CN116226293A - Method and system for generating and managing power customer portrait - Google Patents
Method and system for generating and managing power customer portrait Download PDFInfo
- Publication number
- CN116226293A CN116226293A CN202211690880.0A CN202211690880A CN116226293A CN 116226293 A CN116226293 A CN 116226293A CN 202211690880 A CN202211690880 A CN 202211690880A CN 116226293 A CN116226293 A CN 116226293A
- Authority
- CN
- China
- Prior art keywords
- user
- power
- electricity
- module
- service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a method and a system for generating and managing an electric power customer portrait, which are used for collecting original data of a newly added electric power customer, processing and analyzing the original data, calculating an initial user label of each user through a big data algorithm, analyzing user habits of the initial user labels, determining a corresponding user portrait model, integrating user labels close to the user portrait model, classifying and entering the user label database groups, differentiating service strategies aiming at different user label database groups, periodically updating user labels of corresponding users, and cleaning and adjusting users which do not accord with the user label database groups to enter the corresponding user label database groups. The invention has reasonable structure, can carry out high-quality service with higher specification aiming at high-quality clients in the user tag database group, and can ensure that users have better high-quality experience, thereby reducing user loss.
Description
Technical Field
The invention relates to the technical field of power management, in particular to a method for generating and managing power customer portraits, and also relates to a system for generating and managing the power customer portraits.
Background
Customer portrayal: customer information is labeled, the information overall view of a customer is perfectly abstracted, the customer information overall view can be regarded as the root of enterprise application big data, the user characteristics are researched by knowing the user image of the power customer, the classification and differentiated management of the user can be realized, the user requirements can be further mined, the user is guided to optimize the electricity utilization habit, and therefore the cost is saved, and the profit of an enterprise is improved.
Currently, in a power marketing system, a customer grouping system exists, and the system classifies data recorded by customer groupings based on customer base information, such as dividing power customers into industrial and commercial power customers, agricultural power customers, resident customers and the like according to different target customers.
The existing electric power user portrait cannot flexibly describe the characteristics of the electric power consumer, contains insufficient description information, cannot refine specific customer groups, is inflexible in describing single user characteristics, cannot provide more help on business, has great management pressure in the process of carrying out electric power management on different customers, and is easy to cause problems of high-quality target customer loss and the like.
Disclosure of Invention
The invention aims to provide a method and a system for generating and managing power customer portraits, which are characterized in that the existing power customer portraits cannot flexibly describe the characteristics of power customers, contain insufficient description information, cannot refine specific customer groups, are not flexible enough when describing single user characteristics, cannot provide more help on business, carry out equal treatment on different customers in the process of carrying out power management, have higher management pressure, and are easy to cause problems of high-quality target customer loss and the like.
In order to achieve the above purpose, the present application provides the following technical solutions: a method of power customer representation generation management, comprising the steps of:
s1, collecting original data of newly added power customers;
s2, processing and analyzing the original data, and calculating an initial user label of each user through a big data algorithm;
s3, analyzing the user habit of the initial user tag so as to determine a corresponding user portrait model;
s4, integrating the user labels close to the user portrait model, and classifying the user labels into corresponding user label database groups;
s5, carrying out differentiated service strategies aiming at different user tag database groups;
s6, the user labels of the corresponding users are updated regularly, and the users which do not accord with the user label database groups are cleared and adjusted to enter the corresponding user label database groups.
As a further preferable scheme, the raw data in S1 includes basic information of the user, power consumption type, power consumption condition of the user and payment condition of the user.
As a further preferable scheme, the basic information of the user comprises the name of the user and the electricity address of the current electricity consumer;
the electricity utilization type comprises resident life electricity utilization, industrial and commercial electricity utilization, large industrial electricity utilization and agricultural production electricity utilization;
the electricity consumption state of the user comprises the daily electricity consumption degree of the user, the daily electricity consumption peak period of the user and the electricity consumption valley period;
the user payment status comprises whether the user is full in integral payment after the latest electricity utilization and whether the user is not paying due to arrearages for multiple times, and the user payment status is classified into three user trust levels according to payment status.
