Super-capacity electricity utilization detection method

Abstract

The invention discloses a super-capacity electricity consumption detection method. The method comprises the following steps: storing a user file table and an electricity quantity and electricity charge detail table obtained from a marketing system in a capacity detection database; wherein rated capacity related data of each user is recorded in the user file table, and actual capacity related data of each user is recorded in the electricity quantity and electricity charge detail table; generating an archive data table and an electric quantity data table of each user according to the user archive table and the electric quantity and electric charge detailed table; the archive data table and / or the electric quantity data table comprise a capacity abnormal result column of the user; for any user, judging whether the user uses power in a super-capacity manner or not according to the actual capacity related data, or judging whether the user uses power in a super-capacity manner or not according to the rated capacity related data and the actual capacity related data; and the judgment result is recorded in a capacity abnormity result column of the user. According to the technical scheme provided by the embodiment of the invention, the verification of the super-capacity electricity users can be realized, and the operation safety of the power system can be improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method for detecting over-capacity electricity consumption. Background Art

[0002] In the power system, if users replace transformers privately or use more electricity than the original transformer, it will cause safety hazards to the power supply and use equipment; and some distributed photovoltaic users have the behavior of providing grid-connected electricity by using more electricity than the original capacity to obtain high subsidies. Users' private photovoltaic power generation equipment also has certain safety hazards. Therefore, a method for discovering users who use more electricity than the original capacity is urgently needed to ensure the safe operation of the power system. Summary of the invention

[0003] The present invention provides an over-capacity electricity consumption detection method to realize the verification of over-capacity electricity users, which is beneficial to improving the operation safety of the power system.

[0004] The present invention provides a method for detecting overcapacity electricity consumption, comprising storing a user profile table and a detailed table of power consumption and electricity charges obtained from a marketing system in a capacity detection database; wherein the user profile table records the rated capacity-related data of each user, and the detailed table of power consumption and electricity charges records the actual capacity-related data of each user;

[0005] Generate a file data table and an electricity data table for each user according to the user file table and the electricity charge details table; wherein, for any user, the file data table records the rated capacity-related data of the user, the electricity data table records the actual capacity-related data of the user, and the file data table and / or the electricity data table contain a capacity abnormality result column for the user;

[0006] For any user: determine whether the user is using electricity in excess of capacity based on the actual capacity-related data, or determine whether the user is using electricity in excess of capacity based on the rated capacity-related data and the actual capacity-related data; and record the determination result in the capacity abnormality result column of the user.

[0007] Optionally, the user includes a dedicated transformer user, and for the dedicated transformer user, it is determined whether the user consumes electricity in excess of capacity based on the rated capacity related data and the actual capacity related data.

[0008] Optionally, for the dedicated transformer user, the rated capacity-related data includes: the unit time operating capacity of the transformer associated with the user; the actual capacity-related data includes: the total monthly electricity consumption;

[0009] The determining whether the user exceeds the capacity of electricity consumption according to the rated capacity related data and the actual capacity related data includes:

[0010] When the total monthly electricity consumption is greater than the product of the unit time operating capacity and the total monthly operating time, the total electricity consumption of the dedicated transformer users is determined to be abnormal, and the judgment result is recorded as the total electricity consumption of the dedicated transformer users exceeding the capacity.

[0011] Optionally, the actual capacity related data further includes: monthly peak power, monthly average power and monthly valley power;

[0012] The step of judging whether the user exceeds the capacity of electricity consumption according to the rated capacity related data and the actual capacity related data further includes:

[0013] When the monthly total electricity is less than or equal to the product of the unit time operation capacity and the monthly total operation time, the monthly peak electricity determination step, the monthly average electricity determination step and the monthly valley electricity determination step are respectively performed;

[0014] The monthly peak power judgment step includes: when the monthly peak power is greater than the product of the unit time operation capacity and the monthly peak operation time, determining that the dedicated transformer user peak power is abnormal, and recording the judgment result as the dedicated transformer user peak power exceeding capacity power consumption;

[0015] The monthly average power judgment step includes: when the monthly average power is greater than the product of the unit time operation capacity and the monthly average operation time, determining that the dedicated transformer user average power is abnormal, and recording the judgment result as the dedicated transformer user average power exceeding capacity power consumption;

[0016] The monthly valley electricity quantity judgment step includes: when the monthly valley electricity quantity is greater than the product of the unit time operation capacity and the monthly valley operation time, determining that the dedicated transformer user valley electricity quantity is abnormal, and recording the judgment result as the dedicated transformer user valley electricity quantity exceeding capacity consumption.

