CN112801542A - Credit assessment method for electricity utilization client - Google Patents
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Abstract
The invention provides a credit assessment method for electricity customers, which is used for acquiring basic electricity utilization information of the customers from a business system; selecting power utilization indexes from the basic power utilization information of the client according to evaluation dimensions, wherein the evaluation dimensions comprise basic power utilization attributes, power utilization capacity, payment capacity, external evaluation and power utilization normalization; scoring the electricity utilization index by adopting a numerical analysis method such as kmeans clustering amplification to obtain an index score; adopting a weight analysis method; for example, an analytic hierarchy process weights the power utilization index to obtain an index weight; acquiring a user credit score according to the index weight and the index score; and finally, the credit rating of the client is adjusted according to the power utilization normalization after the credit rating of the client is obtained according to the credit score of the user, so that corresponding real-time power supply, power limitation or power failure operation can be performed according to the credit rating of the client, and economic loss of a power supply company is prevented.
Description
Technical Field
The invention relates to credit assessment of a power system, in particular to a credit assessment method for electricity utilization customers.
Background
Along with the continuous development and deepening of the innovation of the power enterprise system in China, the monopoly situation of the power department is gradually weakened, meanwhile, the market competition of the power department faces stronger and stronger, in the power market, a power supply enterprise needs to face power consumption customers with different credits, and the power selling mode of 'first power consumption and later payment' makes the problem of power charge recovery more a stubborn problem of a power system.
Disclosure of Invention
Therefore, the invention provides the electricity consumer credit assessment method which can be used for carrying out credit grading on the electricity consumers so as to reasonably distribute power supply according to the credit grading condition of the users.
The technical scheme of the invention is realized as follows:
the credit evaluation method for the electricity utilization client comprises the following steps:
step S1, obtaining basic electricity utilization information of the client from the business system;
s2, selecting a power utilization index from the basic power utilization information of the customer according to the evaluation dimension;
step S3, scoring the power utilization index by adopting a numerical analysis method to obtain an index score;
s4, weighting the electricity utilization index by adopting a weight analysis method to obtain an index weight;
step S5, obtaining a user credit score according to the index weight and the index score;
and step S6, obtaining the client credit rating according to the user credit score.
Preferably, the service system in step S1 includes a marketing system, a metering automation system, and a telephone traffic system, and the customer basic electricity consumption information includes customer profile data, payment records, arrearage records, electricity consumption, power supply voltage, illegal electricity consumption and electricity stealing categories, plan setting flags, compensation electricity quantity data information, and appeal acceptance and processing data information.
Preferably, after the basic electricity information of the customer is obtained, in the step S1, the customer is divided into three groups, i.e., a high-voltage group, a low-voltage group, a non-residential group and a low-voltage group, according to the criteria of whether the customer is in a high-voltage group or a low-voltage group, and in the step S2, the electricity utilization index is selected from the basic electricity information of the customer in different groups according to the evaluation dimension.
Preferably, the evaluation dimension of step S2 includes basic power consumption attributes, power consumption capabilities, payment capabilities, external evaluations, and power consumption normalcy, and the specific step of step S2 is to select and obtain a power consumption index from the basic customer power consumption information based on the information entropy according to the basic power consumption attributes, the power consumption capabilities, the payment capabilities, the external evaluations, and the power consumption normalcy, and by combining index historical data.
Preferably, the specific step of step S3 includes:
step S31, carrying out data observation on each power utilization index;
and step S32, combining a kmeans clustering method and the data distribution form of the power utilization indexes to obtain the segmentation result of each power utilization index, and mapping the score to 0-100 to obtain the index score.
Preferably, the data observation of step S31 includes an integrity observation, a service reasonableness observation, and an effectiveness observation, where the integrity observation includes whether there is data in key features, whether there is data in all features, and a time span, the service reasonableness observation includes whether summarized data conforms to service calculation logic, the effectiveness observation includes numerical features and character-type features, the numerical features include whether features should include positive and negative values, a maximum value, a mean value, a median value, an abnormal value, and data continuity, and the character-type features include Chinese names and scrambled codes corresponding to the features.
