Power customer service risk early warning and trend studying and judging method

Abstract

The invention discloses a power customer service risk early warning and trend research and judgment method, and relates to the technical field of power customer risk early warning, and the method comprises the steps: S1, building a power utilization enterprise database; s2, grading the customer volume; s3, establishing a customer credit system; s4, establishing a fund payment mode; s5, evaluating the operation condition of the enterprise; s6, evaluating electricity consumption information of the enterprise; and S7, estimating the payment capability of the customer. The power customer service risk early warning and trend studying and judging method has the beneficial effects that the credit of the enterprise is calculated through the power consumption volume of the enterprise user and the enthusiasm of the enterprise to pay the electric charge, so that the enterprise is graded by utilizing the payment adaptability of the enterprise; therefore, the payment habits of the enterprises can be better utilized to perform grading and classification on the enterprises, so that the power supply unit can better assess the enterprises, the power supply unit can be effectively helped to avoid high-risk enterprises, and response is also facilitated.

Description

Technical Field

[0001] This invention relates to the field of power customer risk early warning technology, specifically a method for power customer service risk early warning and trend analysis. Background Technology

[0002] Electricity, as one of the most important energy sources in contemporary society, directly affects people's normal lives and production activities. In order to allocate electricity rationally, the power supply process can be divided into residential electricity, commercial electricity, and industrial electricity according to the different electricity users and different electricity usage scenarios. Generally, industrial electricity is supplied to factories and other enterprise sites for industrial production. The main characteristics of industrial electricity are large electricity consumption, stable electricity usage time, and a requirement for stable power supply. However, due to the different operating conditions of enterprises, when supplying electricity to enterprises, there are often situations where enterprises are unable to afford electricity bills due to financial difficulties or poor management, resulting in the power supply unit bearing the risk. Therefore, this application proposes a method for risk warning and trend analysis of electricity customer service. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method for risk warning and trend analysis of electricity customer service, which solves the problems mentioned in the background.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for risk warning and trend analysis of electricity customer service, comprising the following steps:

[0005] S1. Establish a database of electricity-consuming enterprises: This step involves establishing a separate database for each enterprise based on their electricity consumption priorities, usage times, and electricity consumption amounts, in order to store their electricity consumption and payment information.

[0006] S2. Classify customers by size: This step involves classifying users into different sizes based on their average monthly electricity consumption.

[0007] S3. Establish a customer credit system: This involves assessing the reliability and timeliness of customers based on their payment information within a given period, and qualitatively determining their creditworthiness.

[0008] S4. Establish payment methods: Steps to provide different payment methods based on the different credit indices of different corporate clients;

[0009] S5. Evaluate the company's business performance: The steps to assess the specific business performance of the client company;

[0010] S6. Assess the company's electricity consumption information: This step involves assessing the company's electricity consumption information for the current and future periods based on the customer's past electricity consumption patterns.

[0011] S7. Estimate Customer's Payment Ability: This step involves estimating the customer's ability to make payments based on the company's operating conditions.

[0012] In this invention, step S1, establishing the electricity-consuming enterprise database, includes the following steps:

[0013] S11. Query the company's monthly electricity consumption: The steps to summarize the company's monthly electricity consumption;

[0014] S12. Summary of Peak Electricity Consumption for Enterprises: Steps for summarizing peak electricity consumption times for each month within a year;

[0015] S13. Summary of Peak and Valley Electricity Consumption Time for Enterprises: Steps for summarizing the peak and valley electricity consumption of enterprises daily;

[0016] S14. Draw a reference diagram of enterprise electricity consumption: Steps to draw a detailed electricity consumption information diagram of the enterprise based on its electricity consumption.

[0017] S15. Summary of Enterprise Electricity Payment Information: Steps for summarizing the monthly payment time, payment amount, and payment items for enterprises.

[0018] In this invention, step S2, classifying customer size, includes the following steps:

[0019] S21. Detecting an enterprise's annual electricity consumption: Steps for calculating the total electricity consumption within a calendar year:

[0020] S22. Calculating a company's monthly electricity consumption within a single year: Steps for dividing the electricity consumption within a calendar year equally and calculating the average monthly electricity consumption:

[0021] S23. Confirm customer electricity consumption volume: This step involves dividing customers into different volumes based on their monthly electricity consumption.