[0017] Optionally, for the dedicated transformer user, the rated capacity-related data includes: the unit time operating capacity of the transformer associated with the user; the actual capacity-related data includes: the total monthly electricity consumption;

[0018] The over-capacity electricity consumption detection method further comprises:

[0019] For any user of the dedicated transformer, when the total monthly electricity consumption is not equal to zero and the operating capacity per unit time is zero, it is determined that the operating capacity is abnormal, and the determination result is recorded as abnormal operating capacity.

[0020] Optionally, the user includes a distributed photovoltaic user, and for the distributed photovoltaic user, it is determined whether the user uses electricity in excess of capacity based on the actual capacity-related data.

[0021] Optionally, for the distributed photovoltaic user, the actual capacity-related data includes: monthly power generation and monthly grid-connected power;

[0022] The determining whether the user has exceeded the capacity of electricity consumption based on the actual capacity-related data includes: when the monthly power generation of the distributed photovoltaic user in the previous month is less than the monthly online power generation of the previous month, and the absolute value of the difference between the monthly power generation of the previous month and the monthly online power generation of the previous month is greater than a preset threshold, determining that the distributed photovoltaic user has exceeded the capacity of electricity consumption.

[0023] Optionally, the user includes a distributed photovoltaic user, and for the distributed photovoltaic user, it is determined whether the user uses electricity in excess of capacity based on the rated capacity related data and the actual capacity related data.

[0024] Optionally, for the distributed photovoltaic user, the actual capacity-related data includes: monthly power generation; the rated capacity-related data includes: the reported capacity of photovoltaic power generation of the distributed photovoltaic user;

[0025] Judging whether the user uses electricity in excess of capacity according to the rated capacity related data and the actual capacity related data includes:

[0026] When the sum of the monthly power generation of the distributed photovoltaic user in the past 12 months is greater than the product of the reported capacity and the annual power generation time, it is determined that the distributed photovoltaic user is consuming electricity in excess of capacity.

[0027] Optionally, the over-capacity electricity consumption detection method further includes:

[0028] When the data in the user profile table and the electricity consumption and fee detailed table of the marketing system changes, the capacity detection database is updated according to the data change record.

[0029] The technical solution of the embodiment of the present invention establishes a capacity detection database dedicated to over-capacity electricity consumption detection, and provides a method for screening and judging whether a user is over-capacity electricity consumption based on the capacity detection database. The capacity detection database stores a user profile table and a detailed table of electricity consumption and electricity charges obtained from the marketing system, and the archive data table and the electricity data table of each user can be obtained according to the user profile table and the detailed table of electricity consumption and electricity charges, and then the user's rated capacity-related data and the user's actual capacity-related data are obtained to judge whether the user is over-capacity electricity consumption. Furthermore, a capacity abnormality result column is also provided in the archive data table and / or the electricity data table, and the judgment result is recorded in the user's capacity abnormality result column, so that the judgment result can be intuitively visible. By making an abnormal judgment on the user's electricity consumption based on the method of establishing a capacity detection database, business personnel can focus on checking users with abnormalities or high probability of abnormalities, and promptly discover users who violate the law in electricity consumption, which can reduce illegal and irregular behaviors, improve the operational safety of the power system, and improve the safety of social public electricity consumption.

[0030] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 A flowchart of an over-capacity power consumption detection method provided according to an embodiment of the present invention;

[0033] Figure 2 A flowchart of a method for detecting over-capacity power consumption of a dedicated transformer user according to an embodiment of the present invention;

[0034] Figure 3 The present invention provides a flow chart of a method for detecting over-capacity electricity consumption of distributed photovoltaic users according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] Figure 1 This is a flow chart of an overcapacity power consumption detection method provided according to an embodiment of the present invention, referring to Figure 1 , the over-capacity power consumption detection methods include:

[0038] S101. The user profile table and the detailed table of electricity consumption and electricity charges obtained from the marketing system are stored in the capacity detection database; wherein the user profile table records the rated capacity-related data of each user, and the detailed table of electricity consumption and electricity charges records the actual capacity-related data of each user.

