Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm(Article)

dc.contributor.authorIslam, M.,
dc.contributor.authorShareef, H.,
dc.contributor.authorMohamed, A.
dc.date.accessioned2025-04-28T09:06:07Z
dc.date.issued2017
dc.description.abstractThe electric vehicle (EV) is considered a premium solution to global warming and various types of pollution. Nonetheless, a key concern is the recharging of EV batteries. Therefore, this study proposes a novel approach that considers the costs of transportation loss, buildup, and substation energy loss and that incorporates harmonic power loss into optimal rapid charging station (RCS) planning. A novel optimization technique, called binary lightning search algorithm (BLSA), is proposed to solve the optimization problem. BLSA is also applied to a conventional RCS planning method. A comprehensive analysis is conducted to assess the performance of the two RCS planning methods by using the IEEE 34-bus test system as the power grid. The comparative studies show that the proposed BLSA is better than other optimization techniques. The daily total cost in RCS planning of the proposed method, including harmonic power loss, decreases by 10% compared with that of the conventional method.
dc.identifier.citationAhmed Bhuiyan, R., Ahmed, N., Amiruzzaman, M., & Islam, M. R. (2020). A robust feature extraction model for human activity characterization using 3-axis accelerometer and gyroscope data. Sensors, 20(23), 6990.
dc.identifier.issn19326203
dc.identifier.urihttp://dspace.uttarauniversity.edu.bd:4000/handle/123456789/461
dc.language.isoen
dc.publisherPublic Library of Science
dc.subjectcomparative study
dc.subjectlightning
dc.subjectalgorithm
dc.subjectcar
dc.subjectelectricity
dc.subjecttheoretical model
dc.titleImproved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm(Article)
dc.typeArticle

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