[0022] The capacity range in S23 includes 100,000 kW / h-200,000 kW / h; 200,000 kW / h-300,000 kW / h; 300,000 kW / h-400,000 kW / h; 400,000 kW / h-500,000 kW / h; 500,000 kW / h-700,000 kW / h; 700,000 kW / h-900,000 kW / h; and above 900,000 kW / h.

[0023] Furthermore, in this invention, step S3, establishing a customer credit system, includes the following steps:

[0024] S31. Inquiry about payment status within the cooperation period: Steps to inquire about the payment status of electricity-consuming enterprises within the cooperation period:

[0025] S32. Record payment delay time: Record the delay time and details of each electricity bill payment due from the electricity-consuming enterprise based on the database;

[0026] S33. Calculate the customer risk index: using The risk index for clients is calculated using the following method: V = size index; t = delay time.

[0027] S34. Rating customer credit based on risk index: Rating customer credit based on risk index. The higher the risk index, the higher the creditworthiness.

[0028] Furthermore, in this invention: the size index is determined based on the size range of the enterprise.

[0029] The volume index is 15 for the range of 100,000 kW / h to 200,000 kW / h.

[0030] The volume index for the range of 200,000 kW / h to 300,000 kW / h is 25.

[0031] The volume index for the range of 300,000 kW / h to 400,000 kW / h is 35.

[0032] The volume index for the range of 400,000 kW / h to 500,000 kW / h is 45.

[0033] The volume index for the range of 500,000 kW / h to 700,000 kW / h is 60.

[0034] The volume index is 80 for the range of 700,000 kW / h to 900,000 kW / h.

[0035] The volume index for volumes above 900,000 kW / h is 100.

[0036] The delay time is as follows: 1 day is 2; 2 days is 3; 3 days is 4; 4 days is 5... and so on.

[0037] Furthermore, in this invention: S5, evaluating the enterprise's operating conditions includes summarizing production capacity, management, and sales.

[0038] The capacity aggregation includes the following steps:

[0039] S511. Calculate the maximum production output of an enterprise: The steps for calculating the maximum theoretical output of an enterprise under full-load conditions;

[0040] S512. Calculate the current production output value of the enterprise: The steps to calculate the output value of the current production plan of the enterprise;

[0041] S513. Calculate the idle rate and reserve output value rate of scattered equipment: The steps to calculate the idle rate of equipment and the unsaturated output value storage rate;

[0042] S514. Calculating the enterprise capacity index: The steps to calculate the capacity index based on the ratio between the enterprise's current output value and its maximum output value;

[0043] The management summary includes the following steps:

[0044] S521. Calculate the number of employees employed one year ago: Steps for calculating the number of employees employed by the current enterprise one year ago;

[0045] S522. Calculate the current number of employees: The steps to calculate the current number of employees employed by the company.

[0046] S523. Calculate personnel changes: Calculate the number of personnel changes within a one-year period, with layoffs being negative and increases being positive;

[0047] S524. Calculate the enterprise management index: Calculate the management index of production enterprises based on the increase or decrease of personnel;

[0048] The sales summary includes the following steps:

[0049] S531. Calculate the corresponding monthly product sales volume: The steps for calculating the products produced by the company in the current month;

[0050] S532. Calculate warehouse inventory: Calculate the inventory of products produced in the current month.

[0051] S533. Calculate product stacking rate: A step that compares product sales rate and stacking rate;

[0052] S534. Calculating the Enterprise Sales Index: Steps for calculating the sales index based on the stacking rate;

[0053] The company's operating status is roughly calculated based on the aforementioned capacity index, management index, and sales index.

