中国电机工程学会信息化专委会．中国电力大数据发展白皮书(2013)[R]．北京：中国电机工程学会,2013．Chinese society for electrical engineering informatization committee．Chinese electric power big data development white paper(2013)[R]．Beijing：Chinese society for electrical engineering,2013(in Chinese)．
[2]
宋亚奇,周国亮,朱永利．智能电网大数据处理技术现状与挑战[J]．电网技术,2013,37(4)：927-935．Song Yaqi,Zhou Guoliang,Zhu Yongli．Present status and challenges of big data processing in smart grid[J]．Power System Technology,2013,37(4)：927-935(in Chinese)．
[3]
田世明,王蓓蓓,张晶．智能电网条件下的需求响应关键技术[J]．中国电机工程学报,2014,34(22)：3576-3589．Tian Shiming,Wang Beibei,Zhang Jing．Key technologies for demand response in smart grid[J]．Proceedings of the CSEE,2014,34(22)：3576-3589(in Chinese)．
[4]
蒋雯倩,李欣然,钱军,等．改进FCM算法及其在电力负荷坏数据处理的应用[J]．电力系统及其自动化学报,2011,23(5)：1-5．Jiang Wenqian,Li Xinran,Qian Jun,et al．Application of improved FCM algorithm in outlier processing of power load[J]．Proceedings of the CSU-EPSA,2011,23(5)：1-5(in Chinese)．
[5]
李翔,顾洁．运用聚类算法预测地区电网典型日负荷曲线[J]．电力与能源,2013,35(1)：47-50．Li Xiang,Gu Jie．Using the clustering algorithm forecast in the power grid typical daily load curve[J]．Power & Energy,2013,35(1)：47-50(in Chinese)．
[6]
黄梅,贺仁睦,杨少兵．模糊聚类在负荷实测建模中的应用[J]．电网技术,2006,30(14)：49-52．Huang Mei,He Renmu,Yang Shaobing．Application of fuzzy clustering in measurement-based load modeling [J]．Power System Technology,2006,30(14)：49-52(in Chinese)．
[7]
李欣然,姜学皎,钱军,等．基于用户日负荷曲线的用电行业分类与综合方法[J]．电力系统自动化,2010,34(10)：56-61．Li Xinran,Jiang Xuejiao,Qian Jun,et al．A classifying and synthesizing method of power consumer industry based on the daily load profile[J]．Automation of Electric Power Systems,2010,34(10)：56-61(in Chinese)．
[8]
李培强,李欣然,陈辉华,等．基于模糊聚类的电力负荷特性的分类与综合[J]．中国电机工程学报,2005,25(24)：73-78．Li Peiqiang,Li Xinran,Chen Huihua,et al．The characteristic classification and synthesis power load based on fuzzy clustering[J]．Proceedings of the CSEE,2005,25(24)：73-78(in Chinese)．
[9]
Chicco G,Napoli R,Piglione F．Comparisons among clustering techniques for electricity customer classification[J]．IEEE Transactions on Power Systems,2006,21(2)：933-940．
[10]
Pakhira M K,Bandyopadhyay S,Maulik U．Validity index for crisp and fuzzy clusters[J]．Pattern Recognition,2004,37(3)：487-501．
[11]
Milligan G,Cooper M．An examination of procedures for determining the number of clusters in a data set [J]．Psychometrika,1985,50(2)：159-179．
[12]
Kim M,Ramakrishna R S．New indices for cluster validity assessment[J]．Pattern Recognition Letters,2005,26(15)：2353-2363．
[13]
Davies D L,Bouldin D W．A cluster separation measure[J]．IEEE Transactions on Pattern Analysis and Machine Intelligence,1979,1(2)：224-227．
[14]
Kwac J,Flora J,Rajagopal R．Household energy consumption segmentation using hourly data[J]．IEEE Transactions on Smart Grid,2014,5(1)：420-430．
[15]
Rodriguez A,Laio A．Clustering by fast search and find of density peaks[J]．Science,2014,344(6191)：1492-1496．
Leisch F,Bagged clustering．Working papers SFB adaptive information systems and modeling in economics and management science[R]．Wien：Institut für Information,1999．
[18]
Dudoit S,Fridlyand J．Bagging to improve the accuracy of a clustering procedure[J]．Bioinformatics,2003,19(9)：1090-1099．
[19]
Sammon J W．A nonlinear mapping for data structure analysis[J]．IEEE Transactions on Computers,1969,18(5)：401-409．
[20]
De Backer S,Naud A,Scheunders P．Non-linear dimensionality reduction techniques for unsupervised feature extraction[J]．Pattern Recognition Letters,1998,19(8)：711-720．
[21]
Wold S,Esbensen K,Geladi P．Principal component analysis[J]．Chemometrics and Intelligent Laboratory Systems,1987,2(1)：37-52．
