Method, device, equipment and storage medium for confirming abnormal electricity users in a substation area

Abstract

The present invention discloses a method, device, equipment and storage medium for confirming users with abnormal electricity consumption in a substation. The method for confirming users with abnormal electricity consumption in a substation includes: obtaining user power data and substation power data of each user in a distribution network substation; calculating the substation line loss of the distribution network substation based on the user power data and the substation power data; grouping users based on the correlation between the user power data and the substation line loss to obtain positive correlation groups, negative correlation groups, low power consumption groups and other user groups; determining the groups with abnormal electricity consumption in the positive correlation groups, negative correlation groups, low power consumption groups and other user groups as power theft groups based on the correlation coefficients between the positive correlation groups and the negative correlation groups and the substation line loss respectively. Based on the correlation coefficient between the groups and the substation line loss, the abnormal user groups are determined as power theft groups, and key investigations are carried out, which effectively reduces the workload of investigating power theft users in the substation and improves the efficiency of investigating power theft users.

Description

Technical Field

[0001] The present invention relates to the technical field of abnormal power consumption confirmation in a distribution network, and particularly to a method, device, equipment and storage medium for confirming abnormal power consumption users in a transformer substation area. Background Art

[0002] Electricity theft refers to the act of illegally occupying electric energy, with the purpose of not paying or paying less electricity bills, and using illegal means to not measure or measure less electricity consumption. The act of electricity theft will affect the normal operation of the power grid, cause a certain degree of damage to the power supply equipment, resulting in the inability of the power supply equipment to work normally, and the power supply equipment is overloaded due to modification, which is likely to cause large-scale power outages in the area under the jurisdiction of the transformer substation.

[0003] When the line loss in the distribution network transformer substation area is in an abnormally high loss state, it means that there may be a metering failure or electricity theft. Since the metering automation system only collects the electricity meter data of low-voltage users in the transformer substation area and partial user voltage and current data, it is difficult to find suspected users from data analysis. Existing anti-electricity theft equipment can only detect abnormal users with specific characteristics, and there are monitoring blind spots. At this time, it is necessary for maintenance and inspection personnel to conduct inspections on all lines and electricity metering devices of the power supply enterprise in the transformer substation area to finally determine the electricity theft users or electricity theft points, which requires a large amount of human resources, and for users who steal electricity only part of the time. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for confirming abnormal power consumption users in a transformer substation area to solve the problem that it is difficult to determine abnormal power consumption users in the distribution network transformer substation area.

[0005] According to one aspect of the present invention, a method for confirming abnormal power consumption users in a transformer substation area is provided, including:

[0006] Obtain the user electricity consumption data and transformer substation area electricity consumption data of each user in the distribution network transformer substation area;

[0007] Calculate the line loss of the distribution network transformer substation area based on the user electricity consumption data and the transformer substation area electricity consumption data;

[0008] Group the users based on the correlation between the user electricity consumption data and the line loss of the transformer substation area to obtain a positive correlation group, a negative correlation group, a low electricity consumption group and the remaining user group;

[0009] Based on the correlation coefficients of the positive correlation group and the negative correlation group with the line loss of the transformer substation area respectively, determine that the group with abnormal power consumption in the positive correlation group, the negative correlation group, the low electricity consumption group and the remaining user group is the electricity theft group.

[0010] Optionally, calculating the line loss of the distribution network substation based on the user power consumption data and the substation power consumption data includes:

[0011] Calculating the sum of the user power consumption data to obtain the total user power consumption data;

[0012] Calculating the line loss of the distribution network substation based on the substation power consumption data and the total user power consumption data.

