Multi-Objective Optimal Sizing Hybrid Power System in a Solar Electric Vehicle Using Particle Swarm Optimization Algorithm

Shi Qiong Zhou; Gui Fang Guo; Yong Yang Xiang

doi:10.4028/www.scientific.net/AMR.694-697.2699

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697Multi-Objective Optimal Sizing Hybrid Power System...

Multi-Objective Optimal Sizing Hybrid Power System in a Solar Electric Vehicle Using Particle Swarm Optimization Algorithm

Abstract:

In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

2699-2703

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.2699

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Cite this paper

Online since:

May 2013

Authors:

Shi Qiong Zhou, Gui Fang Guo, Yong Yang Xiang

Keywords:

Hybrid Power, Multi-Objective Optimal Sizing, Particle Swarm Optimization Algorithm, Solar Electric Vehicle (SEV)

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