Sizing and Energy Management of Parking Lots of Electric Vehicles Based on Battery Storage with Wind Resources in Distribution Network

被引:4
|
作者
Shahrokhi, Saman [1 ]
El-Shahat, Adel [2 ]
Masoudinia, Fatemeh [3 ]
Gandoman, Foad H. [4 ,5 ]
Aleem, Shady H. E. Abdel [6 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Sanandaj Branch, Sanandaj 1584743311, Iran
[2] Purdue Univ, Energy Technol Program, Sch Engn Technol, W Lafayette, IN 47907 USA
[3] Islamic Azad Univ, Dept Elect Engn, Sofian Branch, Sofian 1584743311, Iran
[4] Vrije Univ Brussel VUB, ETEC Dept, Pl Laan 2, B-1050 Brussels, Belgium
[5] Vrije Univ Brussel VUB, MOBI Res Grp, Pl Laan 2, B-1050 Brussels, Belgium
[6] Sci Valley Acad, Valley Higher Inst Engn & Technol, Dept Elect Engn, Al Qalyubia 44971, Egypt
关键词
distribution network; optimal sizing and placement framework; parking lots; cost; arithmetic optimization algorithm; OPTIMIZATION ALGORITHM; OPTIMAL ALLOCATION; RECONFIGURATION; PERFORMANCE;
D O I
10.3390/en14206755
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
In this paper, an optimal sizing and placement framework (OSPF) is performed for electric parking lots integrated with wind turbines in a 33-bus distribution network. The total objective function is defined as minimizing the total cost including the cost of grid power, cost of power losses, cost of charge and discharge of parking lots, cost of wind turbines as well as voltage deviations reduction. In the OSPF, optimization variables are selected as electric parking size and wind turbines, which have been determined optimally using an intelligent method named arithmetic optimization algorithm (AOA) inspired by arithmetic operators in mathematics. The load following strategy (LFS) is used for energy management in the OSPF. The OSPF is evaluated in three cases of the objective function such as minimizing the cost of power losses, minimizing the network voltage deviations, and minimizing the total objective function using the AOA. The capability of the AOA is compared with the well-known particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms for solving the OSPF in the last case. The findings show that the power loss, voltage deviations, and power purchased from the grid are reduced considerably based on the OSPF using the AOA. The results show the lowest total cost of energy and also minimum network voltage deviation (third case) by the AOA in comparison with the PSO and ABC with a higher convergence rate, which confirms the better capability of the proposed method. The results of the first and second cases show the high cost of power purchased from the main grid as well as the high total cost. Therefore, the comparison of different cases confirms that considering the cost index along with losses and voltage deviations causes a compromise between different objectives, and thus the cost of purchasing power from the main network is significantly reduced. Moreover, the voltage profile of the network improves, and also the minimum voltage of the network is also enhanced using the OSPF via the AOA.
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页数:21
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