期刊
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷 32, 期 -, 页码 63-75出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2014.02.018
关键词
Scale free network; Gaussian dynamic particle swarm optimization; Power system; Real power loss minimization
类别
资金
- Science and Technology Development Project of Liaoning Province, China [2010219014]
This paper proposes a hybrid topology scale-free Gaussian-dynamic particle swarm (HTSFGDPS) optimization algorithm for real power loss minimization problem of power system. The swarm population is divided into two parts: hybrid topology population and scale-free topology population. The novel hybrid topology is mixed with fully connected topology and ring topology. Then, it enables the particles to have stronger exploration ability and fast convergence rate at the same time. In the scale-free part, the topology will be gradually generated as the construction process and the optimization process progress synchronously. As a result, the topology exhibits disassortative mixing property, which can improve the swarm population diversity. This work focuses on a new combination of swarm intelligence optimization theory and complex network theory, as well as its application to electric power system. The presented method is tested on IEEE 14-Bus and 30-Bus power system. The numerical results, compared with other stochastic search algorithms, show that HTSFGDPS could find high-quality solutions with higher convergence speed and probability. (C) 2014 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据