Application of Self-Organizing Map (SOM) to Prediction of Oil Temperature of a Substation Transformer

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概要

• 論文の詳細を見る

• Prediction of oil temperature of a transformer has been practiced using a conventional method based on explicit numerical calculations. When the technique is applied, sometimes there is a limitation in the prediction accuracy due to assumption made on the characteristics of the transformer. This paper considers an application of the Self-Organizing Map (SOM) for the prediction of the oil temperature of a substation transformer. In the SOM approach, data of oil temperature, atmospheric temperature and load rate are used for its mapping, and oil temperature data with a limited time interval, forecast atmospheric temperature and load rate are used for the prediction of the oil temperature. Using the SOM, the oil temperature is well predicted. The prediction accuracy obtained is higher comparing with the conventional method based on the transformer characteristics in operational guidelines and the method by transformer thermal modeling proposed recently.

• 社団法人電子情報通信学会の論文
• 2004-06-17

著者

• Ohkita M

  Tottori University Faculty Of Engineering

• Ohkita Masaaki

  Department Of Electrical And Electronic Engineering Faculty Of Engineering Tottori University

• DU Hong

  Department of Electrical and Electronic Engineering, Faculty of Engineering, Tottori University

• Inui Masahiro

  Matsushita Industrial System Engineering Co. Ltd.

• Du Hong

  Department Of Electrical And Electronics Engineering Tottori University

• Kobayashi T

  Department Of Electrical And Electronics Engineering Tottori University

• KOBAYASHI Takuma

  Department of Electrical and Electronics Engineering, Tottori University

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