Online learning recurrent neural network stabilization controller for multi-machine power system

被引：0
|
作者：
Senjyu, T [1 ]
Yoshiteru, M [1 ]
Uezato, K [1 ]
机构：
[1] Univ Ryukyus, Okinawa 9030213, Japan
来源：
2000 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS I-III, PROCEEDINGS | 2000年
关键词：
genetic algorithm; online learning; recurrent neural network stabilization controller;
D O I：
暂无
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：
This paper presents an online learning recurrent neural network stabilization controller to improve the transient stability of power system. Since the proposed recurrent neural network is online tuning type, it can stabilize the power system for different system parameters, operating conditions, and fault point. The proposed controller robustness and effectiveness in damping power system oscillations are illustrated through simulations.
引用
收藏
页码：223 / 228
页数：6
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