CN117035678B

CN117035678B - Multi-dimensional electric charge accounting method and device based on big data

Info

Publication number: CN117035678B
Application number: CN202311050211.1A
Authority: CN
Inventors: 应彩霞; 曹瑞峰; 赵萍; 侯素颖; 袁婷; 林少娃; 吴彬锋; 季李昕; 李莹; 姚雅艳; 叶子强; 吴伟玲; 徐璟; 方智淳; 陈麟红
Original assignee: State Grid Zhejiang Electric Power Co Ltd; Lishui Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Current assignee: State Grid Zhejiang Electric Power Co Ltd; Lishui Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Priority date: 2023-08-18
Filing date: 2023-08-18
Publication date: 2024-03-26
Anticipated expiration: 2043-08-18
Also published as: CN117035678A

Abstract

The invention provides a multi-dimensional electric charge accounting method and device based on big data, comprising the following steps: the server acquires multidimensional data of targets to be detected corresponding to all connected intelligent electric meters in the target area, and sequences all the targets to be detected according to the position dimension information and the industry dimension information to obtain a first sequencing list; the server classifies and adjusts the corresponding targets to be detected in the first sorting list according to the position quantization information and the attribute quantization information to obtain a second sorting list, and performs segmentation processing on the second sorting list to obtain a plurality of sorting segments; the server screens the sub-electric charge values in the electric charge calculation value group according to the attribute quantization information of the target to be detected to determine a target attribute tag corresponding to the target sub-electric charge value; generating a total configuration table according to the fusion setting of the batch configuration data and the second ordering list; and the server performs batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table.

Description

Multi-dimensional electric charge accounting method and device based on big data

Technical Field

The invention relates to a data processing technology, in particular to a multidimensional electricity fee accounting method and device based on big data.

Background

The differential electricity price system is a price strategy for the power supply enterprises to market the electric power commodities, and is a price marketing strategy for the power supply enterprises to properly correct the basic price to sell the electric power commodities according to the specific situation of the users on the electric power demand. In order for the smart meter to perform rapid calculation of the electricity charge, data such as the electricity price needs to be configured for the smart meter in advance, and the difference electricity price can cause the electricity price configured by the smart meter to be different.

In the prior art, when data configuration is performed on the smart meter in a target area, the configuration efficiency is low due to manual one-by-one configuration, and when the configuration quantity is large, the installation and the use of the smart meter are affected.

Therefore, how to combine the multidimensional installation attribute of the intelligent ammeter to perform batch data configuration improves the configuration efficiency, and becomes a problem to be solved urgently.

Disclosure of Invention

The embodiment of the invention provides a multi-dimensional electric charge accounting method and device based on big data, which can be used for carrying out batch data configuration by combining with multi-dimensional installation attributes of intelligent electric meters, and improve configuration efficiency.

In a first aspect of the embodiment of the present invention, a multi-dimensional electricity fee accounting method based on big data is provided, including:

The method comprises the steps that a server obtains multidimensional data of targets to be detected corresponding to all connected intelligent electric meters in a target area, wherein the multidimensional data at least comprise position dimension information and industry dimension information, and a first sorting list is obtained by sorting all the targets to be detected according to the position dimension information and the industry dimension information;

the server respectively determines corresponding position quantization information and attribute quantization information according to the position dimension information and the industry attribute information, and the attribute quantization information of each object to be detected belongs to one quantization value in the corresponding position quantization information;

the server classifies and adjusts the corresponding targets to be detected in the first sorting list according to the position quantization information and the attribute quantization information to obtain a second sorting list, and performs segmentation processing on the second sorting list to obtain a plurality of sorting segments;

the server determines an electric charge calculation value group corresponding to each sequencing segment according to the position quantization information, generates an attribute tag corresponding to each sub-electric charge value in the electric charge calculation value group, and screens the sub-electric charge value in the electric charge calculation value group according to the attribute quantization information of the object to be detected to determine a target attribute tag corresponding to the target sub-electric charge value;

Generating batch configuration data of the corresponding sorting sections according to the electric charge calculation value group and the target attribute label corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table;

and the server performs batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table, and the intelligent electric meter performs configuration of an electric charge calculation value group and a sub-electric charge value and performs electric charge accounting according to the configured data.

Optionally, in one possible implementation manner of the first aspect, the method further includes:

if the server judges that the first industry dimension information of the change of the target to be detected input by the management end is received, determining a second target attribute tag of the target to be detected, traversing the total configuration table, and determining a first target attribute tag corresponding to the first industry dimension information;

generating a corresponding label replacement group according to the second target attribute label and the first target attribute label, and sending the label replacement group to the intelligent ammeter;

after the intelligent ammeter receives the label replacement group, a first target sub-electric charge value is determined in the electric charge calculation value group according to the first target attribute label, and the first target sub-electric charge value is replaced with the previous sub-electric charge value.

