Research On Probabilistic Modeling Of Electric Vehicle Charging Loads And Coordinated Charging And Discharging Strategy Considering Traffic Characteristics

In recent years,problems such as global warming and air pollution have become increasingly prominent.Vehicle exhaust pollution is one of the main sources of air pollution.In this regard,many countries and regions have formulated a timetable for banning the sale of fuel vehicles.In March 2019,Hainan Province issued a clean energy vehicle development plan.It was the first in China to propose a ban on the sale of fuel vehicles by 2030.The main vehicle companies are also accelerating their deployment in the new energy vehicle market.Driven by both policies and market,the scale of electric vehicles and the demand for charging are bound to usher in a new round of growth.Large-scale charging load access will have a greater impact on the safe and stable operation of the power grid.It is urgent to carry out research on related technologies such as modeling of electric vehicle charging load characteristics and coordinated charging and discharging strategies.Establishing an accurate model of the temporal and spatial distribution characteristics of electric vehicle charging load is the basis for analyzing its influence on the operation of the power grid.A probabilistic modeling method for the temporal and spatial distribution characteristics of electric vehicle charging load based on dynamic traffic flow is proposed.The model is composed of the traffic road network model,the spatial-temporal transfer model of vehicles and the probabilistic model of residents’ traveling.The spatial-temporal transfer model of vehicles reflects the influence of traffic condition on the speed and power consumption of EVs.The driving vehicles can dynamically adjust the speed and traveling path according to the traffic condition.The probabilistic model of residents’ traveling establishes the joint probability distribution of travel destination and departure time based on the NHTS data,and the trip chains are obtained by sampling from the model.Simulations are performed based on the road network of a typical urban area,wherein Monte Carlo method is adopted to predict the spatial-temporal distribution characteristics for EV charging load.Compared with the results of the existing methods and the actual EV charging load curve,the correctness and effectiveness of the proposed probabilistic model are demonstrated.The massive electric vehicle charging loads brings great challenges to the operation of the power grid.Guiding the coordinated charging and discharging of electric vehicles is an effective method to improve the safety and economy of power grid operation.A travel optimization model for electric vehicle considering traffic characteristics and a coordinated charging and discharging optimization model considering time-of-use electricity prices are established.The travel behavior and charging and discharging behavior of electric vehicle users are simulated and optimized.The travel optimization model considering traffic characteristics takes minimizing the power consumption of the trip as the optimization goal,and the the optimal trip departure time and driving path are recommended to the electric vehicle users according to the real-time traffic conditions.The coordinated charging and discharging optimization model considering time-of-use electricity price takes minimizing the charging cost as the optimization goal.The optimal charging and discharging time period is recommended to the electric vehicle users according to the travel plan and time-of-use electricity price.Simulations are performed based on the road network and the power gird of a typical urban area.The results show that the recommended travel plan can not only reduce the power consumption of the trip,but also effectively avoid traffic jams and reduce the travel time.The recommended charging and discharging plan obtained can not only reduce the charging cost of electric vehicle owners,but also have a positive impact on the power grid.The recommended travel plan can not only reduce the power consumption of the trip,but also effectively avoid traffic jams and reduce the time consumption of the trip.The orderly charging and discharging optimization model considering the time-of-use electricity price takes minimizing the charging cost as the optimization goal,and recommends the optimal charging and discharging time period for electric vehicle owners according to the travel plan and time-of-use electricity price.The recommended charging scheme can not only reduce the charging cost of electric vehicle owners,but also produce a positive impact of peak shaving and valley filling on the power grid.