Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/78302
Title: การออกแบบที่เหมาะสมที่สุดของโครงสร้างสถานีอัดประจุยานยนต์ไฟฟ้าแบบเร็ว
Other Titles: Optimal design of electric vehicle fast-charging station’s structure
Authors: พีรพัฒน์ อันทะราสี
Authors: สิโรตม์ คุณกิตติ
พีรพัฒน์ อันทะราสี
Keywords: ยานยนต์ไฟฟ้า;สถานีอัดประจุยานยนต์ไฟฟ้าแบบเร็ว;พลังงานหมุนเวียน;เมตาฮิวริสติก อัลกอริทึม
Issue Date: Mar-2023
Publisher: เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่
Abstract: The fast development of electric vehicles has resulted in several topics of research in this area, such as the development of a charging pricing strategy, charging control, location of the charging station, and the structure within the charging station. This paper proposes the optimal design of the structure of an EV fast-charging station (EVFCS) connected with a renewable energy source and battery energy storage systems (BESS) by using metaheuristic algorithms. The optimal design of this structure aims to find the number and power of chargers. Moreover, the renewable energy source and BESS can reduce the impact on the grid, so these energy sources are considered as one of the optimally-designed structure of EVFCS in this work. Thus, it is necessary to determine the optimal sizing of the renewable energy source, BESS, and the grid power connected to EVFCS. This optimal structure can improve the profitability of the station. To solve the optimization problem, three metaheuristic algorithms, including particle swarm optimization (PSO), Salp swarm algorithm (SSA), and arithmetic optimization algorithm (AOA), are adopted. These algorithms aim to find the optimal structure which maximizes the profit of the EVFCS determined by its net present value (NPV), and the results obtained from these algorithms were compared. The results demonstrate that all considered algorithms could find feasible solutions for the optimal design for the EVFCS structure where PSO provided the best NPV, followed by AOA and SSA.
URI: http://cmuir.cmu.ac.th/jspui/handle/6653943832/78302
Appears in Collections:ENG: Theses

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