Artificial neural network power system stabilizers in multi-machine power system environment

Journal Article · Wed Mar 01 00:00:00 EST 1995 · IEEE Transactions on Energy Conversion

DOI:https://doi.org/10.1109/60.372580· OSTI ID:40282

Zhang, Y; Malik, O P; Chen, G P ^[1]

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1. Univ. of Calgary, Alberta (Canada). Dept. of Electrical and Computer Engineering

Effectiveness of an artificial neural network (ANN), functioning as a power system stabilizer (PSS), in damping multi-mode oscillations in a five-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-back propagation 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.

• OSTI ID: 40282
• Report Number(s): CONF-940110-; ISSN 0885-8969; TRN: IM9520%%477
• Journal Information: IEEE Transactions on Energy Conversion, Vol. 10, Issue 1; Conference: 1994 Institute of Electrical and Electronic Engineers (IEEE)/Power Engineering Society (PES) winter meeting, New York, NY (United States), 30 Jan - 3 Feb 1994; Other Information: PBD: Mar 1995
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
POWER SYSTEMS
STABILIZATION
NEURAL NETWORKS
ELECTRIC GENERATORS
TRAINING
ELECTRICAL TRANSIENTS
DAMPING
OSCILLATIONS