[0054] In this invention, step S6, estimating enterprise electricity consumption information, includes the following steps:

[0055] S61. Query electricity consumption information for the most recent 6 months: Steps to query electricity consumption information for the previous 6 months of the current production plan;

[0056] S62. Creating an electricity consumption trend chart: Steps for drawing an electricity consumption trend chart based on the electricity consumption over the past 6 months;

[0057] S63. Query electricity usage information: The steps to query electricity usage information for the same 6 months within the previous two years, and for the following 3 months after the same 6 months within the previous two years, for a total of 9 months;

[0058] S64. Create a comparative electricity consumption trend chart: This step involves drawing an electricity consumption trend chart based on the electricity consumption data obtained from S63 for the past two years.

[0059] S65. Perform trend chart fusion: The step of fusion of two sets of trend charts and the current electricity consumption trend chart;

[0060] S66. Estimating electricity consumption: The step of estimating electricity consumption for the next 3 months based on the integrated trend chart.

[0061] In a further step of this invention: S7, in estimating customer payment ability, the customer's business situation is used to estimate whether they can pay electricity bills.

[0062] Furthermore, in this invention: S4, the payment mode can be divided into prepayment, deposit payment, monthly payment and quarterly payment according to the different credit conditions of corporate customers.

[0063] This invention provides a method for risk warning and trend analysis in electricity customer service, which has the following beneficial effects:

[0064] 1. This method for risk warning and trend analysis of electricity customer service calculates the credit rating of enterprises based on their electricity consumption and willingness to pay electricity bills. By utilizing the enterprises' payment cooperation, it classifies them into different tiers, allowing for better classification and assessment of enterprises based on their payment habits. This enables power supply units to better evaluate enterprises, effectively help them avoid high-risk enterprises, and facilitate response.

[0065] 2. This method for risk warning and trend analysis of electricity customer service can summarize the current operating situation of an enterprise by summarizing its production capacity, management, and sales. Furthermore, it can select different payment schemes based on the enterprise's operating situation, thereby enabling the power supply unit to better avoid risks and ensure that the enterprise can pay its electricity bills. Attached Figure Description

[0066] Figure 1 This is a schematic diagram of the structure of the present invention;

[0067] Figure 2 A flowchart illustrating the process of establishing a database of electricity-consuming enterprises for this invention;

[0068] Figure 3 This is a schematic diagram illustrating the process of classifying customer size according to the present invention.

[0069] Figure 4 This is a flowchart illustrating the process of establishing a customer credit system for this invention.

[0070] Figure 5 This is a flowchart illustrating the process of evaluating enterprise operations according to the present invention.

[0071] Figure 6This is a flowchart illustrating the process of estimating enterprise electricity consumption information according to the present invention. Detailed Implementation

[0072] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0073] Please see Figures 1 to 6 This invention provides a technical solution: a method for risk early warning and trend analysis of electricity customer service, comprising the following steps:

[0074] S1. Establish a database of electricity-consuming enterprises: This step involves establishing a separate database for each enterprise based on their electricity consumption priorities, usage times, and electricity consumption amounts, in order to store their electricity consumption and payment information.

[0075] S2. Classify customers by size: This step involves classifying users into different sizes based on their average monthly electricity consumption.

[0076] S3. Establish a customer credit system: This involves assessing the reliability and timeliness of customers based on their payment information within a given period, and qualitatively determining their creditworthiness.

[0077] S4. Establish payment methods: Steps to provide different payment methods based on the different credit indices of different corporate clients;

[0078] S5. Evaluate the company's business performance: The steps to assess the specific business performance of the client company;

[0079] S6. Assess the company's electricity consumption information: This step involves assessing the company's electricity consumption information for the current and future periods based on the customer's past electricity consumption patterns.

[0080] S7. Estimate Customer's Payment Ability: This step involves estimating the customer's ability to make payments based on the company's operating conditions.

[0081] S1. Establishing a database of electricity-consuming enterprises includes the following steps:

[0082] S11. Query the company's monthly electricity consumption: The steps to summarize the company's monthly electricity consumption;

[0083] S12. Summary of Peak Electricity Consumption for Enterprises: Steps for summarizing peak electricity consumption times for each month within a year;

[0084] S13. Summary of Peak and Valley Electricity Consumption Time for Enterprises: Steps for summarizing the peak and valley electricity consumption of enterprises daily;

[0085] S14. Draw a reference diagram of enterprise electricity consumption: Steps to draw a detailed electricity consumption information diagram of the enterprise based on its electricity consumption.