Optionally, in one possible implementation manner of the first aspect, the server obtains multidimensional data of objects to be detected corresponding to all connected smart meters in the target area, where the multidimensional data at least includes location dimension information and industry dimension information, and the ranking of all the objects to be detected according to the location dimension information and the industry dimension information obtains a first ranking list, including:

dividing the target area into a plurality of subareas according to the area division configuration information of the user on the target area, initializing a sequencing list, and dividing the sequencing list into a plurality of list subareas according to the plurality of subareas;

classifying the targets to be detected into corresponding list subareas according to the position dimension information of the targets to be detected;

and sequentially traversing industry dimension information of the target to be detected in the sub-region of the list, and if the industry dimension information of the target to be detected traversed after judgment is the same as the industry dimension information of the target to be detected traversed before, moving the target to be detected traversed after judgment to the adjacent rear part of the target to be detected traversed before to form a first sequencing list.

Optionally, in one possible implementation manner of the first aspect, the determining, by the server, corresponding location quantization information and attribute quantization information according to the location dimension information and industry attribute information, respectively, where the attribute quantization information of each object to be detected belongs to one quantization value in the corresponding location quantization information includes:

The server determines corresponding position quantization information according to the position dimension information, wherein the position quantization information comprises electric charge calculation value groups corresponding to different industries at corresponding positions;

and determining attribute quantization information of the corresponding industry at the corresponding position according to the industry attribute information, wherein the attribute quantization information is a sub-electricity fee value of the corresponding industry at the corresponding position.

Optionally, in one possible implementation manner of the first aspect, the server classifies and adjusts the target to be detected corresponding to the first ordered list according to the location quantization information and the attribute quantization information to obtain a second ordered list, and performs segmentation processing on the second ordered list to obtain a plurality of ordered segments, including:

sequentially traversing the position quantization information of all list subareas in the first sequencing list, comparing the traversed list subareas with the position quantization information of the previously traversed list subareas, and determining the first quantity of sub-electric charge values of the same industry;

determining a list subarea corresponding to the largest first number of each list subarea as a first adjacent list subarea, and counting the second number of each list subarea as the first list subareas of other list subareas;

And sequencing the corresponding list subareas according to the second quantity to obtain a second sequencing list, and segmenting the list subareas in the second sequencing list according to the first quantity to obtain a plurality of sequencing segments.

Optionally, in one possible implementation manner of the first aspect, the sorting the corresponding list sub-areas according to the second number to obtain a second sorted list, and performing a segmentation process on the multiple list sub-areas in the second sorted list according to the first number to obtain multiple sorted segments includes:

if the second number is less than or equal to 2, each list subarea is arranged directly adjacent to the corresponding first list subarea, wherein the direct adjacent comprises the arrangement of the list subareas at the front part or the rear part of the first list subarea;

if the second number is more than 2, determining a first number of each list subarea corresponding to the same first list subarea, and ordering the list subareas in descending order according to the first number to generate an ordering order;

taking a first list subarea which is taken as a plurality of list subareas as a check list subarea, if the first list subarea corresponding to the check list subarea belongs to one of the plurality of list subareas, orderly selecting the list subareas in the sorting order based on a preset sorting strategy by taking the check list subarea as a center, and sorting the list subareas around the first list subarea;

After judging the ordered second ordered list, taking the list subareas with the same position quantization information as a combined ordered section, and taking the list subareas which do not have the same attribute quantization information as other list subareas as a single ordered section.

if the first list subarea corresponding to the check list subarea does not belong to one of the list subareas, outputting and displaying the list subareas, the check list subareas and the first list subarea corresponding to the check list subarea to a user;

and generating a manual ordering sequence of the first list subareas of the plurality of list subareas, the check list subareas and the check list subareas according to the sequence configuration information of the user.

Optionally, in one possible implementation manner of the first aspect, centering on the first list sub-area, sequentially selecting the list sub-areas in the sorting order based on a preset sorting policy, and sorting the list sub-areas around the first list sub-area includes:

selecting list subareas in the ordering sequence, sequentially placing the list subareas at the directly adjacent rear part and the directly adjacent front part of the first list subarea, taking the list subarea placed at the front part of the first list subarea as a second list subarea, and taking the list subarea placed at the rear part of the first list subarea as a third list subarea;

Selecting the list subareas in the ordering sequence again, and sequentially placing the list subareas at the rear part of the corresponding second list subareas to generate a new second list subarea;

selecting list subareas in the ordering sequence again, and sequentially placing the list subareas in front of the corresponding third list subareas to generate a new third list subarea;

the above steps are continued until there are no more corresponding list sub-areas within the sort order.