[0039] Among them, the user profile table and the detailed record table of electricity consumption and electricity charges can be queried from the marketing system, and the relevant data of each user can be extracted from the user profile table and the detailed record table of electricity consumption and electricity charges.

[0040] Specifically, a capacity detection database is established, and the user profile table and the power consumption and electricity fee details table obtained from the marketing system are stored in the capacity detection database, which is equivalent to completing the initialization of the capacity detection database. The rated capacity-related data of each user can be extracted from the user profile table, and the actual capacity-related data of each user can be extracted from the power consumption and electricity fee details table. Exemplarily, the rated capacity-related data may include the rated capacity of the transformer equipment associated with the user; the actual capacity-related data may include the user's power consumption, power generation, and online power.

[0041] S102. Generate a file data table and a power data table for each user based on the user file table and the power consumption and electricity fee details table; wherein, for any user, the file data table records the user's rated capacity related data, the power data table records the user's actual capacity related data, and the file data table and / or the power data table contains the user's capacity abnormality result column.

[0042] Specifically, according to the user archive table and the detailed table of electricity consumption and electricity charges, a data table is created in the capacity detection database on a household basis, and the data table created for each user includes an archive data table and an electricity consumption data table. Among them, the properties of the archive data table and the relevant data table in the user archive table correspond one to one, and both the archive data table and the user archive table can include a user name (or account number, or any identifier that can represent the user's identity) part and an archive data part. The difference is that the archive data table is a data table for a single user, and its archive data part can only store data related to over-capacity electricity consumption, so as to subsequently verify whether a single user has over-capacity electricity consumption; the user archive table is a general data table containing all users, storing all archive information of all users. And, the properties of the relevant data tables in the electricity data table and the electricity fee details table correspond one to one, and both the electricity data table and the electricity fee details table can include a user name (or account number, or any identifier that can represent the user's identity) part and an electricity fee data part. The difference is that the electricity data table is a data table for a single user, and its electricity data part can only store data related to overcapacity electricity consumption, so as to subsequently verify whether a single user is overcapacity electricity consumption; the electricity fee details table is a total data table containing all users, storing all electricity fee information for all users. It can be understood that, according to the type of actual data, the user name part, the archive data part and the electricity fee data part in each table can specifically include one or more columns of data, which are not specifically limited here. In addition, the capacity abnormality result column of the user can be set in the archive data table and / or the electricity data table to record the user's overcapacity electricity consumption, and the setting position of the capacity abnormality result column can be selected according to demand. By setting the capacity abnormality result column, when the user exceeds the capacity electricity consumption, it can be displayed at the corresponding position of the table, so that the business personnel can be reminded to focus on it.

[0043] For any user, you can first generate a blank archive data table and an electricity data table according to the format of the user archive table and the electricity consumption and fee details table, and add a capacity abnormality result column. Then, extract the user's rated capacity-related data from the user archive table and add it to the archive data table, and extract the user's actual capacity-related data from the electricity consumption and fee details table and add it to the electricity data table; and after determining whether the user is using electricity in excess of capacity, add the determination result to the capacity abnormality result column.

[0044] S103. For any user: determine whether the user's electricity consumption exceeds the capacity according to the actual capacity-related data, or determine whether the user's electricity consumption exceeds the capacity according to the rated capacity-related data and the actual capacity-related data; and record the determination result in the user's capacity abnormality result column.

[0045] Specifically, according to different user types, a specific judgment method can be adaptively selected. For example, for dedicated transformer users (such as dedicated line dedicated transformer users or public line dedicated transformer users), the rated capacity-related data and actual capacity-related data can be compared to judge the user's electricity consumption and determine whether the user's electricity consumption exceeds the capacity. For distributed photovoltaic users, the user's photovoltaic power generation situation can be directly judged based on the actual capacity-related data, or by comparing the rated capacity-related data and the actual capacity-related data, to determine whether the user's photovoltaic power generation is operating beyond the capacity.