[0013] Optionally, grouping the users based on the correlation between the user power consumption data and the substation line loss to obtain a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user group includes:

[0014] Calculating the combination of the user power consumption data that is most positively correlated with the substation line loss as the optimal positive correlation data;

[0015] Taking the users corresponding to the optimal positive correlation data as the positive correlation group;

[0016] Calculating the combination of the user power consumption data that is most negatively correlated with the substation line loss as the optimal negative correlation data;

[0017] Taking the users corresponding to the optimal negative correlation data as the negative correlation group;

[0018] Determining the user power consumption data corresponding to the users other than the positive correlation group and the negative correlation group as the first remaining power consumption data;

[0019] Calculating the combination of the user power consumption data in the first remaining power consumption data that is less than the preset power consumption threshold as the low power consumption data combination;

[0020] Taking the users other than the positive correlation group, the negative correlation group, and the low power consumption group as the remaining user group.

[0021] Optionally, calculating the combination of the user power consumption data that is most positively correlated with the substation line loss as the optimal positive correlation data includes:

[0022] Creating a first temporary group;

[0023] Sequentially transferring the user power consumption data outside the first temporary group into the first temporary group, and calculating the positive correlation between the user power consumption data in the first temporary group after transfer and the substation line loss;

[0024] If the positive correlation increases after transferring the user power consumption data, retaining the user power consumption data in the first temporary group;

[0025] Combine the user power consumption data that will ultimately be retained in the first temporary group as the positively correlated optimal data.

[0026] Optionally, in the step of combining the user power consumption data that will ultimately be retained in the first temporary group as the positively correlated optimal data, it further includes:

[0027] Successively transfer the user power consumption data in the first temporary group out of the first temporary group, and calculate the positive correlation between the user power consumption data in the first temporary group after transfer and the line loss of the substation area;

[0028] If the positive correlation increases after transferring the user power consumption data, transfer the user power consumption data out of the first temporary group.

[0029] Optionally, calculating the combination of user power consumption data that is negatively correlated optimally with the line loss of the substation area as the negatively correlated optimal data includes:

[0030] Create a second temporary group;

[0031] Successively transfer the user power consumption data outside the second temporary group into the second temporary group, and calculate the negative correlation between the user power consumption data in the second temporary group after transfer and the line loss of the substation area;

[0032] If the negative correlation increases after transferring the user power consumption data, retain the user power consumption data in the second temporary group;

[0033] Combine the user power consumption data that will ultimately be retained in the second temporary group as the negatively correlated optimal data.

[0034] Optionally, before the step of combining the user power consumption data that will ultimately be retained in the second temporary group as the negatively correlated optimal data, it further includes:

[0035] Successively transfer the user power consumption data in the second temporary group out of the second temporary group, and calculate the negative correlation between the user power consumption data in the second temporary group after transfer and the line loss of the substation area;

[0036] If the negative correlation increases after transferring the user power consumption data, transfer the user power consumption data out of the second temporary group.

[0037] According to another aspect of the present invention, there is provided a device for confirming abnormal power consumption users in a substation area, including:

[0038] An acquisition module for acquiring user power consumption data and substation area power consumption data of each user in the distribution network substation area;

[0039] A line loss calculation module for calculating the line loss of a distribution network substation based on the user power consumption data and the substation power consumption data of the substation.

[0040] A grouping module for grouping the users based on the correlation between the user power consumption data and the line loss of the substation, obtaining a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user group.

[0041] A determination module for determining, based on the correlation coefficients between the positive correlation group and the negative correlation group and the line loss of the substation respectively, that the group with abnormal power consumption among the positive correlation group, the negative correlation group, the low power consumption group, and the remaining user group is the electricity theft group.

[0042] According to another aspect of the present invention, there is provided a device for confirming abnormal power consumption users in a substation, the device including:

[0043] At least one processor; and

[0044] A memory communicatively connected to the at least one processor; wherein,

[0045] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for confirming abnormal power consumption users in a substation according to any embodiment of the present invention.

[0046] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the method for confirming abnormal power consumption users in a substation according to any embodiment of the present invention when executed.

