| In recent years,environmental pollution and energy shortages are becoming more and more serious.Electric vehicles are strongly supported and promoted by the advantages of environmental protection and energy saving,and the quantity of ownership continues to grow.However,the temporal and spatial distribution of EV charging load has great randomness.As the scale of EVs expands,if the charging behavior is not controlled,the safe and stable operation of power grid will be threatened.At the same time,the uneven distribution and unreasonable layout of charging facilities are prominent,which increases the difficulty of charging and is not conducive to the promotion of EVs.Therefore,it is of great significance for the long-term development of EVs to forecast the charging load,to optimize dispatching for charging and discharging and to plan the charging station.Firstly,this dissertation forecasts EV charging load based on trip chain theory.After the analysis of EVs’ traveling and charging behavior,the charging load calculation model is established.Through the simulation of a case,the results under different charging scenarios,different types of days and different penetration rate are analyzed.Secondly,this dissertation researches on optimal dispatching for EVs considering battery-discharging loss.The optimal dispatching model is established by considering load fluctuation in power grid and users’ cost,and the model is solved by improved particle swarm algorithm.Through the simulation of a case,the battery-discharging loss is calculated using dynamic model,and the optimal dispatching results under different dispatching vehicles and different time-of-use price are compared and analyzed.Thirdly,the hierarchical optimal dispatching for EVs is carried out based on distributed control.According to the hierarchical control architecture,EV users independently develop and submit their acceptable schemes,local dispatching agencies review and select the plan,and control center checks safe operation constraint and conducts management control.Through the case of IEEE 33-bus distribution network with three local dispatching agencies,coordinated control between layers is achieved,and load fluctuations and user costs are reduced under the premise of ensuring safe operation of distribution network.Finally,taking electric taxi as the research object,the charging station planning model is established based on the analysis of behavior characteristics.The charging station capacity is configured using the queuing theory M/G/c model and the charging station location is solved by the method combining Voronoi diagram and improved quantum genetic algorithm.36-bus road network combined with 33-bus distribution network is taken as a case to determine the optimal planning scheme and verify the effectiveness of the planning model. |