As a further preferable scheme, the user portrait model in the S3 is divided into an agricultural production user model, a resident production user model and an industrial and commercial production electricity model, and each different type of user model is divided into three different user tag database groups according to the trust level.
As a further preferred solution, the differentiated service policy in S5 includes the following procedures:
a1, distinguishing target groups;
a2, aiming at clients in the electricity consumption model, dividing the electricity consumption model into three levels of high, medium and low according to the number of trust degree models in the user tag database group;
a3, aiming at clients with different trust degrees, carrying out electric power service operation with different degrees on the clients,
as a further preferred embodiment, the power service operation includes the following measures
1) Aiming at the electricity model client with high trust, the high-quality service with higher specification is achieved,
2) Aiming at the electricity consumption model customers with medium trust level, the measures of encouraging the compensation of the delinquent electricity fee to have rebates and the like are achieved;
3) Aiming at the customers of the electricity consumption model with low trust, the customers corresponding to the customers can be reminded to pay the electricity fees at regular time, and the brake-pulling electricity limiting processing is performed when the electricity consumption is tension or the customers do not pay the fees for a long time.
As a further preferable scheme, the high-quality service with higher specification comprises the steps of periodically carrying out power inspection for customers, periodically developing safe electricity explanation training, informing the power grid of planning preferentially and properly relaxing the payment period when the customers cannot pay on time when great economic difficulty is encountered.
A system for generating and managing power customer portrait includes
The data collection module is used for collecting the original data of the power customer by a user;
the data preprocessing module is used for analyzing the original data so as to generate a corresponding user tag according to the original data;
the label integrating module is used for analyzing and integrating the existing user labels and classifying the corresponding user labels into corresponding user label database groups;
and the differentiated service module is used for performing differentiated power service operation on different user tag database groups.
As a further preferable scheme, the data preprocessing module comprises a tag analysis module and a tag construction module, wherein the tag construction module is used for constructing a user electricity consumption behavior feature set, and the user electricity consumption behavior feature set comprises electricity consumption scale, electricity consumption type, electricity consumption time section difference, electricity consumption temperature difference, daily average load stability, daily average electric quantity utilization rate, electricity consumption rising and falling ring ratio trend and daily peak-valley difference.
As a further preferred solution, the differentiated service module comprises a policy management module and a policy pushing module,
the policy management module is used for making a differentiated service policy by combining service experience and original related policies aiming at a user tag database group of a newly added client;
the policy pushing module is used for configuring service system addresses for differentiated service policy pushing and configuring policy pushing objects under the service system in batches to push out formulated differentiated information pushing policies aiming at different channels.
In summary, the invention has the technical effects and advantages that:
1. the invention has reasonable structure, can collect user labels, classify the user labels according to different data of the user labels and the trust degree of the user, classify different users and put the user labels into corresponding user label database groups, and perform differentiated service strategies on the users in the different user label database groups, so that high-quality service with higher specification can be performed for high-quality clients in the user label database groups, the users can be ensured to have better high-quality experience, thereby reducing the loss of the users, and simultaneously, the whole loss of an electric company is reduced by means of back-off and brake-out electricity limiting at specific time for the users with medium trust degree and poor trust degree.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a method flow diagram of a method and system for power customer representation generation management;
FIG. 2 is a flow chart of a method and system differentiated service policy for power customer representation generation management;
FIG. 3 is a system block diagram of a method and system for power customer representation generation management.
Detailed description of the preferred embodiments
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Examples: referring to FIG. 1, a method for power customer portrait creation management includes the steps of:
s1, collecting original data of newly added power customers;
s2, processing and analyzing the original data, and calculating an initial user label of each user through a big data algorithm;
s3, analyzing the user habit of the initial user tag so as to determine a corresponding user portrait model;
s4, integrating the user labels close to the user portrait model, and classifying the user labels into corresponding user label database groups;
s5, carrying out differentiated service strategies aiming at different user tag database groups;
s6, the user labels of the corresponding users are updated regularly, the users which do not accord with the user label database groups are cleared and adjusted to enter the corresponding user label database groups, the users in the user label database groups can be adjusted by updating the corresponding user labels regularly, better and better service can be provided, poor performance can be degraded, corresponding service is lost, and good habit of the users is promoted.