[0086] S15. Summary of Enterprise Electricity Payment Information: Steps for summarizing the monthly payment time, payment amount, and payment items for enterprises.

[0087] S2, classifying customer size includes the following steps:

[0088] S21. Detecting an enterprise's annual electricity consumption: Steps for calculating the total electricity consumption within a calendar year:

[0089] S22. Calculating a company's monthly electricity consumption within a single year: Steps for dividing the electricity consumption within a calendar year equally and calculating the average monthly electricity consumption:

[0090] S23. Confirm customer electricity consumption volume: This step involves dividing customers into different volumes based on their monthly electricity consumption.

[0091] The capacity range of S23 includes 100,000 kWh-200,000 kWh; 200,000 kWh-300,000 kWh; 300,000 kWh-400,000 kWh; 400,000 kWh-500,000 kWh; 500,000 kWh-700,000 kWh; 700,000 kWh-900,000 kWh; and above 900,000 kWh.

[0092] S3, Establishing a customer credit system includes the following steps:

[0093] S31. Inquiry about payment status within the cooperation period: Steps to inquire about the payment status of electricity-consuming enterprises within the cooperation period:

[0094] S32. Record payment delay time: Record the delay time and details of each electricity bill payment due from the electricity-consuming enterprise based on the database;

[0095] S33. Calculate the customer risk index: using The risk index for clients is calculated using the following method: V = size index; t = delay time.

[0096] S34. Rating customer credit based on risk index: Rating customer credit based on risk index. The higher the risk index, the higher the creditworthiness.

[0097] Among them, the size index is determined based on the size range of the enterprise:

[0098] The volume index is 15 for the range of 100,000 kW / h to 200,000 kW / h.

[0099] The volume index for the range of 200,000 kW / h to 300,000 kW / h is 25.

[0100] The volume index for the range of 300,000 kW / h to 400,000 kW / h is 35.

[0101] The volume index for the range of 400,000 kW / h to 500,000 kW / h is 45.

[0102] The volume index for the range of 500,000 kW / h to 700,000 kW / h is 60.

[0103] The volume index is 80 for the range of 700,000 kW / h to 900,000 kW / h.

[0104] The volume index for volumes above 900,000 kW / h is 100.

[0105] The delay time is as follows: 1 day is 2; 2 days is 3; 3 days is 4; 4 days is 5... and so on.

[0106] Among them: S5, the evaluation of enterprise operation includes a summary of production capacity, a summary of management, and a summary of sales;

[0107] The capacity summary includes the following steps:

[0108] S511. Calculate the maximum production output of an enterprise: The steps for calculating the maximum theoretical output of an enterprise under full-load conditions;

[0109] S512. Calculate the current production output value of the enterprise: The steps to calculate the output value of the current production plan of the enterprise;

[0110] S513. Calculate the idle rate and reserve output value rate of scattered equipment: The steps to calculate the idle rate of equipment and the unsaturated output value storage rate;

[0111] S514. Calculating the enterprise capacity index: The steps to calculate the capacity index based on the ratio between the enterprise's current output value and its maximum output value;

[0112] The management summary includes the following steps:

[0113] S521. Calculate the number of employees employed one year ago: Steps for calculating the number of employees employed by the current enterprise one year ago;

[0114] S522. Calculate the current number of employees: The steps to calculate the current number of employees employed by the company.

[0115] S523. Calculate personnel changes: Calculate the number of personnel changes within a one-year period, with layoffs being negative and increases being positive;

[0116] S524. Calculate the enterprise management index: Calculate the management index of production enterprises based on the increase or decrease of personnel;

[0117] Sales summary includes the following steps:

[0118] S531. Calculate the corresponding monthly product sales volume: The steps for calculating the products produced by the company in the current month;

[0119] S532. Calculate warehouse inventory: Calculate the inventory of products produced in the current month.

[0120] S533. Calculate product stacking rate: A step that compares product sales rate and stacking rate;

[0121] S534. Calculating the Enterprise Sales Index: Steps for calculating the sales index based on the stacking rate;

[0122] The company's operating status is roughly calculated based on the capacity index, management index, and sales index.

