relation: https://khub.utp.edu.my/scholars/5960/
title: Swarm intelligence-based optimization for PHEV charging stations
creator: Rahman, I.
creator: Vasant, P.
creator: Singh, B.S.M.
creator: Abdullah-Al-Wadud, M.
description: In this chapter, Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) technique were applied for intelligent allocation of energy to the Plug-in Hybrid Electric Vehicles (PHEVs). Considering constraints such as energy price, remaining battery capacity, and remaining charging time, they optimized the State-of-Charge (SoC), a key performance indicator in hybrid electric vehicle for the betterment of charging infrastructure. Simulation results obtained for maximizing the highly nonlinear objective function evaluates the performance of both techniques in terms of global best fitness and computation time. © 2015, IGI Global. All rights reserved.
publisher: IGI Global
date: 2015
type: Book
type: PeerReviewed
identifier:   Rahman, I. and Vasant, P. and Singh, B.S.M. and Abdullah-Al-Wadud, M.  (2015) Swarm intelligence-based optimization for PHEV charging stations.     IGI Global, pp. 374-405.  ISBN 9781466682924; 1466682914; 9781466682917     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954245094&doi=10.4018%2f978-1-4666-8291-7.ch012&partnerID=40&md5=636afcf8ff60030352f0598ed2afba91
relation: 10.4018/978-1-4666-8291-7.ch012
identifier: 10.4018/978-1-4666-8291-7.ch012