| 基于粒子群算法的太阳能电动汽车复合能源系统优化 |
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| 引用本文： | 周世琼,郭桂芳,袁骥轩.基于粒子群算法的太阳能电动汽车复合能源系统优化[J].深圳信息职业技术学院学报,2014(1):10-15,19. |
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| 作者姓名： | 周世琼 郭桂芳 袁骥轩 |
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| 作者单位： | [1]深圳信息职业技术学院交通与环境学院,广东深圳518172 [2]西藏民族学院信息工程系,陕西咸阳711200 |
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| 基金项目： | The research is supported by a grant from National Natural Science Foundation of China （No.51166012） |
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| 摘 要： | 太阳能电动汽车的复合能源系统优化匹配问题可以看成一个多目标优化问题,两个相互冲突的目标是极大化系统的峰值功率满足率和极小化系统的成本,前者关系到系统的可靠性后者涉及到样车能否量产,所以两个优化目标都很重要.本文提出了改进的粒子群算法优化配置太阳能电动汽车复合能源系统,这种改进的粒子群算法引进了遗传算法里的变异算子,并且打破常规算法里的加速因子为常数的惯例而使加速因子随时间改变.优化结果显示：改进的粒子群算法也能够很好地解决复合能源系统的多目标优化问题.
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| 关 键 词： | 太阳能电动汽车 粒子群算法 多目标优化 |
Optimization of hybrid power system based on particle swarm algorithm |
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| ZHOU Shiqiong,GUO Guifang,YUAN Jixuan.Optimization of hybrid power system based on particle swarm algorithm[J].Journal of Shenzhen Institute of Information Technology,2014(1):10-15,19. |
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| Authors: | ZHOU Shiqiong GUO Guifang YUAN Jixuan |
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| Institution: | 1. School of Traffic and Environment, Shenzhen Institute of Information Technology, Shenzhen 518172, P.R. China; 2. Department of Information Engineering, Tibet University for Nationalities, Xianyang 711200, P.R. China ) |
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| Abstract: | The sizing of hybrid power system （HPS） can be taken as a multi-objective optimization problem involving two conflicting objectives as minimization of cost and minimization of loss of peak power probability （LPPP）. The improved particle swarm optimization （IPSO） algorithm is proposed for the optimal sizing of HPS problem which combines the PSO with the mutation operator and updates the acceleration factors with time varying. Comparing with the optimization results using adaptive genetic algorithm （AGA）, this proposed method is also well suitable for obtaining the solution of multi-objective optimization problem. |
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| Keywords: | solar electric vehicle particle swarm algorithm multi-objective optimization |
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