As a further preferable scheme, the original data in the S1 comprises the basic information of the user, the electricity consumption type, the electricity consumption condition of the user and the payment condition of the user, and the corresponding user can be conveniently placed into the corresponding user tag database group in the tag generation process by knowing the basic information of the user, so that the follow-up differentiated management is ensured.
As a further preferable scheme, the basic information of the user comprises the name of the user and the electricity address of the current electricity consumer;
the electricity consumption categories comprise resident life electricity consumption, industrial and commercial electricity consumption, large industrial electricity consumption and agricultural production electricity consumption, and by classifying the electricity consumption categories, corresponding measures can be taken in consideration of different electricity consumption categories when differentiated services are carried out;
the electricity consumption state of the user comprises the daily electricity consumption degree of the user, the daily electricity consumption peak period of the user and the electricity consumption valley period;
the user payment status comprises whether the user is full in integral payment after the latest electricity utilization and whether the user is not paying due to arrearages for many times, and the user payment status is divided into three user trust levels according to the payment status, and by carrying out the trust levels, the user can be conveniently judged in which user tag database group the user is according to the different trust levels.
As a further preferable scheme, the user portrait model in the S3 is divided into an agricultural production user model, a resident production user model and an industrial and commercial production electricity model, and each different type of user model is divided into three different user tag database groups according to the trust level.
As a further preferred solution, the differentiated service policy in S5 includes the following procedures:
a1, distinguishing target groups;
a2, aiming at clients in the electricity consumption model, dividing the electricity consumption model into three levels of high, medium and low according to the number of trust degree models in the user tag database group;
a3, aiming at clients with different trust degrees, carrying out electric power service operation with different degrees on the clients,
as a further preferred embodiment, the power service operation includes the following measures
1) The customer of the electricity consumption model with high trust degree can achieve high-quality service with higher specification, the agricultural workers can be trained for safe electricity consumption in the process of the user model for agricultural production, the self-rescue and other problems can be carried out after the problems of electric leakage and the like are met, the circuit of the house circuit can be checked for free in the user model for resident production, the power inspection of the factory circuit is carried out in the process of the electricity consumption model for industrial and commercial production, the measures of potential safety hazards of electricity consumption and the like are reduced, the overall experience of the user is improved, the customer of the electricity consumption model is promoted to be positively matched with the measures of payment and the like,
2) The customer can make measures such as rebate for the electricity consumption model with medium trust degree, and the user can be encouraged to pay enthusiasm under the normal condition of economy by making the rebate for the electricity consumption model with medium trust degree;
3) The customer of the electricity consumption model with low trust degree can be reminded to pay the electricity fee at regular time, and the brake-off electricity limiting processing is carried out when the electricity consumption is tension or the customer does not pay the fee for a long time, and the loss of the electric company can be reduced under the condition that the user cannot maintain the payment effectively through the measures of regular reminding and brake-off electricity limiting.
As a further preferable scheme, the high-quality service with higher specification comprises the steps of periodically carrying out power inspection for customers, periodically developing safe electricity explanation training, informing the power grid of planning preferentially and properly relaxing the payment period when the customers cannot pay on time when great economic difficulty is encountered.
A system for power customer representation generation management, comprising:
the data collection module is used for collecting the original data of the power customer by a user;
the data preprocessing module is used for analyzing the original data so as to generate a corresponding user tag according to the original data;
the label integrating module is used for analyzing and integrating the existing user labels and classifying the corresponding user labels into corresponding user label database groups;
and the differentiated service module is used for performing differentiated power service operation on different user tag database groups.
As a further preferable scheme, the data preprocessing module comprises a tag analysis module and a tag construction module, wherein the tag construction module is used for constructing a user electricity consumption behavior feature set, and the user electricity consumption behavior feature set comprises electricity consumption scale, electricity consumption type, electricity consumption time section difference, electricity consumption temperature difference, daily average load stability, daily average electric quantity utilization rate, electricity consumption rising and falling ring ratio trend and daily peak-valley difference.
