Abstract

Battery Electric Vehicle (BEV) has become a new technological innovation that effectively accelerates electrification due to their short charging and swapping processes. On the other hand, developing charging infrastructure, such as charging stations, still needs to be improved in Indonesia. The absence of government policies regulating charging station design has led each electric motorcycle company to innovate with their own standards. This research aims to implement a proposed Battery Swap Station (BSS) model to minimize swapping costs by optimizing the charging schedule for each exchanged battery based on a case study of one electric motorcycle service provider in Solo. Three factors are considered in searching for the objective function: the number of batteries taken from the stock during daily operations, battery degradation resulting from high charging scheme usage, and the electricity cost used at the station. Genetic Algorithms are proposed to determine the optimal charging scheduling, resulting in the minimum objective function. A series of battery swapping demand case studies are simulated to assess the feasibility of the proposed model, which can serve as a policy reference for the government and companies.

Full Text
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