Optionally, in one possible implementation manner of the first aspect, the generating batch configuration data of the corresponding sorting section according to the electric charge calculation value group and the target attribute tag corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table includes:

establishing a segment data storage space corresponding to each sorting segment, and creating an attribute column in a second sorting list, wherein each attribute cell in the attribute column corresponds to each target to be detected one by one;

determining an electric charge calculation value group corresponding to a corresponding sorting section as common configuration information configured for all targets to be detected in the sorting section, and determining a target attribute label of each target to be detected in the corresponding sorting section as independent configuration information of the corresponding target to be detected, wherein the batch configuration data comprises the common configuration information and the independent configuration information;

And storing the public configuration information into the segment data storage space corresponding to the corresponding sorting segment, establishing a mapping and calling link for calling the segment data storage space at the corresponding sorting segment, and storing the independent configuration information of each target to be detected into the corresponding attribute cell to generate a total configuration table.

Optionally, in one possible implementation manner of the first aspect, the server performs batch configuration of electric charge accounting on the smart meter of the target to be detected based on the total configuration table, and the smart meter performs configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data and performs electric charge accounting, including:

the server traverses each sorting section in turn and invokes the public configuration information in the section data storage space corresponding to each sorting section based on the mapping invoking link;

the server traverses the targets to be detected of the corresponding sorting section to determine corresponding independent configuration information, combines the independent configuration information of each target to be detected with the public configuration information of the corresponding sorting section to obtain combined configuration information of the corresponding targets to be detected and configures the combined configuration information to the intelligent ammeter;

the server directly configures the combination configuration information of the previously traversed targets to be detected to the intelligent ammeter corresponding to the later traversed targets to be detected when judging that the newly traversed targets to be detected in the corresponding sequencing section and the previously traversed targets to be detected have the same independent configuration information;

And the intelligent ammeter carries out the configuration of the electric charge calculation value group and the sub-electric charge value according to the configured data, and carries out electric charge accounting according to the corresponding sub-electric charge value.

In a second aspect of the embodiment of the present invention, there is provided a multi-dimensional electricity fee accounting device based on big data, including:

the acquisition module is used for enabling the server to acquire multidimensional data of all targets to be detected corresponding to all connected intelligent electric meters in the target area, wherein the multidimensional data at least comprises position dimension information and industry dimension information, and a first sorting list is obtained by sorting all targets to be detected according to the position dimension information and the industry dimension information;

the determining module is used for enabling the server to respectively determine corresponding position quantization information and attribute quantization information according to the position dimension information and the industry attribute information, and the attribute quantization information of each object to be detected belongs to one quantization value in the corresponding position quantization information;

the classifying module is used for enabling the server to classify and adjust the corresponding targets to be detected in the first ordered list according to the position quantization information and the attribute quantization information to obtain a second ordered list, and segmenting the second ordered list to obtain a plurality of ordered segments;

The screening module is used for enabling the server to determine an electric charge calculation value group corresponding to each sequencing section according to the position quantization information, generating an attribute tag corresponding to each sub-electric charge value in the electric charge calculation value group, and screening the sub-electric charge values in the electric charge calculation value group according to the attribute quantization information of the object to be detected to determine a target attribute tag corresponding to the target sub-electric charge value;

the fusion module is used for generating batch configuration data of the corresponding sorting sections according to the electric charge calculation value group and the target attribute label corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table;

and the configuration module is used for enabling the server to carry out batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table, and the intelligent electric meter carries out configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data and carries out electric charge accounting.

In a third aspect of an embodiment of the present invention, there is provided an electronic device including: a memory, a processor and a computer program stored in the memory, the processor running the computer program to perform the first aspect of the invention and the methods that the first aspect may relate to.

In a fourth aspect of embodiments of the present invention, there is provided a storage medium having stored therein a computer program for implementing the method of the first aspect and the various possible aspects of the first aspect when executed by a processor.

The beneficial effects are that:

according to the scheme, the intelligent electric meters are subjected to data configuration by combining the multidimensional data of the targets to be detected corresponding to all the connected intelligent electric meters in the target area to obtain corresponding quantized information. Wherein the multidimensional data includes a location dimension and an industry attribute dimension. And then sequencing by combining the quantization information to obtain sequencing segments, combining the electric charge calculation value groups and the target attribute labels of each sequencing segment to obtain batch configuration data, and then fusing the batch configuration data with a second sequencing list to generate a total configuration table, so as to carry out batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected. According to the scheme, batch data configuration can be carried out by combining the multidimensional installation attribute of the intelligent electric meter, and the configuration efficiency is improved.

Before batch configuration is carried out, dividing a target area to obtain a plurality of subareas, dividing an ordering list according to the plurality of subareas to obtain a plurality of list subareas, classifying targets to be detected by combining position dimensions, ordering the targets to be detected by combining industry dimension information to obtain a first ordering list, and segmenting the plurality of list subareas in a second ordering list by combining the list subareas corresponding to the largest first number of each list subarea as adjacent first list subareas and number dimensions to obtain a plurality of ordering segments. Then, the scheme establishes a segment data storage space corresponding to each sequencing segment, creates attribute columns in the second sequencing list, obtains public configuration information and independent configuration information to carry out batch configuration, and finally carries out configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data by the intelligent ammeter, and carries out electric charge accounting according to the corresponding sub-electric charge value. By the mode, configuration efficiency can be improved through batch configuration.

