Title:
PREDICTING THE OIL TEMPERATURE OF A TRANSFORMER
Document Type and Number:
WIPO Patent Application WO/2014/078830
Kind Code:
A3
Abstract:
Method and system for predicting an oil temperature of a transformer for a desired load and/or predicting a load that a transformer can support for a desired time. A machine learning algorithm is developed using historical data of a transformer. After the algorithm is developed, historical data corresponding to the transformer are input into the algorithm to develop a profile of the transformer describing how the temperature of oil within the transformer is expected to change as a function of a desired load. Using the profile, the oil temperature of the transformer is predicted for a desired load. In this way, a prediction is made as to whether and/or for how long a transformer may support a desired load before the oil temperature reaches a specified threshold and/or before the transformer fails due to the load.
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Inventors:
DAGNINO ALDO (US)
CHEIM LUIZ (US)
LIN LAN (US)
PATEL POORVI (US)
CHEIM LUIZ (US)
LIN LAN (US)
PATEL POORVI (US)
Application Number:
PCT/US2013/070696
Publication Date:
August 28, 2014
Filing Date:
November 19, 2013
Export Citation:
Assignee:
ABB TECHNOLOGY AG (CH)
DAGNINO ALDO (US)
CHEIM LUIZ (US)
LIN LAN (US)
PATEL POORVI (US)
DAGNINO ALDO (US)
CHEIM LUIZ (US)
LIN LAN (US)
PATEL POORVI (US)
International Classes:
G05B13/02; H01F27/40
Other References:
QING HE ET AL: "Prediction of Top-Oil Temperature for Transformers Using Neural Networks", IEEE TRANSACTIONS ON POWER DELIVERY, IEEE SERVICE CENTER, NEW YORK, NY, US, vol. 15, no. 4, 1 October 2000 (2000-10-01), XP011049941, ISSN: 0885-8977
Attorney, Agent or Firm:
FISCHER, Marcus, A. (LLC6505 Rockside Road,Suite 33, Independence OH, US)
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