[0047] The technical solution of the embodiment of the present invention calculates the line loss of the substation through the user power consumption data and the substation power consumption data of each user in the distribution network substation, and realizes grouping users into a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user group by calculating the correlation between the user power consumption data and the line loss of the substation. Finally, based on the correlation coefficient between the group and the line loss of the substation, the group with abnormal users is determined as the electricity theft group for key investigation, effectively reducing the workload of investigating electricity theft users in the substation and improving the investigation efficiency of electricity theft users.

[0048] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0050] Figure 1 is a flowchart of a method for confirming abnormal power consumption users in a power distribution area according to Embodiment 1 of the present invention;

[0051] Figure 2 is a schematic structural diagram of a device for confirming abnormal power consumption users in a power distribution area according to Embodiment 2 of the present invention;

[0052] Figure 3 is a schematic structural diagram of a device for confirming abnormal power consumption users in a power distribution area according to Embodiment 3 of the present invention. Detailed Embodiments

[0053] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0054] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0055] Embodiment 1

[0056] Figure 1FIG. 0 is a flowchart of a method for confirming abnormal power consumption users in the first embodiment of the present invention. This embodiment is applicable to the situation of judging and determining abnormal line losses in the distribution network area. This method can be executed by a device for confirming abnormal power consumption users in the area. The device for confirming abnormal power consumption users in the area can be implemented in the form of hardware and / or software, and can be configured in software and / or hardware, and can be configured in a computer device, such as a server, a workstation, a personal computer, etc. As Figure 1 shown, the method includes:

[0057] S110. Obtain the user power consumption data and the area power consumption data of each user in the distribution network area.

[0058] The distribution network refers to the power network that receives electric energy from the transmission network or regional power plants and distributes it locally through distribution facilities or step by step according to voltage levels to various users. It is composed of overhead lines, cables, poles, distribution transformers, disconnect switches, reactive power compensators and some auxiliary facilities, etc., and plays an important role in distributing electric energy in the power network. And the area usually refers to the power supply range or area of (one) transformer. There are a certain number of power users in this area or range. In the area, metering equipment is usually set to count the power supply, and a watt-hour meter device is set for each user to record the power consumption data of the user. Finally, based on the power supply and the power consumption data of the user, the power supply situation and line losses in the area can be calculated.

[0059] In a specific implementation, the user power consumption data and the area power consumption data can be obtained from the metering equipment in the area and the watt-hour metering equipment set for the corresponding users, or the corresponding user power consumption data and area power consumption data can be exported from the metering automation system on the power grid service platform. In the embodiments of the present invention, the specific acquisition method is not limited, as long as the user power consumption data and the area power consumption data that meet the requirements of the application solution can be obtained.

[0060] S120. Calculate the area line loss of the distribution network area based on the user power consumption data and the area power consumption data.

[0061] The area line loss generally refers to the power loss in the area, including the energy loss caused by the transmission of electric energy through transmission lines, the accuracy of metering equipment, power theft, etc. In the embodiments of the present invention, the calculation of the area line loss is mainly by subtracting the total power consumption of the metered users from the power supply in the area.

[0062] Exemplarily, it may include the following steps:

[0063] S121. Calculate the total of the user power consumption data to obtain the total user power consumption data. In the embodiments of the present invention, the obtained user power consumption data is the total power consumption of users measured by the power metering devices installed at each user in the distribution network substation area within a unit time period. What needs to be done in this step is to count the total power consumption of all users within a unit time to obtain the power curve of time and power consumption.

[0064] S122. Calculate the substation area line loss of the distribution network substation area based on the substation area power data and the total user power consumption data. What needs to be done in this step is to calculate the line loss within a unit time in the substation area based on the line loss calculation principle, and then obtain the line loss curve of the substation area and time.

[0065] S130. Group users based on the correlation between the user power consumption data and the substation area line loss to obtain a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user groups.

[0066] In a specific implementation, the positive and negative correlations between the power consumption of users in the substation area and the substation area line loss can be calculated, and then the users with correlation coefficients within a certain threshold range can be classified into the positive correlation group and the negative correlation group. Finally, the remaining users can be classified into the low power consumption group and the remaining user groups based on the magnitude of the power consumption.

