ARTIFICIAL NEURAL-NETWORK POWER-SYSTEM STABILIZERS IN MULTIMACHINE POWER-SYSTEM ENVIRONMENT

被引:40
|
作者
ZHANG, Y
MALIK, OP
CHEN, GP
机构
[1] Department of Electrical and Computer Engineering, The University of Calgary, Calgary, Alberta
关键词
POWER SYSTEM STABILIZER; ARTIFICIAL NEURAL NETWORK; INVERSE PLANT; MULTILAYER NETWORK ERROR BACKPROPAGATION; MULTIMACHINE; MULTI-MADE OSCILLATION;
D O I
10.1109/60.372580
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Effectiveness of an artificial neural network (ANN), functioning as a power system stabilizer (PSS), in damping multi-mode oscillations in a Ave-machine power system environment is investigated in this paper. Accelerating power of the generating unit is used as the input to the ANN PSS. The proposed ANN PSS using a multilayer neural network with error-backpropagation training method was trained over the full working range of the generating unit with a large variety of disturbances. The ANN was trained to memorize the reverse input/output mapping of the synchronous machine. Results show that the proposed ANN PSS can provide good damping for both local and inter-area modes of oscillations.
引用
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页码:147 / 155
页数:9
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