Drawings

Fig. 1 is a schematic flow chart of a multi-dimensional electric charge accounting method based on big data provided by the embodiment of the invention;

fig. 2 is a schematic structural diagram of a multi-dimensional electric charge accounting device based on big data according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein.

It should be understood that, in various embodiments of the present invention, the sequence number of each process does not mean that the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

It should be understood that in the present invention, "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that in the present invention, "plurality" means two or more. "and/or" is merely an association relationship describing an association object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "comprising A, B and C", "comprising A, B, C" means that all three of A, B, C comprise, "comprising A, B or C" means that one of the three comprises A, B, C, and "comprising A, B and/or C" means that any 1 or any 2 or 3 of the three comprises A, B, C.

It should be understood that in the present invention, "B corresponding to a", "a corresponding to B", or "B corresponding to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may also determine B from a and/or other information. The matching of A and B is that the similarity of A and B is larger than or equal to a preset threshold value.

As used herein, "if" may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to detection" depending on the context.

The technical scheme of the invention is described in detail below by specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.

Referring to fig. 1, a flow chart of a multi-dimensional electric charge accounting method based on big data according to an embodiment of the present invention includes S1-S6:

s1, a server acquires multidimensional data of targets to be detected corresponding to all connected intelligent electric meters in a target area, wherein the multidimensional data at least comprises position dimension information and industry dimension information, and a first sorting list is obtained by sorting all the targets to be detected according to the position dimension information and the industry dimension information.

The target area may be pre-planned by the user, for example, a administrative area.

The method and the device can obtain multidimensional data of targets to be detected corresponding to all connected intelligent electric meters in the target area, wherein the targets to be detected can be users in the target area, and the multidimensional data at least comprise position dimension information and industry dimension information. The location dimension information may be regional location dimension information, and the industry dimension information may be, for example, business, industrial, residential, etc. dimension information.

According to the scheme, all targets to be detected are ranked by combining the position dimension information and the industry dimension information to obtain a first ranking list.

In some embodiments, S1 (the server obtains multidimensional data of objects to be detected corresponding to all connected smart meters in the target area, where the multidimensional data at least includes location dimension information and industry dimension information, and the first ranking list is obtained by ranking all the objects to be detected according to the location dimension information and the industry dimension information) includes S11-S13:

s11, dividing the target area into a plurality of subareas according to the area division configuration information of the user on the target area, initializing a sorting list, and dividing the sorting list into a plurality of list subareas according to the plurality of subareas.

The division of the region may be, for example, dividing a administrative region into a plurality of sub-regions, and then dividing the ordered list into a plurality of list sub-regions by combining the plurality of sub-regions.

S12, classifying the targets to be detected into corresponding list subareas according to the position dimension information of the targets to be detected.

It can be appreciated that, in the above manner, the list sub-areas may be used to classify the targets to be detected, so that one list sub-area corresponds to the targets to be detected in one sub-area, that is, a plurality of users corresponding to one sub-area.

And S13, sequentially traversing industry dimension information of the to-be-detected targets in the sub-region of the list, and if the industry dimension information of the to-be-detected targets traversed after judgment is the same as the industry dimension information of the to-be-detected targets traversed before, moving the to-be-detected targets traversed after judgment to adjacent rear parts of the to-be-detected targets traversed before to form a first ordered list.

After a plurality of list subareas are obtained, the scheme sequentially traverses industry dimension information of the targets to be detected in the list subareas.

If the industry dimension information of the target to be detected, which is traversed after the judgment, is the same as the industry dimension information of the target to be detected, which is traversed before, the scheme can move the target to be detected, which is traversed after the judgment, to the adjacent rear part of the target to be detected, so as to form a first sorting list.

It can be appreciated that in the above manner, the industry dimension is utilized to sort the plurality of objects to be detected in the sub-area of the list, so that the objects to be detected in the same industry are arranged together to obtain the first sorted list.

S2, the server respectively determines corresponding position quantization information and attribute quantization information according to the position dimension information and the industry attribute information, and the attribute quantization information of each object to be detected belongs to one quantization value in the corresponding position quantization information.

The scheme can respectively determine corresponding position quantization information and attribute quantization information by combining the position dimension information and the industry attribute information, namely, the position and the industry are quantized to obtain corresponding quantization information. Wherein, the attribute quantization information of each object to be detected belongs to one quantization value in the quantization information of the corresponding position.

In some embodiments, S2 (the server determines, according to the location dimension information and the industry attribute information, corresponding location quantization information and attribute quantization information, respectively, where the attribute quantization information of each object to be detected belongs to one of quantization values in the corresponding location quantization information) includes S21-S22:

s21, the server determines corresponding position quantization information according to the position dimension information, wherein the position quantization information comprises electric charge calculation value sets corresponding to different industries at corresponding positions.

