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https://doi.org/10.1109/59.317554
Title: | Hybrid model for transient stability evaluation of interconnected longitudinal power systems using neural network/pattern recognition approach | Authors: | Chang, C.S. Srinivasan, Dipti Liew, A.C. |
Issue Date: | Feb-1994 | Citation: | Chang, C.S., Srinivasan, Dipti, Liew, A.C. (1994-02). Hybrid model for transient stability evaluation of interconnected longitudinal power systems using neural network/pattern recognition approach. IEEE Transactions on Power Systems 9 (1) : 85-92. ScholarBank@NUS Repository. https://doi.org/10.1109/59.317554 | Abstract: | A methodology for evaluation of transient stability of medium size interconnected longitudinal power systems has been developed using a hybrid neural network/ pattern recognition approach. Assessment of transient stability is done using a fast pattern recognition algorithm at each load level, accurately predicted by a neural network on a half-hourly basis. As opposed to the conventional approaches, this hybrid strategy can make fast decisions with less computations. | Source Title: | IEEE Transactions on Power Systems | URI: | http://scholarbank.nus.edu.sg/handle/10635/80554 | ISSN: | 08858950 | DOI: | 10.1109/59.317554 |
Appears in Collections: | Staff Publications |
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