity of the distribution area to be investigated is used as the theoretical line loss value of the distribution area to be investigated.

[0116] The theoretical line loss rate of the transformer substation to be inspected is calculated as the ratio between the theoretical line loss value and the power supply of the substation to be inspected.

[0117] In this embodiment of the invention, after calculating the average power loss rate of a typical distribution area, the difference between the power supply and the sales volume of the distribution area to be investigated is used as the actual line loss value of the distribution area to be investigated. The actual line loss rate of the distribution area to be investigated is calculated based on the ratio between the actual line loss value and the power supply. Then, the theoretical line loss value of the distribution area to be investigated is calculated based on the product between the average power loss rate of the typical distribution area and the transformer capacity of the distribution area to be investigated. Similarly, the theoretical line loss rate of the distribution area to be investigated is calculated based on the ratio between the theoretical line loss value and the power supply of the distribution area to be investigated.

[0118] Furthermore, the calculation process for the difference between the power supply and the electricity sales of the area to be investigated in the sub-step is as follows:

[0119] △AT j =G dj -S dj

[0120] Among them, △A Tj Let G be the actual line loss value of the j-th typical transformer area. dj S represents the power supply of the j-th transformer substation to be inspected. dj This represents the electricity sales volume of the j-th distribution area to be checked;

[0121] Furthermore, the calculation process for the ratio between the actual line loss value and the power supply of the area to be inspected in the sub-step is as follows:

[0122]

[0123] Among them, L sj S represents the actual line loss rate of the j-th transformer area to be inspected. dj For the electricity sales volume of the j-th distribution area to be checked, G dj The power supply of the j-th transformer substation to be inspected;

[0124] Furthermore, the calculation process for the product of the average power loss rate of a typical distribution area and the transformer capacity of the distribution area to be investigated in the sub-step is as follows:

[0125]

[0126] Among them, L j S represents the theoretical line loss value for the j-th transformer area to be investigated.j S represents the transformer capacity of the j-th transformer substation to be inspected. Tj Let n be the transformer capacity of the j-th transformer substation to be inspected, and n be the total number of transformer substations to be inspected.

[0127] Furthermore, the calculation process for the ratio between the theoretical line loss value and the power supply of the area to be investigated in the sub-step is as follows:

[0128]

[0129] Among them, L lj Let L be the theoretical line loss rate of the j-th transformer area to be investigated. j Let G be the theoretical line loss value of the j-th transformer area to be investigated. dj Let J represent the power supply of the j-th transformer substation to be inspected.

[0130] It is worth mentioning that since the low-voltage distribution areas that have historically experienced electricity theft or abnormal transformer operating parameters are selected as the distribution areas to be investigated, it is necessary to use the product of the average power loss rate of typical distribution areas and the transformer capacity of the distribution area to be investigated as the theoretical power loss of the line in the distribution area to be investigated (i.e., the theoretical line loss value), and then the theoretical line loss rate of the distribution area to be investigated can be calculated.

[0131] Step 207: Select the stations to be investigated that have an actual line loss rate greater than the theoretical line loss rate as stations to be burglarized.

[0132] It is worth mentioning that a percentage threshold can be set as a standard for judging radio stations that are being burglarized. For example, if the absolute value of the difference between the theoretical line loss rate and the actual line loss rate of the radio station to be investigated is greater than the ratio of the actual line loss rate (or theoretical line loss rate) to the set percentage threshold, the radio station to be investigated can also be considered as a radio station that is being burglarized.

[0133] Step 208: Obtain time series data corresponding to each electricity metering device in the theft area, and calculate the multivariate correlation between the time series data and the actual line loss value.

[0134] Optionally, step 208 may include the following sub-steps:

[0135] Obtain electricity consumption data recorded by each electricity metering device in the area of ​​the stolen electricity at fixed time intervals, and generate time series data groups for one or more time intervals;

[0136] Calculate the first correlation between the voltage time series data set of the metering device and the actual line loss data set;

[0137] The second correlation between the current time series data set of the metering device and the actual line loss data set is calculated.

[0138] The third correlation between the time series data of the metering device readings and the actual line loss data is calculated.

[0139] The multiplication of the first, second, and third correlations is calculated as the multivariate correlation between the time series data and the actual line loss value.

