| 基于蚁群优化算法和k阶近邻法的暂态稳定评估特征选择 |
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| 引用本文： | 章小强,管霖.基于蚁群优化算法和k阶近邻法的暂态稳定评估特征选择[J].广东电力,2011,24(12):29-35. |
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| 作者姓名： | 章小强 管霖 |
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| 作者单位： | 1. 广东电网公司深圳供电局,广东 深圳,518001
2. 华南理工大学电力学院,广东 广州,510640 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 提出了基于蚁群优化算法和k阶近邻法相结合的嵌入式特征选择算法.选择稳态潮流量构成电力系统暂态稳定评估的输入特征集,针对输入特征集包含的大量冗余信息,特征选择结果中可能包含一定冗余特征的缺陷,先用聚类的方法裁剪冗余性特征,然后用所提算法选择和稳定状况强相关的关键特征,提高了特征选择的 效率.通过对3机9节点和10机...
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| 关 键 词： | 暂态稳定评估 特征选择 蚁群优化算法 k阶近邻分类器 |
Feature Selection for Transient Stability Assessment Based on ACO and k-NN |
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| ZHANG Xiao-qiang,GUAN Lin.Feature Selection for Transient Stability Assessment Based on ACO and k-NN[J].Guangdong Electric Power,2011,24(12):29-35. |
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| Authors: | ZHANG Xiao-qiang GUAN Lin |
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| Affiliation: | 1.Shenzhen Power Supply Bureau of Guangdong Power Grid Corp.,Shenzhen,Guangdong 518001,China;2.School of Electric Power,South China University of Technology,Guangzhou,Guangdong 510640,China) |
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| Abstract: | Embedded feature selection method based on ACO and k-NN is presented.Steady-state flow is selected as input feature set for transient stability assessment of power system.In view of large amount of redundant information in input feature set,there may be some redundant defects in selected features.The clustering method is firstly adopted to cut out redundancy and key features strongly correlated to stability are to select through mentioned method,which can enhance efficiency of feature selection.By calculation on 9-bus system of machine 3 and 39-bus system,the regulations formed by selected features can accurately judge stability level of the system and the result validates efficiency of the method.The method can be generally used in systems of different scales. |
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| Keywords: | transient stability assessment feature selection ACO k-NN |
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