Research of Power Consumers Behavior Using Fuzzy C-means Algorithm

DOI

10.2991/icmse-18.2018.29How to use a DOI?

Keywords

Clustering, fuzzy C-means algorithm, monthly load curve, concavity degree analysis, power service strategy.

Abstract

Fuzzy C-means (FCM) algorithm is used to cluster monthly power consumption data of power consumers, which has been pretreated, in a certain domestic area, and power consumers clusters in three different months and each of clustering centers can be obtained. According to the algorithm, the reliability of the algorithm is evaluated. The clustering center obtained in a certain month is brought into an algorithm for evaluating the degree of coincidence, by which the clustering result of the month can be proved reasonable. Based on the above clustering results, it can be seen that there are some characteristics in different types of power consumers in August and fluctuations within power grid. On the basis of the above described, power companies can make out different power service strategies for all kinds of power consumers so as to reduce fluctuations in power grid and improve the efficiency of power usage.

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/).

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TY  - CONF
AU  - Xiaohui Chang
AU  - Lei Yu
AU  - Yulong Han
AU  - Tao He
AU  - Xiayi Hao
PY  - 2018/05
DA  - 2018/05
TI  - Research of Power Consumers Behavior Using Fuzzy C-means Algorithm
BT  - Proceedings of the 2018 8th International Conference on Manufacturing Science and Engineering (ICMSE 2018)
PB  - Atlantis Press
SP  - 145
EP  - 148
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-18.2018.29
DO  - 10.2991/icmse-18.2018.29
ID  - Chang2018/05
ER  -