文章基本信息

标题：On Predicted Research Methods of Supply Capacity of Micro-grid Based on Improved Particle Swarm Optimization
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作者：Lu, Ning ; Liu, Ying
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2013
卷号：8
期号：10
页码：2706-2710
DOI：10.4304/jcp.8.10.2706-2710
语种：English
出版社：Academy Publisher
摘要：Micro-grid is a kind of distributed low-voltage supply network by integrating various distributed powers, energy storage systems and controlled load. In micro-grid, distributed power can be divided into certain and stochastic power. The prediction on supply capacity of micro-grid focuses on electric energy production by stochastic power. The wind energy power is predicted in this paper by support vector machine (SVM) and the combination method of improved particle swarm optimization (PSO) and simulated annealing (SA) which forms a hybrid algorithm of SA-IPSO to optimize SVM model parameter adaptively. The case study have proved that this algorithm adjusts model parameter by adaptive learning, so this predicted model track the fluctuation and change of wind energy power effectively and further predict the total supply capacity of micro-grid more accurately.
关键词：micro-grid;stochastic power;particle swarm optimization;wind power;simulated annealing