ARTIFICIAL NEURAL NETWORKS AND THEIR APPLICATIONS TO POWER-SYSTEMS - A BIBLIOGRAPHICAL SURVEY

被引:75
作者
VANKAYALA, VSS
RAO, ND
机构
[1] Department of Electrical and Computer Engineering, University of Calgary, Calgary
基金
加拿大自然科学与工程研究理事会;
关键词
NEURAL NETWORK MODELS; NEURAL NETWORK POWER SYSTEM APPLICATIONS;
D O I
10.1016/0378-7796(93)90081-O
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 networks (ANNs), representing computational paradigms based on a biological metaphor, are rapidly gaining popularity among power system researchers. The number of ANN applications to electric power system problems has increased dramatically in the last two years, fired by both theoretical and application successes in a variety of disciplines. The theory and application developments associated with ANNs are largely interdisciplinary. More than 3500 publications are cited in the literature on ANNs and related applications. Because of limitations on space, this paper has a limited but well-defined objective, namely, to focus attention on significant ANN-related publications involving typical power system problems, and provide epitomizing evaluation and critical comment. More specifically, this paper presents a bibliographical survey of the research and explosive development of many ANN-related applications in electric power systems based on a subset of over 60 published articles. A brief overview of the ANN theory, models and applications is presented. Potential areas of application are identified and future trends are discussed.
引用
收藏
页码:67 / 79
页数:13
相关论文
共 90 条
[51]  
Mathur, Samad, Neural networks—a tutorial for the power industry, Proc. Am. Power Conf., 52, pp. 239-244, (1990)
[52]  
Mathur, Et al., Turbine back pressure identification and optimization with learning neural networks, Proc. ISA Int. Conf., pp. 229-236, (1990)
[53]  
Proc. NSF Workshop Applications of Artificial Neural Networks Methodology in Power Systems Engineering, (1990)
[54]  
Proc. 1st Int. Forum Applications of Artificial Neural Networks to Power Systems, (1991)
[55]  
Pao, A connectionist-net approach to autonomous machine learning of effective process control strategies, Int. Conf. Manufacturing Science and Technology of the Future, (1987)
[56]  
Kolmogrov, On the representation of continuous functions of several variables by superposition of continuous functions of smaller number of variables, Dokl. Akad. Nauk SSSR, 108, pp. 179-182, (1959)
[57]  
BrainMaker Reference Manual, (1992)
[58]  
Eliot, Holliday, Expert systems and neural networks: an experimental study of methodological expertise, Int. J. Neural Networks Res. Appl., 1, 2, pp. 96-106, (1989)
[59]  
Vankayala, Rao, Fast contingency screening through optimizing Hopfield neural networks, Conf. Electrical and Computer Engineering, pp. 199-204, (1993)
[60]  
Hsu, Yang, Design of artificial neural network for short term load forecasting, Part I: Self-organizing feature maps for day type identification, 138, pp. 407-413, (1991)