The application of combinatorial optimization by Genetic Algorithm and Neural Network

被引：10
|
作者：
Zhou, Shiqiong [1 ]
Kang, Longyun [1 ]
Guo, Guifang [1 ]
Zhang, Yanning [1 ]
Cao, Jianbo [1 ]
Cao, Binggang [1 ]
机构：
[1] Xian Jiaotong Univ, Sch Mech Engn, Xian 710049, Peoples R China
来源：
ICIEA 2008: 3RD IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, PROCEEDINGS, VOLS 1-3 | 2008年
关键词：
D O I：
10.1109/ICIEA.2008.4582512
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A optimization model of sizing the storage section in a renewable power generation system was set up, and two methods were used to solve the model: Genetic Algorithm or combinatorial optimization by Genetic Algorithm and Neural Network. The system includes the photovoltaic arrays, the lead-acid battery and a flywheel. The optimal sizing can be considered as a constrained optimization problem: minimization the total capacity of energy storage system, subject to the main constraint of the Loss of Power Supply Probability (LPSP). Both of the two optimal algorithm got good results. We can see that, combinatorial optimization by Genetic Algorithm and Neural Network can lessen the calculation time, with the results change little.
引用
收藏
页码：227 / 231
页数：5
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