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


ABSTRACT: The 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.

SUBMITTER: Islam MM 

PROVIDER: S-EPMC5722383 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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

Islam Md Mainul MM   Shareef Hussain H   Mohamed Azah A  

PloS one 20171208 12


The 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  ...[more]

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