基于欧氏动态时间弯曲距离与熵权法的负荷曲线聚类方法

宋军英; 崔益伟; 李欣然; 钟伟; 邹鑫; 李培强

doi:10.7500/AEPS20191016008

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基于欧氏动态时间弯曲距离与熵权法的负荷曲线聚类方法

学术研究 | 更新时间：2025-06-16

- 基于欧氏动态时间弯曲距离与熵权法的负荷曲线聚类方法
- Load Curve Clustering Method Based on Euclidean Dynamic Time Warping Distance and Entropy Weight
- 电力系统自动化-方正平台 2020年44卷第15期页码：87-94
- 作者机构：
  
  1. 国网湖南省电力有限公司，湖南省长沙市 410077
  2. 湖南大学电气与信息工程学院，湖南省长沙市 410082
- 作者简介：
  
  宋军英(1969—)，女，博士，教授级高级工程师，主要研究方向：电力系统运行与控制。E-mail：276435879@qq.com
  崔益伟(1997—) ，男，硕士研究生，主要研究方向：电力系统仿真与建模。E-mail：229069079@qq.com
  李欣然(1957—)，男，通信作者，博士，教授，主要研究方向：电力系统分析控制、负荷建模。E-mail：lixinran1013@qq.com
- 基金信息：
  
  国家重点研发计划资助项目(2017YFB0903403)
- DOI：10.7500/AEPS20191016008
  中图分类号：
- 收稿日期：2019-10-16，
  
  修回日期：2020-02-03，
  
  网络出版日期：2020-05-11，
  
  纸质出版日期：2020-08-10
- 稿件说明：
移动端阅览
宋军英,崔益伟,李欣然等.基于欧氏动态时间弯曲距离与熵权法的负荷曲线聚类方法[J].电力系统自动化,2020,44(15):87-94.

SONG Junying,CUI Yiwei,LI Xinran,et al.Load Curve Clustering Method Based on Euclidean Dynamic Time Warping Distance and Entropy Weight[J].Automation of Electric Power Systems,2020,44(15):87-94.
宋军英,崔益伟,李欣然等.基于欧氏动态时间弯曲距离与熵权法的负荷曲线聚类方法[J].电力系统自动化,2020,44(15):87-94. DOI： 10.7500/AEPS20191016008.

SONG Junying,CUI Yiwei,LI Xinran,et al.Load Curve Clustering Method Based on Euclidean Dynamic Time Warping Distance and Entropy Weight[J].Automation of Electric Power Systems,2020,44(15):87-94. DOI： 10.7500/AEPS20191016008.

摘要

为了改善目前负荷建模中聚类方法相似度衡量不准确及聚类结果质量较差的问题，综合运用

-means及熵权法原理，提出一种基于欧氏距离与动态时间弯曲距离的日负荷曲线聚类方法。首先，采用欧氏距离与动态时间弯曲距离分别衡量日负荷曲线的整体分布特性、局部动态特性与整体动态特性。然后，引入熵权法自适应配置3种特性的权重系数。最后，采用

-means聚类算法，以所提相似度衡量方法为依据，对用电日负荷曲线进行聚类。算例对某省区电网典型用户的日负荷曲线展开聚类分析，结果表明所提方法相似度衡量指标合理

且在聚类质量、鲁棒性等方面具有一定的优越性，可以真实反映该地区的用户用电特性，满足在线负荷建模的应用需求。

Abstract

In order to improve the accuracy of similarity measurement and the quality of clustering results in current load modeling

a daily load curve clustering method based on Euclidean distance and dynamic time warping distance is proposed by using the principle of

-means and entropy weight method. Firstly

Euclidean distance and dynamic time warping distance are adopted to measure the overall distribution characteristics

local dynamic characteristics and overall dynamic characteristics of the daily load curves. Secondly

entropy weight method is introduced to adaptively configure the weight coefficients of these three characteristics. Finally

-means clustering algorithm is used to cluster the daily load curves based on the proposed similarity measurement method. The clustering analysis of daily load curves of typical consumers in a provincial power grid is made. The results show that the similarity measurement indices selected in the proposed method are reasonable

and the method has certain advantages in clustering quality and robustness

which can truly reflect the power consumption characteristics of consumers in this area and meet the application requirements of online load modeling.

关键词

Keywords

references

蒋正邦 , 吴浩 , 程祥 , 等 . 基于多元聚类模型与两阶段聚类修正算法的变电站特性分析 [J]. 电力系统自动化 , 2018 , 42 ( 15 ): 157 - 163 .

JIANG Zhengbang , WU Hao , CHENG Xiang , et al . Analysis of substation characteristics based on multivariate clustering model and two-stage clustering-correction algorithm [J]. Automation of Electric Power Systems , 2018 , 42 ( 15 ): 157 - 163 .

