An integrated fuzzy logic approach for valuation of power transformer's degree of healthiness or faultiness.

A substantial number of power transformers that are in use mainly in developing countries are aged and operating beyond their technical design life. This has forced many power utility entities to embrace condition-based maintenance strategies in an effort to prolong assets functionality and reduce equipment failures. To maximize the continuous use of aging power system assets, it is essential to comprehend the variables that pose a threat to the technical and operational lifetime. This paper proposes a model for estimating Degree of Healthiness (DOH) or Faultiness (DOF) of power transformers by synthesizing multiple measured variables, grouped into factors and calculating their corresponding scores. The numerical scores are translated to qualitative assessments through fuzzy logic inference system and thus DOH/DOF derived from the factors is evaluated to give an overall valuation of the in-service power transformer. Furthermore, a nonintrusive degree of polymerization (DP) model based on furans, carbon oxide ratios and methanol as DP pointers is also factored to map the paper insulation condition. Fuzzy rules formulation was centered on variable weighting values established through Analytical Hierarchical Process (AHP) approach. To diagnose the transformer incipient faults, a modified Duval pentagon methodology was employed in interpretation of the Dissolved Gas Analysis (DGA). The accuracy and effectiveness of the established Modified Combined Duval Pentagon (MCDP) technique is high as compared to those of the Pentagon 1 & 2 and combined pentagon methods using the six IEC faults. Results from DOH/DOF evaluation have indicated that DGAF and DPF are more impactful relative to the other factors. Timely knowledge of DOH/DOF of an in-service power transformer can have a great impact in asset managers' decision making on transformer maintenance and loading management.