Research On Electricity Retailers-Electric Vehicle Interactive Price Scheme Under Ubiquitous Power Internet Of Things

In the new round of power system reform,how to use the huge data information to maximize the profit in the power market competition has become the core issue of concern for the electricity retailers.The key to profitability lies in the energy deviation penalty mechanism of the electricity retailers.In order to reduce the appraisal cost,this paper studies the electricity retailers in the context of the Ubiquitous Power Internet of Things by using machine learning methods for load prediction,and from the perspective of guiding electric vehicle cooperation and seeking to compensate for deviations in appraisal power.In this paper,we first apply evolutionary game theory to construct a model of the interaction game between an electricity retailers and an electric vehicle user,calculating various equilibrium points of the interaction model through Lee Yapunov stability theory,and determined the factors that affect the cooperation between the two parties in the interaction process by analyzing their cooperation relationship.By analyzing the actual cases,a reasonable range of charging and discharging prices is solved,and a minimum feasible deviation rate curve with cooperation significance is deduced to provide a reference for whether or not the electricity retailers will engage in interactive cooperation.Based on this,this paper further analyzes the response measures of electricity retailers in the face of possible negative deviation penalty.Using Elman neural network,combined with meteorological data extracted from the data sharing platform of the Ubiquitous Power Internet of Things,the customer load is predicted;according to the predictable electricity sales of the electricity retailers on left days after the month,the risk of deviating electricity is judged.For analyzing the risk of deviation penalty mechanism under the current strategy of electricity retailers-electric vehicle user interaction,we formulated a reasonable cooperative price based on the relationship between the incentive peice and the motivation of electric vehicle users to participate in the regulation,and dynamically regulated the charging and discharging price to guide electric vehicle users,so as to finally achieve a balance between the profit of the electricity retailers company and the risk of deviation penalty mechanism.The results of the algorithm show that the interaction model and the interaction method proposed in this paper can effectively avoid the risk of deviated power penalty for power retailers,and promote cooperation between power retailers and electric vehicle users under the condition that the deviated power is satisfied,resulting in higher benefits for both parties.