Fast voltage contingency selection using fuzzy parallel self-organizing hierarchical neural network

被引：30
|
作者：
Pandit, M [1 ]
Srivastava, L
Sharma, J
机构：
[1] MITS, Dept Elect Engn, Gwalior, India
[2] Indian Inst Technol, Dept Elect Engn, Roorkee, Uttar Pradesh, India
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 2003年 / 18卷 / 02期
关键词：
angular distance-based clustering; contingency ranking; fuzzy neural network; fuzzy overall performance index; linguistic categories; membership values; parallel self-organizing hierarchical neural network; ranking module; screening module;
D O I：
10.1109/TPWRS.2003.810993
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A fuzzy neural, network comprising of a screening module and ranking module is proposed for online voltage contingency screening and ranking. A four-stage multioutput parallel self-organizing hierarchical neural network (PSHNN) has been presented in this paper to serve as the ranking module to rank the screened critical contingencies online based (in a static fuzzy performance index formulated by combining voltage violations and voltage stability margin. Compared to the deterministic crisp ranking, the proposed approach provides a more informative and flexible ranking and is very effective in handling contingencies lying on the boundary between two severity classes. Angular distance-based clustering has been employed to reduce the dimension of the fuzzy PSHNN. The potential of the fuzzy PSHNN to provide insight into the ranking process, without having to go through the complicated task of rule framing is demonstrated on IEEE 30-bus system and a practical 75-bus Indian system.
引用
收藏
页码：657 / 664
页数：8
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