Method and device for identifying abnormal power consumption user, electronic equipment and storage medium

Abstract

The application provides a kind of identification method, device, electronic equipment and storage medium of abnormal user of electricity use.The method comprises: obtaining the peak time period, flat time period and valley time period corresponding to the peak time electricity consumption, flat time electricity consumption and valley time electricity consumption of target user in each unit time period in target time period;Based on the peak time electricity consumption, flat time electricity consumption and valley time electricity consumption of each unit time period, calculate the peak time period balance coefficient, flat time period balance coefficient and valley time period balance coefficient that the electricity consumption distribution balance degree of peak time period, flat time period and valley time period of target user in all unit time periods is characterized;Based on peak time period balance coefficient, flat time period balance coefficient, valley time period balance coefficient and preset threshold value, identify whether target user is abnormal user of electricity use in target time period, and generate electricity abnormal user label for target user when target user is abnormal user of electricity use.The application can accurately identify abnormal user of electricity use, and then avoid that circuit safety exists greater hidden danger.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power monitoring, and in particular to a method and device for identifying an abnormal electricity user, an electronic device and a storage medium. BACKGROUND

[0002] In recent years, electric energy has become the main energy at present, and the circuit safety in the process of power transmission is also paid more and more attention. It is found in practice that the abnormal electricity use in the process of power transmission may have a certain influence on the circuit safety.

[0003] In the prior art, when investigating the abnormal electricity use of a user, a technical personnel usually identifies an abnormal electricity user by offline patrol. However, this investigation method is low in efficiency and difficult to accurately identify the real abnormal electricity user, thereby causing a great hidden danger in the circuit safety.

[0004] Therefore, how to efficiently and accurately identify an abnormal electricity user is a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The embodiments of the present application provide a method and device for identifying an abnormal electricity user, an electronic device and a storage medium, to solve the problems of low efficiency and low accuracy in investigating an abnormal electricity user in the prior art.

[0006] In a first aspect, the embodiments of the present application provide a method for identifying an abnormal electricity user, comprising:

[0007] obtaining peak-time electricity consumption, flat-time electricity consumption and valley-time electricity consumption corresponding to a peak time period, a flat time period and a valley time period of each unit time period of a target user in a target time period;

[0008] calculating a peak time period balance coefficient, a flat time period balance coefficient and a valley time period balance coefficient representing the electricity consumption distribution balance degree of the peak time period, the flat time period and the valley time period of the target user in all unit time periods based on the peak-time electricity consumption, the flat-time electricity consumption and the valley-time electricity consumption of each unit time period;

[0009] identifying whether the target user is an abnormal electricity user in the target time period based on the peak time period balance coefficient, the flat time period balance coefficient, the valley time period balance coefficient and a preset threshold, and generating an abnormal electricity user label for the target user when the target user is an abnormal electricity user.

[0010] In a possible implementation, the peak-time power consumption, the flat-time power consumption and the valley-time power consumption of each unit time period are used to calculate a peak-time period balance coefficient, a flat-time period balance coefficient and a valley-time period balance coefficient that represent the balance degree of the power consumption distribution of the target user in all unit time periods, including:

[0011] The peak-time power consumption, the flat-time power consumption and the valley-time power consumption of each unit time period are used to calculate a peak-time power consumption proportion, a flat-time power consumption proportion and a valley-time power consumption proportion of each unit time period, respectively.

[0012] The peak-time power consumption proportion, the flat-time power consumption proportion and the valley-time power consumption proportion of all unit time periods are used to calculate the peak-time period balance coefficient, the flat-time period balance coefficient and the valley-time period balance coefficient.

[0013] In a possible implementation, the peak-time power consumption proportion, the flat-time power consumption proportion and the valley-time power consumption proportion of all unit time periods are used to calculate the peak-time period balance coefficient, the flat-time period balance coefficient and the valley-time period balance coefficient, including:

[0014] The smallest M-bit peak-time power consumption proportion in the peak-time power consumption proportions of all unit time periods is recorded as a first peak-time power consumption proportion set, the largest N-bit peak-time power consumption proportion in the peak-time power consumption proportions of all unit time periods is recorded as a second peak-time power consumption proportion set, and the peak-time period balance coefficient is calculated based on the first peak-time power consumption proportion set and the second peak-time power consumption proportion set; M and N are positive integers.

[0015] The smallest M-bit flat-time power consumption proportion in the flat-time power consumption proportions of all unit time periods is recorded as a first flat-time power consumption proportion set, the largest N-bit flat-time power consumption proportion in the flat-time power consumption proportions of all unit time periods is recorded as a second flat-time power consumption proportion set, and the flat-time period balance coefficient is calculated based on the first flat-time power consumption proportion set and the second flat-time power consumption proportion set.

[0016] The smallest M-bit valley-time power consumption proportion in the valley-time power consumption proportions of all unit time periods is recorded as a first valley-time power consumption proportion set, the largest N-bit valley-time power consumption proportion in the valley-time power consumption proportions of all unit time periods is recorded as a second valley-time power consumption proportion set, and the valley-time period balance coefficient is calculated based on the first valley-time power consumption proportion set and the second valley-time power consumption proportion set.

[0017] In a possible implementation, the calculation of the peak-time period balancing coefficient, the flat-time period balancing coefficient and the valley-time period balancing coefficient based on the peak-time power consumption proportion, the flat-time power consumption proportion and the valley-time power consumption proportion of all unit time periods comprises:

[0018] The average value of the peak-time power consumption proportion of all unit time periods is denoted as a first average value, a first variance of the peak-time power consumption proportion of all unit time periods is calculated based on the first average value, and the peak-time period balancing coefficient is calculated based on the first variance;

[0019] The average value of the flat-time power consumption proportion of all unit time periods is denoted as a second average value, a second variance of the flat-time power consumption proportion of all unit time periods is calculated based on the second average value, and the flat-time period balancing coefficient is calculated based on the second variance;

[0020] The average value of the valley-time power consumption proportion of all unit time periods is denoted as a third average value, a third variance of the valley-time power consumption proportion of all unit time periods is calculated based on the third average value, and the valley-time period balancing coefficient is calculated based on the third variance.

[0021] In a possible implementation, the preset threshold comprises a first preset threshold corresponding to the peak-time period balancing coefficient, a second preset threshold corresponding to the flat-time period balancing coefficient and a third preset threshold corresponding to the valley-time period balancing coefficient.

[0022] The identification of whether the target user in the target time period is an abnormal power consumption user based on the peak-time period balancing coefficient, the flat-time period balancing coefficient, the valley-time period balancing coefficient and a preset threshold comprises:

[0023] The judgment of whether the peak-time period balancing coefficient meets a first preset condition based on the peak-time period balancing coefficient and the first preset threshold, the judgment of whether the flat-time period balancing coefficient meets a second preset condition based on the flat-time period balancing coefficient and the second preset threshold, and the judgment of whether the valley-time period balancing coefficient meets a third preset condition based on the valley-time period balancing coefficient and the third preset threshold.

