Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control

Application of Improved Fuzzy C-means Clustering Analysis Method of Load Characteristics Stats

Authors
Lin Li, Dong Liu, Ying Du, Junli Liu
Corresponding Author
Lin Li
Available Online April 2016.
DOI
10.2991/icmemtc-16.2016.234How to use a DOI?
Keywords
fuzzy C-means clustering; load characteristic; power load; cluster analysis
Abstract

Power load is the active part of safe and stable operation of the entire power system. Establishing realistic dynamic load model is important meaning for power system planning and operation. In this paper practical load modeling idea is adopted for clustering analysis of the data of load characteristics with fuzzy C-means method to provide a basis for load management decisions.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
978-94-6252-173-5
ISSN
2352-5401
DOI
10.2991/icmemtc-16.2016.234How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Lin Li
AU  - Dong Liu
AU  - Ying Du
AU  - Junli Liu
PY  - 2016/04
DA  - 2016/04
TI  - Application of Improved Fuzzy C-means Clustering Analysis Method of Load Characteristics Stats
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1182
EP  - 1186
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.234
DO  - 10.2991/icmemtc-16.2016.234
ID  - Li2016/04
ER  -