[0067] In one embodiment, S130 may include:

[0068] S131. Calculate the optimal combination of user power consumption data that is positively correlated with the substation area line loss as the optimal positive correlation data.

[0069] S132. Use the users corresponding to the optimal positive correlation data as the positive correlation group.

[0070] In the embodiments of the present invention, there are several users in the substation area, and only the power consumption of some users may be subject to power theft, while the power consumption of other users is normal. For users who may be subject to power theft, the correlation between their power consumption data and the line loss of the substation area is the largest. What needs to be done in this step is to group the users in the substation area, calculate the positive correlation between the overall user power consumption data of the group and the line loss of the substation area, and determine one or more combinations of users with the highest positive correlation as the positive correlation group. The combination of the user power consumption data corresponding to this group of users is the optimal positive correlation data.

[0071] In a specific implementation, there are many ways to determine the optimal combination of user power consumption data that is positively correlated with the substation area line loss. Exemplarily, it may include:

[0072] S1321. Create a first temporary group. By creating a first temporary group, it is used to temporarily store the user power consumption data during the calculation process.

[0073] Optionally, the user power consumption data of a user can be added to the first temporary group as a preset first temporary group.

[0074] S1322. Sequentially transfer the user power consumption data outside the first temporary group into the first temporary group, and calculate the positive correlation between the user power consumption data in the first temporary group after the transfer and the substation area line loss. If the positive correlation increases after transferring the user power consumption data, retain the user power consumption data in the first temporary group.

[0075] In a specific implementation, by sequentially transferring the user power consumption data outside the first temporary group into the first temporary group and calculating the positive correlation between the sum of the user power consumption data in the group and the substation area line loss, the traversal calculation of the users in the substation area and the substation area line loss can be realized.

[0076] S1323. Combine the user power consumption data finally retained in the first temporary group as the optimal positive correlation data.

[0077] In an optional embodiment, before S1324, it further includes:

[0078] S1324. Sequentially transfer the user power consumption data in the first temporary group out of the first temporary group, and calculate the positive correlation between the user power consumption data in the first temporary group after the transfer and the substation area line loss. If the positive correlation increases after transferring the user power consumption data, transfer the user power consumption data out of the first temporary group.

[0079] By transferring the user data again and calculating the positive correlation between the remaining data after the transfer and the substation area line loss again, the reliability of the filtered user power consumption data can be further ensured.

[0080] S133. Calculate the combination of user power consumption data with the optimal negative correlation with the substation area line loss as the optimal negative correlation data.

[0081] S134. Use the users corresponding to the optimal negative correlation data as the negative correlation group.

[0082] The grouping method for the negative correlation group can be the same as that for the positive correlation group, or other methods can be adopted, as long as the combination of the user power consumption data of the negative correlation group has the optimal negative correlation with the substation area line loss.

[0083] Exemplarily, it may include:

[0084] S1341. Create a second temporary group;

[0085] S1342. Sequentially transfer the user power consumption data outside the second temporary group into the second temporary group, and calculate the negative correlation between the user power consumption data in the second temporary group after the transfer and the line loss of the transformer substation area. If the negative correlation increases after the transfer of the user power consumption data, retain the user power consumption data in the second temporary group.

[0086] S1343. Sequentially transfer the user power consumption data in the second temporary group out of the second temporary group, and calculate the positive correlation between the user power consumption data in the second temporary group after the transfer and the line loss of the transformer substation area. If the positive correlation increases after the transfer of the user power consumption data, transfer the user power consumption data out of the second temporary group.

[0087] S1344. Combine the user power consumption data finally retained in the second temporary group as the optimal negatively correlated data.

[0088] S135. Determine the user power consumption data corresponding to the users except those in the positive correlation group and the negative correlation group as the first remaining power consumption data.

