Power interconnected system clustering with advanced fuzzy C-mean algorithm

作     者：王洪梅 KIM Jae-Hyung JUNG Dong-Yean LEE Sang-Min LEE Sang-Hyuk 

作者机构：School of MechatronicsChangwon National University Daeho Tech Co.Ltd.Changwon 641-465Korea Department of Electronics EngineeringInha University 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2011年第18卷第1期

页      面：190-195页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0801[工学-力学（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：Work supported by the Second Stage of Brain Korea 21 Projects Work(2010-0020163) supported by Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education,Science and Technology of Korea 

主　　题：fuzzy C-mean similarity measure distance measure interconnected system clustering 

摘      要：An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.