[0140] It should be noted that the formula for calculating the first correlation between the voltage time series data set of the metering device and the actual line loss value data set in the sub-step is as follows:

[0141]

[0142] Among them, R um (S um ,Y m S represents the first correlation between the voltage time series data set of the metering device and the actual line loss data set. um This is the m-th group of voltage time series data from the metering device. Y is the median of the voltage time series data set. m This represents the actual line loss value of the m-th group of the metering device. This is the median of the data set of actual line loss values ​​from the metering device.

[0143] The formula for calculating the second correlation between the current time series data set of the metering device and the actual line loss value data set in the sub-step is as follows:

[0144]

[0145] Among them, R im (S im ,Y m S represents the second correlation between the metering device current time series data set and the actual line loss value data set. im This represents the m-th set of current time series data from the metering device. Y is the mode of the current time series data set. m This represents the actual line loss value of the m-th group of the metering device. The mode of the actual line loss data set of the metering device;

[0146] The formula for calculating the third correlation between the time series data set of metering device readings and the actual line loss data set in the sub-step is as follows:

[0147]

[0148] Among them, R sm (S sm ,Y m S represents the third correlation between the time series data of the metering device readings and the data of actual line loss values. sm This is the time series data of the m-th group of meter readings from the metering device. Y is the mean of the time series data set of measurement readings. m This represents the actual line loss value of the m-th group of the metering device. This is the average of the data set of actual line loss values ​​from the metering device.

[0149] The formula for calculating the multiplication of the first, second, and third correlations in the sub-step as the multivariate correlation between the time series data and the actual line loss value is as follows:

[0150] Rz=RumRimRsm

[0151] Among them, R z R represents the multivariate correlation between the first, second, and third correlations and the actual line loss value. um For the first correlation, R im For the second correlation, R sm This is the third correlation.

[0152] A time series refers to a series of continuous data points sampled and acquired by an electricity metering device. A time series of length N is represented as S = (S1, S2, ..., S...). n ), where each sequence point represents a tuple S. i =(X i ,T i ), X i T is the data value recorded by the electricity metering device. i These are time recording points; a time series data set refers to the electricity consumption data recorded by an electricity metering device at fixed time intervals, generating a time series data set at one or more time intervals. A set of time series data can be used to represent a complete working period of the electricity metering device. In the power grid system, the electricity metering device generally records electricity consumption data every 15 seconds and reports it to the electricity metering automation system. The process of generating a time series data set can be represented as follows: Let e ​​= {E1, E2, ..., E...} m} represents the electricity metering device in the same low-voltage distribution area, where E m (m = 1, 2, ..., m) represents the m-th electricity metering device, and each electricity metering device corresponds to a time series data set. in, This represents the k-th time series data group of the electricity metering device Em.

[0153] In this embodiment of the invention, when it is necessary to calculate the multivariate correlation of all electricity metering devices in a certain electricity theft area, for example, 24-hour electricity consumption data of all electricity metering devices in the electricity theft area are selected, and correlation analysis is performed in 1-hour units to generate 24 sets of time series data. According to the type of electricity consumption data collected by the electricity metering devices, they are divided into voltage time series data group, current time series data group, and meter reading time series data group. The first correlation between the voltage time series data group and the actual line loss value data group, the second correlation between the current time series data group and the actual line loss value data group, and the third correlation between the meter reading time series data group and the actual line loss value data group are calculated. The multivariate correlation between the first correlation, the second correlation, and the third correlation is used as the multivariate correlation between the electricity metering device time series data and the actual line loss value of the corresponding area.

[0154] Furthermore, step 208, calculating the multivariate correlation between the time series data and the actual line loss value, may also include the following sub-steps:

[0155] Based on the pre-compiled tables of suspected coefficients for electricity metering device attributes and electricity consumption, the multiplication values ​​between the suspected coefficients for introduced attributes and electricity consumption and the first, second, and third correlations are calculated as the multivariate correlation between the time series data of the electricity metering device and the actual line loss value of the corresponding transformer area.

[0156] The formulas for calculating the product of the introduced attribute suspicion coefficient and the electricity consumption suspicion coefficient with the first correlation, second correlation, and third correlation are as follows:

[0157] Rz=KsKlRumRimRsm

[0158] Among them, R z To introduce a multivariate correlation between the attribute suspicion coefficient and the electricity consumption suspicion coefficient, and the first, second, and third correlations with the actual line loss value, K s K is the attribute suspicion coefficient. l R is the coefficient for suspicion of electricity consumption. um For the first correlation, R im For the second correlation, R sm This is the third correlation.