[0089] S136. Calculate the combination of user power consumption data in the first remaining power consumption data that is less than the preset power consumption threshold as the low power consumption data combination.

[0090] In the embodiment of the present invention, the low power consumption data is determined by means of threshold comparison.

[0091] S137. Take the users except those in the positive correlation group, the negative correlation group and the low power consumption group as the remaining user groups.

[0092] S140. Based on the correlation coefficients between the positive correlation group and the negative correlation group and the line loss of the transformer substation area respectively, determine that the group with abnormal electricity consumption among the positive correlation group, the negative correlation group, the low power consumption group and the remaining user groups is the electricity theft group.

[0093] For the positive correlation group, the negative correlation group, the low power consumption group and the remaining user groups, among which the positive correlation group, the negative correlation group and the low power consumption group are the objects that need to be focused on, that is to say, the users with abnormal metering are probably distributed in these groups. Further, it can be judged by setting a threshold. When the correlation coefficients of the positive correlation group and the negative correlation group are greater than the preset threshold, it is determined as the abnormal electricity consumption user group. When the correlation coefficients of the positive correlation group and the negative correlation group are both less than the preset threshold, it is considered that the low power consumption group belongs to the abnormal electricity consumption user group. Finally, perform abnormal sorting on the positive correlation group, the negative correlation group, the low power consumption group and the remaining user groups, and check in the order of sorting during the investigation, which effectively reduces the workload and difficulty of the investigation, and only needs to check the electricity users corresponding to the groups targeted.

[0094] In an embodiment of the present invention, the line loss of the distribution network substation area is calculated through the user power consumption data of each user in the substation area and the substation area power consumption data, and by calculating the correlation between the user power consumption data and the substation area line loss, users are classified into a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user groups. Finally, based on the correlation coefficient between the group and the substation area line loss, the group with abnormal users is determined as the power theft group for key investigation, effectively reducing the workload of investigating power theft users in the substation area and improving the investigation efficiency of power theft users.

[0095] In an optional embodiment, for the power theft group determined in S140, the discreteness between user power consumption data can also be calculated to determine the key users within the group, so as to further improve the efficiency during the investigation operation.

[0096] Embodiment 2

[0097] Figure 2 It is a schematic structural diagram of a device for confirming abnormal power consumption users in a substation area provided in Embodiment 2 of the present invention. As Figure 2 shown, the device includes an acquisition module 21, a line loss calculation module 22, a grouping module 23, and a determination module 24, where:

[0098] The acquisition module 21 is configured to acquire the user power consumption data of each user in the distribution network substation area and the substation area power consumption data;

[0099] The line loss calculation module 22 is configured to calculate the line loss of the distribution network substation area based on the user power consumption data and the substation area power consumption data;

[0100] The grouping module 23 is configured to group users based on the correlation between the user power consumption data and the substation area line loss, and obtain a positive correlation group, a negative correlation group, a low power consumption group, and the remaining user groups;

[0101] The determination module 24 is configured to determine that the groups with abnormal power consumption among the positive correlation group, the negative correlation group, the low power consumption group, and the remaining user groups are power theft groups based on the correlation coefficients between the positive correlation group and the negative correlation group and the substation area line loss respectively.

[0102] Optionally, the line loss calculation module 22 includes:

[0103] The total calculation unit is configured to calculate the total of the user power consumption data to obtain the total user power consumption data;

[0104] The line loss calculation unit is configured to calculate the line loss of the distribution network substation area based on the substation area power consumption data and the total user power consumption data.

