Conceptual designs of AI-based systems for local prediction of voltage collapse

Journal Article · Thu Feb 01 00:00:00 EST 1996 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/59.485995· OSTI ID:244738

Yabe, K; Koda, J; Yoshida, K ^[1]; Chiang, K H; Khedkar, P S; Leonard, D J; Miller, N W ^[2]

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1. Tokyo Electric Power Co. (Japan)
2. General Electric Co., Schenectady, NY (United States)

Vulnerability of modern power systems to locally initiated voltage collapse gives rise to a need for methods to measure local voltage security and to predict voltage instability. The paper presents a novel architecture based on a suite of AI technologies and three-dimensional PQV surfaces which provides prediction of local voltage collapse and indices of system voltage security. Robustness and adaptation are demonstrated on difficult and realistic power system simulation models.

• OSTI ID: 244738
• Report Number(s): CONF-950103-; ISSN 0885-8950; TRN: IM9627%%60
• Journal Information: IEEE Transactions on Power Systems, Vol. 11, Issue 1; Conference: Winter meeting of the IEEE Power Engineering Society, New York, NY (United States), 29 Jan - 2 Feb 1995; Other Information: PBD: Feb 1996
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
POWER SYSTEMS
STABILITY
ON-LINE MEASUREMENT SYSTEMS
ARTIFICIAL INTELLIGENCE
ELECTRIC POTENTIAL