Life Extension Of Transformer Mineral Oil Using AI-Based Strategy For Reduction Of Oxidative Products
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Abstract
The power system operational reliability depends on the proper functioning of transformers. The decreased quality of mineral oil deteriorates the insulation of the transformer results in the failure of the transformer. Thus, maintaining the quality of the mineral oil is a severe issue for power utilities. The major cause of mineral oil deterioration is the formation of oxidative products due to the over-temperature and overloading conditions. This research paper presents an artificial intelligence-based strategy for the reduction of oxidative products by regulating the temperature level accordingly. During the various critical operating conditions, the temperature sensor measures the temperature of mineral oil. The neural network is trained to recognise the various abnormal events according to increased temperature level.
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