[0046] The technical solution of the embodiment of the present invention establishes a capacity detection database dedicated to over-capacity electricity consumption detection, and provides a method for screening and judging whether a user is over-capacity electricity consumption based on the capacity detection database. The capacity detection database stores a user profile table and a detailed table of electricity consumption and electricity charges obtained from the marketing system, and the archive data table and the electricity data table of each user can be obtained according to the user profile table and the detailed table of electricity consumption and electricity charges, and then the user's rated capacity-related data and the user's actual capacity-related data are obtained to judge whether the user is over-capacity electricity consumption. Furthermore, a capacity abnormality result column is also provided in the archive data table and / or the electricity data table, and the judgment result is recorded in the capacity abnormality result column, so that the judgment result can be intuitively visible. By making an abnormal judgment on the user's electricity consumption based on the method of establishing a capacity detection database, business personnel can focus on checking users with abnormalities or high probability of abnormalities, and promptly discover users who violate the law in electricity consumption, which can reduce illegal and irregular behaviors, improve the operational safety of the power system, and improve the safety of social public electricity consumption.

[0047] It is understandable that when the data in the user profile table and the electricity consumption and fee detailed table of the marketing system changes, the capacity detection database is updated according to the data change record, such as updating the user profile table and the electricity consumption and fee detailed table, and updating each profile data table and electricity consumption data table. In this way, the timeliness of the capacity detection database can be guaranteed, and the accuracy of over-capacity electricity consumption detection can be further guaranteed.

[0048] Based on the above embodiment, optionally, the user may exemplarily include a dedicated transformer user and a distributed photovoltaic user. The method for detecting over-capacity electricity consumption for a dedicated transformer user is different from the method for detecting over-capacity electricity consumption for a distributed photovoltaic user, which are described separately below.

[0049] In one embodiment, optionally, the user includes a dedicated transformer user. For the dedicated transformer user, it is determined whether the user is using electricity in excess of capacity based on the rated capacity-related data and the actual capacity-related data. Among them, the rated capacity-related data of the dedicated transformer user may include the unit time operating capacity of the transformer associated with the user and the reported capacity of the transformer (or contract capacity), etc., and the actual capacity-related data may include the monthly electricity consumption (specifically, it may include the monthly total electricity, monthly peak electricity, monthly average electricity, and monthly valley electricity). Exemplarily, it may be determined whether the user is using electricity in excess of capacity based on the unit time operating capacity and the monthly electricity consumption. The method for detecting over-capacity electricity consumption of dedicated transformer users is described in detail below.

[0050] Optionally, for dedicated transformer users, the actual capacity-related data includes: monthly total electricity consumption. Judging whether the user is using electricity in excess of capacity based on the rated capacity-related data and the actual capacity-related data includes:

[0051] When the total monthly electricity consumption is greater than the product of the operating capacity per unit time and the total monthly operating time, the total electricity consumption of the dedicated transformer users is judged to be abnormal, and the judgment result is recorded as the total electricity consumption of the dedicated transformer users exceeding the capacity.

[0052] The unit time operation capacity can be specifically understood as the capacity of the transformer when it is running at full load per hour. The total monthly operation time can be specifically understood as the product of 24 hours and the number of days in the month. For example, the total monthly operation time can be the product of 24 hours and 30 days, or the product of 24 hours and 31 days.

[0053] Furthermore, the determination result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0054] Based on the above embodiments, optionally, the actual capacity-related data further includes: monthly peak electricity, monthly average electricity and monthly valley electricity.

[0055] Judging whether the user uses electricity in excess of capacity according to the rated capacity related data and the actual capacity related data, further comprising:

[0056] When the monthly total electricity is less than or equal to the product of the operating capacity per unit time and the monthly total operating time, the monthly peak electricity judging step, the monthly average electricity judging step or the monthly valley electricity judging step is respectively executed.

[0057] The monthly peak electricity consumption judgment step includes: when the monthly peak electricity consumption is greater than the product of the operating capacity per unit time and the monthly peak operating time, it is determined that the peak electricity consumption of the dedicated transformer user is abnormal, and the judgment result is recorded as the peak electricity consumption of the dedicated transformer user exceeding the capacity.

