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

Saman Shahrokhi, Adel El-Shahat, Fatemeh Masoudinia, Foad H. Gandoman and Shady H. E. Abdel Aleem
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Saman Shahrokhi: Department of Electrical Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj 1584743311, Iran
Adel El-Shahat: Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA
Fatemeh Masoudinia: Department of Electrical Engineering, Sofian Branch, Islamic Azad University, Sofian 1584743311, Iran
Foad H. Gandoman: ETEC Department & MOBI Research Group, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussel, Belgium
Shady H. E. Abdel Aleem: Department of Electrical Engineering, Valley Higher Institute of Engineering and Technology, Science Valley Academy, Al-Qalyubia 44971, Egypt

Energies, 2021, vol. 14, issue 20, 1-21

Abstract: 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.

Keywords: distribution network; optimal sizing and placement framework; parking lots; cost; arithmetic optimization algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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