Abstract
This article proposes a methodology for diagnosing faults in oil-immersed power transformers that considers correlation as a random variable and models the power transformer diagnosis problem as a hypothesis testing problem. Based on conventional estimation and detection theory, a novel diagnosis methodology for oil-immersed power transformer faults is developed by minimizing the maintenance cost of an oil-immersed power transformer. Unlike previous work, this is the first work to consider the optimization of the maintenance cost. Moreover, the proposed methodology is verified with a benchmark test based on 950 data sets of real historic records, and the results show that the accuracy of failure detection with this approach can reach 92.85% while the maintenance cost is minimized. Finally, the experimental results indicate that the proposed methodology displays promising performance and can be used as a tool for the diagnosis of incipient faults in oil-immersed power transformers.
Highlights
Power transformers are some of the most critical and expensive pieces of equipment in electric power systems
A novel diagnosis methodology for minimizing the maintenance cost of an oil-immersed power transformer is proposed. This is the first work to consider the optimization of the maintenance cost
As mentioned earlier, based on the information associated with the gases dissolved in power transformer oil, many incipient fault detection methods for power transformers have been developed in the literature
Summary
Power transformers are some of the most critical and expensive pieces of equipment in electric power systems. The insulating oil in oil-immersed power transformers in the power supply operation of the Taiwan Power Company, Taiwan, follows the standard procedures in the maintenance manuals of substation equipment. Based on the premise of a stable power supply and equipment safety, the authorities and maintenance department of the Taiwan Power Company, Taiwan, convened relevant technical units and manufacturers to investigate, discuss, and concurrently conduct partial discharge detection for the abnormal gas content in the insulating oil to identify the cause and seek improvement methods. It is necessary to rely on high-quality technologies and experience to diagnose oil-immersed power transformers For this purpose, an innovative diagnostic methodology is developed from a large amount of data, correlation coefficient theory and classical estimation theory in this article.
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