[0058] The peak power consumption can be specifically understood as the power consumed by the user during peak hours. The monthly peak operation time can be specifically understood as the product of the daily peak operation time and the number of days in the month. For example, if the daily peak operation time is 7 hours, the monthly peak operation time can be the product of 7 hours and 30 days, or it can be the product of 7 hours and 31 days.

[0059] Furthermore, the determination result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0060] The steps of judging the monthly average electricity consumption include: when the monthly average electricity consumption is greater than the product of the operating capacity per unit time and the monthly average operating time, judging that the average electricity consumption of the dedicated transformer user is abnormal, and recording the judgment result as the average electricity consumption of the dedicated transformer user exceeding the capacity.

[0061] The average power consumption can be specifically understood as the power consumption between the peak hours and the off-peak hours. The monthly average operation time can be specifically understood as the product of the daily average operation time and the number of days in the month. For example, if the daily average operation time is 9 hours, the monthly peak operation time can be the product of 9 hours and 30 days, or it can be the product of 9 hours and 31 days.

[0062] Furthermore, the determination result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0063] The monthly valley electricity consumption judgment step includes: when the monthly valley electricity consumption is greater than the product of the operating capacity per unit time and the monthly valley operating time, it is determined that the valley electricity consumption of the dedicated transformer user is abnormal, and the judgment result is recorded as the valley electricity consumption of the dedicated transformer user exceeding the capacity.

[0064] The valley power consumption can be specifically understood as the power used by the user during the off-peak period. The monthly valley operation time can be specifically understood as the product of the daily valley operation time and the number of days in the month. For example, if the daily valley operation time is 8 hours, the monthly peak operation time can be the product of 8 hours and 30 days, or it can be the product of 8 hours and 31 days.

[0065] Furthermore, the determination result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0066] Optionally, for dedicated transformer users, when judging whether the user is using electricity beyond capacity, the operating time of each type can be appropriately set to allow the operating time deviation threshold to avoid misjudgment. Exemplarily, the operating time deviation threshold can be within 20%. Taking the operating time deviation threshold of 20% as an example, the total monthly operating time can be the product of 24 hours and the number of days in the month multiplied by 120%. The same applies to the monthly peak operating time, monthly average operating time, and monthly valley operating time, which will not be repeated.

[0067] Figure 2 This is a flowchart of a method for detecting over-capacity power consumption of a dedicated transformer user according to an embodiment of the present invention, referring to Figure 2 Based on the above embodiment, optionally, the method for detecting over-capacity electricity consumption includes:

[0068] S201. Store the user profile table and power consumption and fee details table obtained from the marketing system in the capacity detection database.

[0069] S202. Generate an archive data table and an electricity data table for each dedicated transformer user based on the user archive table and the electricity consumption and electricity fee details table; wherein, for any user, the archive data table records the unit time operating capacity of the user's associated transformer, and the electricity data table records the user's monthly total electricity, monthly peak electricity, monthly average electricity and monthly valley electricity, and the archive data table and / or electricity data table contains the user's capacity abnormality result column.

[0070] S203, determine whether the total monthly power consumption is greater than the product of the operating capacity per unit time and the total monthly operating time; if so, execute S204; if not, execute S205-S207.

[0071] This step can be specifically understood as: when the total monthly electricity consumption is greater than the product of the operating capacity per unit time and the total monthly operating time, execute S204; when the total monthly electricity consumption is less than or equal to the product of the operating capacity per unit time and the total monthly operating time, execute the monthly peak electricity consumption judgment step (S205), the monthly average electricity consumption judgment step (S206) and the monthly valley electricity consumption judgment step (S207) respectively.

[0072] S204, determining that the total power consumption of the dedicated transformer users is abnormal, and outputting in the user's capacity abnormality result column that the total power consumption of the dedicated transformer users exceeds the capacity power consumption.

[0073] S205. When the monthly peak power consumption is greater than the product of the operating capacity per unit time and the monthly peak operating time, it is determined that the peak power consumption of the dedicated transformer user is abnormal, and the peak power consumption of the dedicated transformer user exceeds the capacity consumption is output in the user's capacity abnormality result column.

