Research On Credit Risk Evaluation And Prevention&Control Strategies Of H Electricity Sales Company

With the continuous advancement of electricity market-oriented reform,electricity sales companies are playing an increasingly important role in the electricity market.Through market-oriented operation,electricity sales companies promote the optimal allocation of power resources and the marketization of electricity prices,improve the efficiency and transparency of the electricity market and promote the development of the power industry.However,as the number of electricity sales companies increases,their credit risk is gradually highlighted.Therefore,evaluating the credit risk of electricity sales companies is a key link in ensuring the stability of transactions in the electricity market.This paper takes the reform of the electricity sales side of the electricity market as the research background,and takes the H electricity sales company as a case study to evaluate its credit risk and analyze its prevention and control strategies.Firstly,summarize current research status of credit evaluation of electricity sales companies at home and abroad,combine with the relevant policies of credit evaluation of China’s electricity market,and summarize the credit risk evaluation methods of electricity sales companies from the perspectives of rating evaluation method and model evaluation method,compare and analyze the multi-objective optimization decision theory and multi-attribute decision theory.Secondly,construct a credit measurement model for electricity sales companies which based on fuzzy optimal worst method and cloud.In this model,the evaluation index is weighted by the fuzzy optimal worst method to make it comparable and stable.The credit rating of the electricity sales company is visually displayed through the cloud model,and the Statistical dispersion of its possible risks is identified through the digital characteristic entropy of the normal cloud to measure the reliability of the electricity sales company.Finally,based on the fuzzy optimal worst method and cloud model,the credit risk level of H Electricity Sales Company is evaluated.According to the cloud model analysis results of H Electricity Sales Company,the proportion of professional technicians,contract performance rate,customer retention rate and current ratio have a greater impact on the credit risk of H Electricity Sales Company.Finally,the corresponding prevention and control suggestions are put forward.This paper analyzes the credit risk factors of H Electricity Sales Company and proposes corresponding prevention and control strategies,which has certain guiding significance for improving H Electricity Sales Company’s credit risk prevention and control capabilities.At the same time,it is also hoped that this study can provide a theoretical basis for credit risk prevention and control issues in the electricity trading market and other electricity sales companies.