[0105] The grouping module 23 includes:

[0106] A positive correlation optimal calculation unit for performing calculations on the user power consumption data combinations that are most positively correlated with the line loss in the substation area as the positive correlation optimal data;

[0107] A positive correlation grouping unit for grouping the users corresponding to the positive correlation optimal data as the positive correlation grouping;

[0108] A negative correlation optimal calculation unit for performing calculations on the user power consumption data combinations that are most negatively correlated with the line loss in the substation area as the negative correlation optimal data;

[0109] A negative correlation grouping unit for grouping the users corresponding to the negative correlation optimal data as the negative correlation grouping;

[0110] A remaining determination unit for determining the user power consumption data corresponding to the users other than the positive correlation grouping and the negative correlation grouping as the first remaining power consumption data;

[0111] A low power consumption grouping unit for calculating the user power consumption data combinations in the first remaining power consumption data that are less than a preset power consumption threshold as the low power consumption data combinations;

[0112] An other users grouping unit for grouping the users other than the positive correlation grouping, the negative correlation grouping, and the low power consumption grouping as the other users grouping.

[0113] Optionally, the positive correlation optimal calculation unit may include:

[0114] A first temporary grouping subunit for creating a first temporary grouping;

[0115] A first positive correlation calculation subunit for sequentially transferring the user power consumption data outside the first temporary grouping into the first temporary grouping and calculating the positive correlation between the user power consumption data in the first temporary grouping after the transfer and the line loss in the substation area;

[0116] A first transfer-in subunit for retaining the user power consumption data in the first temporary grouping if the positive correlation increases after the transfer of the user power consumption data;

[0117] A positive correlation confirmation subunit for taking the user power consumption data combination finally retained in the first temporary grouping as the positive correlation optimal data.

[0118] It further includes:

[0119] A second positive correlation calculation subunit for sequentially transferring the user power consumption data in the first temporary grouping out of the first temporary grouping and calculating the positive correlation between the user power consumption data in the first temporary grouping after the transfer and the line loss in the substation area;

[0120] A first transfer-out subunit for transferring the user power consumption data out of the first temporary grouping if the positive correlation increases after the transfer of the user power consumption data.

[0121] The negatively correlated grouping unit may include:

[0122] A second temporary grouping subunit, configured to create a second temporary grouping;

[0123] A first negative correlation calculation subunit, configured to sequentially transfer the user power consumption data outside the second temporary grouping into the second temporary grouping, and calculate the negative correlation between the user power consumption data in the second temporary grouping after the transfer and the line loss of the transformer substation area;

[0124] A second transfer-in subunit, configured to, if the negative correlation increases after transferring in the user power consumption data, retain the user power consumption data in the second temporary grouping;

[0125] A negative correlation confirmation subunit, configured to combine the user power consumption data finally retained in the second temporary grouping as the optimal negatively correlated data.

[0126] It further includes:

[0127] A second negative correlation calculation subunit, configured to sequentially transfer the user power consumption data in the second temporary grouping out of the second temporary grouping, and calculate the negative correlation between the user power consumption data in the second temporary grouping after the transfer and the line loss of the transformer substation area;

[0128] A second transfer-out subunit, configured to, if the negative correlation increases after transferring out the user power consumption data, transfer the user power consumption data out of the second temporary grouping.

[0129] The transformer substation area abnormal power consumption user confirmation device provided by the embodiment of the present invention can execute the transformer substation area abnormal power consumption user confirmation method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0130] Embodiment III

[0131] Figure 3 FIG. shows a schematic structural diagram of a transformer substation area abnormal power consumption user confirmation device 10 that can be used to implement the embodiments of the present invention. The transformer substation area abnormal power consumption user confirmation device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The transformer substation area abnormal power consumption user confirmation device can also represent various forms of mobile devices, such as, personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0132] As Figure 3As shown, the device 10 for confirming abnormal electricity - using users in a power distribution area includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as a read - only memory (ROM) 12, a random - access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read - only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random - access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 for confirming abnormal electricity - using users in a power distribution area can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0133] Multiple components in the device 10 for confirming abnormal electricity - using users in a power distribution area are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the device 10 for confirming abnormal electricity - using users in a power distribution area to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0134] The processor 11 can be various general - purpose and / or special - purpose processing components with processing and computing capabilities. Some examples of the processor 11 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial - intelligence (AI) computing chips, various processors running machine - learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for confirming abnormal electricity - using users in a power distribution area.

