Real power transfer capability calculations using multi-layer feed-forward neural networks

被引：68

作者：

Luo, X ^{[1
]}

Patton, AD ^{[1
]}

Singh, C ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Elect Engn, College Stn, TX 77843 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2000年 / 15卷 / 02期

基金：

美国国家科学基金会;

关键词：

artificial neural network; quickprop algorithm; transfer capability; optimal power flow; reliability management;

D O I：

10.1109/59.867192

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 proposes a neural network solution methodology for the problem of real power transfer capability calculations. Based on the optimal power flow formulation of the problem, the inputs for the neural network are generator status, line status and load status and the output is the transfer capability. The Quickprop algorithm is used in the paper to train the neural network. A case study of IEEE 30-bus system is presented demonstrating the feasibility of this approach. The new method will be, useful for reliability assessment in the new utility environment.

引用

页码：903 / 908

页数：6