Preferably, the specific step of step S4 includes:
step S41, processing and converting the electricity utilization indexes by adopting an analytic hierarchy process aiming at basic attributes, electricity utilization capacity, payment capacity and external evaluation to obtain subjective and objective weight values of each electricity utilization index;
and step S42, acquiring index weight by adopting a grey correlation algorithm according to the subjective and objective weight values.
Preferably, the structure of the analytic hierarchy process in step S41 includes a target layer, a criterion layer, a sub-criterion layer, and a scheme layer from top to bottom, where a decision target unit is disposed in the target layer, k criterion units are disposed in the criterion layer, m criterion units are disposed in each layer of the sub-criterion layer, n scheme units are disposed in the scheme layer, and all units of the previous layer are connected to each unit of the next layer.
Preferably, the specific step of step S5 is to multiply each index weight of the user by the index score of each index to obtain the user credit score.
Preferably, the specific step of step S6 is: and dividing the credit score of the user into a plurality of preliminary credit levels by adopting a clustering algorithm, and adjusting the preliminary credit levels by combining with the electricity utilization indexes under the electricity utilization standardization to obtain the credit levels of the client.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an electricity customer credit evaluation method, which comprises the steps of obtaining customer basic electricity information from a business system, selecting electricity utilization indexes from the customer basic electricity information according to different evaluation dimensions, respectively grading and weighting the electricity utilization indexes by adopting a numerical analysis method and a weight analysis method, respectively obtaining index scores and index weights, finally obtaining user credit scores according to the index weights and the index scores, then obtaining customer credit grades according to the user credit scores, finally judging the credit conditions of users according to the customer credit grades, carrying out electricity limiting treatment on users with lower grades, carrying out power protection treatment on users with higher credit grades, realizing differentiated treatment of electricity customers, and avoiding economic loss of power supply companies.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only preferred embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart of a method for assessing credit of electricity using customers according to the present invention;
FIG. 2 is a radar chart of the evaluation dimension of the credit assessment method for electricity customers according to the present invention;
FIG. 3 is a schematic diagram of data observation of a method for assessing consumer credit in accordance with the present invention;
FIG. 4 is an architecture diagram of an analytic hierarchy process of a method for assessing consumer credit in accordance with the present invention.
Detailed Description
For a better understanding of the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described with reference to the accompanying drawings.
Referring to fig. 1, the present invention provides a method for evaluating credit of a power consumer, including the following steps:
step S1, obtaining basic electricity utilization information of the client from the business system;
preferably, the service system in step S1 includes a marketing system, a metering automation system, and a telephone traffic system, and the customer basic electricity consumption information includes customer profile data, payment records, arrearage records, electricity consumption, power supply voltage, illegal electricity consumption and electricity stealing categories, plan setting marks, compensation electricity quantity data information, and appeal acceptance and processing data information; after the basic electricity utilization information of the client is obtained, the client is divided into three groups, namely high-voltage non-residents, low-voltage residents and low-voltage residents according to the standard of high voltage and low voltage and whether the residents are resident or not.
After the electricity utilization customers are divided into three groups according to high voltage and low voltage and whether residents belong to the three groups, the electricity utilization customers in each group correspond to the basic electricity utilization information of the individual customers.
Step S2, selecting power utilization indexes from the basic power utilization information of the customers in different groups according to the evaluation dimension;
referring to fig. 2, the evaluation dimension of step S2 includes basic power consumption attributes, power consumption capabilities, payment capabilities, external evaluation, and power consumption normalization, and the specific step of step S2 is to select and obtain a power consumption index from the basic power consumption information of the customer based on the information entropy according to the basic power consumption attributes, the power consumption capabilities, the payment capabilities, the external evaluation, and the power consumption normalization, and by combining index historical data.
After the electricity utilization customers are grouped, the electricity utilization indexes are obtained from the basic electricity utilization information of the customers grouped by all the customers based on 5 evaluation dimensions, so that a credit characteristic index system is constructed, and in the construction of the electricity utilization indexes, indexes reflecting the current credit level and indexes reflecting the long-term credit level can be selected.