[0123] Among them, S6, the estimated enterprise electricity consumption information includes the following steps:

[0124] S61. Query electricity consumption information for the most recent 6 months: Steps to query electricity consumption information for the previous 6 months of the current production plan;

[0125] S62. Creating an electricity consumption trend chart: Steps for drawing an electricity consumption trend chart based on the electricity consumption over the past 6 months;

[0126] S63. Query electricity usage information: The steps to query electricity usage information for the same 6 months within the previous two years, and for the following 3 months after the same 6 months within the previous two years, for a total of 9 months;

[0127] S64. Create a comparative electricity consumption trend chart: This step involves drawing an electricity consumption trend chart based on the electricity consumption data obtained from S63 for the past two years.

[0128] S65. Perform trend chart fusion: The step of fusion of two sets of trend charts and the current electricity consumption trend chart;

[0129] S66. Estimating electricity consumption: The step of estimating electricity consumption for the next 3 months based on the integrated trend chart.

[0130] Among them: S7, in the estimation of customer payment ability, the customer's business situation is used to estimate whether they can pay electricity bills.

[0131] Among them, S4, the payment model can be divided into prepayment, deposit payment, monthly payment and quarterly payment depending on the credit status of the enterprise customer.

[0132] In summary, this method for risk warning and trend analysis of electricity customer service, when in use, first establishes a separate database for each electricity-consuming enterprise based on its electricity consumption focus, time of use, and amount of electricity consumed, in order to store the enterprise's electricity consumption and payment information. Users are categorized into different sizes based on their average monthly electricity consumption. The reliability and timeliness of customers are assessed based on their payment information within a given period, and their credit is qualitatively determined. Different payment methods are provided based on the different credit indices of different enterprise customers. When predicting risk trends, the specific operating conditions of the customer enterprise are assessed. The electricity consumption information for the current and future periods is evaluated based on the customer's past electricity consumption data, and the enterprise's ability to pay is predicted based on its operating conditions.

[0133] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A power customer service risk early warning and trend judgment method, characterized in that: It comprises the following steps: S1, establishing power consumption enterprise database: according to the power consumption of the enterprise, the power consumption time and the power consumption of different enterprises to establish a separate database to save the enterprise power consumption and payment information steps; S2, the customer size classification: according to the different customer average monthly power consumption will be divided into different size steps; S3, the establishment of customer credit system: according to the customer cycle of payment information on the reliability, timeliness of the evaluation, and the credit of qualitative steps; S4, the establishment of payment mode: according to the different credit index of different enterprise customers to provide different payment mode steps; S5, the evaluation of enterprise management: the specific business of the customer enterprise evaluation steps; S6, the evaluation of enterprise power consumption information: according to the customer in the past cycle of power consumption of enterprise current time period and future time period of power consumption information evaluation steps; S7, the estimation of customer payment ability: according to the customer enterprise management to estimate its payment ability steps.

2. The method according to claim 1, characterized in that: The S1, establishing power consumption enterprise database comprises the following steps: S11, query enterprise monthly power consumption: the enterprise monthly power consumption summary steps; S12, enterprise power consumption peak summary: enterprise in a single month of power consumption peak time summary steps; S13, enterprise power consumption peak and valley time summary: enterprise daily power consumption peak and valley value summary steps; S14, draw enterprise power consumption reference diagram: according to the enterprise power consumption draw enterprise detailed power consumption information diagram steps; S15, enterprise power consumption payment information summary: enterprise monthly payment time, payment amount, payment project summary steps.

3. The method according to claim 1, characterized in that: The S2, the customer size classification comprises the following steps: S21, detection of enterprise annual power consumption: the total amount of power consumption in a natural year calculation steps: S22, calculation of enterprise monthly power consumption in a year: the power consumption in a natural year, the average monthly power consumption calculation steps: S23, confirm the customer size: according to the different monthly power consumption, the customer is divided into different size steps; The S23 size range includes 100000 kw / h-200000 kw / h; 200000 kw / h-300000 kw / h; 300000 kw / h-400000 kw / h; 400000 kw / h-500000 kw / h; 500000 kw / h-700000 kw / h; 700000 kw / h-900000 kw / h and 900000 kw / h above.

