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变电站为中心配电网电压等高线时序态势图片的聚类分析
引用本文:章坚民,申世伟,黄晟,陈士云,陈彤,章剑光.变电站为中心配电网电压等高线时序态势图片的聚类分析[J].电力系统自动化,2017,41(8):125-132.
作者姓名:章坚民  申世伟  黄晟  陈士云  陈彤  章剑光
作者单位:杭州电子科技大学自动化学院, 浙江省杭州市 310018,杭州电子科技大学自动化学院, 浙江省杭州市 310018,杭州电子科技大学自动化学院, 浙江省杭州市 310018,浙江华云信息科技有限公司, 浙江省杭州市 310012,浙江华云信息科技有限公司, 浙江省杭州市 310012,国网绍兴供电公司, 浙江省杭州市 312000
基金项目:国家自然科学基金资助项目(51677047);浙江省重点自然科学基金资助项目(LZ12E07001)
摘    要:基于电气接线图并按特定图形设计的时序态势图,其图形特征是网络结构、运行方式、接入源荷及各类电气元件行为、量测数据等动态潮流的一种高维融合映射。通过基于刻画态势图片的关键但数量有限的图形特征量的聚类分析,从中获取态势图中隐藏的规律和有价值的知识。文中提出变电站为中心的配电网电压等高线时序态势图片的特征向量及其计算算法;探索了基于图片特征向量的态势时序图片聚类分析方法,提出了聚类中心图片(典型图片)的图片相似度、时间离散度及其计算算法。以典型日96幅电压态势时序图为案例,介绍了所提方法的效果以及分析结果,并进行了近两个月的长时序图片聚类的初步应用分析。

关 键 词:态势感知  时序态势图  图片聚类分析  图片特征向量  图片相似度  时间离散度
收稿时间:2016/11/3 0:00:00
修稿时间:2017/2/22 0:00:00

Clustering Analysis of Voltage Contour Time-sequence Situation Pictures in Substation-centralized Distribution Network
ZHANG Jianmin,SHEN Shiwei,HUANG Sheng,CHEN Shiyun,CHEN Tong and ZHANG Jianguang.Clustering Analysis of Voltage Contour Time-sequence Situation Pictures in Substation-centralized Distribution Network[J].Automation of Electric Power Systems,2017,41(8):125-132.
Authors:ZHANG Jianmin  SHEN Shiwei  HUANG Sheng  CHEN Shiyun  CHEN Tong and ZHANG Jianguang
Affiliation:College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China,College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China,College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China,Zhejiang Huayun Information Technology Co. Ltd., Hangzhou 310012, China,Zhejiang Huayun Information Technology Co. Ltd., Hangzhou 310012, China and State Grid Shaoxing Electric Power Supply Company, Shaoxing 312000, China
Abstract:The time-sequence situation picture based on the electrical wiring diagram is designed according to a specific diagram. Its characteristic vector is a high dimensional mapping of the fusion of dynamic power flows such as network structure, operation mode, action of load and other equipment, and measurement data. Through the clustering analysis based on the limited number of core characteristic vectors used to describe the time-sequence situation pictures, the hidden rule and valuable knowledge in situation pictures can be acquired. As a trial, the characteristic vector of voltage contour situation picture of substation-centralized distribution network is defined and its calculating methods are proposed. The characteristic vector based clustering analysis method of time-sequence situation pictures is explored. Several new measurement indices for the clustering classification, including picture similarity and time dispersion of clustered center pictures(typical pictures), are proposed to help with best picture clustering. By taking the 96 voltage time-sequence situation pictures in a typical day as an example, the effect of the proposed method and the analysis results are described. The preliminary clustering analysis of situation pictures with a long time-sequence of approximately two months has been carried on. This work is supported by National Natural Science Foundation of China(No. 51677047)and Zhejiang Provincial Natural Science Foundation of China(No. LZ12E07001).
Keywords:situation awareness  time-sequence situation picture  picture-based clustering analysis  characteristic vector of picture  picture similarity  time dispersion
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