Coordinated Charging Strategies For Electric Vehicles Considering Interaction Of "Source-Grid-Load"

With the fossil energy crisis and environment problem becoming more and more serious,eco-friendly electric vehicles(EVs)begin to get energetic development.Fortunately,EVs often have the dwell time longer than their batteries' full-charging time,therefore,EVs can be deemed as controllable loads.Through charging management or guidance for electric vehicle fleets and making reasonable charging schedule for EVs,EVs can not only mitigate their adverse effects to power grid,e.g,energy losses increasing,power quality deterioration and voltage fluctuations,but also contribute to the stability and economy of power grid.Given this background,in the framework of interactions between "Source-Grid-Load",the battery charging strategies for EVs are studied,the main contents include:1)The travel habits for typical EVs are analyzed and the uncoordinated EV charging load model is presented.The method for calculating uncoordinated EV charging load based on Monte Carlo simulation is proposed.2)Based on an EV demand response model,a bi-level mathematical model using time-of-use price as a control signal for EVs charging management is developed.By solving the bi-level model,a time-of-use pricing scheme can be obtained to stimulate EVs changing their charging behaviors for peak shaving and valley filling.Finally,the effectiveness of the proposed method is verified using a modified IEEE 30-bus testing system.3)A two-stage robust optimization method for providing reserve services for wind power by EV charging management is proposed for the purpose of minimizing the overall power system operation cost,considering the charging requirements to be satisfied with the extra reserve requirement introduced by the uncertainty of wind power.In this method,the uncertainty of wind power is modeled by the interval number and the allowed EV charging range is evaluated by it's state of charge and plug-in/plug-out time.The modified Garver's 6-bus system and IEEE 39-bus system are employed to verify the effectiveness of the proposed robust model.