A neural network approach to adaptive protective systems problem in the complex power generating units

被引:0
|
作者
Halinka, A
Sowa, P
Szewczyk, M
Sztandera, L [1 ]
机构
[1] Philadelphia Univ, Philadelphia, PA 19144 USA
[2] Silesian Tech Univ, PL-44100 Gliwice, Poland
关键词
D O I
10.1002/(SICI)1098-111X(200004)15:4<291::AID-INT2>3.0.CO;2-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Practical successes have been achieved with neural network models in a variety of domains, including energy-related industry. The large, complex design space of electrical power systems (EPS) is only minimally explored in current practice. The satisfactory results that nevertheless have been obtained testify that: neural networks are a robust modeling technology; at the same time, however, the lack of a systematic design approach implies that the best neural network models generally remain undiscovered for most applications. This paper presents an approach to an adaptive protective systems problem in the complex power generating units. First, we demonstrate the complex interdependencies between various parameters of EPS protection systems. We then present an approach, based on protection and adaptation criteria, for designing a neural network based adaptive protection system. (C) 2000 John Wiley & Sons, Inc.
引用
收藏
页码:291 / 302
页数:12
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