[0159] It is worth mentioning that the pre-compiled tables of suspicion coefficients for electricity metering device attributes and electricity consumption can be compiled based on the type of user to which the metering device belongs, the electricity consumption category of the user, and expert experience. The compilation process is existing technology. For example, government agency users are considered more reliable and belong to the high-demand electricity consumption type, therefore their electricity metering device attribute suspicion coefficient K is relatively high. s The coefficient for suspicion of electricity consumption can be set at 0.10, K. lThe value is 0.80; however, the supervision of electricity metering devices for paddy field irrigation users is difficult due to their high electricity demand, which falls under the category of high-volume electricity consumption. Therefore, the suspicion coefficient K for their electricity metering devices is high. s The value can be set at 1.15, with the electricity consumption suspicion coefficient K. l It is 0.50;

[0160] For example, the user attribute suspicion coefficient table is shown in Table 1 below:

[0161]

[0162]

[0163] Table 1

[0164] For example, the electricity consumption suspicion factor table is shown in Table 2 below:

[0165] Electricity consumption type <![CDATA[Electricity consumption suspicion coefficient K l > Large amount of electricity 0.5 High demand for electricity 0.8 Residential electricity 0.95 Ordinary electricity 1

[0166] Table 2

[0167] Step 209: Select electricity metering devices with a multivariate correlation higher than the preset correlation index as electricity theft metering devices.

[0168] In an embodiment of the present invention, after calculating the multivariate correlation between the electricity metering device and the actual line loss value of the electricity theft area, the electricity metering device with a multivariate correlation higher than the preset correlation index is selected as the electricity theft metering device.

[0169] It is worth mentioning that the preset correlation index can be adjusted according to the frequency of electricity theft incidents in the area to be investigated, and there is no limitation here;

[0170] When the multivariate correlation index of an electricity metering device is close to the preset correlation index (e.g., the absolute value of the difference between the preset correlation index and the multivariate correlation index is less than 1%), the electricity metering device can be considered a suspected electricity theft metering device that requires close attention.

[0171] In practice, electricity theft methods can be broadly categorized into two types: those targeting the electricity metering device itself and those targeting the primary system. The former mainly includes undervoltage, undercurrent, phase-shifting, and differential voltage theft. Besides altering the meter wiring, users may replace current transformers or apply strong magnetic interference to the meter for single-phase, two-phase, or three-phase theft. To avoid detection, they typically only steal a portion of the electricity. When the ratio of the three-phase loads is relatively fixed, the amount of electricity stolen using these methods shows a strong positive correlation with the metered electricity consumption. The latter often bypasses the meter by connecting to a concealed location before the meter. In practice, these users generally do not steal all the electricity to avoid detection, but rather connect high-energy-consuming devices or parts of the workshop to the meter. In this case, there is also a positive correlation between the stolen electricity and the metered electricity consumption. In summary, among common electricity theft methods, the amount of electricity stolen by users often shows a positive correlation with the metered electricity consumption.

[0172] Under correct line-transformer-user-meter relationship conditions, changes in low-voltage distribution area line loss are mainly caused by electricity theft. Non-theft electricity consumption has a negligible impact on line loss. There is a positive correlation between the metered electricity consumption of theft users and the distribution area line loss, and an implicit causal relationship exists. Therefore, when the actual electricity consumption of a theft user increases or decreases, the reading on their electricity meter also increases or decreases proportionally, and the amount of stolen electricity changes accordingly. In low-voltage distribution areas with relatively stable loads, the line loss rate will change accordingly.

[0173] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating the relationship between the line loss value of the transformer area and multivariate data in an embodiment of the present invention;

[0174] like Figure 3 The low-voltage distribution area shown has four low-voltage users: User 1, User 2, User 3, and User 4. The graph shows the data curves of electricity meter readings and daily line loss values ​​for the area from day 1 to day 15. From the time corresponding to recording point 1 to the time corresponding to recording point 2, it can be seen that as the electricity meter reading of User 1 increases, their actual electricity consumption increases, and the amount of electricity stolen also increases, causing the line loss value of the area to gradually increase. Other users who did not steal electricity, such as Users 2 and 4, have electricity meter readings consistent with their actual electricity consumption, and their line loss values ​​are within the reasonable range for the area, not causing drastic changes in the line loss value. From the time corresponding to recording point 1 to the time corresponding to recording point 3, although the electricity meter reading of User 3 is relatively low, its trend is consistent with the trend of the line loss value. Therefore, there is a positive correlation between the electricity meter readings of users who steal electricity and the line loss value of the area, expressed as:

[0175]

[0176] In the formula, L is the line loss rate, G is the power supply, S is the power sales, ΔW is the line loss value, ΔW1 is the power loss generated by the transmission line, and ΔW2 is the amount of electricity stolen.

