Comparative analysis of risks which are accompanied by the use of typical and boundary gases concentrations for the diagnostics of high voltage transformers
Keywords: diagnostics, transformers, analysis of dissolved gases, boundary and typical concentrations, integral distribution functions, minimum risk method, probabilities of erroneous and correct decisions
AbstractThe aim of the scientific research provided in the article is to increase the operational reliability of high-voltage power transformers by reducing the possible risks when diagnosing high-voltage equipment based on the analysis of gases dissolved in oil. We described the method for determining the boundary (typical) gas concentrations by the integral function method, which is recommended by some existing standards, and the author’s method for determining the boundary concentrations of gases ensuring a minimum of possible economic damage in case of taking erroneous decisions. The analysis of boundary concentrations of gases obtained by the method of integral functions and the method of minimum risk showed that boundary values differ significantly for the same data, depending on the method of determination. To determine the reliability of decision-making we used a comparative analysis of risk values that may arise while making a diagnosis of high-voltage transformers based on the analysis of gases dissolved in oil, the boundary values of gas concentrations obtained by the integral function method and the minimum risk method, as well as the boundary values of gas concentrations regulated by known international and national standards were used. The study has revealed that the use of typical values of gas concentrations obtained by integrated distribution functions is accompanied by one of the highest risk values. The lowest risk value is provided by the boundary concentrations obtained by the minimum risk method. The method proposed for determining the boundary values of gas concentrations, taking into account the influence of the most relevant factors, allows significantly lower the values of possible risks and consequently can increase the operational reliability of high-voltage transformers, especially those that are used outside the normative service life.