Neural network-based self-organizing fuzzy controller for transient stability of multimachine power systems
- National Taiwan Institute of Technology, Taipei (Taiwan, Province of China). Dept. of Electrical Engineering
An efficient self-organizing neural fuzzy controller (SONFC) is designed to improve the transient stability of multimachine power systems. First, an artificial neural network (ANN)-based model is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the ANN model. With the excellent learning capability inherent in the ANN, the traditional heuristic fuzzy control rules and input-output fuzzy membership functions can be optimally tuned from training examples by the back propagation learning algorithm. Considerable rule-matching times of the inference engine in the traditional fuzzy system can be saved. To illustrate the performance and usefulness of the SONFC, comparative studies with a bang-bang controller are performed on the 34-generator Taipower system with rather encouraging results.
- OSTI ID:
- 94102
- Report Number(s):
- CONF-940702-; ISSN 0885-8969; TRN: IM9538%%75
- Journal Information:
- IEEE Transactions on Energy Conversion, Vol. 10, Issue 2; Conference: 1994 Institute of Electrical and Electronic Engineers/Power Engineering Society (IEEE/PES) summer meeting, San Francisco, CA (United States), 24-28 Jul 1994; Other Information: PBD: Jun 1995
- Country of Publication:
- United States
- Language:
- English
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