[0177] In low-voltage distribution areas, when a user steals electricity, the current reading on the user's electricity metering device will gradually increase as the user's load increases, while the voltage reading will gradually decrease. At this time, the line loss rate of the low-voltage distribution area will also increase. The power consumption, current, and voltage readings in the user's metering device are easy to collect, and analyzing the changes in these three values ​​can serve as key data for analyzing users who steal electricity.

[0178] Those skilled in the art should understand that, in the embodiments of the present invention, the counting units of the variables in the description of the calculation steps and the calculation formula can be adjusted according to actual needs, and preferably the counting units of all variables are uniform;

[0179] For example, in an embodiment of the present invention, the formula for calculating the power loss value of a typical transformer area is as follows:

[0180]

[0181] Among them, △A Ti Let G be the power loss value of the i-th typical transformer area, in MWh. di The power supply of the i-th typical transformer substation is expressed in MWh and S. di The electricity sales volume of the i-th typical distribution area is expressed in MWh.

[0182] In this embodiment of the invention, typical and untraceable transformer substations are selected from multiple low-voltage substations using electricity theft event markers and transformer operating parameters. After calculating the actual line loss rate of the untraceable substation, the theoretical line loss rate of the untraceable substation is calculated using the average power loss rate of the typical substation. By comparing the theoretical and actual line loss rates of the untraceable substation, the electricity theft substation is further identified. This solves the technical problem in the prior art that data calculations are required for all users' electricity metering devices in a large number of substations, resulting in a large range of calculation errors. By calculating the multidimensional correlation between the voltage time series data, current time series data, and metering reading time series data of each electricity metering device in the electricity theft substation and the actual line loss value data of the electricity theft substation, electricity metering devices with multidimensional correlation higher than the preset correlation index are selected as electricity theft metering devices. The correlation between the electricity metering device and the actual line loss value of the electricity theft substation is calculated from multidimensional data, avoiding the influence of abnormal data in one dimension on the correlation calculation results and improving the accuracy of electricity theft metering device location.

[0183] Please see Figure 4 , Figure 4 This is a schematic diagram of the device structure of one embodiment of the electricity theft metering device locator of this application.

[0184] This invention provides a device for locating electricity theft metering devices, comprising:

[0185] The basic data acquisition module 401 is used to acquire basic data of multiple low-voltage distribution areas;

[0186] The transformer area screening module 402 is used to screen the transformer areas to be checked and typical transformer areas from the low-voltage transformer areas according to the basic data of the transformer areas;

[0187] The average power loss rate calculation module 403 is used to calculate the corresponding average power loss rate based on the basic data of a typical transformer substation.

[0188] The line loss calculation module 404 is used to calculate the actual line loss value, actual line loss rate and theoretical line loss rate of the transformer substation to be investigated based on the average power loss rate and the basic data of the transformer substation to be investigated.

[0189] The radio station theft screening module 405 is used to screen radio stations whose actual line loss rate is greater than the theoretical line loss rate as radio stations to be investigated.

[0190] The time series acquisition module 406 is used to acquire the time series data corresponding to each electricity metering device in the electricity theft area;

[0191] The multivariate correlation calculation module 407 is used to calculate the multivariate correlation between time series data and actual line loss values;

[0192] The electricity theft metering device screening module 408 is used to screen electricity metering devices whose multivariate correlation is higher than the preset correlation index as electricity theft metering devices.

[0193] Optionally, the basic data acquisition module 401 is specifically used for:

[0194] It can acquire electricity theft event markers, transformer operating parameters, transformer capacity, electricity sales, and electricity supply from multiple low-voltage distribution areas.

[0195] Optionally, the transformer area filtering module 402 is specifically used for:

[0196] The low-voltage transformer area corresponding to the electricity theft event is matched as the initial transformer area;

[0197] The remaining low-voltage distribution areas, excluding the initial distribution area, are identified as typical distribution areas;

[0198] Determine if there are any abnormalities in the transformer operating parameters corresponding to each initial distribution area;

[0199] If there are abnormalities in the transformer operating parameters, the corresponding initial transformer area will be designated as the transformer area to be investigated.

[0200] Optionally, the average power loss rate calculation module 403 is specifically used for:

[0201] The difference between the power supply and the power sales of a typical distribution area is calculated as the power loss value of the typical distribution area.