[0135] In some embodiments, the method for confirming abnormal electricity - using users in a power distribution area can be implemented as a computer program tangibly embodied in a computer - readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 10 for confirming abnormal electricity - using users in a power distribution area via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for confirming abnormal electricity - using users in a power distribution area described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for confirming abnormal electricity - using users in a power distribution area by any other appropriate means (e.g., by means of firmware).

[0136] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0137] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0138] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0139] To provide interaction with a user, the systems and techniques described herein can be implemented on a device for confirming abnormal power consumption users in a power distribution area, which has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the device for confirming abnormal power consumption users in the power distribution area. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0140] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0141] The computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0142] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0143] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for identifying users with abnormal electricity consumption in a substation, characterized in that: include: Obtain the user power data and area power data of each user in the distribution network area; Calculate the area line loss of the distribution network area based on the user power data and the area power data; Calculating the user power data combination with the best positive correlation with the line loss in the substation area as the best positive correlation data; including: creating a first temporary group; sequentially transferring the user power data outside the first temporary group into the first temporary group, and calculating the positive correlation between the user power data in the first temporary group and the line loss in the substation area after transferring; if the positive correlation increases after transferring the user power data, retaining the user power data in the first temporary group; sequentially transferring the user power data in the first temporary group out of the first temporary group, and calculating the positive correlation between the user power data in the first temporary group and the line loss in the substation area after transferring; if the positive correlation increases after transferring the user power data out, transferring the user power data out of the first temporary group, and taking the user power data combination finally retained in the first temporary group as the best positive correlation data; The users corresponding to the optimal positive correlation data are grouped as positive correlation groups; Calculating the user power data combination with the best negative correlation with the area line loss as the negatively correlated optimal data; including: creating a second temporary group; transferring the user power data outside the second temporary group into the second temporary group in sequence, and calculating the negative correlation between the user power data in the second temporary group and the area line loss after the transfer; if the negative correlation increases after the transfer of the user power data, retaining the user power data in the second temporary group; and taking the user power data combination finally retained in the second temporary group as the negatively correlated optimal data; The users corresponding to the optimal negative correlation data are grouped as negative correlation groups; Determine the user power data corresponding to users other than the positive correlation group and the negative correlation group as first remaining power data; Calculating the user power consumption data combination that is less than a preset power consumption threshold value in the first remaining power consumption data as a low power consumption group; The users except the positive correlation group, the negative correlation group and the low power consumption group are grouped as remaining users; Based on the correlation coefficients of the positive correlation group and the negative correlation group with the substation line loss respectively, the group with abnormal power consumption among the positive correlation group, the negative correlation group, the low power consumption group and the remaining user groups is determined to be the power theft group; when the correlation coefficients of the positive correlation group and the negative correlation group are greater than a preset threshold, they are identified as the user group with abnormal power consumption; when the correlation coefficients of the positive correlation group and the negative correlation group are both less than the preset threshold, the low power consumption group is considered to belong to the user group with abnormal power consumption.

2. The method for identifying users with abnormal electricity consumption in a substation area according to claim 1, characterized in that: The calculating the area line loss of the distribution network area based on the user power data and the area power data includes: Calculate the sum of the user power data to obtain the user total power data; The substation line loss of the distribution network substation is calculated based on the substation power data and the user total power data.

3. The method for identifying users with abnormal electricity consumption in a substation area according to claim 1, characterized in that: The method of finally retaining the user power data combination in the first temporary group as positively correlated optimal data further includes: sequentially retrieving the user power data in the first temporary group from the first temporary group, and calculating the positive correlation between the user power data in the first temporary group after retrieving and the line loss in the station area; If the positive correlation increases after the user power data is retrieved, the user power data is retrieved from the first temporary group.

