Data driven modeling for power transformer lifespan evaluation

Charles V. Trappey, Amy J.C. Trappey, Lin Ma, Wan Ting Tsao

研究成果: Article同行評審

11 引文 斯高帕斯(Scopus)

摘要

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation's energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

原文English
頁(從 - 到)80-93
頁數14
期刊Journal of Systems Science and Systems Engineering
23
發行號1
DOIs
出版狀態Published - 1 1月 2014

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