Considering The Charging And Discharging Economic Dispatch Strategy Of Electric Vehicles Connected To The Smart Grid

The automobile industry plays an important role in the process of economic development,but with the increase of the cars number in society,exhaust has become one of the sources of urban air pollution.Electric vehicles plays an important role in energy saving,emission-reduction and alleviation of urban pollution due to their environmentally friendly characteristic.The disorderly charging behavior of large-scale electric vehicles aggravates grid fluctuation and affects the safe and stable operation of the grid.By studying the interaction between smart grids and electric vehicles,this paper establishes a charging load optimization scheduling model in which electric vehicles participate in smart grid demand-side response.While meeting the charging demand of electric vehicles,it reduces grid fluctuation and improves the stability of the power grid through reasonable planning of charging loads.The main research content of this article is introduced as follows:Firstly,establish an electric vehicle charging load forecasting model.A certain area is divided into four parts according to usage habits,and the parking time of electric vehicles in each area is different.Analyze the factors that affect the charging load of electric vehicles,and determine the probability model of each factor.The Monte Carlo method is used to obtain the charging load of electric vehicles in different areas.Secondly,establish a charging strategy optimization model between the charging station and the electric taxi.The Stackelberg game model is established between the electric taxi and the charging station,and the regional hot spot information is considered in the electric taxi charging decision model,and the reliability coefficient is considered in the charging station pricing model.A hierarchical iterative method is used to solve the equilibrium point of the game model.Through four cases,the influence of hot information and reliability coefficients on equilibrium is studied.The simulation results show that the charging decision and pricing decision taking into account the hotspot information and the reliability coefficient can reduce the cost of the vehicle and increase the revenue of the charging station.Finally,this paper studies the pricing strategy and charging decision between the distribution network and electric vehicle aggregators.In order to facilitate the management of the charging load of electric vehicles,electric vehicle aggregators have been introduced.Each aggregator is responsible for the total charging load of electric private cars and electric taxis in their respective areas.A two-level interaction model was established between the distribution network and electric vehicle aggregators.Taking into account the uncertainty of the charging load of electric taxis,a two-level robust optimization model was established,and the robust optimization model was linearized using duality theory.The distribution network side optimizes the transaction price under the consideration of power flow constraints.There are both inequality constraints and equality constraints in the model,which are solved by Lagrangian functions.The simulation results show that the scheduling scheme obtained by this method has stronger robustness and reliability.