Application of artificial neural networks in voltage stability assessment
- Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Electrical Engineering
Voltage stability problems have been one of the major concerns for electric utilities as a result of system heavy loading. This paper reports on an investigation on the application of ANNs in voltage stability assessment. A multi-layer feed-forward artificial neural network (ANN) with error back-propagation learning is proposed for calculation of voltage stability margins (VSM). Based on the energy method, a direct mapping relation between system loading conditions and the VSMs is set up via the ANN. A systematic method for selecting the ANN`s input variables was developed using sensitivity analysis. The effects of ANN`s training pattern sensitivity problems were also studied by dividing system operating conditions into several loading levels based on sensitivity analysis. Extensive testing of the proposed ANN-based approach indicate its viability for power system voltage stability assessment. Simulation results on five test systems are reported in the paper.
- OSTI ID:
- 160603
- Report Number(s):
- CONF-950103-; ISSN 0885-8950; TRN: IM9603%%185
- Journal Information:
- IEEE Transactions on Power Systems, Vol. 10, Issue 4; Conference: Winter meeting of the IEEE Power Engineering Society, New York, NY (United States), 29 Jan - 2 Feb 1995; Other Information: PBD: Nov 1995
- Country of Publication:
- United States
- Language:
- English
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