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

Journal Article · · IEEE Transactions on Power Systems
DOI:https://doi.org/10.1109/59.485995· OSTI ID:244738
; ;  [1]; ; ; ;  [2]
  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--
Journal Information:
IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 1 Vol. 11; ISSN ITPSEG; ISSN 0885-8950
Country of Publication:
United States
Language:
English

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