[0024] If at least one of the following conditions is met, the target user in the target time period is identified as an abnormal power consumption user: the peak-time period balancing coefficient meets the first preset condition, the flat-time period balancing coefficient meets the second preset condition, and the valley-time period balancing coefficient meets the third preset condition.

[0025] In a possible implementation, the preset threshold comprises a mean balancing coefficient threshold.

[0026] identify whether the target user in the target time period is an abnormal electricity user based on the peak period balance coefficient, the flat period balance coefficient, the valley period balance coefficient, and a preset threshold value, including:

[0027] calculate an average balance coefficient based on the peak period balance coefficient, the flat period balance coefficient, and the valley period balance coefficient;

[0028] determine whether the average balance coefficient meets a fourth preset condition based on the average balance coefficient and the average balance coefficient threshold value;

[0029] if the average balance coefficient meets the fourth preset condition, identify that the target user in the target time period is an abnormal electricity user.

[0030] In a possible implementation, before obtaining the peak time electricity consumption, the flat time electricity consumption, and the valley time electricity consumption corresponding to the peak period, the flat period, and the valley period of each unit time period of the target user in the target time period, the method further includes:

[0031] obtain historical electricity consumption data of each unit time period of the target user in a historical time period;

[0032] perform clustering analysis on the historical electricity consumption data to obtain a plurality of historical classified electricity consumption data;

[0033] determine the peak period, the flat period, and the valley period of each unit time period based on the plurality of historical classified electricity consumption data.

[0034] In a second aspect, an embodiment of the present application provides an abnormal electricity user identification device, including:

[0035] a data acquisition module configured to obtain peak time electricity consumption, flat time electricity consumption, and valley time electricity consumption corresponding to a peak period, a flat period, and a valley period of each unit time period of a target user in a target time period;

[0036] a coefficient calculation module configured to calculate a peak period balance coefficient, a flat period balance coefficient, and a valley period balance coefficient based on the peak time electricity consumption, the flat time electricity consumption, and the valley time electricity consumption of each unit time period, the peak period balance coefficient, the flat period balance coefficient, and the valley period balance coefficient representing a balance degree of electricity consumption distribution of the peak period, the flat period, and the valley period of the target user in all unit time periods;

[0037] a user identification module configured to identify whether the target user in the target time period is an abnormal electricity user based on the peak period balance coefficient, the flat period balance coefficient, the valley period balance coefficient, and a preset threshold value, and generate an abnormal electricity user label for the target user when the target user is an abnormal electricity user.

[0038] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method according to the first aspect or any possible implementation manner of the first aspect when executing the computer program.

[0039] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and the computer program implements the steps of the method according to the first aspect or any possible implementation manner of the first aspect when executed by a processor.

[0040] The embodiments of the present application provide a method and device for identifying an abnormal user of electricity, an electronic device, and a storage medium. The electricity consumption data of each unit time period of peak, flat, and valley time periods of a target user in a target time period is obtained, and the balance coefficient of each time period reflecting the balance degree of electricity consumption distribution of the target user is calculated based on the obtained electricity consumption data of each time period. Finally, whether the target user has an abnormal electricity consumption condition can be accurately and efficiently identified according to the balance coefficient of each time period. When the target user has an abnormal electricity consumption, a label is generated for the target user to mark the user as an abnormal user of electricity. In this way, the normal user of electricity and the abnormal user of electricity can be effectively distinguished based on the balance degree of electricity consumption distribution of the peak time period, the flat time period, and the valley time period of the target user in the target time period. Based on the identification result, the abnormal electricity consumption condition of the target user marked by the label can be timely and effectively corrected, thereby effectively avoiding the problem that the circuit safety has a large hidden danger due to the abnormal electricity consumption of the target user. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0042] Figure 1 is the implementation flowchart of the method for identifying an abnormal user of electricity provided by the embodiments of the present application;

[0043] Figure 2 is a structural schematic diagram of the device for identifying an abnormal user of electricity provided by the embodiments of the present application;

[0044] Figure 3 is a schematic diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0045] In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular architectures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known methods, devices, circuits, and

[0046] In order to make the objects, technical solutions and advantages of the present application clearer, the following will be described in conjunction with the specific embodiments and the accompanying drawings.

[0047] Figure 1 The implementation flowchart of the method for identifying the power consumption abnormal user provided by the embodiments of the present application is shown in Figure 1 The method for identifying the power consumption abnormal user provided by the embodiments of the present application comprises the following steps.

[0048] Step 101: Obtain the peak-time power consumption, the flat-time power consumption and the valley-time power consumption corresponding to the peak time, the flat time and the valley time of each unit time period of the target user in a target time period.

[0049] In step 101, exemplary, the unit time period can be one day, and the target time period contains multiple unit time periods, which can be 30 days, 90 days or 180 days, etc. When obtaining the power consumption, the power consumption is obtained in unit time period, i.e. the peak-time power consumption corresponding to the peak time, the flat-time power consumption corresponding to the flat time and the valley-time power consumption corresponding to the valley time of the target user in the target time period are obtained. In this embodiment, by obtaining the power consumption data of each time period of the target user in the target time period, it is beneficial to subsequently judge whether the target user is a power consumption abnormal user based on the power consumption data.

[0050] In one possible implementation, before obtaining the peak-time power consumption, the flat-time power consumption and the valley-time power consumption corresponding to the peak time, the flat time and the valley time of each unit time period of the target user in the target time period, the method further comprises the following steps.

[0051] Obtain the historical power consumption data of each unit time period of the target user in a historical time period.

[0052] Perform clustering analysis on the historical power consumption data to obtain a plurality of historical classified power consumption data.

[0053] Determine the peak time, the flat time and the valley time of each unit time period based on the plurality of historical classified power consumption data.

[0054] In this embodiment, each unit time period includes a peak period, a flat period and a valley period. The division of the periods can be divided according to the amount of electricity per capita. For example, the period with high electricity per capita can be defined as the peak period, the period with reasonable electricity per capita can be defined as the flat period, and the period with low electricity per capita can be defined as the valley period. Specifically, the historical electricity consumption data of the target user can be obtained, and the peak, flat and valley periods can be divided based on the historical electricity consumption data of the target user. For example, clustering analysis can be used to divide the periods. Specifically, the historical electricity consumption data of the target user in each unit time period can be obtained. The historical electricity consumption data is clustered and analyzed to obtain a plurality of historical classified electricity consumption data. The peak period, flat period and valley period of each unit time period are determined based on the plurality of historical classified electricity consumption data. For example, the unit time period is one day. The peak period can be 8:00-11:00 and 18:00-23:00 every day, the flat period can be 7:00-8:00 and 11:00-18:00 every day, and the valley period can be 0:00-7:00 and 23:00-24:00 every day. In this embodiment, the historical electricity consumption data of the target user is analyzed by clustering analysis algorithm to realize accurate division of each period in the unit time period, which is conducive to ensuring the accuracy of calculating the balance coefficient of each period, thereby accurately identifying the abnormal electricity consumption user.

