Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid

被引:137
|
作者
Jian, Linni [1 ]
Zheng, Yanchong [1 ,2 ]
Xiao, Xinping [2 ]
Chan, C. C. [3 ,4 ]
机构
[1] South Univ Sci & Technol China, Dept Elect & Elect Engn, Shenzhen, Peoples R China
[2] Wuhan Univ Technol, Sch Sci, Wuhan 430070, Peoples R China
[3] Univ Hong Kong, Dept Elect & Elect Engn, Pokfulam, Hong Kong, Peoples R China
[4] Inst Adv Sustainabil Studies, Potsdam, Germany
关键词
Plug-in electric vehicle; Vehicle-to-grid; Optimal scheduling; Load variance; Smart grid; ENERGY MANAGEMENT; DIVIDED OPTIMIZATION; CHARGING STRATEGY; POTENTIAL IMPACT; EV AGGREGATOR; WIND POWER; LOAD; NETWORKS; SYSTEM; IMPLEMENTATION;
D O I
10.1016/j.apenergy.2015.02.030
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Vehicle-to-grid (V2G) operation of plug-in electric vehicles (PEVs) is attracting increasing attention since it can assist to improve the efficiency and reliability of power grid, as well as reduce the operating cost and greenhouse gas emission of electric vehicles. Within the scheme of V2G operation, PEVs are expected to serve as a novel distributed energy storage system (ESS) to help achieve the balance between supply and demand of power grid. One of the key difficulties concerning its practical implementation lies in that the availability of PEVs as ESS for grid remains highly uncertain due to their mobility as transportation tools. To address this issue, a novel event-triggered scheduling scheme for V2G operation based on the scenario of stochastic PEV connection to smart grid is proposed in this paper. Firstly, the mathematical model is formulated. Secondly, the preparation of input data for systematic evaluation is introduced and the case study is conducted. Finally, statistic analysis results demonstrate that our proposed V2G scheduling scheme can dramatically smooth out the fluctuation in power load profiles. (c) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:150 / 161
页数:12
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