Optimal sizing of energy storage system in solar energy electric vehicle using genetic algorithm and neural network

被引:0
|
作者
Zhou, Shiqiong [1 ]
Kang, Longyun [1 ,2 ]
Cheng, MiaoMiao [1 ]
Cao, Binggang [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China
[2] S China Univ Technol, Sch Automot Engn, Guangzhou 510640, Peoples R China
关键词
battery flywheel; genetic algorithm; neural network;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Owing to sun's rays distributing randomly and discontinuously and load fluctuation, energy storage system is very important in Solar Energy Electric Vehicle (SEEV). The combinatorial optimization by genetic algorithm and neural network was used to optimize the energy storage system (including storage batteries and flywheel).In the optimization design, the operation strategy of the system was fixed and used to instruct the simulation about the system's operation. And the optimal objective was selected as minimizing the total capital cost of the energy storage system, subject to the main constraint of the Loss of Power Supply Probability (LPSP). Studies have proved that the combinatorial optimization by genetic algorithm and neural network converges well, lessen calculation time and it is feasible.
引用
收藏
页码:720 / 729
页数:10
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