Energy Procurement And Retail Price Determination Model Of An Electricity Retailer Considering ESS&EVs

Since the beginning of the power system reform in 2015,more and more social capital has been allocated in the electricity sales business,and the competition on the electricity sales side has become increasingly fierce.This paper focuses on the decision-making of electricity retailers that consider electric vehicles and energy storage systems after the electricity sales market is open.First of all,in order to make the decision-making scheme more tolerant to the risks brought by electricity price at market and users’ load fluctuation,the uncertain factors and treatment methods in the decision-making of purchasing and selling electricity are studied.For the uncertainties such as market electricity price and user load that can be predicted by the time series method,the ARIMA-based scenario generation method based on historical data,is used to obtain the ARIMA fitting model and data fluctuation information,and then randomly generate the white noise sequence that could satisfy the probability characteristics of the data.So a set of scenarios is obtained.Introduce a scenario reduction method based on Kantorovich distance,and reduce the generated large number of scenarios.A reduction set that can describe the uncertainty characteristics of random variables well and meet the computational efficiency is obtained.The Monte Carlo simulation of the uncertainty parameters of the electric vehicle is used to obtain the relevant parameters.Secondly,with the goal of minimizing the cost of electricity purchase by electricity retailers,a decision-making model considering energy storage systems and electric vehicles was established for power purchase companies.The results show that both adjusting the charging mode of the electric vehicle to free charging and adding the energy storage system can reduce the electricity purchase cost of the electricity sales company.Although the energy storage system improves the energy management efficiency of the electricity sales company,its effect on the cost reduction is weaker than the electric vehicle charging and discharging mode adjustment’s.Finally,a double-layer decision-making model for electricity retailers was established.The upper model aims at maximizing sales profit,and the lower model aims at minimizing the energy cost of electric vehicles.The upper and lower models are interconnected by retail electricity prices and electric vehicle charging plans,and jointly optimize the retail electricity price of the electricity sales company,the charging plan of the electric vehicle,and the proportion of electricity purchased by the power company.For the regular user,a user load model based on the price-quota curve is established.For the electric vehicle users who choose the free charging mode,the relationship between energy consumption and retail electricity price is analyzed.The example shows that the two-layer model can make reasonable retail pricing for regular users and electric vehicle users,and optimize the proportion of electricity purchased by different power sources.While meeting the minimum charging cost of electric vehicle users and the goal of maximizing the profitability of the electricity retailers,a win-win investment portfolio is provided for the electricity retailers and users.