As a further preferred solution, the differentiated service module comprises a policy management module and a policy pushing module,
the policy management module is used for making a differentiated service policy by combining service experience and original related policies aiming at a user tag database group of a newly added client;
the policy pushing module is used for configuring service system addresses for differentiated service policy pushing and configuring policy pushing objects under the service system in batches to push out formulated differentiated information pushing policies aiming at different channels.
Finally, it should be noted that: the foregoing description is only illustrative of the preferred embodiments of the present invention, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements or changes may be made without departing from the spirit and principles of the present invention.
Claims (10)
1. A method for power customer representation generation management, comprising the steps of:
s1, collecting original data of newly added power customers;
s2, processing and analyzing the original data, and calculating an initial user label of each user through a big data algorithm;
s3, analyzing the user habit of the initial user tag so as to determine a corresponding user portrait model;
s4, integrating the user labels close to the user portrait model, and classifying the user labels into corresponding user label database groups;
s5, carrying out differentiated service strategies aiming at different user tag database groups;
s6, the user labels of the corresponding users are updated regularly, and the users which do not accord with the user label database groups are cleared and adjusted to enter the corresponding user label database groups.
2. The method for generating and managing a power customer portrait according to claim 1 where the raw data in S1 includes basic information of a user, a power class, a power condition of the user, and a payment condition of the user.
3. The method for power customer portrayal generation management of claim 2, wherein the basic information of the user includes a name of the user and an electricity address of the current electricity customer;
the electricity utilization type comprises resident life electricity utilization, industrial and commercial electricity utilization, large industrial electricity utilization and agricultural production electricity utilization;
the electricity consumption state of the user comprises the daily electricity consumption degree of the user, the daily electricity consumption peak period of the user and the electricity consumption valley period;
the user payment status comprises whether the user is full in integral payment after the latest electricity utilization and whether the user is not paying due to arrearages for multiple times, and the user payment status is classified into three user trust levels according to payment status.
4. The method for generating and managing electric power customer portrayal according to claim 1, wherein the user portrayal models in S3 are divided into an agricultural production user model, a residential production user model and an industrial and commercial production electricity model, and each of the different kinds of user models is divided into three different user tag database groups according to a trust level.
5. The method of power customer portrait creation management according to claim 1 where the differentiated service policy in S5 includes the following flow:
a1, distinguishing target groups;
a2, aiming at clients in the electricity consumption model, dividing the electricity consumption model into three levels of high, medium and low according to the number of trust degree models in the user tag database group;
a3, aiming at clients with different trust degrees, carrying out power service operation with different degrees on the clients.
6. The method of power customer portrait creation management according to claim 5 where said power service operation includes the following measures
1) Aiming at the electricity model client with high trust, the high-quality service with higher specification is achieved,
2) Aiming at the electricity consumption model customers with medium trust level, the measures of encouraging the compensation of the delinquent electricity fee to have rebates and the like are achieved;
3) Aiming at the customers of the electricity consumption model with low trust, the customers corresponding to the customers can be reminded to pay the electricity fees at regular time, and the brake-pulling electricity limiting processing is performed when the electricity consumption is tension or the customers do not pay the fees for a long time.
7. The method of claim 6, wherein the higher quality service includes regular power inspection for customers, regular development of safe power instruction training, priority notification of grid planning, and proper relaxation of payment terms when no on-time payment is possible in the event of significant economic difficulties.
8. A system for power customer representation generation management for use in the method of power customer representation generation management of any of claims 1-7, comprising
The data collection module is used for collecting the original data of the power customer by a user;
the data preprocessing module is used for analyzing the original data so as to generate a corresponding user tag according to the original data;
the label integrating module is used for analyzing and integrating the existing user labels and classifying the corresponding user labels into corresponding user label database groups;
and the differentiated service module is used for performing differentiated power service operation on different user tag database groups.