[0074] S206. When the monthly average power consumption is greater than the product of the operating capacity per unit time and the monthly average operating time, it is determined that the average power consumption of the dedicated transformer user is abnormal, and the special transformer user average power consumption exceeding the capacity is output in the user's capacity abnormality result column.

[0075] S207. When the monthly valley electricity consumption is greater than the product of the operating capacity per unit time and the monthly valley operating time, it is determined that the valley electricity consumption of the dedicated transformer user is abnormal, and the valley electricity consumption of the dedicated transformer user exceeds the capacity consumption is output in the user's capacity abnormality result column.

[0076] The technical solution of the embodiment of the present invention can quickly determine the specific type of over-capacity electricity consumption when a dedicated transformer user consumes electricity in excess of capacity, and can improve the integrity and effectiveness of data stored in the capacity detection database. It can also improve the timeliness of checking over-capacity electricity consumption by dedicated transformer users, and can reduce illegal electricity theft.

[0077] It is understandable that steps S203 to S207 need to be executed for each dedicated transformer user. In addition, when the total power of a dedicated transformer user is abnormal, steps S205 to S207 can be further executed, that is, when the total power of a dedicated transformer user is judged to be abnormal, the peak power of the dedicated transformer user, the average power of the dedicated transformer user, or the valley power of the dedicated transformer user can be further judged.

[0078] Optionally, based on the above embodiments, for dedicated transformer users, the over-capacity power consumption detection method further includes:

[0079] For any dedicated transformer user, when the total electricity consumption in the month is not equal to zero and the operating capacity per unit time is zero, the operating capacity is judged to be abnormal, and the judgment result is recorded as abnormal operating capacity.

[0080] Specifically, when the total monthly electricity is not zero, it indicates that energy consumption is generated due to the operation of the equipment. When the operating capacity per unit time is zero, it indicates that the actual output capacity of the transformer per unit time is zero. For example, the transformer may be in a shutdown state, a fault state, or an abnormal working state. Therefore, when the total monthly electricity is not equal to zero and the operating capacity per unit time is zero, it is regarded as an abnormality, indicating that the operating capacity is abnormal, and the judgment result is recorded as an abnormal operating capacity. Furthermore, the judgment result can be recorded in the capacity abnormality result column of the user in the archive data table and / or the electricity data table. By judging whether the operating capacity of the transformer is abnormal, the normal operation of the equipment and the stability of the power system can be guaranteed.

[0081] In another embodiment, optionally, the user includes a distributed photovoltaic user. For the distributed photovoltaic user, it can be determined whether the user is using electricity in excess of capacity based on actual capacity-related data, or it can be determined whether the user is using electricity in excess of capacity based on rated capacity-related data and actual capacity-related data. The method for detecting over-capacity electricity consumption of distributed photovoltaic users is described in detail below.

[0082] In one embodiment, for distributed photovoltaic users, the actual capacity-related data may include: monthly power generation and monthly grid-connected power. Distributed photovoltaic users have power generation meters (i.e., electric energy meters, specifically electric energy meters for the power generated by distributed photovoltaic users), and the power generated by distributed photovoltaics is the power generation; distributed photovoltaic users also have power purchase meters (i.e., electric energy meters, specifically electric energy meters for the power supply bureau to purchase power), and the power purchased by the power supply bureau is the grid-connected power.

[0083] In this case, it can be determined whether the user is using electricity in excess of capacity based on actual capacity-related data, specifically: when the monthly power generation of the distributed photovoltaic user last month is less than the monthly online power generation of the previous month, and the absolute value of the difference between the monthly power generation of the previous month and the monthly online power generation of the previous month is greater than the preset threshold, it is determined that the distributed photovoltaic user is using electricity in excess of capacity.

