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Hybrid Particle Swarm and Gravitational Search Optimization Techniques for Charging Plug-In Hybrid Electric Vehicles

Rahman, Imran and Vasant, Pandian and Mahinder Singh, Balbir Singh and Abdullah-Al-Wadud, M. (2016) Hybrid Particle Swarm and Gravitational Search Optimization Techniques for Charging Plug-In Hybrid Electric Vehicles. In: Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics. Advances in Computational Intelligence and Robotics (ACIR) . IGI Global, pp. 471-504. ISBN 9781466696440

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Abstract

Electrification of Transportation has undergone major modifications since the last decade. Success of combining smart grid technology and renewable energy exclusively depends upon the large-scale participation of Plug-in Hybrid Electric Vehicles (PHEVs) towards reach the desired pollution-free transportation industry. One of the key Performance pointers of hybrid electric vehicle is the State-of-Charge (SoC) which needs to be enhanced for the advancement of charging station using computational intelligence methods. In this Chapter, authors applied Hybrid Particle swarm and gravitational search Optimization(PSOGSA) technique for intelligently allocating energy to the PHEVs considering constraints such as energy price, remaining battery capacity, and remaining charging time. Computational experiment results attained for maximizing the highly non-linear fitness function estimates the performance measure of both the techniques in terms of best fitness value and computation time.

Item Type:Book Section
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Academic Subject One:Academic Department - Electrical And Electronics - Instrumentation and Control - Modeling and Optimization - Modeling of distillation column
Departments / MOR / COE:Departments > Fundamental & Applied Sciences
ID Code:11894
Deposited By: Pandian Vasant
Deposited On:07 Oct 2016 01:42
Last Modified:07 Oct 2016 01:42

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