林舜江 , 李欣然 , 刘杨华，等 . 电力负荷动特性分类方法研究 [J]. 电力系统自动化 , 2005 , 29 ( 22 ): 38 - 43 .

LIN Shunjiang , LI Xinran , LIU Yanghua , et al . A classification method for aggregated load dynamic characteristics [J]. Automation of Electric Power Systems , 2005 ， 29 ( 22 ): 38 - 43 .

张斌 , 庄池杰 , 胡军 , 等 . 结合降维技术的电力负荷曲线集成聚类算法 [J]. 中国电机工程学报 , 2015 , 35 ( 15 ): 3741 - 3749 .

ZHANG Bin , ZHUANG Chijie , HU Jun , et al . Ensemble clustering algorithm combined with dimension reduction techniques for power load profiles [J]. Proceedings of the CSEE , 2015 , 35 ( 15 ): 3741 - 3749 .

RAMOS S , DUARTE J M M , SOARES J , et al . Typical load profiles in the smart grid context—a clustering methods comparison [C]// 2012 IEEE Power and Energy Society General Meeting , July 22 - 26 , San Diego, USA: 1 - 8 .

CHENG D , ZHU Q , HUANG J , et al . A novel cluster validity index based on local cores [J]. IEEE Transactions on Neural Networks and Learning Systems , 2019 , 30 ( 4 ): 985 - 999 .

王帅 , 杜欣慧 , 姚宏民 , 等 . 面向含多种用户类型的负荷曲线聚类研究 [J]. 电网技术 , 2018 , 42 ( 10 ): 3401 - 3412 .

WANG Shuai , DU Xinhui , YAO Hongmin , et al . Research on load curve clustering with multiple user types [J]. Power System Technology , 2018 , 42 ( 10 ): 3401 - 3412 .

刘思 , 李林芝 , 吴浩 , 等 . 基于特性指标降维的日负荷曲线聚类分析 [J]. 电网技术 , 2016 , 40 ( 3 ): 797 - 803 .

LIU Si , LI Linzhi , WU Hao , et al . Cluster analysis of daily load curves using load pattern indexes to reduce dimensions [J]. Power System Technology , 2016 , 40 ( 3 ): 797 - 803 .

宋军英 , 何聪 , 李欣然 , 等 . 基于特征指标降维及熵权法的日负荷曲线聚类方法 [J]. 电力系统自动化 , 2019 , 43 ( 20 ): 65 - 72 .

SONG Junying , HE Cong , LI Xinran , et al . Daily load curve clustering method based on feature index dimension reduction and entropy weight method [J]. Automation of Electric Power Systems , 2019 , 43 ( 20 ): 65 - 72 .

FIGUEIREDO V , RODRIGUES F , VALE Z , et al . An electric energy consumer characterization framework based on data mining techniques [J]. IEEE Transactions on Power Systems , 2005 , 20 ( 2 ): 596 - 602 .

赵文清 , 龚亚强 . 基于Kernel K -means的负荷曲线聚类 [J]. 电力自动化设备 , 2016 , 36 ( 6 ): 203 - 207 .

ZHAO Wenqing , GONG Yaqiang . Load curve clustering based on Kernel K -means [J]. Electric Power Automation Equipment ， 2016 , 36 ( 6 ): 203 - 207 .

石亮缘 , 周任军 , 张武军 , 等 . 采用深度学习和多维模糊C均值聚类的负荷分类方法 [J]. 电力系统及其自动化学报 , 2019 , 31 ( 7 ): 43 - 50 .

SHI Liangyuan , ZHOU Renjun , ZHANG Wujun , et al . Load classification method using deep learning and multi- dimensional fuzzy C-means clustering [J]. Proceedings of the CSU-EPSA , 2019 , 31 ( 7 ): 43 - 50 .

李阳 , 刘友波 , 刘俊勇 , 等 . 基于形态距离的日负荷数据自适应稳健聚类算法 [J]. 中国电机工程学报 , 2019 , 39 ( 12 ): 3409 - 3420 .

LI Yang , LIU Youbo , LIU Junyong , et al . Self-adaptive and robust clustering algorithm for daily load profiles based on morphological distance [J]. Proceedings of the CSEE , 2019 , 39 ( 12 ): 3409 - 3420 .

王潇笛 , 刘俊勇 , 刘友波 , 等 . 采用自适应分段聚合近似的典型负荷曲线形态聚类算法 [J]. 电力系统自动化 , 2019 , 43 ( 1 ): 110 - 121 .

WANG Xiaodi , LIU Junyong , LIU Youbo , et al . Shape clustering algorithm of typical load curves based on adaptive piecewise aggregate approximation [J]. Automation of Electric Power Systems , 2019 , 43 ( 1 ): 110 - 121 .