The server can determine corresponding position quantization information by combining the position dimension information, wherein the position quantization information comprises electric charge calculation value sets corresponding to different industries at corresponding positions.

It will be appreciated that, in general, a sub-area will include a plurality of industries, and the electricity charge calculation values corresponding to the different industries are different, that is, the electricity prices are different, for example, the electricity prices of the industry and the residence industry may be different, and the electricity charge calculation values of the same industry in a sub-area are generally the same, because the sub-area of the present solution is a small area obtained by dividing the target area. Therefore, the scheme can obtain the electric charge calculation value group, wherein the electric charge calculation value group comprises a plurality of electric charge calculation values of a plurality of industries.

S22, determining attribute quantization information of the corresponding industry at the corresponding position according to the industry attribute information, wherein the attribute quantization information is a sub-electricity fee value of the corresponding industry at the corresponding position.

After the electric charge calculation value group corresponding to the subarea is obtained, the scheme can be used for determining attribute quantization information of the corresponding industry at the corresponding position by combining the industry attribute information, namely, the industry attribute information is utilized to find the sub-electric charge value, namely, the electric charge of the corresponding industry from the electric charge calculation value group.

And S3, the server classifies and adjusts the corresponding targets to be detected in the first ordered list according to the position quantization information and the attribute quantization information to obtain a second ordered list, and performs segmentation processing on the second ordered list to obtain a plurality of ordered segments.

After the position quantization information and the attribute quantization information are obtained, the scheme combines the position quantization information and the attribute quantization information to classify and adjust the corresponding targets to be detected in the first sorting list to obtain a second sorting list, and performs segmentation processing on the second sorting list to obtain a plurality of sorting segments.

In some embodiments, S3 (the server classifies and adjusts the target to be detected corresponding to the first ordered list according to the location quantization information and the attribute quantization information to obtain a second ordered list, and performs a segmentation process on the second ordered list to obtain a plurality of ordered segments) includes S31-S33:

s31, sequentially traversing the position quantization information of all the list subareas in the first sequencing list, comparing the traversed list subareas with the position quantization information of the previously traversed list subareas, and determining the first quantity of the sub-electric charge values of the same industry.

The method comprises the steps of traversing position quantization information of all list subareas in a first sequencing list in sequence, comparing the traversed list subareas with position quantization information of the previously traversed list subareas, and finding out first quantity of sub-electric charge values of the same industry.

Illustratively, the list sub-regions within the first ordered list have A, B, C, D corresponding to sub-regions A, B, C, D, respectively. For example, a is the same as B in industry, business, and residential dimensions, then the first number is 3, i.e., the same industry as between different areas a and B has a consistent number of sub-electricity rates of 3, and for example, a first number between a and C is 2, and a first number between a and D is 1.

S32, determining a list subarea corresponding to the first maximum number of each list subarea as a first adjacent list subarea, and counting the second number of each list subarea as the first list subareas of other list subareas.

In the above example, the list sub-area corresponding to the first largest number of list sub-areas a is B, that is, B is the first list sub-area adjacent to a.

At the same time, the scheme counts each list sub-region as a second number of the first list sub-regions of the other list sub-regions. For example, when the first number between B and C is also 3, then B is also the first list sub-region of the list sub-regions for C, and the second number at this time is 2.

S33, sorting the corresponding list subareas according to the second quantity to obtain a second sorting list, and carrying out segmentation processing on the plurality of list subareas in the second sorting list according to the first quantity to obtain a plurality of sorting segments.

According to the scheme, the corresponding list subareas are ordered according to the second quantity to obtain a second ordered list, and the plurality of list subareas are segmented in the second ordered list according to the first quantity to obtain a plurality of ordered segments.

Wherein S33 (sorting the corresponding list sub-regions according to the second number to obtain a second sorted list, and performing a segmentation process on the plurality of list sub-regions in the second sorted list according to the first number to obtain a plurality of sorted segments) includes S331-S334:

and S331, if the second number is less than or equal to 2, each list subarea is arranged directly adjacent to the corresponding first list subarea, wherein the directly adjacent comprises that the list subareas are arranged at the front part or the rear part of the first list subarea.

It will be appreciated that if the second number is equal to or less than 2, the corresponding list sub-region may be arranged directly adjacent to its corresponding first list sub-region, either in front of or behind the first list sub-region.

And S332, if the second number is more than 2, determining a first number of each list subarea corresponding to the same first list subarea, and ordering the list subareas in a descending order according to the first number to generate an ordering order.

If the second number is larger than 2, that is, more list subareas adjacent to the same first list subarea are needed, the scheme can determine the first number of each list subarea corresponding to the same first list subarea, and sort the list subareas in descending order according to the first number to generate a sort order.

For example, B is the first list sub-region of A, C, D, a first number of a is 3, a first number of c is 2, and a first number of d is 1, then ordering the list sub-regions in descending order according to the first number results in A, C, D.

