Indonesian Journal of Electrical Engineering and Computer Science Vol. 11, No. 1, July 2018, pp. 82~89 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v11.i1.pp82-89  82 Journal homepage: http://iaescore.com/journals/index.php/ijeecs Optimal Charging Schedule Coordination of Electric Vehicles in Smart Grid Wan Iqmal Faezy Wan Zalnidzam 1 , Hasmaini Mohamad 2 , Nur Ashida Salim 3 , Hazlie Mokhlis 4 , Zuhaila Mat Yasin 5 1,2,3,5 Faculty of Electrical Engineering, Universiti Teknologi MARA, 4000 Shah Alam, Selangor, Malaysia 4 Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia Article Info ABSTRACT Article history: Received Jan 20, 2018 Revised Mar 10, 2018 Accepted Apr 2, 2018 The increasing penetration of electric vehicle (EV) at distribution system is expected in the near future leading to rising demand for power consumption. Large scale uncoordinated charging demand of EVs will eventually threatens the safety operation of the distribution network. Therefore, a charging strategy is needed to reduce the impact of charging. This paper proposes an optimal centralized charging schedule coordination of EV to minimize active power losses while maintaining the voltage profile at the demand side. The performance of the schedule algorithm developed using particle swarm optimization (PSO) technique is evaluated at the IEEE-33 Bus radial distribution system in a set time frame of charging period. Coordinated and uncoordinated charging schedule is then compared in terms of active power losses and voltage profile at different level of EV penetration considering 24 hours of load demand profile. Results show that the proposed coordinated charging schedule is able to achieve minimum total active power losses compared to the uncoordinated charging. Keywords: Electric vehicle Charging coordination Distribution system Particle swarm optimization Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Wan Iqmal Faezy Wan Zalnidzam, Faculty of Electrical Engineering, Universiti Teknologi MARA, 4000 Shah Alam, Selangor, Malaysia. Email: iqmalfaezy94@gmail.com 1. INTRODUCTION Transportation sector is among the largest contributors for excessive carbon emission in the environment which lead to the deployment of electric vehicle (EV) as alternative to reduce the environmentally damaging impact from conventional vehicles. However, impact of increasing power demand due to comparatively high consumption of EV’s batteries during charging grows concern on the utilities. In addition, large-scale penetration of EVs lead to a potential increase on the peak load demand of the local distribution networks especially when EV users practice the uncontrolled charging scheme [1]. Therefore, several studies have been conducted to propose smart charging control strategies of EVs by using various optimization techniques [2],[3] to reduce the mentioned impact and improve the operation of electrical grid. Authors in [4]-[6] proposed charging schedules to minimize the charging cost of EV as well as minimizing the burden on distribution network by finding hourly optimal charging power transfer as variable. However, the proposed schedules are questionable since they lack the inclusion of power flow model and network constraints in their methodology. A centralized charging strategy is proposed where the active power of EVs charging is controlled by regulating the voltage and frequency at connection point [7]. There are many benefits of using this technique such as reducing the voltage deviation in residential distribution networks [8] and maximizing the penetration of EV with vehicle to grid (V2G) capability as a distributed energy resource (DER) in islanded grid [9]. The charging strategy is also proposed in [10],[11] to minimize