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《AUTOMATION OF ELECTRIC POWER SYSTEMS》 2000-02
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HYBRID NEURAL NETWORK APPROACH TO DYNAMIC VOLTAGE STABILITY ANALYSIS

Fu Ying, T. S. Chung(The Hong Kong Polytechnic University, Hong Kong, China)  
An innovative application of artificial neural network (ANN) approach to dynamic voltage stability analysis ispresented. The approach developed is based on a self--organizing hierarchical neural network (SHNN), with hybrid of selforganizing input feature and the multilayer perceptron (MLP) neural network. Two SHNN models are 'utilized in theproposed approach. The first one is used to classify the power system, to determine whether it is dynamically stable orunstable. The second one is used for the dynamically stable system to predict the voltage magnitudes at all Po buses. Thetraining set patterns are generated by carrying out dynamic simulations. using induction motor and constant P--Q load models.The proposed method is demonstrated in dynamic voltage stability determination and bus voltage magnitude estimation atdifferent loading conditions for two test systems: WSCC 9-bus system and New England 39--bus system. The performance ofthe SHNN is tested and found to be effective in application.
【CateGory Index】: TM71
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