[0055] Step 102: Based on the peak time electricity consumption, flat time electricity consumption and valley time electricity consumption of each unit time period, the peak period balance coefficient, flat period balance coefficient and valley period balance coefficient representing the electricity consumption distribution balance degree of the target user in all unit time periods are calculated.

[0056] In step 102, the peak time period balancing coefficient corresponding to the peak time period can be calculated according to the peak time electricity consumption of the target user in each unit time period in the target time period, the flat time period balancing coefficient corresponding to the flat time period can be calculated according to the flat time electricity consumption of the target user in each unit time period in the target time period, and the valley time period balancing coefficient corresponding to the valley time period can be calculated according to the valley time electricity consumption of the target user in each unit time period in the target time period. Wherein, the peak time period balancing coefficient is used to represent the balance degree of the electricity consumption distribution of the target user in the peak time period in the target time period, the flat time period balancing coefficient is used to represent the balance degree of the electricity consumption distribution of the target user in the flat time period in the target time period, and the valley time period balancing coefficient is used to represent the balance degree of the electricity consumption distribution of the target user in the valley time period in the target time period. In this embodiment, by calculating the peak time period balancing coefficient corresponding to the peak time period, the flat time period balancing coefficient corresponding to the flat time period, and the valley time period balancing coefficient corresponding to the valley time period in the target time period, and based on the peak time period balancing coefficient, the flat time period balancing coefficient and the valley time period balancing coefficient reflecting the balance degree of the electricity consumption distribution of the target user in each time period, it is beneficial to realize the accurate identification of the abnormal electricity user.

[0057] In a possible implementation, based on the peak time electricity consumption, the flat time electricity consumption and the valley time electricity consumption of each unit time period, the peak time period balancing coefficient, the flat time period balancing coefficient and the valley time period balancing coefficient representing the balance degree of the electricity consumption distribution of the target user in all unit time periods are calculated, including:

[0058] Based on the peak time electricity consumption, the flat time electricity consumption and the valley time electricity consumption of each unit time period, the peak time electricity consumption proportion, the flat time electricity consumption proportion and the valley time electricity consumption proportion of each unit time period are calculated respectively.

[0059] Based on the peak time electricity consumption proportion, the flat time electricity consumption proportion and the valley time electricity consumption proportion of all unit time periods, the peak time period balancing coefficient, the flat time period balancing coefficient and the valley time period balancing coefficient are calculated.

[0060] In this embodiment, the proportion of the power consumption of each time period in the corresponding unit time period can be determined according to the power consumption of each time period in each unit time period, and the balance coefficient of each time period can be calculated based on the proportions of the power consumption. For example, the proportion of the peak-time power consumption in the corresponding unit time period in each unit time period can be calculated, the proportion of the flat-time power consumption in the corresponding unit time period in each unit time period can be calculated, and the proportion of the valley-time power consumption in the corresponding unit time period in each unit time period can be calculated. The proportion of the peak-time power consumption in each unit time period is the ratio of the power consumption of the peak time period of the target user in the unit time period to the power consumption of the unit time period. The proportion of the flat-time power consumption in each unit time period is the ratio of the power consumption of the flat time period of the target user in the unit time period to the power consumption of the unit time period. The proportion of the valley-time power consumption in each unit time period is the ratio of the power consumption of the valley time period of the target user in the unit time period to the power consumption of the unit time period. After determining the proportion of the power consumption of each time period in the unit time period, the balance coefficient of each time period can be calculated according to the proportion of the power consumption of each time period in all unit time periods of the target time period.

[0061] In this embodiment, by calculating the proportion of the power consumption of each time period in each unit time period of the target time period, and then calculating the balance coefficient of each time period based on the proportion of the power consumption of each time period, the balance degree of the power consumption distribution of each time period in the target time period of the user can be accurately reflected, and the accurate identification of the abnormal user can be realized based on the balance degree of the power consumption distribution of each time period.

[0062] In addition, the peak-time period balance coefficient, the flat-time period balance coefficient and the valley-time period balance coefficient can be directly determined based on the peak-time power consumption, the flat-time power consumption and the valley-time power consumption of the target user in each unit time period of the target time period. In this way, the peak-time period balance coefficient, the flat-time period balance coefficient and the valley-time period balance coefficient can directly reflect the distribution of the power consumption of the target user in the target time period, and the balance degree of the power consumption distribution of each time period can be determined based on the distribution of the power consumption, so as to realize the accurate identification of the abnormal user.

[0063] In a possible implementation, the peak-time period balance coefficient, the flat-time period balance coefficient and the valley-time period balance coefficient are calculated based on the proportions of the peak-time power consumption, the flat-time power consumption and the valley-time power consumption of all unit time periods, including:

[0064] The minimum M peak time electricity consumption proportion in all unit time periods is recorded as a first peak time electricity consumption proportion set, and the maximum N peak time electricity consumption proportion in all unit time periods is recorded as a second peak time electricity consumption proportion set, and a peak time period balance coefficient is calculated based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set. M and N are positive integers.

[0065] The minimum M peak time electricity consumption proportion in all unit time periods is recorded as a first peak time electricity consumption proportion set, and the maximum N peak time electricity consumption proportion in all unit time periods is recorded as a second peak time electricity consumption proportion set, and a peak time period balance coefficient is calculated based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set. M and N are positive integers.

[0066] The minimum M peak time electricity consumption proportion in all unit time periods is recorded as a first peak time electricity consumption proportion set, and the maximum N peak time electricity consumption proportion in all unit time periods is recorded as a second peak time electricity consumption proportion set, and a peak time period balance coefficient is calculated based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set. M and N are positive integers.

[0067] In this embodiment, the minimum M peak time electricity consumption proportion in all unit time periods of the target user in the target time period is selected and recorded as a first peak time electricity consumption proportion set, the maximum N peak time electricity consumption proportion in all unit time periods of the target user in the target time period is selected and recorded as a second peak time electricity consumption proportion set, and then a peak time period balance coefficient is calculated based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set. M and N are positive integers.

[0068] For example, the peak time period balance coefficient is calculated based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set, which can be: calculating the average value of all peak time electricity consumption proportions in the first peak time electricity consumption proportion set, recorded as a fourth average value, calculating the average value of all peak time electricity consumption proportions in the second peak time electricity consumption proportion set, recorded as a fifth average value; calculating the first ratio of the fourth average value and the fifth average value, and taking the first ratio as the peak time period balance coefficient. In this case, the larger the peak time period balance coefficient is, the more balanced the electricity consumption distribution of the target user in the target time period is. For example, if the peak time period balance coefficient is 1, it means that the peak time period electricity consumption proportion of each unit time period of the target user in the target time period is consistent, so that the size of the peak time period balance coefficient can be used to determine whether the target user is an abnormal electricity consumption user, thereby achieving accurate identification of abnormal electricity consumption users.

