Research On Optimal Scheduling Strategy Of Electric Vehicles Charging And Discharging In V2G Mode

Nowadays,the car has become an indispensable means of transportation in people’s lives.Traditional cars use oil,diesel and other non-renewable energy as fuel,which not only aggravates the depletion of resources,but also causes environmental pollution.The emergence of electric vehicles(EV)has effectively solved this problem.Electric vehicles use electric energy to replace the traditional fossil fuel combustion for driving,which will not emit harmful gases and reduce the use of non-renewable energy.In recent years,with the strong support of China,more and more people use electric vehicles.However,with the emergence of more and more electric vehicles,the following problems are a series of problems on the grid side caused by their connection to the grid charging,and their charging load has become an important load in the grid.Therefore,how to carry out intelligent scheduling of electric vehicle charging is an urgent problem to be solved.At the same time,in recent years,it is also vigorously developing renewable energy power generation.When renewable energy power generation and electric vehicle charging are integrated into the power grid,it brings challenges to the power grid dispatching.This paper systematically analyzes the operation characteristics of large-scale electric vehicles connected to the microgrid and the law of renewable energy generation,and introduces the mathematical modeling method of charging and discharging characteristics of electric vehicles in detail.Aiming at the problem of coordinated charging and discharging of electric vehicles to achieve peak shaving and valley filling effect,this paper proposed a collaborative optimization strategy of electric vehicles and renewable energy based on microgrid mode.Firstly,the mathematical model of EV charging load and users’ behavior characteristics are established,including SOC consumed by EV driving,and probability distribution of EV driving range and initial charging time.According to the mathematical model established above,factors such as initial charging time and initial state of charge are randomly selected for simulation,and the total disordered charging demand of large-scale networked electric vehicles within a day is obtained by Monte Carlo simulation method.At this time,it can be concluded that the charging demand of electric vehicles without any policy or incentive measures will lead to the increase of grid load demand and peak-valley difference,and cause system fluctuations.Secondly,the mathematical models of wind power generation and photovoltaic power generation are established.The output of wind power and photovoltaic are obtained in a day through Matlab/Simulink simulation,and the equivalent load is obtained by superposing the typical daily load of the microgrid.A collaborative optimization model of EVs and renewable energy was established.Taking the standard deviation of equivalent load minimization as the objective function,the optimal charging and discharging power of EVs was solved by quadratic programming considering the operating power limit of microgrid,EV charging and discharging power,SOC and quantity constraints.The proposed strategy can effectively absorb renewable energy generation and reduce load peak-valley difference.Finally,a scheduling model based on price-based demand response is proposed.Based on the time-of-use(TOU)price,a dynamic TOU electricity price strategy was proposed to guide EV users to charge in different periods and distribute the load,so as to realize the load load clipping and valley filling of the microgrid and ensure the safe and stable operation of the microgrid.