Enhancement in Static Security Assessment for a Power System Using an Optimal Artificial Neural Network

被引：0

作者：

Al-Masri, A. ^{[1
]}

Ab Kadir, M. Z. A. ^{[2
]}

Hizam, H. ^{[1
]}

Mariun, N. ^{[1
]}

Khairuddin, A.

Jasni, J. ^{[1
]}

机构：

[1] Univ Putra Malaysia, Fac Engn, Dept Elect & Elect Engn, Serdang, Malaysia

[2] Univ Putra Malaysia, CELP, Serdang, Malaysia

来源：

INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE | 2010年 / 5卷 / 03期

关键词：

Neural Network; Back Propagation (BP); Power System; Load-Flow; Security Assessment; Contingencies; RANKING;

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：

Artificial Neural Network (ANN) is addressed as a tool for the power system security assessment. The goals of this study are to test the reliability of ANN in Static Security Assessment (SSA) by determining the security level due to changes in aspects of contingencies and load increases and to compare the results of ANN and Load-Flow models in terms of accuracy and computational time. The proposed method has been successfully tested on 5-bus and IEEE 30-bus test systems. ANN can provide the security states of the current operating point and enhanced to be faster and more accurate. Copyright (C) 2010 Praise Worthy Prize S.r.l. - All rights reserved.

引用

页码：1095 / 1102

页数：8

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