9. The system for generating and managing power customer portraits according to claim 8, wherein the data preprocessing module comprises a tag analysis module and a tag construction module, wherein the tag construction module is used for constructing a user power consumption behavior feature set, and the user power consumption behavior feature set comprises a power consumption scale, a power consumption category, a power consumption time-period difference, a power consumption temperature difference, a daily average load stability, a daily average power utilization rate, a power consumption rising and falling loop ratio trend and a daily peak-valley difference.
10. The system for power customer portrayal generation management of claim 8, wherein the differentiated services module comprises a policy management module and a policy pushing module,
the policy management module is used for making a differentiated service policy by combining service experience and original related policies aiming at a user tag database group of a newly added client;
the policy pushing module is used for configuring service system addresses for differentiated service policy pushing and configuring policy pushing objects under the service system in batches to push out formulated differentiated information pushing policies aiming at different channels.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211690880.0A CN116226293A (en) | 2022-12-28 | 2022-12-28 | Method and system for generating and managing power customer portrait |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211690880.0A CN116226293A (en) | 2022-12-28 | 2022-12-28 | Method and system for generating and managing power customer portrait |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116226293A true CN116226293A (en) | 2023-06-06 |
Family
ID=86570676
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211690880.0A Pending CN116226293A (en) | 2022-12-28 | 2022-12-28 | Method and system for generating and managing power customer portrait |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116226293A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116821523A (en) * | 2023-08-30 | 2023-09-29 | 山西合力思创科技股份有限公司 | Personnel matching logic verification method and device, electronic equipment and storage medium |
-
2022
- 2022-12-28 CN CN202211690880.0A patent/CN116226293A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116821523A (en) * | 2023-08-30 | 2023-09-29 | 山西合力思创科技股份有限公司 | Personnel matching logic verification method and device, electronic equipment and storage medium |
| CN116821523B (en) * | 2023-08-30 | 2023-11-24 | 山西合力思创科技股份有限公司 | Personnel matching logic verification method and device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11699198B2 (en) | Methods and systems for machine-learning for prediction of grid carbon emissions | |
| US10896203B2 (en) | Digital analytics system | |
| Li et al. | Impact factors analysis on the probability characterized effects of time of use demand response tariffs using association rule mining method | |
| EP3115959B1 (en) | Data analysis system and method | |
| US7779290B2 (en) | Computer implemented systems and methods for pre-emptive service and improved use of service resources | |
| JP6738801B2 (en) | Energy management system and method | |
| Li et al. | A personalized electricity tariff recommender system based on advanced metering infrastructure and collaborative filtering | |
| CN109634942A (en) | A kind of energy data exception judgment method and device | |
| CN110852519A (en) | Optimal profit method considering various types of loads for electricity selling companies | |
| Rathnayaka et al. | Formation of virtual community groups to manage prosumers in smart grids | |
| Wang et al. | Smart Meter Data Analytics | |
| Joseph et al. | Real‐time retail price determination in smart grid from real‐time load profiles | |
| Zhou et al. | Smart energy management | |
| CN116226293A (en) | Method and system for generating and managing power customer portrait | |
| JP2005045899A (en) | System and method for electric power transaction | |
| CN115081893A (en) | User electricity consumption data analysis method and device, electronic equipment and readable storage medium | |
| CN114048200A (en) | User electricity consumption behavior analysis method considering missing data completion | |
| Asghari et al. | Selecting and prioritizing the electricity customers for participating in demand response programs | |
| Bu et al. | Distributed unit commitment scheduling in the future smart grid with intermittent renewable energy resources and stochastic power demands | |
| CN115809406B (en) | Fine granularity classification method, device, equipment and storage medium for electric power users | |
| Osypova | Consumption pattern detection through the use of machine learning: clustering techniques for non-technical losses detection RERORT | |
| US20230402848A1 (en) | Energy storage optimization system | |
| Subhash et al. | Analysis of Smart Grid Data for Appliance Prediction and Efficient Power Consumption | |
| Pawar et al. | Electricity Forecasting Using Machine Learning: A Review | |
| Qian et al. | Enhancing power utilization analysis: detecting aberrant patterns of electricity consumption |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |