Perpustakaan Digital ITB

Solid insulation in power transformer deteriorates due to aging processes during its operation. The widely used parameter for determining paper insulation condition is the Degree of Polymerization (DP). Nowadays DP measurement techniques without damage the components of the transformer insulation system or interfere with the transformer service time is needed. The most common method is using furan analysis to estimate DP value but still have external factor which impact to the accuracy of furan measurement e.g. oil replacement or reclamation, also uncertainties and dynamics factor e. g. different period of measurement after oil processing, different temperature and time of measurement. Several estimation algorithms has been developed to determine the condition of the solid insulation of oil-immersed power transformer using the Degree of Polymerization (DP) by considering chemical and dielectric parameters of un-inhibited oils. This contribution therefore is aimed at develop an algorithm to estimate the DP value of paper insulation for transformers immersed with inhibited oil. Dielectric characteristic parameters, i.e. Water content, Acidity, Interfacial Tension (IFT), Breakdown Voltage (BDV) as well as Dissolved Gas Analysis (DGA), i.e. carbon monoxide (CO) and carbon dioxide (CO2) are processed and evaluated using specialized Fuzzy Inference System (FIS) and Adaptive Neuro Fuzzy Inference System (ANFIS). An algorithm implemented to find the most significant parameters to DP value and generate rules for fuzzy sets based on the information gain according to entropy of the measurement data. Estimation result observed and evaluated so that FIS and ANFIS is suitable to estimate insulation condition for inhibited insulation oil. In addition, accelerated aging sample data found suitable to use in algorithms to predict insulation condition on field operating transformer.