Optimal Dispatching Strategy Of Electric Vehicle Considering Combined Demand Response And Long-time Scale

With the rapid development of the global economy,the problems of environmental pollution and energy depletion are becoming more and more serious.Alleviating the world energy shortage and reducing carbon emissions have attracted extensive attention of governments and people all over the world in recent years.In this context,the promotion of electric vehicles(EVs)has important strategic significance in solving global climate change and reducing total carbon emissions.However,if EVs are not reasonably guided,it will have a significant negative impact on the EVs and the power grid,when the charging infrastructure and the acceptance capacity of the power grid are not perfect.Therefore,it is necessary to optimize the dispatching effect of electric vehicle aggregator(EVA)and EV users.This paper establishes an EV optimal dispatching strategy considering combined demand response and long-time scale to coordinated optimize the EVA and EV users,so as to reduce the impact of EVs access on the power grid.For EVA,this paper takes the maximization revenues of EVA and the minimization of load fluctuation as the optimization objectives.This paper establishes two EVA dispatching strategies considering combined demand response,fixed contract strategy and flexible contract strategy,to optimize the comprehensive benefits of EVA.In the two EVA dispatching strategies,the price-based and incentive-based demand response are considered.The two types of demand response are used to cluster the EV groups,which are optimized for different EV groups.The simulation results show that the combined demand response is composed of price-based demand response and incentive-based demand response,which can greatly improve the comprehensive benefits of EVA,and has certain feasibility.Compared with the fixed contract strategy and the flexible contract strategy,the flexible contract strategy is more conducive to the coordination and optimization of EVA and EV users.For EV users,this paper takes the minimization of the dispatching cost and psychological effect of mileage anxiety of EV users as the optimization objectives.This paper establishes a long-time scale EV charging/discharging dispatching model.The total dispatching cost considering the battery loss cost of EVs and the psychological effect of mileage anxiety based on Weber-Fechner law are quantified.An upper dispatching model aiming at improving the dispatching cost of EV users and reducing the psychological effect of mileage anxiety is established to guide the charging and discharging process of EVs in a long time scale.The lower real-time optimization model optimizes the daily EV charging and discharging process and aims to follow the discharging results of the upper discharging model.The simulation results show that the charging and dischargding process can be carried out from a more macro perspective to avoid the benefit degradation caused by short-time local optimization.By quantifying the psychological effect of EV users,it can maintain a low psychological effect for a long time in the charging and discharging process of EV,and improve the satisfaction of EV users.For the collaborative optimization system composed of EVA and EVs,this paper establishes an EV optimal discharging strategy considering combined demand response and long-time scale.It takes the comprehensive benefits of EVA and EV users as the optimization objectives.The time-of-use(TOU)price and the incentive discount and independent price compensation are considered.The EV groups caused by two types of demand response are optimized respectively.The simulation results show that the optimal discharging strategy proposed in this chapter is friendly to EVA and EVs.Moreover,independent price compensation is more favorable for EVA,compared with incentive discount.Under the condition of reducing incentive discounts and improving compensation parameters,the discharging cost and psychological effect of EV users can also be optimized.Obviously,it is better for EVA and EV users.In conclusion,the EV optimal discharging strategy considering combined demand response and long-time scale established in this paper can improve the comprehensive benefits of EV groups and EVA.It can reduce the burden and impact of EV access on the power grid,alleviate the mileage anxiety of EVs and the lack of charging facilities,and help achieve the grand goals of carbon neutralization through the optimal discharging of the charging and discharging process of large-scale EVs.