Research On The Method Of Setting Tariff For Non-cooperative Game Of Multiple Electricity Selling Entities

Under the background of the in-depth promotion of the reform of the electricity market,the electricity sale market has been opened up,and various social capital has been included in the scope of electricity sale to participate in the market competition on the electricity sale side,forming the power market pattern of buying more and selling more,and making the electricity trade market-oriented.The opening of the electricity selling side has brought great influence to the traditional power industry.On the one hand,it opens the user’s choice and allows the user to freely choose the electricity selling company transaction.On the other hand,the price of purchasing and selling electricity has changed from the government pricing in the past to a price mechanism in which electricity sellers negotiate independently and bid in the market,gradually forming a price mechanism in which the purchase and sale price of electricity are determined by the market.In this case,if electricity selling enterprises want to gain competitive advantages,they must optimize the strategy of buying and selling electricity,and reasonably set the price of selling electricity according to the market demand to improve the competitiveness of enterprises.Therefore,it is of great importance and value to study the purchasing and selling strategies of electricity selling companies in the market environment.In this thesis,starting from the purchasing and selling decisions of electricity selling companies,the process of electricity pricing by non-cooperative game between electricity selling companies is studied under the condition of multiple electricity selling entities co-existing in the market environment.The main work contents are as follows:First of all,based on the analysis of the relationship between multi-selling entities and multi-users in the electricity selling market,the income model of multi-selling entities under the framework of non-cooperative game is established,which includes the income of the electricity selling companies,the purchase cost of the medium and long-term market and the spot market and maintenance cost,and the market share model is established by using the Logit function based on the electricity price.Secondly,in view of the Logit market share model based on electricity price,which did not fully consider the user’s power consumption preference and the key factors affecting their choice behavior,a user utility evaluation system based on FAHP(fuzzy analytic hierarchy process)was established,and the AHP and Fuzzy topsis were used to solve the user utility model of power selling companies,and the market shares of power selling companies under the comprehensive influence of multiple indicators were calculated.Then,based on the conditional value at risk,the purchasing and selling bilateral risk model of electricity selling companies is established.By introducing the risk aversion coefficient and aiming at the comprehensive utility maximization of the income and conditional risk loss of electricity selling companies,the non-cooperative pricing model of multi-electricity selling entities with different risk preferences is constructed.Finally,genetic algorithm was used to solve the game model and simulation verification was carried out in Python environment.The calculation example provides the results of non-cooperative game pricing for three electricity selling companies with three types of users based on the Logit electricity price model and the Fuzzy AHP to determine market share;Based on the simulation of spot market electricity prices and user evaluation uncertainty,the results of non-cooperative game pricing considering bilateral risks are presented;And a comparative analysis was conducted on the obtained results,which showed that the proposed model is more in line with the actual situation of the electricity market,optimizing the purchase proportion and electricity price of the power selling company,enhancing the revenue of the power selling company,and provide reference for the decision making of electricity purchasing and selling.