Improved Monitoring and Diagnosis of Transformer Solid Insulation Using Pertinent Chemical Indicators

Transformers are generally considered to be the costliest assets in a power network. The lifetime of transformer is mainly attributable condition its solid insulation, which turn measured and described according degree polymerization (DP) cellulose. Since determination DP index complex time-consuming requires taken out service, utilities prefer indirect non-invasive methods determining based on byproduct cellulose aging. This paper analyzes insulation degradation by measuring furan concentration, recently introduced methanol, dissolved gases like carbon oxides hydrogen, insulating oil. A group service-aged distribution transformers were selected for practical investigation oil samples different kinds tests. Based maintenance planning strategy utility weighted combination chemical indicators, neural network was also developed categorize state certain classes. method proved able improve diagnostic capability thus providing with more reliable tools avoiding catastrophic failure transformers.