Step S3, scoring the power utilization index by adopting a numerical analysis method to obtain an index score;
preferably, the specific step of step S3 includes:
step S31, carrying out data observation on each power utilization index;
and step S32, combining a kmeans clustering method and the data distribution form of the power utilization indexes to obtain the segmentation result of each power utilization index, and mapping the score to 0-100 to obtain the index score.
The method comprises the steps of analyzing data distribution states by using a KDE (KDE) graph and a box graph, formulating a single index scoring standard based on an analysis result and a normal distribution principle, specifically, carrying out data observation, null value and abnormal value processing on each power utilization index, combining a kmeans clustering method and the data distribution form of the index, finally carrying out segmentation result on each index, and mapping the index score to 0-100, thereby obtaining the index score.
Referring to fig. 3, the data observation of step S31 includes an integrity observation, a service reasonableness observation and an effectiveness observation, the integrity observation includes whether key features have data, whether all features have data and time span, the service reasonableness observation includes whether summarized data conforms to service calculation logic, the effectiveness observation includes numerical features and character-type features, the numerical features include whether features should contain positive and negative values, a maximum value, a mean value, a median value, an abnormal value and data continuity, and the character-type features include feature corresponding to chinese names and messy codes.
When data observation is carried out on all the characteristics, the characteristic missing condition can be obtained, the electricity utilization indexes are subjected to data observation, and reliable and high-quality data support can be provided for credit evaluation.
S4, weighting the electricity utilization index by adopting a weight analysis method to obtain an index weight;
preferably, the specific step of step S4 includes:
step S41, processing and converting the electricity utilization indexes by adopting an analytic hierarchy process aiming at basic attributes, electricity utilization capacity, payment capacity and external evaluation to obtain subjective and objective weight values of each electricity utilization index;
and step S42, acquiring index weight by adopting a grey correlation algorithm according to the subjective and objective weight values.
Referring to fig. 4, the architecture of the analytic hierarchy process of step S41 includes a target layer, a criterion layer, a sub-criterion layer, and a scheme layer from top to bottom, where a decision target unit is disposed in the target layer, k criterion units are disposed in the criterion layer, m criterion units are disposed in each of the sub-criterion layers, n scheme units are disposed in the scheme layer, and all units of the previous layer are connected to each unit of the next layer.
When the weight of the electricity utilization index is calculated, calculation is carried out according to the evaluation dimension, and in the calculation, the electricity utilization normalization is not considered, the electricity utilization normalization generally refers to illegal electricity stealing behaviors and electricity utilization behaviors, the behaviors belong to serious loss of credit behaviors, the data distribution of the illegal electricity stealing times and the illegal electricity utilization times is concentrated, and the data distribution is not suitable for weight analysis, so the index under the dimension does not participate in the calculation of the client credit score, and is directly used for adjusting the credit grade subsequently.
Step S5, obtaining a user credit score according to the index weight and the index score;
preferably, the specific step of step S5 is to multiply each index weight of the user by the index score of each index to obtain the user credit score.
And step S6, obtaining the client credit rating according to the user credit score.
Preferably, the specific step of step S6 is: and dividing the credit score of the user into a plurality of preliminary credit levels by adopting a clustering algorithm, and adjusting the preliminary credit levels by combining with the electricity utilization indexes under the electricity utilization standardization to obtain the credit levels of the client.
Specifically, when each user is in use, the user is brought into different credit levels according to the credit score of the user, the level is adjusted according to the power utilization standardization of the user, and the credit level of the user is finally obtained, so that power supply and power failure can be regulated and controlled according to the credit level of the user.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. The credit assessment method for electricity customers is characterized by comprising the following steps:
step S1, obtaining basic electricity utilization information of the client from the business system;
s2, selecting a power utilization index from the basic power utilization information of the customer according to the evaluation dimension;
step S3, scoring the power utilization index by adopting a numerical analysis method to obtain an index score;
s4, weighting the electricity utilization index by adopting a weight analysis method to obtain an index weight;
step S5, obtaining a user credit score according to the index weight and the index score;
and step S6, obtaining the client credit rating according to the user credit score.