4. The method according to claim 1, characterized in that: The S3, the establishment of customer credit system comprises the following steps: S31, query period payment: query the cooperation period of power consumption enterprise payment steps: S32, record the delay time: according to the database of power consumption enterprise each time the delay time, delay of payment record; S33. Calculate the customer risk index: using The risk index for clients is calculated using the following method: V = size index; t = delay time. S34, according to the risk index of customer credit rating: according to the risk index of customer credit rating, the higher the risk index, the higher the credit.

5. The method according to claim 4, characterized in that: The size index is determined according to the size range of the enterprise: 100000 kw / h-200000 kw / h range of size index is 15; 200000 kw / h-300000 kw / h range of size index is 25; 30-40 million kw / h, the volume index is 35; 40-50 million kw / h, the volume index is 45; 50-70 million kw / h, the volume index is 60; 70-90 million kw / h, the volume index is 80; 90 million kw / h above, the volume index is 100; The delay time is: 1 day is 2; 2 days is 3; 3 days is 4; 4 days is 5; and so on.

6. The method of claim 1, wherein the method further comprises: The S5, evaluating the enterprise operation situation includes production capacity summary, management summary and sales summary; The production capacity summary includes the following steps: S511, calculating the maximum production value of the enterprise: the step of calculating the maximum theoretical production value of the enterprise under full load state; S512, calculating the current production value of the enterprise: the step of calculating the production value of the production plan of the current production plan of the enterprise; S513, calculating the idle rate of scattered equipment and the reserve production value rate: the step of calculating the idle rate of equipment and the unsaturated production value storage rate; S514, calculating the enterprise production capacity index: the step of calculating the production capacity index according to the ratio between the current production value and the maximum production value of the enterprise; The management summary includes the following steps: S521, calculating the number of workers employed one year ago: the step of calculating the number of workers employed one year ago of the current enterprise; S522, calculating the number of current employees: the step of calculating the number of current employees of the current enterprise; S523, calculating the number of personnel changes: calculating the number of personnel changes in a one-year period, negative for layoffs and positive for increases; S524, calculating the enterprise management index: calculating the management index of the production enterprise according to the increase and decrease of personnel; The sales summary includes the following steps: S531, calculating the product sales of the corresponding month: the step of calculating the products produced by the enterprise in the current month; S532, calculating the warehouse accumulation: the step of calculating the warehouse accumulation of the products produced in the current month; S533, calculating the product accumulation rate: the step of comparing the product sales rate and the accumulation rate; S534, calculating the enterprise sales index: the step of calculating the sales index according to the accumulation rate; According to the production capacity index, the management index and the sales index, the enterprise operation situation is roughly calculated.

7. The method of claim 1, wherein the method further comprises: The S6, estimating the enterprise electricity consumption information includes the following steps: S61, querying the electricity consumption information of the last 6 months: the step of querying the electricity consumption information of the last 6 months of the current production plan; S62, making electricity trend chart: the step of drawing the electricity trend according to the electricity consumption of the last 6 months; S63, querying the electricity consumption information: the step of querying the electricity consumption information of the same 6 months in the last two years, and the information of the same 6 months and the next 3 months in the last two years, a total of 9 months; S64, making comparison electricity trend chart: the step of drawing the electricity trend chart of the electricity consumption of the last two years queried in S63; S65, trend chart fusion: the step of fusing two sets of trend charts and the current electricity trend chart; S66, electricity consumption estimation: the step of estimating the electricity consumption in the next 3 months according to the fused trend chart.

8. The method according to claim 1, characterized in that: The S7, the estimated customer payment ability uses the operating condition of the customer to estimate whether the customer can pay the electricity fee.

9. The method of claim 1, wherein the method further comprises: determining a risk level of the power customer based on the power customer service data; and determining a trend of the power customer based on the power customer service data. The S4, the payment mode is divided into the prepayment payment, the deposit payment, the monthly payment and the quarterly payment according to the credit condition of the enterprise customer.

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