[0084] For example, the preset threshold value may be 10kW. When the monthly power generation of the previous month is less than the monthly grid-connected power of the previous month, and the absolute value of the difference between the monthly power generation of the previous month and the monthly grid-connected power of the previous month is greater than 10kW, it is considered abnormal, indicating that the distributed photovoltaic user is using electricity at an excess capacity. Further, the judgment result may be recorded as the distributed photovoltaic user is operating at an excess capacity, and the judgment result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0085] In another embodiment, optionally, for distributed photovoltaic users, the actual capacity-related data include: monthly power generation; the rated capacity-related data include: the reported capacity (or contract capacity) of photovoltaic power generation of distributed photovoltaic users. The reported capacity can be specifically understood as the rated power generation capacity of the entire photovoltaic system of the distributed photovoltaic user.

[0086] In this case, it can be determined whether the user is using electricity in excess of capacity based on the rated capacity-related data and the actual capacity-related data. Specifically, when the sum of the monthly power generation of distributed photovoltaic users in the past 12 months is greater than the product of the reported capacity and the annual power generation time, it is determined that the distributed photovoltaic user is using electricity in excess of capacity.

[0087] The annual power generation time can be specifically understood as the annual power generation hours, for example, 1000 hours. Furthermore, the annual power generation hours can appropriately set the upper limit of power generation time fluctuation to avoid misjudgment. Then, the annual power generation time can be the product of the annual power generation hours and the upper limit of power generation time fluctuation. Exemplarily, the upper limit of power generation time fluctuation can be greater than 100% and less than or equal to 140%.

[0088] Furthermore, the determination result may be recorded in the capacity abnormality result column of the user in the archive data table and / or the power data table.

[0089] Figure 3 This is a flow chart of a method for detecting excessive power consumption of distributed photovoltaic users according to an embodiment of the present invention, with reference to Figure 3 Based on the above embodiments, the over-capacity power consumption detection method includes:

[0090] S301. Store the user profile table and power consumption and electricity fee details table obtained from the marketing system in the capacity detection database.

[0091] S302. Generate an archive data table and an electricity data table for each distributed photovoltaic user based on the user archive table and the electricity consumption and electricity fee details table; wherein, for any user, the archive data table records the user's photovoltaic power generation capacity, and the electricity data table records the user's power generation and online electricity, and the archive data table and / or electricity data table contains the user's capacity abnormality result column.

[0092] S303, determine whether the following conditions are met at the same time: the monthly power generation of the distributed photovoltaic user last month is less than the monthly grid-connected power generation last month, and the absolute value of the difference between the monthly power generation last month and the monthly grid-connected power generation last month is greater than a preset threshold; if so, execute S305; if not, end.

[0093] S304, determine whether the sum of the monthly power generation of the distributed photovoltaic users in the past 12 months is greater than the product of the reported capacity and the annual power generation time; if so, execute S305; if not, end.

[0094] S305: Determine whether the distributed photovoltaic user is using electricity in excess of its capacity, and output the distributed photovoltaic user's over-capacity operation in the user's capacity abnormality result column.

[0095] The technical solution of the embodiment of the present invention can timely discover defaulting users by judging whether distributed photovoltaic users are operating in excess of capacity, and can prevent some distributed photovoltaic users from obtaining high subsidies by providing online electricity in excess of capacity and defrauding government subsidies.

[0096] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0097] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting excessive power consumption, characterized in that: include: The user profile table and the detailed table of power consumption and electricity charges obtained from the marketing system are stored in the capacity detection database; wherein the user profile table records the rated capacity-related data of each user, and the detailed table of power consumption and electricity charges records the actual capacity-related data of each user; Generate a file data table and an electricity data table for each user according to the user file table and the electricity charge details table; wherein, for any user, the file data table records the rated capacity-related data of the user, the electricity data table records the actual capacity-related data of the user, and the file data table and / or the electricity data table contain a capacity abnormality result column for the user; For any user: determine whether the user is using electricity in excess of capacity based on the actual capacity-related data, or determine whether the user is using electricity in excess of capacity based on the rated capacity-related data and the actual capacity-related data; and record the determination result in the capacity abnormality result column of the user.

2. The method for detecting excessive power consumption according to claim 1, characterized in that: The users include dedicated transformer users. For the dedicated transformer users, it is determined whether the users use electricity in excess of capacity based on the rated capacity related data and the actual capacity related data.