[0202] Calculate the sum of all power loss values ​​and the sum of all transformer capacities in all typical distribution areas.

[0203] The average power loss rate of several typical transformer substations is obtained by calculating the ratio between the power loss value and the capacity value.

[0204] Optionally, the line loss calculation module 404 is specifically used for:

[0205] The difference between the power supply and the electricity sales of the transformer substation to be inspected is calculated as the actual line loss value of the transformer substation to be inspected.

[0206] The ratio between the actual line loss value and the power supply of the transformer substation to be inspected is used as the actual line loss rate of the transformer substation to be inspected.

[0207] The product of the average power loss rate of a typical distribution area and the transformer capacity of the distribution area to be investigated is used as the theoretical line loss value of the distribution area to be investigated.

[0208] The theoretical line loss rate of the transformer substation to be inspected is calculated as the ratio between the theoretical line loss value and the power supply of the substation to be inspected.

[0209] Optionally, the time series acquisition module 406 is specifically used for:

[0210] Obtain electricity consumption data recorded by each electricity metering device in the area where the electricity is stolen at fixed time intervals, and generate time series data sets for one or more time intervals.

[0211] Optionally, the multivariate correlation calculation module 407 is specifically used for:

[0212] Calculate the first correlation between the voltage time series data set of the metering device and the actual line loss data set;

[0213] The second correlation between the current time series data set of the metering device and the actual line loss data set is calculated.

[0214] The third correlation between the time series data of the metering device readings and the actual line loss data is calculated.

[0215] The multiplication of the first, second, and third correlations is calculated as the multivariate correlation between the time series data and the actual line loss value.

[0216] This invention provides a device for locating electricity theft metering devices, including a processor and a memory.

[0217] The memory is used to store program code and transmit the program code to the processor;

[0218] The processor is used to execute the electricity theft metering device locating method according to any embodiment of the present invention based on the instructions in the program code.

[0219] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described device and module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0220] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or modules may be electrical, mechanical, or other forms.

[0221] The modules described as separate components may or may not be physically separate. The components used for module computation may or may not be physical units; that is, they may be located in one place or distributed across multiple network modules. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0222] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0223] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for locating electricity theft metering devices, characterized in that, include: Obtain basic data of multiple low-voltage distribution areas; Based on the basic data of the low-voltage distribution area, select the distribution area to be investigated and typical distribution areas from the low-voltage distribution area; Calculate the corresponding average power loss rate based on the basic data of the typical transformer area. Based on the average power loss rate and the basic data of the transformer area to be inspected, calculate the actual line loss value, actual line loss rate and theoretical line loss rate of the transformer area to be inspected. Select the electricity metering areas to be investigated where the actual line loss rate is greater than the theoretical line loss rate as the electricity theft areas, and obtain the time series data corresponding to each electricity metering device in the electricity theft areas; Calculate the multivariate correlation between the time series data and the actual line loss value, and screen the electricity metering devices whose multivariate correlation is higher than the preset correlation index as electricity theft metering devices. The step of acquiring time-series data corresponding to each electricity metering device in the stolen electricity zone and calculating the multivariate correlation between the time-series data and the actual line loss value includes: Obtain electricity consumption data recorded by each electricity metering device in the theft radio zone at fixed time intervals, and generate one or more time series data groups under the time intervals; Calculate the first correlation between the voltage time series data set of the metering device and the actual line loss value data set; Calculate the second correlation between the current time series data set of the metering device and the actual line loss value data set; Calculate the third correlation between the time series data set of the metering device readings and the data set of actual line loss values; The multiplication of the first correlation, the second correlation, and the third correlation is calculated as the multivariate correlation between the time series data and the actual line loss value.

2. The method for locating electricity theft metering devices according to claim 1, characterized in that, The basic data for the distribution area includes electricity theft event markers and transformer operating parameters; the step of screening the distribution areas to be investigated and typical distribution areas from the low-voltage distribution areas according to the basic data includes: The low-voltage distribution area corresponding to the electricity theft event marker is used as the initial distribution area; The remaining low-voltage distribution areas, excluding the initial distribution area, are identified as typical distribution areas; Determine whether there are any abnormalities in the transformer operating parameters corresponding to each initial distribution area; If the transformer operating parameters are abnormal, the corresponding initial transformer area will be designated as the transformer area to be investigated.

