Power system dynamic security enhancement using artificial neural networks and energy margin

Conference · Fri Nov 01 00:00:00 EST 1996

OSTI ID:389936

Momoh, J A; Effiong, C B ^[1]

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1. Howard Univ., Washington, DC (United States). Electrical Engineering Dept.

A framework for dynamic security enhancement based on area-wise preventive control is proposed. The power system is partitioned into areas for stability evaluation using the transient energy margin. Area vulnerability is evaluated based on the sensitivity of the energy margin w.r.t. controls in the given areas of the system. The areas of the system which contribute significantly to instability are labeled critical or weak areas and preventive control is applied in those areas of the system. The final control application is achieved by the use of artificial neural network (ANN) to compute the control inputs.

• OSTI ID: 389936
• Report Number(s): CONF-960426-; TRN: IM9646%%221
• Resource Relation: Conference: 58. annual meeting of the American power conference, Chicago, IL (United States), 9-11 Apr 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the American Power Conference. Volume 58-II; McBride, A.E. [ed.]; PB: 886 p.
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
POWER SYSTEMS
STABILIZATION
ELECTRICAL TRANSIENTS
NEURAL NETWORKS
ARTIFICIAL INTELLIGENCE