APPLICATION OF PROBABILISTIC APPROACHES FOR RELIABILITY ASSESSMENT AND DIAGNOSTICS OF POWER TRANSFORMERS

Power transformers are critical elements of electrical power systems, and their failures can lead to significant economic and operational consequences. Traditional diagnostic methods are often deterministic and may not fully capture the uncertainty inherent in degradation processes. This paper investigates the use of probabilistic methods, including Bayesian inference and reliability functions, for transformer diagnostics. Statistical data on common fault modes, dissolved gas analysis (DGA), and insulation failures are processed with probabilistic modeling. The results demonstrate that probabilistic methods provide higher accuracy in failure prediction and improve decision-making under uncertainty.