S333, taking a first list subarea which is a plurality of list subareas as a check list subarea, if the first list subarea corresponding to the check list subarea belongs to one of the plurality of list subareas, orderly selecting the list subareas in the sorting order based on a preset sorting strategy by taking the check list subarea as a center, and sorting the list subareas around the first list subarea.

In the scheme, B is taken as a check list sub-region, if a first list sub-region corresponding to the check list sub-region belongs to one of a plurality of previous list sub-regions, the check list sub-region is taken as a center, and list sub-regions in a sorting order are sequentially selected based on a preset sorting strategy to sort the list sub-regions around the first list sub-region.

The method for sorting the list subareas around the first list subareas sequentially selects the list subareas in the sorting order based on a preset sorting strategy by taking the first list subareas as a center comprises the following steps:

the first 2 list sub-regions within the ordering order are selected, placed immediately next to and immediately before the first list sub-region, with the list sub-region placed before the first list sub-region being the second list sub-region, and the list sub-region placed after the first list sub-region being the third list sub-region.

First, the first 2 list subregions in the ordering order are selected, and are sequentially placed at the immediately adjacent rear part and the immediately adjacent front part of the first list subregion, the list subregion placed at the front part of the first list subregion is used as a second list subregion, and the list subregion placed at the rear part of the first list subregion is used as a third list subregion. For example, a is the second list sub-region and C is the third list sub-region.

And selecting the list subareas in the ordering sequence again, and sequentially placing the list subareas at the rear part of the corresponding second list subareas to generate a new second list subarea.

For example, D is placed at the rear of the corresponding second list sub-region C, generating a new second list sub-region.

And selecting the list subareas in the sorting order again, and sequentially placing the list subareas in front of the corresponding third list subareas to generate a new third list subarea.

It will be appreciated that through the above-described loop, the list sub-regions within the ordering order may be arranged sequentially around the first list sub-region.

S334, after judging that the ordered second ordered list is obtained, taking the list subareas with the same position quantization information as a combined ordered section, and taking the list subareas which do not have the same attribute quantization information as other list subareas as a single ordered section.

After judging that the ordered second ordered list is obtained, the scheme takes the list subareas with the same position quantization information as a combined ordered section and takes the list subareas which do not have the same attribute quantization information as other list subareas as a single ordered section.

On the basis of the above embodiment, the method further comprises:

and if the first list subarea corresponding to the check list subarea does not belong to one of the list subareas, outputting and displaying the list subareas, the check list subareas and the first list subarea corresponding to the check list subarea to a user.

In some cases, if the first list sub-region corresponding to the check list sub-region does not belong to one of the plurality of list sub-regions, the check list sub-region, and the first list sub-region corresponding to the check list sub-region are output and displayed to the user to remind the user to perform the active operation.

The manual ordering sequence of the first list subareas of the list subareas, the check list subareas and the check list subareas, namely the active intervention ordering, is generated by combining the sequence configuration information of the user.

And S4, the server determines an electric charge calculation value group corresponding to each sequencing section according to the position quantization information, generates an attribute tag corresponding to each sub-electric charge value in the electric charge calculation value group, and screens the sub-electric charge value in the electric charge calculation value group according to the attribute quantization information of the object to be detected to determine a target attribute tag corresponding to the target sub-electric charge value.

The server of the scheme can combine the position quantization information to determine the electric charge calculation value group corresponding to each sorting section, and then a group of electric charge calculation values corresponding to each sorting section are obtained.

Then, an attribute tag corresponding to each of the sub-electric charge values within the electric charge calculation value is generated, and may be, for example, an industry tag, for example, a value such as 1, 2, 3, or the like instead. And then, screening the sub-electric charge values in the electric charge calculation value group according to the attribute quantization information (industry information) of the target to be detected, and determining a target attribute label corresponding to the target sub-electric charge value.

S5, generating batch configuration data of the corresponding sorting sections according to the electric charge calculation value group and the target attribute label corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table.

According to the scheme, batch configuration data of the corresponding sorting sections are generated by combining the electric charge calculation value groups corresponding to the sorting sections and the target attribute labels, and then the batch configuration data and the second sorting list are fused and set to generate a total configuration table.

In some embodiments, S5 (generating batch configuration data of each sorting section according to the electric charge calculation value group and the target attribute label corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table) includes S51-S53:

s51, establishing a segment data storage space corresponding to each sorting segment, and creating an attribute column in the second sorting list, wherein each attribute cell in the attribute column corresponds to each target to be detected one by one.

The scheme can construct a segment data storage space corresponding to each sorting segment, and simultaneously creates an attribute column in the second sorting list, wherein each attribute cell in the attribute column corresponds to each target to be detected one by one.

S52, determining an electric charge calculation value group corresponding to the corresponding sorting section as common configuration information configured for all targets to be detected in the sorting section, and determining target attribute labels of all targets to be detected in the corresponding sorting section as independent configuration information of the corresponding targets to be detected, wherein the batch configuration data comprise the common configuration information and the independent configuration information.

