Health assessment of transformers using online and offline parameters - Sah, Pradip Prasad; Madhusudan Nyaupane; Prabesh Babu Adhikari; Sujal Mainali; Kulung, Ninamhang (Journal of Innovations in Engineering Education, 2026)
Distribution transformers at substations are crucial assets in power system, whose failure can cause major operational disruptions, safety risks, and economic losses, thus making effective condition assessment essential for ensuring reliability and minimizing outages. This paper presents Supervisory Control and Data Acquisition (SCADA)-based transformer Health Index (HI) method that combines both Offline Parameters (OFPs) which include transformer age, historical loading, maintenance history, and environmental conditions and Online Parameters (ONPs) which incorporate real-time operational stresses like voltage, current, active power, oil temperature, and winding temperature. The proposed HI formulation applies a rule based, explainable scoring and weighting scheme to combine OFPs and ONPs into a single normalized metric where based on published failure statistics and utility-specific evidence, a weightage of 30% for OFPs and 70% for ONPs is adopted, emphasizing operational stress while accounting for long-term degradation. The computed HI is categorized as Good (85–100%), Fair (65–85%), Poor (50–65%), or Very Poor (0–50%). The method is tested using one year of data from two parallel 66/11 kV, 30 MVA power transformers and overall HI values of 0.598 and 0.567 for Transformer 1 and Transformer-2 respectively classify that both are in the fair condition category, suggesting the need for enhanced inspection rather than immediate replacement, while degradation-rate analysis confirms stable long-term operation.