3. The method for detecting excessive power consumption according to claim 2, characterized in that: For the dedicated transformer user, the rated capacity related data includes: the unit time operating capacity of the transformer associated with the user; the actual capacity related data includes: the total monthly electricity; The determining whether the user exceeds the capacity of electricity consumption according to the rated capacity related data and the actual capacity related data includes: When the total monthly electricity consumption is greater than the product of the unit time operating capacity and the total monthly operating time, the total electricity consumption of the dedicated transformer users is determined to be abnormal, and the judgment result is recorded as the total electricity consumption of the dedicated transformer users exceeding the capacity.

4. The method for detecting excessive power consumption according to claim 3, characterized in that: The actual capacity related data also includes: monthly peak power, monthly average power and monthly valley power; The step of judging whether the user exceeds the capacity of electricity consumption according to the rated capacity related data and the actual capacity related data further includes: When the monthly total electricity is less than or equal to the product of the unit time operation capacity and the monthly total operation time, the monthly peak electricity determination step, the monthly average electricity determination step and the monthly valley electricity determination step are respectively performed; The monthly peak power judgment step includes: when the monthly peak power is greater than the product of the unit time operation capacity and the monthly peak operation time, determining that the dedicated transformer user peak power is abnormal, and recording the judgment result as the dedicated transformer user peak power exceeding capacity power consumption; The monthly average power judgment step includes: when the monthly average power is greater than the product of the unit time operation capacity and the monthly average operation time, determining that the dedicated transformer user average power is abnormal, and recording the judgment result as the dedicated transformer user average power exceeding capacity power consumption; The monthly valley electricity quantity judgment step includes: when the monthly valley electricity quantity is greater than the product of the unit time operation capacity and the monthly valley operation time, determining that the dedicated transformer user valley electricity quantity is abnormal, and recording the judgment result as the dedicated transformer user valley electricity quantity exceeding capacity consumption.

5. The method for detecting excessive power consumption according to any one of claims 2 to 4, characterized in that: For the dedicated transformer user, the rated capacity related data includes: the unit time operating capacity of the transformer associated with the user; the actual capacity related data includes: the total monthly electricity; The over-capacity electricity consumption detection method further comprises: For any user of the dedicated transformer, when the total monthly electricity consumption is not equal to zero and the operating capacity per unit time is zero, it is determined that the operating capacity is abnormal, and the determination result is recorded as abnormal operating capacity.

6. The method for detecting excessive power consumption according to claim 1, characterized in that: The users include distributed photovoltaic users. For the distributed photovoltaic users, it is determined whether the users use electricity in excess of capacity based on the actual capacity related data.

7. The method for detecting excessive power consumption according to claim 6, characterized in that: For the distributed photovoltaic users, the actual capacity-related data include: monthly power generation and monthly grid-connected power; The determining whether the user has exceeded the capacity of electricity consumption based on the actual capacity-related data includes: when the monthly power generation of the distributed photovoltaic user in the previous month is less than the monthly online power generation of the previous month, and the absolute value of the difference between the monthly power generation of the previous month and the monthly online power generation of the previous month is greater than a preset threshold, determining that the distributed photovoltaic user has exceeded the capacity of electricity consumption.

8. The method for detecting excessive power consumption according to claim 1, characterized in that: The users include distributed photovoltaic users. For the distributed photovoltaic users, it is determined whether the users use electricity in excess of capacity based on the rated capacity related data and the actual capacity related data.

9. The method for detecting excessive power consumption according to claim 8, characterized in that: For the distributed photovoltaic users, the actual capacity-related data include: monthly power generation; the rated capacity-related data include: the reported capacity of photovoltaic power generation of the distributed photovoltaic users; Judging whether the user uses electricity in excess of capacity according to the rated capacity related data and the actual capacity related data includes: When the sum of the monthly power generation of the distributed photovoltaic user in the past 12 months is greater than the product of the reported capacity and the annual power generation time, it is determined that the distributed photovoltaic user is consuming electricity in excess of capacity.

10. The method for detecting excessive power consumption according to claim 1, characterized in that: Also includes: When the data in the user profile table and the electricity consumption and fee detailed table of the marketing system changes, the capacity detection database is updated according to the data change record.

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