Research on power transformer maintenance strategy based on RCM and multidimensional normal cloud model

Power transformers are the most crucial link in the power transmission and transformation system, providing strong support for ensuring the reliable operation of the system. A key research focus of the State Grid Corporation of China is how to quickly diagnose and identify potential risk points in the operation of power transformers, based on the actual operating conditions of the grid, while employing corresponding maintenance strategies and minimizing various risks caused by excessive maintenance. This paper, based on Reliability Centered Maintenance (RCM) theory, utilizes oil chromatography indicators, electrical indicators, insulation degradation indicators, and short-circuit electromagnetic indicators as evaluation factors for assessing the operating conditions of power transformers. A multidimensional normal cloud model is established for evaluating power transformers, categorizing their non-failure operating conditions into five types. The entropy weight method is used to determine the weight of various indicators, and state evaluation factors are combined to achieve a state score for the power transformer, which further guides the development of maintenance strategies. Finally, using historical operational data from a 110kV transformer, this paper analyzes the transformer with the proposed state evaluation model, validating the scientific and effective nature of the designed maintenance strategy for power transformers.