4.7 Article

Design of power quality enhanced sustainable bidirectional electric vehicle charging station in distribution grid

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 74, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2021.103242

Keywords

Electric vehicle charging station; Bidirectional converters; Distribution static compensator; Adaptive neuro fuzzy controller; Power quality

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This article introduces a sustainable bidirectional electric vehicle charging station, which incorporates a distribution static compensator to improve station quality, facilitate power flow between grid and vehicle, and alleviate grid current harmonics. The system performance is evaluated with different controllers, with the adaptive neuro-fuzzy controller demonstrating better performance.
Integration of electric vehicle charging stations with the distribution grid rises the grid current harmonics. In this article, a sustainable bidirectional electric vehicle charging station in the distribution grid is designed. The quality of the charging station is improved by employing an adaptive neuro-fuzzy controlled distribution static compensator. The proposed sustainable bidirectional electric vehicle charging station comprises a 3-phase bidirectional ac-dc converter, bidirectional chopper, distribution static compensator and a lithium-ion battery. The bidirectional converters facilitate power flow from grid to vehicle and vice-versa. The decoupled current and dc voltage control method has been implemented for a 3-phase bidirectional converter. A multi-step current control strategy is exploited to control the bidirectional chopper. Distribution static compensator alleviates the grid current harmonics. The proposed system performance is evaluated with two kinds of controllers such as proportional - integral and adaptive neuro-fuzzy controller based on the distribution static compensator dc-side voltage and grid current harmonics. The proposed system has been modelled in MATLAB/Simulink and validated through software in the loop setup comprising of dSPACE (DS1202) hardware. The validated results show that the adaptive neuro-fuzzy controller provides better performance.

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