An optimal joint planning of DGs and electric vehicle charging stations in grid-connected and islanded microgrids

被引:7
|
作者
Zainab, Fasiha [1 ]
Naz, Komal [1 ]
Mehmood, Khawaja Khalid [1 ]
Bukhari, Syed Basit Ali [1 ]
Wadood, Abdul [2 ]
Khalid, Hassan Abdullah [1 ]
Park, Herie [3 ]
机构
[1] Natl Univ Sci & Technol NUST, Dept Elect Engn Power, USPCAS E, Islamabad, Pakistan
[2] Air Univ Islamabad, Dept Elect Engn, Aerosp & Aviat Campus, Kamra, Pakistan
[3] Dong A Univ, Dept Elect Engn, Busan, South Korea
基金
新加坡国家研究基金会;
关键词
distributed power generation; distribution networks; electric vehicles; DISTRIBUTION-SYSTEMS; GENETIC ALGORITHM; OPTIMIZATION; INTEGRATION; GENERATION;
D O I
10.1049/rpg2.12686
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper proposes a new framework for the planning of both distributed generators (DGs) and electric vehicle charging stations (EVCSs). The proposed method efficiently produces a unified solution for the joint planning of DGs and EVCSs for both grid-connected and islanded scenarios. The problem is formulated as a novel two-stage planning problem. The first stage determines the locations and sizes of the DGs with locations of EVCSs in grid-connected scenario, whereas the second stage planning identifies the optimal islands under the islanded microgrid scenario. A non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the first stage planning problem; in this stage, the algorithm minimizes two objective functions: the system-losses and total cost. In the second stage, another single objective optimization problem is designed which minimizes supply voltage variations to find optimal islands for the DGs and EVCSs to ensure a secure supply of power for EVs. The proposed framework is implemented on the IEEE 33-bus system and verified with four test cases. The results demonstrate the effectiveness of the proposed method and show that the sizes and locations of DGs, and locations of EVCSs are adequate for both grid-connected and islanded microgrids.
引用
收藏
页码:1623 / 1634
页数:12
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