Research and Application of Power Consumers Behavior Analysis Based on K-means Algorithm

DOI

10.2991/iceesd-18.2018.44How to use a DOI?

Keywords

Cluster Analysis, K-means Algorithm, Power Consumers Behavior Analysis, Monthly Load Curve, Power Service Strategy

Abstract

K-means algorithm is used to analyze pretreated monthly load data of power consumers from a certain domestic area in China. It can get different clusters in three months, and those can be roughly divided power consumers into different types, such as residents, businesses and factories based on power customers’ behavior analysis. A measure is introduced to evaluate the reliability of the algorithm. According to the above clustering results, it can be found out that the power consumption characteristics of all kinds of consumers in the corresponding months. In view of these characteristics, this paper can play a guiding role in formulating the corresponding power service strategy for different types of power consumers in power supply companies.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Genghuang Yang
AU  - Xiayi Hao
AU  - Yingmei Zhang
PY  - 2018/05
DA  - 2018/05
TI  - Research and Application of Power Consumers Behavior Analysis Based on K-means Algorithm
BT  - Proceedings of the 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018)
PB  - Atlantis Press
SP  - 266
EP  - 270
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceesd-18.2018.44
DO  - 10.2991/iceesd-18.2018.44
ID  - Yang2018/05
ER  -