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/).
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 -