Multi-time Scale Coordinated Optimization Strategy For Plug-in Electric Vehicle Considering Uncertainty In Distribution System/a Microgrid

Recently,due to the increasing severity of energy crisis and environment issues,national governments have fostered the adoption and development of the low-carbon generation and transport technology represented by renewable energy sources(RES)and plug-in electric vehicle(PEV).The energy transformation to low carbon energy and transport systems requires not only the large-scale adoption of clean technologies and efficiency measures,but also new energy management strategies to efficiently incorporate these innovations in the existing infrastructure.Therefore,it is necessary to optimize the charging and discharging patterns of the PEV in the environment of smart grid with the purpose of efficient RES consumption.In this paper,different optimization scheduling models for the PEV are studied based on different time steps,the main work is presented as follows:1)The stochastic models of wind power system and photovoltaic(PV)power system are built considering uncertainty.The state space model and the load model of each PEV are presented by modeling the driving behaviors of PEV owners.The load characteristic of bettery energy storage(BES)is analyzed similar to PEV.2)A priority-based intraday scheduling strategy for PEV is proposed in the local distributed power system without renewable energy sources.Considering the habits of PEV owners,combined with the two-stage supply-demand coordinated optimization method and the evaluation model of schedulable ability(SA),the optimal threshold value of SA for PEV is determined to minimize the peak-valley difference of the system.The SA value of each PEV and the optimal threshold value of SA are compared to determine whether the PEV has the priority of being scheduled.Accordingly,reasonable fleet size of PEVs is decided for the optimization scheduling.The numerical analyses show that the load characteristics of the distributed power system and economics of PEV owners could be both improved by the proposed optimization model.3)A multi-time scale coordinated optimization strategy for PEV is proposed in a microgrid integrated with wind power and PV power and BES,which consists of intraday rolling time scale and real time scale.During the dynamic optimization,a new pricing is developed according to the relationship between RES output supply and load demand,and a model predictive control(MPC)method is applied to minimize daily total cost of microgrid considering uncertainties.Based on the results of dynamic optimization,a dynamic evaluation model of SA for response executor is developed.Scheduling priority of each response executor is then determined based on the values of SA and required amount of power compensation,then the rule-based real time power allocation is carried out according to the determined priority of each response executor.Numerical simulations on a residential microgrid show that the RES accommodation and the load characteristics of the mircrogrid and economics of supply and demand sides could be improved through the proposed optimization method.Based on the corporation of dynamic optimization and real time power allocation,the proposed optimization method shows significant advantages in dealing with the uncertainties.