[0069] Alternatively, a second ratio of the fifth average value and the fourth average value can also be calculated, and the second ratio is taken as the peak period balance coefficient. In this case, the smaller the peak period balance coefficient, the more balanced the power consumption distribution of the target user in the peak period of the target time period, and the target user can also be determined to be an abnormal power consumption user by judging the size of the peak period balance coefficient, thereby achieving accurate identification of abnormal power consumption users.

[0070] The M smallest power consumption proportions in the normal period of the target user in all unit time periods in the target time period are selected as a first normal period power consumption proportion set, the N largest power consumption proportions in the normal period of the target user in all unit time periods in the target time period are selected as a second normal period power consumption proportion set, and then a normal period balance coefficient is calculated based on the first normal period power consumption proportion set and the second normal period power consumption proportion set. M and N are positive integers.

[0071] For example, the normal period balance coefficient is calculated based on the first normal period power consumption proportion set and the second normal period power consumption proportion set as follows: an average value of all normal period power consumption proportions in the first normal period power consumption proportion set is calculated and taken as a sixth average value, an average value of all normal period power consumption proportions in the second normal period power consumption proportion set is calculated and taken as a seventh average value, and a third ratio of the sixth average value and the seventh average value is calculated and taken as the normal period balance coefficient. In this case, the larger the normal period balance coefficient, the more balanced the power consumption distribution of the target user in the normal period of the target time period. For example, when the normal period balance coefficient is 1, it indicates that the normal period power consumption proportions of the target user in each unit time period in the target time period are consistent, and thus the target user can be determined to be an abnormal power consumption user by judging the size of the normal period balance coefficient, thereby achieving accurate identification of abnormal power consumption users.

[0072] Alternatively, a fourth ratio of the seventh average value and the sixth average value can also be calculated, and the fourth ratio is taken as the normal period balance coefficient. In this case, the smaller the normal period balance coefficient, the more balanced the power consumption distribution of the target user in the normal period of the target time period, and the target user can also be determined to be an abnormal power consumption user by judging the size of the normal period balance coefficient, thereby achieving accurate identification of abnormal power consumption users.

[0073] The M smallest power consumption proportions in the normal period of the target user in all unit time periods in the target time period are selected as a first normal period power consumption proportion set, the N largest power consumption proportions in the normal period of the target user in all unit time periods in the target time period are selected as a second normal period power consumption proportion set, and then a normal period balance coefficient is calculated based on the first normal period power consumption proportion set and the second normal period power consumption proportion set. M and N are positive integers.

[0074] For example, the valley period balance coefficient can be calculated based on the first valley time electricity consumption proportion set and the second valley time electricity consumption proportion set as follows: an eighth average value of all valley time electricity consumption proportions in the first valley time electricity consumption proportion set is calculated, and a ninth average value of all valley time electricity consumption proportions in the second valley time electricity consumption proportion set is calculated; a fifth ratio of the eighth average value to the ninth average value is calculated, and the fifth ratio is taken as the valley period balance coefficient. In this case, the larger the valley period balance coefficient is, the more balanced the electricity consumption distribution of the target user in the target time period is. For example, if the valley period balance coefficient is 1, it means that the valley time electricity consumption proportion of each unit time period of the target user in the target time period is consistent, so that whether the target user is an abnormal electricity consumption user can be determined by judging the size of the valley period balance coefficient, thereby achieving accurate identification of abnormal electricity consumption users.

[0075] Alternatively, a sixth ratio of the ninth average value to the eighth average value can also be calculated, and the sixth ratio is taken as the valley period balance coefficient. In this case, the smaller the valley period balance coefficient is, the more balanced the electricity consumption distribution of the target user in the target time period is, and whether the target user is an abnormal electricity consumption user can also be determined by judging the size of the valley period balance coefficient, thereby achieving accurate identification of abnormal electricity consumption users.

[0076] In addition, in the embodiment, the values of M and N can be the same or different. For example, M and N can be specific positive integer values such as 10, 20, etc. Further, the values of M and N can also be determined based on a preset calculation strategy. For example, in calculating the peak period balance coefficient, M can take the number corresponding to 10% of the total number of peak time electricity consumption proportions, and N can take the number corresponding to 15% of the total number of peak time electricity consumption proportions. For example, if the total number of peak time electricity consumption proportions of all unit time periods is 200, 10% includes 20, and 15% includes 30, so that the peak period balance coefficient can be the ratio of the average value of the smallest 20 peak time electricity consumption proportions to the average value of the largest 30 peak time electricity consumption proportions.

[0077] In this embodiment, considering that the closer the minimum peak-time electricity consumption proportion to the maximum peak-time electricity consumption proportion in all peak-time electricity consumption proportions in the target time period, the more balanced the electricity consumption distribution of the target user in the peak-time period (similarly, the closer the minimum off-peak-time electricity consumption proportion to the maximum off-peak-time electricity consumption proportion in all off-peak-time electricity consumption proportions in the target time period, the more balanced the electricity consumption distribution of the target user in the off-peak-time period; the closer the minimum valley-time electricity consumption proportion to the maximum valley-time electricity consumption proportion in all valley-time electricity consumption proportions in the target time period, the more balanced the electricity consumption distribution of the target user in the valley-time period), therefore, the balance coefficient of each time period can be determined based on the average of the minimum partial electricity consumption proportion and the average of the maximum partial electricity consumption proportion in each time period, so as to accurately identify whether the target user is an electricity abnormal user according to the calculated balance coefficient of each time period.

[0078] In a possible implementation, the peak-time period balance coefficient, the off-peak-time period balance coefficient and the valley-time period balance coefficient are calculated based on the peak-time electricity consumption proportion, the off-peak-time electricity consumption proportion and the valley-time electricity consumption proportion of all unit time periods, including:

[0079] The average of the peak-time electricity consumption proportions of all unit time periods is recorded as a first average value, a first variance of the peak-time electricity consumption proportions of all unit time periods is calculated based on the first average value, and the peak-time period balance coefficient is calculated based on the first variance.

[0080] The average of the off-peak-time electricity consumption proportions of all unit time periods is recorded as a second average value, a second variance of the off-peak-time electricity consumption proportions of all unit time periods is calculated based on the second average value, and the off-peak-time period balance coefficient is calculated based on the second variance.

[0081] The average of the valley-time electricity consumption proportions of all unit time periods is recorded as a third average value, a third variance of the valley-time electricity consumption proportions of all unit time periods is calculated based on the third average value, and the valley-time period balance coefficient is calculated based on the third variance.

[0082] In this embodiment, whether the target user is an electricity abnormal user can be determined based on the fluctuation of the electricity consumption proportion of each time period in all unit time periods of the target user in the target time period. For example, the average of the peak-time electricity consumption proportions of all unit time periods in the target time period is calculated and recorded as a first average value, a first variance of the peak-time electricity consumption proportions of all unit time periods is calculated based on the first average value and each peak-time electricity consumption proportion, and the first variance is taken as the peak-time period balance coefficient. For example, the peak-time period balance coefficient is 0, which indicates that the peak-time period electricity consumption proportion of each unit time period of the target user in the target time period is consistent, so that whether the target user is an electricity abnormal user can be determined by judging the size of the peak-time period balance coefficient, thereby realizing accurate identification of electricity abnormal users.

