Load Forecasting And Optimal Scheduling Of Charging And Discharging Of Electric Vehicles Considering Time And Space Distribution

Compared with traditional fuel vehicles,electric vehicles have the advantages of green and environmental protection,which can effectively control the greenhouse effect and alleviate the excessive use of non-renewable energy.However,the disordered charging of electric vehicles in time and space will have many impacts on the power grid,such as increasing the loss of power grid,affecting the stability of power grid operation,etc.At the same time,electric vehicle is also a flexible energy storage element,which can realize energy interaction with the power grid.Therefore,it is of great guiding significance to clarify the charging load demand of electric vehicles in the space-time dimension and to use its energy storage characteristics to reasonably schedule its charging and discharging behavior to improve the load distribution of the power grid,meet the peak shaving demand of the power grid and improve the economy of vehicle charging.Therefore,this thesis establishes a time-space prediction model for the charging load of electric vehicles,analyzes the charging load demand of different types of electric vehicles in different functional areas in detail,and proposes a hierarchical optimization scheduling strategy for the charging and discharging behavior of electric private cars with a large inventory at present,and finally optimizes its access space location to reduce the network loss of the distribution network.The main research contents are summarized as follows:Firstly,the charging load of electric vehicles has a unique space-time distribution characteristics,which is closely related to urban road structure,charging mode,user travel characteristics and charging characteristics.Therefore,considering the influence of urban road attribute characteristics on the spatial distribution of charging load,a traffic network model considering topological structure,road impedance,driving speed and functional zoning is established;In order to record the space-time information of charging load,a distribution network model is established;In order to reflect the traffic and battery attributes of electric vehicles,a single electric vehicle model is established;Based on the model,the charging load of various electric vehicles is predicted in time and space.Finally,the impact of different types of electric vehicle charging loads on the security of distribution network is evaluated through the obtained results of charging load space-time distribution.Then,in view of the characteristics of electric private cars such as large charging load,concentrated charging time and long idle time,a hierarchical optimization scheduling strategy for electric private cars is proposed,which guides the charging and discharging behavior of real-time access to electric vehicles in the lower real-time scheduling through the load expectation curve obtained by the upper daily scheduling.In the upper layer,firstly,cluster electric vehicles to eliminate the high-dimensional problems caused by different electric vehicles;Secondly,considering the battery loss caused by the discharge of electric vehicles,taking the minimum total charge and discharge cost of users,the minimum load variance and peak-valley difference of the distribution network as the goal,the Northern Hawk and the improved sparrow search hybrid algorithm are used to solve the optimal charge and discharge quantity of electric vehicles at each time;The lower dispatching uses the load expectation curve obtained from the upper dispatching to guide the charging and discharging behavior of the electric vehicle in real time.Finally,an example is used to verify the feasibility of the proposed strategy.Finally,aiming at the impact of electric vehicle access to different distribution network nodes on its network loss,an optimization strategy of electric vehicle space access location is proposed with the goal of reducing the network loss of distribution network.Secondly,aiming at the fact that the space scheduling of electric vehicles is a mixed-integer nonlinear programming problem,the traditional power flow equations and constraints are transformed into a second-order cone form through intermediate variables,and then into a nonlinear convex programming problem,and the final solution is obtained by solving the second-order cone programming;The access location is optimized in IEEE33 distribution network model.