| With the large-scale development of the Electric Vehicles(EVs),the disadvantages of a large number of random loads connected to the power grid have become increasingly prominent.At the same time,the mobile energy storage value of electric vehicles has received widespread attention,and electric vehicles interact with the power grid(Vehicle-to-Grid,V2G)technology came into being.As a kind of distributed energy storage,electric vehicles have the characteristics of small monomer capacity,wide spatial distribution,large aggregation capacity,and strong mobility,which puts higher requirements on the orderly control of electric vehicle energy storage.This thesis takes the electric vehicle mobile energy storage as the research object and the electric vehicle large-scale application as the research background.The research is carried out from the establishment of mobile energy storage model,prediction of the temporal and spatial distribution of mobile energy storage load,mobile energy storage cooperative renewable energy dispatching strategy,and research on time-of-use electricity price of mobile energy storage.First,a mobile energy storage model for electric vehicles is established.Based on the model of parking generation rate,the characteristics of EV mobile energy storage are analyzed with gridded region as a unit,and the modeling ideas and principles are described.A state characterization model for electric vehicles is established,and a state-of-charge process for electric vehicles based on mobile characteristics is presented,which is used as the basis for the following research.Secondly,a method for predicting the load space-time distribution of electric vehicles considering the characteristics of mobile energy storage is proposed.Based on the mobile model,a stochastic constrained programming method is used to establish a stochastic model of electric vehicle mobile energy storage.Monte Carlo simulation technology is used to predict the spatiotemporal distribution of electric vehicle load under random charging.Case study is conducted in two different scenarios,and the impact of electric vehicle load on the distribution network under random charging is analyzed from three aspects: load curve,voltage,and network loss.Thirdly,a synergy dispatching strategy for mobile vehicle energy storage and renewable energy is proposed.Based on the mobile energy storage model,a synergy V2 G strategy for EV mobile storage and renewable energy is proposed with the minimum load fluctuation of power gird as its optimization objective,which considers the constraints of power flow,battery performance,owner demands and EV mobility.The case study is conducted in three different scenes including different mobile characteristics,EV scales and renewable energy generation installed capacity.The simulation results reveal the influence of EV mobility on the proposed strategy and validate the feasibility of the proposed model.Finally,the electricity price incentive method applicable to electric vehicle users is studied,and the optimal charging pricing method for electric vehicle mobile energy storage is proposed under the time-of-use electricity price mechanism.Based on the attractive model,the electric vehicle demand price elasticity model considering the state of charge of the battery is established according to the characteristics of electric vehicle users,and the derivation process of the model is explained in detail.In order to coordinate the interests of both the grid and the owners,the optimal TOU pricing strategy for EVs based on mobile characteristics is proposed.The simulation results show that the optimal TOU charging price based on the above model and strategy can smooth the load curve and reduce the cost of the owners. |
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