14th International Conference on Industrial Engineering and Operations Management

Allocation Optimization of An Electrical Vehicle Charging Station Using Ant Colony Algorithm

Sulistyo Prabowo Adhi Karno, Apriani Soepardi & Agus Ristono
Publisher: IEOM Society International
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Track: Optimization
Abstract

Limited energy sourced from fossil fuels and world climate change is a challenge for energy security because the provision of adequate and affordable energy sources is imperative to support sustainable growth and development. In 2021, the largest energy consumption is in the transportation sector, which is or 33 percent of the total national energy consumption. World climate change and fluctuations in the cost of fossil energy make the demand for electric vehicles one of the alternative choices in driving with the reason to reduce carbon dioxide gas emissions. The purpose of this study is to  develop a model based on ant colony algorithm to determine the number of charging stations and locate them that minimize total setup cost, namely the initial cost of developing and the total power capacity of prospective charging stations, index of active power reduction, reactive power loss reduction and voltage profile improvement, and the probability of electric vehicles arrivals using ant colony algorithms. Objective functions are founded from weighting of function elements by Analytical Network Process. The location of the study was carried out by applying a model to the real case, namely the Trans Java toll road section which is the longest and most populous toll road section in Java, stretching between Jakarta to Surabaya, with a road length of about 1200 KM and daily traffic density of 688,000 vehicles.

Published in: 14th International Conference on Industrial Engineering and Operations Management, Dubai, UAE

Publisher: IEOM Society International
Date of Conference: February 12-14, 2024

ISBN: 979-8-3507-1734-1
ISSN/E-ISSN: 2169-8767