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|Title:||Hybrid model for transient stability evaluation of interconnected longitudinal power systems using neural network/pattern recognition approach||Authors:||Chang, C.S.
|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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