2. The electricity consumer credit evaluation method of claim 1, wherein the business system in step S1 includes a marketing system, a metering automation system and a traffic system, and the basic electricity consumption information of the consumer includes consumer profile data, payment record, arrearage record, electricity consumption, power supply voltage, illegal electricity stealing category, plan mark, compensation electricity quantity data information, and appeal acceptance and processing data information.
3. The electricity consumption customer credit evaluation method according to claim 1, wherein the step S1 is to divide the customer into three groups, i.e. high-voltage, low-voltage non-residents and low-voltage residents, based on the criteria of high voltage, low voltage and whether residents are present after obtaining the basic electricity consumption information of the customer, and the step S2 is to select electricity consumption indexes from the basic electricity consumption information of the customer in different groups according to the evaluation dimension.
4. The method for assessing credit of an electricity consumption customer as claimed in claim 1, wherein the evaluation dimensions of step S2 include basic electricity consumption attributes, electricity consumption capabilities, payment capabilities, external evaluations and electricity consumption normalcy, and the specific step of step S2 is to select and obtain electricity consumption indexes from basic customer electricity consumption information based on entropy according to the basic electricity consumption attributes, electricity consumption capabilities, payment capabilities, external evaluations and electricity consumption normalcy, and in combination with index historical data.
5. The electricity consumer credit assessment method according to claim 1, wherein said step S3 comprises the following steps:
step S31, carrying out data observation on each power utilization index;
and step S32, combining a kmeans clustering method and the data distribution form of the power utilization indexes to obtain the segmentation result of each power utilization index, and mapping the score to 0-100 to obtain the index score.
6. The electricity consumer credit assessment method according to claim 5, wherein said data observation of step S31 includes integrity observation, business rationality observation and validity observation, said integrity observation includes whether key features have data, whether all features have data and time span, said business rationality observation includes whether summarized data conforms to business computation logic, said validity observation includes numerical type features and character type features, said numerical type features includes whether features should contain positive and negative values, most abnormal values, mean values, median values and data continuity, said character type features includes feature corresponding Chinese names and messy codes.
7. The electricity consumer credit assessment method according to claim 1, wherein said step S4 comprises the following steps:
step S41, processing and converting the electricity utilization indexes by adopting an analytic hierarchy process aiming at basic attributes, electricity utilization capacity, payment capacity and external evaluation to obtain subjective and objective weight values of each electricity utilization index;
and step S42, acquiring index weight by adopting a grey correlation algorithm according to the subjective and objective weight values.
8. The electricity consumption customer credit evaluation method according to claim 7, wherein the hierarchy analysis method of the step S41 comprises a target layer, a criterion layer, a sub-criterion layer and a scheme layer from top to bottom, wherein the target layer is provided with decision target units, the criterion layer is provided with k criterion units, each sub-criterion layer is provided with m criterion units, the scheme layer is provided with n scheme units, and all the units of the previous layer are connected with each unit of the next layer.
9. The electricity consumer credit evaluation method according to claim 1, wherein the step S5 is embodied by multiplying the weight of each index of the user by the index score of each index to obtain the user credit score.
10. The electricity consumer credit assessment method according to claim 1, wherein said step S6 comprises the following steps: and dividing the credit score of the user into a plurality of preliminary credit levels by adopting a clustering algorithm, and adjusting the preliminary credit levels by combining with the electricity utilization indexes under the electricity utilization standardization to obtain the credit levels of the client.
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| CN114596105A (en) * | 2022-03-23 | 2022-06-07 | 江苏云快充新能源科技有限公司 | Method, device, equipment and medium for evaluating credit of charging user |
| CN116029535A (en) * | 2023-03-27 | 2023-04-28 | 东莞先知大数据有限公司 | Water supply pressure early warning method and device, electronic equipment and storage medium |
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Application publication date: 20210514 |