The method and the device can determine the electric charge calculation value group corresponding to the corresponding sorting section as common configuration information configured for all targets to be detected in the sorting section, namely a group of data corresponding to the corresponding sorting section, and then determine the target attribute label of each target to be detected in the corresponding sorting section as independent configuration information of the corresponding target to be detected, namely independent data corresponding to the target to be detected.

Wherein the batch configuration data includes common configuration information and independent configuration information.

S53, storing the public configuration information into the segment data storage space corresponding to the corresponding sorting segment, establishing a mapping and calling link for calling the segment data storage space at the corresponding sorting segment, and storing the independent configuration information of each target to be detected into the corresponding attribute cell to generate a total configuration table.

The scheme stores the common configuration information into the segment data storage space corresponding to the corresponding sequencing segment, and establishes a mapping retrieval link for retrieving the segment data storage space at the corresponding sequencing segment so as to retrieve the corresponding common configuration information by using the mapping retrieval link. And simultaneously, storing the independent configuration information of each target to be detected into the corresponding attribute cell to generate a total configuration table.

And S6, the server performs batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table, and the intelligent electric meter performs configuration of an electric charge calculation value group and a sub-electric charge value and performs electric charge accounting according to the configured data.

The server of the scheme can carry out batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected by combining the total configuration table, and the intelligent electric meter carries out configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data and carries out electric charge accounting.

In some embodiments, S6 (the server performs batch configuration of electric charge accounting for the smart meter of the target to be detected based on the total configuration table, the smart meter performs configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data and performs electric charge accounting) includes S61-S64:

S61, the server traverses each sorting section in turn and invokes the public configuration information in the section data storage space corresponding to each sorting section based on the mapping invoking link.

The server of the scheme can traverse each sorting section in turn and call the public configuration information in the section data storage space corresponding to each sorting section based on the mapping call link.

S62, the server traverses the targets to be detected in the corresponding sorting section to determine corresponding independent configuration information, combines the independent configuration information of each target to be detected with the public configuration information of the corresponding sorting section, obtains combined configuration information of the corresponding targets to be detected, and configures the combined configuration information to the intelligent ammeter.

The server traverses the targets to be detected of the corresponding sorting section to determine corresponding independent configuration information, and meanwhile, the independent configuration information of each target to be detected is combined with the public configuration information of the corresponding sorting section to obtain combined configuration information of the corresponding targets to be detected and the combined configuration information is configured to the intelligent ammeter.

And S63, the server directly configures the combination configuration information of the previously traversed targets to be detected to the intelligent ammeter corresponding to the later traversed targets to be detected when judging that the newly traversed targets to be detected in the corresponding sequencing section and the previously traversed targets to be detected have the same independent configuration information.

Meanwhile, if the server judges that the newly traversed target to be detected in the corresponding sequencing section and the previously traversed target to be detected have the same independent configuration information, namely the configuration information is the same, the server directly configures the combination configuration information of the previously traversed target to the intelligent ammeter corresponding to the subsequently traversed target to be detected.

S64, the intelligent ammeter performs configuration of the electric charge calculation value group and the sub-electric charge value according to the configured data, and performs electric charge accounting according to the corresponding sub-electric charge value.

The intelligent ammeter of the scheme can be combined with the configured data to configure an electric charge calculation value group and a sub-electric charge value, and electric charge accounting is carried out according to the corresponding sub-electric charge value.

On the basis of the above embodiment, the method further comprises:

if the server judges that the first industry dimension information of the change of the target to be detected input by the management end is received, the second target attribute label of the target to be detected is determined, and the first target attribute label corresponding to the first industry dimension information is determined by traversing the total configuration table.

It will be appreciated that some industries of the object to be tested may change, and the administrator may actively intervene to make data adjustments. If the server judges that the first industry dimension information of the change of the target to be detected input by the management end is received, determining a second target attribute tag of the target to be detected, traversing the total configuration table, and determining a first target attribute tag corresponding to the first industry dimension information.

And generating a corresponding label replacement group according to the second target attribute label and the first target attribute label, and sending the label replacement group to the intelligent ammeter.

The scheme can combine the second target attribute tag and the first target attribute tag to generate a corresponding tag replacement group, and send the tag replacement group to the intelligent ammeter.

After receiving the tag replacement group, the intelligent ammeter can combine the first target attribute tag to determine a first target sub-electric charge value in the electric charge calculation value group, and then replace the first target sub-electric charge value with the previous sub-electric charge value.

Referring to fig. 2, a schematic structural diagram of a multi-dimensional electric charge accounting device based on big data according to an embodiment of the present invention includes:

The embodiment of the invention provides electronic equipment, which comprises: a processor, a memory and a computer program; wherein the method comprises the steps of

And a memory for storing the computer program, which may also be a flash memory (flash). Such as application programs, functional modules, etc. implementing the methods described above.

And the processor is used for executing the computer program stored in the memory to realize each step executed by the equipment in the method. Reference may be made in particular to the description of the embodiments of the method described above.