[0083] An average value of the normal time electricity consumption proportion of all unit time periods in the target time period is calculated, denoted as a second average value, a second variance of the normal time electricity consumption proportion of all unit time periods is calculated based on the second average value and each normal time electricity consumption proportion, and the second variance is taken as the normal time period balance coefficient. For example, if the normal time period balance coefficient is 0, it indicates that the normal time period electricity consumption proportion of each unit time period of the target user in the target time period is consistent, so that whether the target user is an abnormal electricity user can be determined by judging the size of the normal time period balance coefficient, thereby realizing accurate identification of the abnormal electricity user.

[0084] An average value of the valley time electricity consumption proportion of all unit time periods in the target time period is calculated, denoted as a third average value, a third variance of the valley time electricity consumption proportion of all unit time periods is calculated based on the third average value and each valley time electricity consumption proportion, and the third variance is taken as the valley time period balance coefficient. For example, if the valley time period balance coefficient is 0, it indicates that the valley time period electricity consumption proportion of each unit time period of the target user in the target time period is consistent, so that whether the target user is an abnormal electricity user can be determined by judging the size of the valley time period balance coefficient, thereby realizing accurate identification of the abnormal electricity user.

[0085] Step 103: Based on the peak time period balance coefficient, the normal time period balance coefficient, the valley time period balance coefficient and the preset threshold, whether the target user in the target time period is an abnormal electricity user is identified, and an abnormal electricity user label is generated for the target user when the target user is an abnormal electricity user.

[0086] In step 103, whether the target user is an abnormal electricity user can be identified based on the comparison of the peak time period balance coefficient, the normal time period balance coefficient, the valley time period balance coefficient and the preset threshold, and an abnormal electricity user label is generated for the target user when the target user is determined to be an abnormal electricity user.

[0087] For example, for a normal electricity user, the electricity consumption distribution of the peak time period of each unit time period of the user in the target time period should be relatively balanced, that is, the balance degree of the electricity consumption distribution of the peak time period of the user in the target time period represented by the peak time period balance coefficient of the normal electricity user should be relatively high. Correspondingly, if the balance degree of the electricity consumption distribution of the peak time period of the user in the target time period represented by the peak time period balance coefficient of a certain user is relatively low, it indicates that the user is likely to be an abnormal electricity user.

[0088] In addition, the abnormal electricity user label can represent an abnormal electricity user, so that subsequent relevant staff can determine the abnormal electricity user based on the label, and then maintain the power transmission line, effectively avoiding the problem that the circuit safety has a large hidden danger.

[0089] In a possible implementation, the preset threshold value includes: a first preset threshold value corresponding to the peak period balance coefficient, a second preset threshold value corresponding to the flat period balance coefficient, and a third preset threshold value corresponding to the valley period.

[0090] Based on the peak period balance coefficient, the flat period balance coefficient, the valley period balance coefficient, and the preset threshold value, whether the target user in the target time period is an abnormal electricity user is identified, including:

[0091] Based on the peak period balance coefficient and the first preset threshold value, whether the peak period balance coefficient meets the first preset condition is determined, based on the flat period balance coefficient and the second preset threshold value, whether the flat period balance coefficient meets the second preset condition is determined, and based on the valley period balance coefficient and the third preset threshold value, whether the valley period balance coefficient meets the third preset condition is determined.

[0092] If at least one of the following conditions is met: the peak period balance coefficient meets the first preset condition, the flat period balance coefficient meets the second preset condition, and the valley period balance coefficient meets the third preset condition, it is identified that the target user in the target time period is an abnormal electricity user.

[0093] In this embodiment, the preset threshold value can be a threshold value corresponding to each period, that is, the preset threshold value can be a first preset threshold value corresponding to the peak period balance coefficient, a second preset threshold value corresponding to the flat period balance coefficient, and a third preset threshold value corresponding to the valley period. In this way, when identifying an abnormal electricity user based on the balance coefficient of each period and the preset threshold value, the balance coefficient of each period can be compared with the respective corresponding preset threshold value to identify an abnormal electricity user.

[0094] In the first example, in the case of taking the first ratio as the peak period balance coefficient, it is determined whether the peak period balance coefficient is less than the first preset threshold value, and if the peak period balance coefficient is less than the first preset threshold value, it indicates that the target user is an abnormal electricity user; in the case of taking the third ratio as the flat period balance coefficient, it is determined whether the flat period balance coefficient is less than the second preset threshold value, and if the flat period balance coefficient is less than the second preset threshold value, it indicates that the target user is an abnormal electricity user; in the case of taking the fifth ratio as the valley period balance coefficient, it is determined whether the valley period balance coefficient is less than the third preset threshold value, and if the valley period balance coefficient is less than the third preset threshold value, it indicates that the target user is an abnormal electricity user. Based on the above three cases in the first example, if at least one of them is met, it can be determined that the target user is an abnormal electricity user.

[0095] In the second example, in the case of taking the second ratio as the peak period balancing coefficient, it is judged whether the peak period balancing coefficient is greater than the first preset threshold value. If the peak period balancing coefficient is greater than the first preset threshold value, it indicates that the target user is an electricity abnormal user. In the case of taking the fourth ratio as the flat period balancing coefficient, it is judged whether the flat period balancing coefficient is greater than the second preset threshold value. If the flat period balancing coefficient is greater than the second preset threshold value, it indicates that the target user is an electricity abnormal user. In the case of taking the sixth ratio as the valley period balancing coefficient, it is judged whether the valley period balancing coefficient is greater than the third preset threshold value. If the valley period balancing coefficient is greater than the third preset threshold value, it indicates that the target user is an electricity abnormal user. Based on the above three cases in the second example, if at least one of them is satisfied, it can be determined that the target user is an electricity abnormal user.

[0096] In the third example, in the case of taking the first variance as the peak period balancing coefficient, it is judged whether the peak period balancing coefficient is greater than the first preset threshold value. If the peak period balancing coefficient is greater than the first preset threshold value, it indicates that the target user is an electricity abnormal user. In the case of taking the second variance as the flat period balancing coefficient, it is judged whether the flat period balancing coefficient is greater than the second preset threshold value. If the flat period balancing coefficient is greater than the second preset threshold value, it indicates that the target user is an electricity abnormal user. In the case of taking the third variance as the valley period balancing coefficient, it is judged whether the valley period balancing coefficient is greater than the third preset threshold value. If the valley period balancing coefficient is greater than the third preset threshold value, it indicates that the target user is an electricity abnormal user. Based on the above three cases in the third example, if at least one of them is satisfied, it can be determined that the target user is an electricity abnormal user.

