K-means based cluster analysis of residential smart meter measurements

被引:37
作者
Al-Wakeel, Ali [1 ]
Wu, Jianzhong [1 ]
机构
[1] Cardiff Univ, Sch Engn, Cardiff CF24 3AA, S Glam, Wales
来源
CUE 2015 - APPLIED ENERGY SYMPOSIUM AND SUMMIT 2015: LOW CARBON CITIES AND URBAN ENERGY SYSTEMS | 2016年 / 88卷
关键词
Smart meter measurements; k-means; cluster analysis; ENERGY-CONSUMPTION; LOAD PROFILES; SEGMENTATION; CUSTOMERS; CURVES;
D O I
10.1016/j.egypro.2016.06.066
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
080707 [能源环境工程]; 082001 [油气井工程];
摘要
A clustering module based on the k-means cluster analysis method was developed. Smart meter based residential load profiles were used to validate the clustering module. Several case studies were implemented using daily and segmented load profiles of individual and aggregated smart meters. Simulation results defined in terms of the relationship between the clustering ratio and the segmentation time window reveal that the minimum clustering ratio is obtained for the shortest time window of segmentation. Results also show that a small number of clusters is recommended for highly correlated load profiles. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:754 / 760
页数:7
相关论文
共 14 条
[1]
[Anonymous], 2011, CER11080A
[2]
[Anonymous], BASIC STAT USING SAS
[3]
Bandyopadhyay S., 2013, UNSUPERVISED CLASSIF, P75
[4]
Dynamic clustering segmentation applied to load profiles of energy consumption from Spanish customers [J].
Benitez, Ignacio ;
Quijano, Alfredo ;
Diez, Jose-Luis ;
Delgado, Ignacio .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 55 :437-448
[5]
Open source clustering software [J].
de Hoon, MJL ;
Imoto, S ;
Nolan, J ;
Miyano, S .
BIOINFORMATICS, 2004, 20 (09) :1453-1454
[6]
Short-term load forecasting, profile identification, and customer segmentation: A methodology based on periodic time series [J].
Espinoza, M ;
Joye, C ;
Belmans, R ;
De Moor, B .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (03) :1622-1630
[7]
Gan G, 2007, ASA SIAM SER STAT AP, V20, P1, DOI 10.1137/1.9780898718348
[8]
Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data [J].
Hsu, David .
APPLIED ENERGY, 2015, 160 :153-163
[9]
Typification of load curves for DSM in Brazil for a smart grid environment [J].
Macedo, Maria N. Q. ;
Galo, Joaquim J. M. ;
Almeida, Luiz A. L. ;
Lima, Antonio C. C. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 67 :216-221
[10]
A clustering approach to domestic electricity load profile characterisation using smart metering data [J].
McLoughlin, Fintan ;
Duffy, Aidan ;
Conlon, Michael .
APPLIED ENERGY, 2015, 141 :190-199