Multitime scale coordinated scheduling for electric vehicles considering photovoltaic/wind/battery generation in microgrid

被引:14
|
作者
Ren, Lina [1 ]
Song, Zeyu [1 ]
Mao, Chenhong [1 ]
Liu, Fucai [1 ]
机构
[1] Yanshan Univ, Key Lab Ind Comp Control Hebei Prov, Qinhuangdao 066004, Hebei, Peoples R China
基金
中国国家自然科学基金;
关键词
electric vehicle; microgrid; multiobjective optimization; optimal scheduling; vehicle-to-grid; STOCHASTIC MATHEMATICAL-MODEL; RENEWABLE ENERGY; MANAGEMENT; MULTISTAGE; PRICE;
D O I
10.1002/2050-7038.2821
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The problem of multitime scale coordinated scheduling for electric vehicles (EVs) with vehicle-to-grid (V2G) technology is formulated for a microgrid with photovoltaic/wind/battery generation. The life of the energy storage system in the microgrid, and the benefits for EV users are considered as the optimization goals. Reasonable measures of the charging and discharging behaviors of EVs are considered to construct the objective functions. A stratified sequencing method is designed to transform the multiobjective optimization problem into a single-objective nonlinear optimization problem that can be solved through adaptive particle swarm optimization (APSO). Then an optimal multitime scale coordinated scheduling scheme can be obtained. The effectiveness and feasibility of the methods are verified by simulation results.
引用
收藏
页数:15
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