[0097] In addition, in the embodiment, the first preset threshold value, the second preset threshold value and the third preset threshold value can be obtained by a clustering algorithm, or can be directly set according to experience statistics, which is not limited in the present application. Taking the first preset threshold value obtained by the clustering algorithm as an example, the peak period data set is analyzed by the clustering algorithm, and the first preset threshold value is determined based on the clustering result. The peak period data set includes the peak period balancing coefficient corresponding to the electricity normal user and the peak period balancing coefficient corresponding to the electricity abnormal user. The clustering result includes two categories, one of which is the peak period balancing coefficient of the electricity normal user, and the other of which is the peak period balancing coefficient of the electricity abnormal user. When the first preset threshold value is determined based on the clustering result, the smallest peak period balancing coefficient in the category of the electricity normal user can be taken as the first preset threshold value.

[0098] In this embodiment, since the balance coefficient of each time period can represent the balance degree of the power consumption distribution of the target user in each time period of the target time period, the user with unbalanced power consumption distribution, i.e., the user with abnormal power consumption, can be determined by setting a preset threshold for the peak time period balance coefficient, the flat time period balance coefficient and the valley time period balance coefficient respectively. In this embodiment, when identifying the user with abnormal power consumption, the peak time period balance coefficient is compared with the first preset threshold, the flat time period balance coefficient is compared with the second preset threshold, and the valley time period balance coefficient is compared with the third preset threshold. Finally, based on the comparison result, it is further identified whether the user is the user with abnormal power consumption. In this way, the user with abnormal power consumption can be accurately identified.

[0099] In a possible implementation, the preset threshold includes a mean balance coefficient threshold.

[0100] Identifying whether the target user is the user with abnormal power consumption in the target time period based on the peak time period balance coefficient, the flat time period balance coefficient, the valley time period balance coefficient and the preset threshold includes:

[0101] Calculating a mean balance coefficient based on the peak time period balance coefficient, the flat time period balance coefficient and the valley time period balance coefficient.

[0102] Judging whether the mean balance coefficient meets a fourth preset condition based on the mean balance coefficient and the mean balance coefficient threshold.

[0103] If the mean balance coefficient meets the fourth preset condition, identifying that the target user is the user with abnormal power consumption in the target time period.

[0104] In this embodiment, whether the target user is the user with abnormal power consumption can be identified based on only one preset threshold. Specifically, the average of the peak time period balance coefficient, the flat time period balance coefficient and the valley time period balance coefficient is calculated, and the average is recorded as the mean balance coefficient. If the balance coefficient of each time period is calculated in the manner in the first example, when the mean balance coefficient is less than the mean balance coefficient threshold, it can be determined that the target user is the user with abnormal power consumption. If the balance coefficient of each time period is calculated in the manner in the second or third example, when the mean balance coefficient is greater than the mean balance coefficient threshold, it can be determined that the target user is the user with abnormal power consumption.

[0105] In this embodiment, whether the target user is the user with abnormal power consumption is identified based on only one mean balance coefficient threshold. In this way, the workflow can be effectively simplified, and the workload can be reduced. At the same time, the mean of the peak time period balance coefficient, the flat time period balance coefficient and the valley time period balance coefficient is taken as the mean balance coefficient, and compared with the mean balance coefficient threshold, which can effectively avoid contingency, and thus the user with abnormal power consumption can be better identified.

[0106] The embodiment of the present application provides a kind of identification method of abnormal user of electricity, by obtaining the electricity consumption data of target user in each unit time period in target time period peak, flat, valley period, and based on the electricity consumption data of each period obtained, the equilibrium coefficient of each period that can reflect the balance degree of target user electricity consumption distribution is calculated, finally according to the equilibrium coefficient of each period, whether target user exists abnormal electricity consumption condition can be accurately and efficiently identified, when target user exists abnormal electricity consumption, corresponding label is generated for the target user to mark the user as abnormal user of electricity, in this way, based on the balance degree of electricity consumption distribution of target user in peak period, flat period, valley period in target time period, normal user of electricity and abnormal user of electricity can be effectively distinguished, and based on the identification result, the abnormal electricity consumption condition of target user marked by label can be timely and effectively corrected, and then effectively avoid the problem that circuit safety exists greater hidden danger caused by target user electricity abnormality.

[0107] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0108] The following is the device embodiment of the present application, and for the details not described in detail, reference can be made to the corresponding method embodiments described above.

[0109] Figure 2 The structure diagram of the identification device of abnormal user of electricity provided by the embodiment of the present application is shown, only the part related to the embodiment of the present application is shown for convenience, and the details are as follows:

[0110] As Figure 2 shown, the identification device of abnormal user of electricity 2 comprises:

[0111] The data acquisition module 201 is used for acquiring the peak time electricity consumption, flat time electricity consumption and valley time electricity consumption corresponding to peak period, flat period and valley period of each unit time period of target user in target time period.

[0112] The coefficient calculation module 202 is used for calculating the peak period equilibrium coefficient, flat period equilibrium coefficient and valley period equilibrium coefficient representing the balance degree of electricity consumption distribution of peak period, flat period and valley period of target user in all unit time periods based on the peak time electricity consumption, flat time electricity consumption and valley time electricity consumption of each unit time period.

[0113] The user identification module 203 is used for identifying whether target user in target time period is abnormal user of electricity based on peak period equilibrium coefficient, flat period equilibrium coefficient, valley period equilibrium coefficient and preset threshold, and generating abnormal user of electricity label for target user when target user is abnormal user of electricity.

[0114] The embodiment of the present application provides a kind of identification device of abnormal user of electricity, by obtaining the electricity consumption data of target user in each unit time period in target time period peak, flat, valley period, and based on the electricity consumption data of each period obtained, the equilibrium coefficient of each period that can reflect the balance degree of target user electricity consumption distribution is calculated, finally according to the equilibrium coefficient of each period, whether target user exists abnormal electricity consumption condition can be accurately and efficiently identified, when target user exists abnormal electricity consumption, corresponding label is generated for the target user to mark the user as abnormal user of electricity, in this way, based on the balance degree of electricity consumption distribution of target user in peak period, flat period, valley period in target time period, normal user of electricity and abnormal user of electricity can be effectively distinguished, and based on the identification result, the abnormal electricity consumption condition of target user marked by label can be timely and effectively corrected, and then effectively avoid the problem that circuit safety exists greater hidden danger caused by target user abnormal electricity consumption.

[0115] In a possible implementation, before the data acquisition module 201 obtains the peak-time electricity consumption, flat-time electricity consumption and valley-time electricity consumption corresponding to the peak period, flat period and valley period of each unit time period of target user in target time period, it is further specifically used for:

[0116] Obtain historical electricity consumption data of target user in each unit time period in historical time period.

[0117] Cluster analysis is performed on the historical electricity consumption data to obtain a plurality of historical classified electricity consumption data.

[0118] Determine the peak period, flat period and valley period of each unit time period based on the plurality of historical classified electricity consumption data.

