電動汽車可調(diào)度能力模型與日內(nèi)優(yōu)先調(diào)度策略
發(fā)布時間:2018-03-10 07:42
本文選題:電動汽車 切入點:可調(diào)度能力 出處:《電力系統(tǒng)自動化》2017年02期 論文類型:期刊論文
【摘要】:提出了"可調(diào)度能力"概念,表征單輛電動汽車(EV)基于車電互聯(lián)技術接入特定配電網(wǎng)參與系統(tǒng)運行調(diào)控時的動態(tài)能量平衡能力,并構(gòu)建了EV日內(nèi)優(yōu)先調(diào)度模型。首先,為精細量化EV可調(diào)度能力,綜合EV電池損耗程度、用戶信用度和反向供電能力等建立EV可調(diào)度能力分析模型;其次,以配電網(wǎng)總負荷峰谷差最小化為指標,結(jié)合EV可調(diào)度能力分析模型與供需兩側(cè)協(xié)同優(yōu)化的兩階段優(yōu)化調(diào)度模型,兼顧用戶用車習慣確定可調(diào)度能力最優(yōu)閾值;最后,基于新入網(wǎng)EV的可調(diào)度能力評估結(jié)果與最優(yōu)閾值的數(shù)值關系,判斷車輛有無優(yōu)先調(diào)度權(quán),從而構(gòu)建了單輛車的事件驅(qū)動型日內(nèi)優(yōu)先調(diào)度方法。以某居民區(qū)充放電設施集群為例進行了仿真分析,算例結(jié)果驗證了所提模型的合理性、有效性。
[Abstract]:In this paper, the concept of "schedulable capability" is proposed to characterize the dynamic energy balance ability of a single electric vehicle (EV) when it is connected to a specific distribution network to participate in the system operation and control based on the vehicle-electricity interconnection technology, and a EV in-day priority dispatching model is constructed. In order to accurately quantify EV schedulability, combining EV battery loss, user credit and reverse power supply ability, an EV schedulability analysis model is established. Secondly, the minimum peak-valley difference of total load of distribution network is taken as the index. Combining EV schedulability analysis model with two-stage optimal scheduling model of both sides of supply and demand, the optimal threshold of schedulable capacity is determined by taking account of the custom of user vehicle. Finally, Based on the numerical relationship between the evaluation results of the new EV schedulability and the optimal threshold value, the priority scheduling power of the vehicle is judged. An event-driven in-day priority scheduling method for a single vehicle is constructed, and the simulation results of charging and discharging facilities cluster in a residential area show that the proposed model is reasonable and effective.
【作者單位】: 浙江工業(yè)大學信息工程學院;國網(wǎng)浙江省電力公司電力科學研究院;
【基金】:國家自然科學基金資助項目(51507153) 浙江省自然科學基金資助項目(LY16E070005)~~
【分類號】:TM73
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