In the alternative, the memory may be separate or integrated with the processor.

When the memory is a device separate from the processor, the apparatus may further include:

and the bus is used for connecting the memory and the processor.

The present invention also provides a storage medium having stored therein a computer program for implementing the methods provided by the various embodiments described above when executed by a processor.

The storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media can be any available media that can be accessed by a general purpose or special purpose computer. For example, a storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). In addition, the ASIC may reside in a user device. The processor and the storage medium may reside as discrete components in a communication device. The storage medium may be read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tape, floppy disk, optical data storage device, etc.

The present invention also provides a program product comprising execution instructions stored in a storage medium. The at least one processor of the device may read the execution instructions from the storage medium, the execution instructions being executed by the at least one processor to cause the device to implement the methods provided by the various embodiments described above.

In the above embodiments of the terminal or the server, it should be understood that the processor may be a central processing unit (english: central Processing Unit, abbreviated as CPU), or may be other general purpose processors, digital signal processors (english: digital Signal Processor, abbreviated as DSP), application specific integrated circuits (english: application Specific Integrated Circuit, abbreviated as ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims

1. The multi-dimensional electric charge accounting method based on big data is characterized by comprising the following steps:

the server carries out batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table, and the intelligent electric meter carries out configuration of an electric charge calculation value group and a sub electric charge value according to the configured data and carries out electric charge accounting;

the server classifies and adjusts the target to be detected corresponding to the first ordered list according to the position quantization information and the attribute quantization information to obtain a second ordered list, and performs segmentation processing on the second ordered list to obtain a plurality of ordered segments, wherein the method comprises the following steps:

Sorting the corresponding list subareas according to the second quantity to obtain a second sorting list, and carrying out segmentation processing on the plurality of list subareas in the second sorting list according to the first quantity to obtain a plurality of sorting segments;

the step of sorting the corresponding list subareas according to the second quantity to obtain a second sorting list, and the step of carrying out segmentation processing on the plurality of list subareas in the second sorting list according to the first quantity to obtain a plurality of sorting segments comprises the following steps:

taking a first list subarea which is taken as a plurality of list subareas as a check list subarea, if the first list subarea corresponding to the check list subarea belongs to one of the plurality of list subareas, taking the check list subarea as a center, sequentially selecting the list subareas in an ordering sequence based on a preset ordering strategy, and ordering the list subareas around the check list subarea;

2. The multi-dimensional electric charge accounting method based on big data according to claim 1, further comprising:

3. The multi-dimensional electric charge accounting method based on big data according to claim 1, wherein,

The server obtains multidimensional data of targets to be detected corresponding to all connected intelligent electric meters in a target area, wherein the multidimensional data at least comprises position dimension information and industry dimension information, and a first sorting list is obtained by sorting all targets to be detected according to the position dimension information and the industry dimension information, and the method comprises the following steps:

4. The multi-dimensional electric charge accounting method based on big data according to claim 3, wherein,

the server respectively determines corresponding position quantization information and attribute quantization information according to the position dimension information and the industry attribute information, wherein the attribute quantization information of each object to be detected belongs to one quantization value in the corresponding position quantization information, and the method comprises the following steps:

5. The multi-dimensional electric charge accounting method based on big data according to claim 1, further comprising:

6. The multi-dimensional electric charge accounting method based on big data according to claim 5, wherein,

the method for sorting the list sub-areas around the check list sub-areas sequentially selects the list sub-areas in the sorting order based on a preset sorting strategy by taking the check list sub-areas as a center comprises the following steps:

Selecting the first 2 list subareas in the ordering sequence, sequentially placing the first list subarea at the directly adjacent rear part and the directly adjacent front part of the first list subarea, taking the list subarea placed at the front part of the check list subarea as a second list subarea, and taking the list subarea placed at the rear part of the check list subarea as a third list subarea;

7. The multi-dimensional electric charge accounting method based on big data according to claim 6, wherein,

generating batch configuration data of the corresponding sorting sections according to the electric charge calculation value group and the target attribute label corresponding to each sorting section, and fusing the batch configuration data with the second sorting list to generate a total configuration table, wherein the method comprises the following steps:

8. The multi-dimensional electric charge accounting method based on big data according to claim 7, wherein,

the server performs batch configuration of electric charge accounting on the intelligent electric meter of the target to be detected based on the total configuration table, the intelligent electric meter performs configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data and performs electric charge accounting, and the method comprises the following steps:

the intelligent ammeter carries out configuration of an electric charge calculation value group and a sub-electric charge value according to the configured data, and carries out electric charge accounting according to the corresponding sub-electric charge value;

9. Multi-dimensional electric charge accounting device based on big data, characterized by comprising:

10. An electronic device, comprising: a memory, a processor and a computer program stored in the memory, the processor running the computer program to perform the method of any one of claims 1 to 8.

11. A storage medium having stored therein a computer program for implementing the method of any of claims 1 to 8 when executed by a processor.