[0119] In a possible implementation, when the coefficient calculation module 202 calculates the peak period equilibrium coefficient, flat period equilibrium coefficient and valley period equilibrium coefficient representing the balance degree of electricity consumption distribution of target user in all unit time periods in peak period, flat period and valley period based on the peak-time electricity consumption, flat-time electricity consumption and valley-time electricity consumption of each unit time period, it is specifically used for:

[0120] Based on the peak-time electricity consumption, flat-time electricity consumption and valley-time electricity consumption of each unit time period, respectively calculate the peak-time electricity consumption proportion, flat-time electricity consumption proportion and valley-time electricity consumption proportion of each unit time period.

[0121] Corresponding calculate the peak period equilibrium coefficient, flat period equilibrium coefficient and valley period equilibrium coefficient based on the peak-time electricity consumption proportion, flat-time electricity consumption proportion and valley-time electricity consumption proportion of all unit time periods.

[0122] In a possible implementation, when the coefficient calculation module 202 calculates the peak period balancing coefficient, the flat period balancing coefficient and the valley period balancing coefficient based on the peak time electricity consumption proportion, the flat time electricity consumption proportion and the valley time electricity consumption proportion of all unit time periods, the coefficient calculation module 202 is specifically configured to:

[0123] record the minimum M-bit peak time electricity consumption proportion in the peak time electricity consumption proportions of all unit time periods as a first peak time electricity consumption proportion set, record the maximum N-bit peak time electricity consumption proportion in the peak time electricity consumption proportions of all unit time periods as a second peak time electricity consumption proportion set, and calculate the peak period balancing coefficient based on the first peak time electricity consumption proportion set and the second peak time electricity consumption proportion set; wherein M and N are positive integers.

[0124] record the minimum M-bit flat time electricity consumption proportion in the flat time electricity consumption proportions of all unit time periods as a first flat time electricity consumption proportion set, record the maximum N-bit flat time electricity consumption proportion in the flat time electricity consumption proportions of all unit time periods as a second flat time electricity consumption proportion set, and calculate the flat period balancing coefficient based on the first flat time electricity consumption proportion set and the second flat time electricity consumption proportion set.

[0125] record the minimum M-bit valley time electricity consumption proportion in the valley time electricity consumption proportions of all unit time periods as a first valley time electricity consumption proportion set, record the maximum N-bit valley time electricity consumption proportion in the valley time electricity consumption proportions of all unit time periods as a second valley time electricity consumption proportion set, and calculate the valley period balancing coefficient based on the first valley time electricity consumption proportion set and the second valley time electricity consumption proportion set.

[0126] In a possible implementation, when the coefficient calculation module 202 calculates the peak period balancing coefficient, the flat period balancing coefficient and the valley period balancing coefficient based on the peak time electricity consumption proportion, the flat time electricity consumption proportion and the valley time electricity consumption proportion of all unit time periods, the coefficient calculation module 202 is specifically configured to:

[0127] record the average value of the peak time electricity consumption proportions of all unit time periods as a first average value, calculate the first variance of the peak time electricity consumption proportions of all unit time periods based on the first average value, and calculate the peak period balancing coefficient based on the first variance.

[0128] record the average value of the flat time electricity consumption proportions of all unit time periods as a second average value, calculate the second variance of the flat time electricity consumption proportions of all unit time periods based on the second average value, and calculate the flat period balancing coefficient based on the second variance.

[0129] record the average value of the valley time electricity consumption proportions of all unit time periods as a third average value, calculate the third variance of the valley time electricity consumption proportions of all unit time periods based on the third average value, and calculate the valley period balancing coefficient based on the third variance.

[0130] In a possible implementation, the preset threshold in the user identification module 203 includes: a first preset threshold corresponding to the peak period balance coefficient, a second preset threshold corresponding to the flat period balance coefficient, and a third preset threshold corresponding to the valley period.

[0131] When the user identification module 203 identifies whether the target user in the target time period is the electricity abnormal user based on the peak period balance coefficient, the flat period balance coefficient, the valley period balance coefficient, and the preset threshold, the user identification module 203 is specifically configured to:

[0132] The peak period balance coefficient is determined based on the first preset threshold, the flat period balance coefficient is determined based on the second preset threshold, and the valley period balance coefficient is determined based on the third preset threshold.

[0133] If at least one of the following conditions is met: the peak period balance coefficient meets the first preset condition, the flat period balance coefficient meets the second preset condition, and the valley period balance coefficient meets the third preset condition, the target user in the target time period is identified as the electricity abnormal user.

[0134] In a possible implementation, the preset threshold in the user identification module 203 includes: a mean balance coefficient threshold.

[0135] When the user identification module 203 identifies whether the target user in the target time period is the electricity abnormal user based on the peak period balance coefficient, the flat period balance coefficient, the valley period balance coefficient, and the preset threshold, the user identification module 203 is specifically configured to:

[0136] The mean balance coefficient is calculated based on the peak period balance coefficient, the flat period balance coefficient, and the valley period balance coefficient.

[0137] The mean balance coefficient is determined based on the mean balance coefficient threshold.

[0138] If the mean balance coefficient meets the fourth preset condition, the target user in the target time period is identified as the electricity abnormal user.

[0139] Figure 3 A schematic diagram of an electronic device is provided for the embodiments of the present application. As shown in the figure, the electronic device 3 of the embodiment includes a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30. The processor 30 implements the steps in each of the electricity abnormal user identification method embodiments described above when executing the computer program 32, for example. Figure 3 Figure 1 ​The steps 101-103 are shown. Alternatively, the processor 30 implements the functions of the modules in each of the above-described apparatus embodiments when executing the computer program 32, for example Figure 2 The functions of the modules 201-203 are shown.

[0140] The computer program 32 can be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 32 in the electronic device 3. For example, the computer program 32 can be divided into Figure 2 The modules 201-203 are shown.

[0141] The electronic device 3 can be a desktop computer, a notebook, a palm computer, a cloud server, and the like. The electronic device 3 can include, but is not limited to, the processor 30, the memory 31. Those skilled in the art can understand that Figure 3 The electronic device 3 is only an example and does not constitute a limitation on the electronic device 3, and can include more or fewer components than those shown, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus, and the like.

[0142] The processor 30 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0143] The memory 31 can be an internal storage unit of the electronic device 3, for example, a hard disk or a memory of the electronic device 3. The memory 31 can also be an external storage device of the electronic device 3, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. Further, the memory 31 can also include both the internal storage unit and the external storage device of the electronic device 3. The memory 31 is used to store the computer program and other programs and data required by the electronic device. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0144] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0145] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in detail in a certain embodiment can refer to the relevant description of other embodiments.

