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Swarm Intelligence-Based Optimization for PHEV Charging Stations
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Author(s): Imran Rahman (Universiti Teknologi Petronas, Malaysia), Pandian Vasant (University of Technology Petronas, Malaysia), Balbir Singh Mahinder Singh (Universiti Teknologi Petronas, Malaysia)and M. Abdullah-Al-Wadud (King Saud University, Saudi Arabia)
Copyright: 2015
Pages: 32
Source title:
Handbook of Research on Swarm Intelligence in Engineering
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)and Paramartha Dutta (Visva-Bharati University, India)
DOI: 10.4018/978-1-4666-8291-7.ch012
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Abstract
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 non-linear objective function evaluates the performance of both techniques in terms of global best fitness and computation time.
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