4. The method for identifying users with abnormal electricity consumption in a substation according to claim 1, characterized in that: Before taking the user power data combination finally retained in the second temporary group as negatively correlated optimal data, the method further includes: sequentially retrieving the user power data in the second temporary group from the second temporary group, and calculating the negative correlation between the user power data in the second temporary group after retrieving and the line loss in the substation area; If the negative correlation increases after the user power data is retrieved, the user power data is retrieved from the second temporary group.

5. A device for confirming abnormal electricity consumption in a substation, characterized in that: include: An acquisition module is used to acquire the user power data and the area power data of each user in the distribution network area; A line loss calculation module, used for calculating the area line loss of the distribution network area based on the user power data and the area power data; A grouping module, used to group the users based on the correlation between the user power consumption data and the line loss in the substation area, to obtain a positive correlation group, a negative correlation group, a low power consumption group and other user groups; A determination module, configured to determine, based on the correlation coefficients of the positive correlation group and the negative correlation group with the line loss of the substation area, the group with abnormal power consumption among the positive correlation group, the negative correlation group, the low power consumption group and the remaining user groups, as a power theft group; When the correlation coefficients of the positive correlation group and the negative correlation group are greater than a preset threshold, they are identified as an abnormal power consumption user group; when the correlation coefficients of the positive correlation group and the negative correlation group are both less than the preset threshold, the low power consumption group is considered to belong to the abnormal power consumption user group; Wherein, the grouping module includes: A positive correlation optimal calculation unit, used to calculate the user power data combination with the best positive correlation with the line loss in the substation area as the positive correlation optimal data; A positive correlation grouping unit, used for executing the user corresponding to the positive correlation optimal data as a positive correlation group; A negative correlation optimal calculation unit, used to calculate the user power data combination with the optimal negative correlation with the line loss in the station area as the negative correlation optimal data; A negative correlation grouping unit, used for executing the user corresponding to the negative correlation optimal data as a negative correlation group; a remaining determination unit, configured to determine the user power data corresponding to users other than the positive correlation group and the negative correlation group as first remaining power data; A low power consumption grouping unit, configured to calculate the user power consumption data combination less than a preset power consumption threshold in the first remaining power consumption data as a low power consumption group; A remaining user grouping unit, used for grouping the users except the positive correlation group, the negative correlation group and the low power consumption group as remaining user groups; The positive correlation optimal calculation unit comprises: A first temporary grouping subunit, configured to execute creation of a first temporary grouping; A first positive correlation calculation subunit is used to sequentially transfer the user power data outside the first temporary group into the first temporary group, and calculate the positive correlation between the user power data in the first temporary group after the transfer and the line loss in the station area; A first import subunit, configured to retain the user power data in the first temporary group if the positive correlation increases after the user power data is imported; a positive correlation confirmation subunit, configured to execute the combination of the user power data finally retained in the first temporary group as positive correlation optimal data; Also includes: A second positive correlation calculation subunit is used to sequentially call out the user power data in the first temporary group from the first temporary group, and calculate the positive correlation between the user power data in the first temporary group after calling out and the line loss in the station area; A first calling out subunit, configured to call out the user power data from the first temporary group if the positive correlation increases after calling out the user power data; The negative correlation grouping unit includes: a second temporary grouping subunit, configured to execute creation of a second temporary grouping; A first negative correlation calculation subunit, configured to sequentially transfer the user power data outside the second temporary group into the second temporary group, and calculate the negative correlation between the user power data in the second temporary group after transfer and the line loss in the station area; A second import subunit, configured to retain the user power data in the second temporary group if the negative correlation increases after the user power data is imported; The negative correlation confirmation subunit is used to execute the combination of the user power data finally retained in the second temporary group as the negative correlation optimal data.

6. A user confirmation device for abnormal electricity consumption in a substation, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for confirming users of abnormal electricity consumption in a substation according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for confirming users with abnormal electricity consumption in a substation according to any one of claims 1 to 4 when executed.

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