[0146] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0147] In the embodiments of the present application, it should be understood that the disclosed apparatus / equipment and method can be implemented in other manners. For example, the described apparatus / equipment embodiments are merely schematic. For example, the division of the modules or units is merely logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0148] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0149] In addition, each functional unit in the various embodiments of the present application can be integrated into a processing unit, or each unit can be physically present separately, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0150] The integrated module / unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by computer programs instructing related hardware, and the computer programs can be stored in a computer readable storage medium. When the processor executes the computer programs, the steps of the above-mentioned various user identification methods can be implemented. The computer programs include computer program codes, which can be in the form of source code, object code, executable files or some intermediate forms. The computer readable medium can include any entity or device capable of carrying the computer program codes, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer readable medium can include appropriate contents according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0151] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those ordinarily skilled in the art should understand: the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for identifying an abnormal user of electricity, characterized by, The method comprises: obtaining peak time period, flat time period and valley time period corresponding to peak time electricity consumption, flat time electricity consumption and valley time electricity consumption of a target user in each unit time period in a target time period; based on the peak time electricity consumption, the flat time electricity consumption and the valley time electricity consumption of each unit time period, respectively calculating the peak time electricity consumption ratio, the flat time electricity consumption ratio and the valley time electricity consumption ratio of each unit time period; the smallest M-bit peak time electricity consumption ratio in the peak time electricity consumption ratio of all unit time periods is recorded as a first peak time electricity consumption ratio set, the largest N-bit peak time electricity consumption ratio in the peak time electricity consumption ratio of all unit time periods is recorded as a second peak time electricity consumption ratio set, and the peak time period balance coefficient is calculated based on the first peak time electricity consumption ratio set and the second peak time electricity consumption ratio set; wherein M and N are positive integers; the smallest M-bit flat time electricity consumption ratio in the flat time electricity consumption ratio of all unit time periods is recorded as a first flat time electricity consumption ratio set, the largest N-bit flat time electricity consumption ratio in the flat time electricity consumption ratio of all unit time periods is recorded as a second flat time electricity consumption ratio set, and the flat time period balance coefficient is calculated based on the first flat time electricity consumption ratio set and the second flat time electricity consumption ratio set; the smallest M-bit valley time electricity consumption ratio in the valley time electricity consumption ratio of all unit time periods is recorded as a first valley time electricity consumption ratio set, the largest N-bit valley time electricity consumption ratio in the valley time electricity consumption ratio of all unit time periods is recorded as a second valley time electricity consumption ratio set, and the valley time period balance coefficient is calculated based on the first valley time electricity consumption ratio set and the second valley time electricity consumption ratio set; based on the peak time period balance coefficient, the flat time period balance coefficient, the valley time period balance coefficient and a preset threshold, whether the target user in the target time period is an electricity abnormal user is identified, and when the target user is an electricity abnormal user, an electricity abnormal user label is generated for the target user.

2. The method of claim 1, wherein, The preset threshold includes: a first preset threshold corresponding to the peak time period balance coefficient, a second preset threshold corresponding to the flat time period balance coefficient, and a third preset threshold corresponding to the valley time period; based on the peak time period balance coefficient, the flat time period balance coefficient, the valley time period balance coefficient and a preset threshold, whether the target user in the target time period is an electricity abnormal user is identified, and when the target user is an electricity abnormal user, an electricity abnormal user label is generated for the target user. based on the peak time period balance coefficient and the first preset threshold, whether the peak time period balance coefficient meets a first preset condition is judged, based on the flat time period balance coefficient and the second preset threshold, whether the flat time period balance coefficient meets a second preset condition is judged, and based on the valley time period balance coefficient and the third preset threshold, whether the valley time period balance coefficient meets a third preset condition is judged; if at least one of the peak time period balance coefficient meets the first preset condition, the flat time period balance coefficient meets the second preset condition and the valley time period balance coefficient meets the third preset condition is satisfied, it is identified that the target user in the target time period is an electricity abnormal user. 3.The method of claim 1, wherein, The preset threshold includes: an average balance coefficient threshold; The peak period equalization coefficient, the flat period equalization coefficient, and the valley period equalization coefficient are used to identify whether the target user in the target time period is an abnormal electricity user. An average equalization coefficient is calculated based on the peak period equalization coefficient, the flat period equalization coefficient, and the valley period equalization coefficient. It is judged whether the average equalization coefficient meets a fourth preset condition based on the average equalization coefficient and the average equalization coefficient threshold. If the average equalization coefficient meets the fourth preset condition, it is identified that the target user in the target time period is an abnormal electricity user. 4.The method of claim 1, wherein, Before obtaining the peak time electricity consumption, the flat time electricity consumption, and the valley time electricity consumption corresponding to the peak period, the flat period, and the valley period of each unit time period of the target user in the target time period, the following steps are further included. Obtain historical electricity consumption data of each unit time period of the target user in a historical time period. Cluster analysis is performed on the historical electricity consumption data to obtain a plurality of historical classified electricity consumption data. Determine the peak period, the flat period, and the valley period of each unit time period based on the plurality of historical classified electricity consumption data.

5. An abnormal user of electricity identification device, characterized by, The data acquisition module is configured to obtain the peak time electricity consumption, the flat time electricity consumption, and the valley time electricity consumption corresponding to the peak period, the flat period, and the valley period of each unit time period of the target user in the target time period. The coefficient calculation module is configured to calculate the peak time electricity consumption ratio, the flat time electricity consumption ratio, and the valley time electricity consumption ratio of each unit time period based on the peak time electricity consumption, the flat time electricity consumption, and the valley time electricity consumption of each unit time period, respectively; record the smallest M-bit peak time electricity consumption ratio in the peak time electricity consumption ratio of all unit time periods as a first peak time electricity consumption ratio set, record the largest N-bit peak time electricity consumption ratio in the peak time electricity consumption ratio of all unit time periods as a second peak time electricity consumption ratio set, and calculate the peak period equalization coefficient based on the first peak time electricity consumption ratio set and the second peak time electricity consumption ratio set; wherein M and N are positive integers; record the smallest M-bit flat time electricity consumption ratio in the flat time electricity consumption ratio of all unit time periods as a first flat time electricity consumption ratio set, record the largest N-bit flat time electricity consumption ratio in the flat time electricity consumption ratio of all unit time periods as a second flat time electricity consumption ratio set, and calculate the flat period equalization coefficient based on the first flat time electricity consumption ratio set and the second flat time electricity consumption ratio set; record the smallest M-bit valley time electricity consumption ratio in the valley time electricity consumption ratio of all unit time periods as a first valley time electricity consumption ratio set, record the largest N-bit valley time electricity consumption ratio in the valley time electricity consumption ratio of all unit time periods as a second valley time electricity consumption ratio set, and calculate the valley period equalization coefficient based on the first valley time electricity consumption ratio set and the second valley time electricity consumption ratio set. The user identification module is configured to identify whether the target user in the target time period is an abnormal electricity user based on the peak period equalization coefficient, the flat period equalization coefficient, and the valley period equalization coefficient, and generate an abnormal electricity user label for the target user if the target user is an abnormal electricity user. ​ 6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, wherein the computer program comprises the following steps of: receiving a request for a resource from a client; determining whether the client is authorized to access the resource; and if the client is authorized to access the resource, providing the resource to the client. The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 4.

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