SHARABIANI A , DARABI H , REZAEI A , et al . Efficient classification of long time series by 3-D dynamic time warping [J]. IEEE Transactions on Systems , Man , and Cybernetics: Systems , 2017 , 47 ( 10 ): 2688 - 2703 .

YIN H , YANG S , MA S , et al . A novel parallel scheme for fast similarity search in large time series [J]. China Communications , 2015 , 12 ( 2 ): 129 - 140 .

周任军 , 石亮缘 , 汤吉鸿 , 等 . 多功率曲线协整度约束下的源-荷-储优化协整模型 [J]. 中国电机工程学报 , 2019 , 39 ( 12 ): 3454 - 3465 .

ZHOU Renjun , SHI Liangyuan , TANG Jihong , et al . Source-load-storage optimization cointegration model under multi-power curve cointegration degree constraints [J]. Proceedings of the CSEE , 2019 , 39 ( 12 ): 3454 - 3465 .

欧阳森，石怡理 . 改进熵权法及其在电能质量评估中的应用 [J]. 电力系统自动化， 2013 ， 37 ( 21 )： 156 - 159 .

OUYANG Sen ， SHI Yili . A new improved entropy method and its application in power quality evaluation [J]. Automation of Electric Power Systems , 2013 , 37 ( 21 )： 156 - 159 .

刘洋 , 许立雄 , 王剑 . 计及数据类别不平衡的海量用户负荷典型特征高性能提取方法 [J]. 中国电机工程学报 , 2019 , 39 ( 14 ): 4093 - 4104 .

LIU Yang , XU Lixiong , WANG Jian . A high performance extraction method for massive user load typical characteristics considering data class imbalance [J]. Proceedings of the CSEE , 2019 , 39 ( 14 ): 4093 - 4104 .

LI C , CAI W , YU C , et al . Electricity consumption behavior analysis based on adaptive weighted-feature K -means-AP clustering [J]. IET Generation , Transmission & Distribution , 2019 , 13 ( 12 ): 2352 - 2361 .

TEERARATKUL T , O’NEILL D , LALL S . Shape-based approach to household electric load curve clustering and prediction [J]. IEEE Transactions on Smart Grid , 2018 , 9 ( 5 ): 5196 - 5206 .

李春燕 , 蔡文悦 , 赵溶生 , 等 . 基于优化SAX和带权负荷特性指标的AP聚类用户用电行为分析 [J]. 电工技术学报 , 2019 , 34 ( 增刊1 ): 368 - 377 .

LI Chunyan ， CAI Wenyue ， ZHAO Rongsheng ， et al . Customer behavior analysis based on affinity propagation algorithm with optimized SAX and weighted load characteristic indices [J]. Transactions of China Electrotechnical Society , 2019 , 34 ( Supplement 1 ): 368 - 377 .

徐青山 , 娄藕蝶 , 郑爱霞 , 等 . 基于近邻传播聚类和遗传优化的非侵入式负荷分解方法 [J]. 电工技术学报 , 2018 , 33 ( 16 ): 3868 - 3878 .

XU Qingshan ， LOU Oudie ， ZHENG Aixia ， et al . A non-intrusive load decomposition method based on affinity propagation and genetic algorithm optimization [J]. Transactions of China Electrotechnical Society , 2018 , 33 ( 16 )： 3868 - 3878 .

傅德胜 , 周辰 . 基于密度的改进 K 均值算法及实现 [J]. 计算机应用 , 2011 , 31 ( 2 ): 432 - 434 .

FU Desheng , ZHOU Chen . Improved K -means algorithm and its implementation based on density [J]. Journal of Computer Applications , 2011 , 31 ( 2 ): 432 - 434 .

PARK K , SON S . A novel load image profile-based electricity load clustering methodology [J]. IEEE Access , 2019 , 7 : 59048 - 59058 .

BERNDT D J , CLIFFORD J . Using dynamic time warping to find patterns in time series [EB/OL]. [ 2019-04-26 ]. http://www.doc88.com/p-7344583600168.html http://www.doc88.com/p-7344583600168.html .

谢心蕊 , 雷秀仁 , 赵岩 . MI和改进PCA的降维算法在股价预测中的应用 [J/OL]. 计算机工程与应用 [ 2019-12-13 ]. https://kns.cnki.net/KCMS/detail/11.2127.TP.20191213.1248.008.html https://kns.cnki.net/KCMS/detail/11.2127.TP.20191213.1248.008.html .

XIE Xinrui , LEI Xiuren , ZHAO Yan . Application of mutual information and improved PCA dimensionality reduction algorithm in stock price [J/OL]. Computer Engineering and Applications [ 2019-12-13 ]. https://kns.cnki.net/KCMS/detail/11.2127.TP.20191213.1248.008.html https://kns.cnki.net/KCMS/detail/11.2127.TP.20191213.1248.008.html .

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