3. The method for locating electricity theft metering devices according to claim 1, characterized in that, The basic data of the distribution area includes transformer capacity, electricity sales, and electricity supply. The step of calculating the corresponding average power loss rate based on the basic data of the typical distribution area includes: The difference between the power supply and the power sales of the typical distribution area are calculated as the power loss value of the typical distribution area. Calculate the sum of all the energy loss values ​​and the sum of the transformer capacities of all the typical distribution areas; The average power loss rate of multiple typical transformer substations is obtained by calculating the ratio between the power loss value and the capacity value.

4. The method for locating electricity theft metering devices according to claim 3, characterized in that, The step of calculating the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer substation to be inspected based on the average power loss rate and the basic data of the substation to be inspected includes: The difference between the power supply of the area to be inspected and the electricity sales of the area to be inspected is calculated as the actual line loss value of the area to be inspected. The ratio between the actual line loss value and the power supply of the transformer substation to be inspected is calculated as the actual line loss rate of the transformer substation to be inspected. The product of the average power loss rate of the typical distribution area and the transformer capacity of the distribution area to be investigated is used as the theoretical line loss value of the distribution area to be investigated. The theoretical line loss value is calculated as the ratio between the theoretical line loss value and the power supply of the transformer area to be inspected, which is then used as the theoretical line loss rate of the transformer area to be inspected.

5. The method for locating electricity theft metering devices according to claim 1, characterized in that, The formula for calculating the first correlation between the voltage time series data set of the metering device and the actual line loss value data set is as follows: In the formula, The first correlation is between the voltage time series data set of the metering device and the actual line loss value data set. This refers to the m-th group of voltage time series data from the metering device. The median of the voltage time series data set. This represents the actual line loss value of the m-th group of the metering device. This is the median of the actual line loss data set of the metering device.

6. The method for locating electricity theft metering devices according to claim 1, characterized in that, The formula for calculating the second correlation between the current time series data set of the metering device and the actual line loss value data set is as follows: In the formula, This represents the second correlation between the current time series data set of the metering device and the actual line loss value data set. This refers to the m-th set of current time series data from the metering device. The mode of the current time series data set. This represents the actual line loss value of the m-th group of the metering device. The mode of the actual line loss data set of the metering device.

7. The method for locating electricity theft metering devices according to claim 1, characterized in that, The formula for calculating the third correlation between the time series data set of the metering device readings and the data set of actual line loss values ​​is as follows: In the formula, The third correlation is between the time series data of the metering device readings and the data of the actual line loss values. This refers to the time series data of the m-th group of metering readings from the metering device. The mean of the time series data set of the measurement readings. This represents the actual line loss value of the m-th group of the metering device. This is the average of the actual line loss data set of the metering device.

8. A device for locating electricity theft metering devices, characterized in that, The searching device includes: The basic data acquisition module is used to acquire basic data of multiple low-voltage distribution areas; The transformer area screening module is used to screen transformer areas to be inspected and typical transformer areas from the low-voltage transformer areas according to the basic transformer area data. The average power loss rate calculation module is used to calculate the corresponding average power loss rate based on the basic data of the typical transformer area. The line loss calculation module is used to calculate the actual line loss value, actual line loss rate, and theoretical line loss rate of the transformer substation to be inspected based on the average power loss rate and the basic data of the transformer substation to be inspected. The tapping area screening module is used to screen tapping areas whose actual line loss rate is greater than the theoretical line loss rate as tapping areas. The time series acquisition module is used to acquire time series data corresponding to each electricity metering device in the theft radio zone; The multivariate correlation calculation module is used to calculate the multivariate correlation between the time series data and the actual line loss value; The electricity theft metering device screening module is used to screen electricity metering devices whose multivariate correlation is higher than a preset correlation index as electricity theft metering devices. The time series acquisition module is specifically used to: acquire electricity consumption data recorded by each electricity metering device in the theft radio zone at fixed time intervals, and generate one or more time series data groups under the time intervals; The multivariate correlation calculation module is specifically used for: Calculate the first correlation between the voltage time series data set of the metering device and the actual line loss value data set; Calculate the second correlation between the current time series data set of the metering device and the actual line loss value data set; Calculate the third correlation between the time series data set of the metering device readings and the data set of actual line loss values; The multiplication of the first correlation, the second correlation, and the third correlation is calculated as the multivariate correlation between the time series data and the actual line loss value.

9. A device for locating electricity theft metering devices, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the electricity theft metering device locating method according to any one of claims 1-7 according to the instructions in the program code.

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