Electric charge risk assessment and early warning method and system

Abstract

The invention belongs to the technical field of electric charge risk assessment and management, and relates to an electric charge risk assessment and early warning method and system. The method comprises: regularly obtaining power consumption credit rating of users, the creditc including high, relatively high, relatively low and low; evaluating the arrearage risk level of the user according to thecurrent power consumption credit rating and arrearage information of the user; executing a corresponding early warning operation according to the arrearage risk level of the user. The method is basedon power consumption credit rating evaluation of users. The comprehensiveness, fairness and objectivity of indexes can be ensured, multi-level judgment is realized, the relationship between the weight and the evaluation result is adjusted according to the requirements, and the discrimination is realized for the importance degree of the evaluation indexes, so that the evaluation is more adaptive to the actual situation, the risk level is more accurately executed for credit evaluation, and early warning is facilitated.

Description

technical field [0001] The invention relates to the technical field of electricity charge risk assessment and management, in particular to an electricity charge risk assessment and early warning method and system. Background technique [0002] In recent years, power companies have had to spend extra manpower and material resources to solve these problems due to customers’ malicious arrears of electricity bills, electricity leakage, etc., and this is a great waste to the economy of the power company and the economy of society , the lack of credit management has affected the normal business activities of power companies. Therefore, the power company's research on the "one household, one policy" electricity fee recovery risk management and control system based on power customer credit management, preventing electricity fee arrears, and timely recovery of electricity fees have become important issues that power companies must face. [0003] Therefore, how to scientifically, obj...

AI Technical Summary

Problems solved by technology

Among them, the Analytic Hierarchy Process can hardly be used when faced with a particularly large number of indicators, because the construction of the reciprocal matrix needs to be completed manually, and when people compare many indicators in pairs, the fairness and objectivity cannot be guaranteed at all. And the efficiency is very low, so the application scenarios of the AHP are relatively simple; on the other hand, when the entropy weight method is faced with an evaluation index with a particularly large degree of dispersion, the weight will be too large due to the large entropy value, which will affect the evaluation results. Therefore, in the process of actual application, there will be a phenomenon that the obtained weight does not conform to the actual situation.

As a result, it is much more difficult to evaluate the risk level based on user credit in the future. Therefore, it is difficult to achieve targeted early warning based on the above information

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