Evaluating the Credit of New Energy Power Generation Enterprises in Power Market Based on Fuzzy Best-Worst and Improved Matter-Element Extension Method

Under the background of new power system, the proportion of new energy power generation enterprises in the power market is gradually increasing. With the further expansion of China's power trading scale, the increasingly fierce market competition and the instability of new energy output, the credit problems of new energy power generation enterprises in the trading process can not be ignored. Therefore, improving and perfecting the credit system of new energy power generation enterprises is a necessary condition for building a modern market system. Firstly, the credit indicators of new energy power generation enterprises are constructed from the three dimensions of performance ability, performance behavior and performance willingness. Then, a credit index evaluation model of new energy power generation enterprises based on fuzzy best-worst and improved matter-element extension method is proposed. Finally, an empirical study is carried out, and the analysis results show that scheduling discipline compliance,historical credit and participation rate of market-oriented transaction have a greater impact on the credit of new energy power generation enterprises and they should focus on in market transactions. The model proposed in this paper can effectively deal with the ambiguity of indicators in the credit evaluation of new energy power companies. Through comparison with other models, the effectiveness of the model proposed in this paper in the credit evaluation of power companies is further verified. Construction provides method support