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JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)
Electrical Engineering     
Economic benefit evaluation of V2G aggregator for frequency regulation
YE Li ya, WANG Zhen, WEN Fu shuan, YANG Jun, JIANG Dao zhuo
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  

A multi-period bidirectional charging/discharging optimization model was proposed for economic dispatches of electric vehicles (EVs) for their participation in system frequency regulation. A heuristic prediction-correction iteration algorithm was developed to evaluate the real battery wear cost for each EV. The schedule of charging/discharging and regulation capacity for EV individuals were determined with the consideration of battery wear cost, regulation capacity demand and drivers' transportation demand. According to the different travel characteristics of private cars, public buses and taxies, several typical scenarios were developed for EV's participation in frequency regulation. EV's travel behavior parameters were simulated using stochastic simulation method. The frequency regulation benefits and battery wear costs caused by these three types of EVs were investigated by simulation studies to validate the effectiveness of the proposed method. Results show that the proposed heuristic prediction-correction iteration algorithm can effectively reduce the dispatch deviation caused by the battery wear cost prespecification.



Published: 22 September 2016
CLC:  TM 711  
Cite this article:

YE Li ya, WANG Zhen, WEN Fu shuan, YANG Jun, JIANG Dao zhuo. Economic benefit evaluation of V2G aggregator for frequency regulation. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2016, 50(9): 1831-1840.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2016.09.26     OR     http://www.zjujournals.com/eng/Y2016/V50/I9/1831


V2G代理商调频服务经济效益评估

针对电动汽车调频经济调度问题,构建多时段双向充放电优化调度模型,提出启发式预测校正迭代方法,用于评估电动汽车个体的真实电池寿命折损成本.综合考虑电池寿命折损、调频容量需求和用户出行需求等因素,制定电动汽车的充放电和调频容量计划.结合私家车、公交车和出租车的出行规律,设定若干典型调频场景,采用随机时序模拟方法模拟车辆出行参数.仿真分析3类代理商在不同场景下的调频效益以及电池寿命折损情况,说明所提方法和模型的有效性.结果表明,所提出的启发式预测校正迭代方法能够有效减少电池折损费用预设引起的调度计划偏差.

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