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Power Transformers are one of the most important and critical devices of any power system network so the interpretation of the faults and failures within transformers are of utmost importance. In monitoring the condition of the transformers sweep frequency response analysis has gained huge interest in assessing the core or winding disintigrity and deformations, open or shorted turns, axial or radial shifts etc. Changes in core and winding can be detected from the knowledge of poles and zeroes of the transfer function by statistical and mathematical indicators. In spite of efforts of researchers on SFRA there is no universally accepted or systematic method to detect deformations of winding and core of transformers. This new method is based on multiresolution decomposition technique using discrete wavelet transform. This method is further supported by statistical and mathematical indicators using the frequency band where faults actually exist which adds robustness and accuracy to the diagnosis of the fault. This methodology is tested for several cases of transformers and validated using two of the cases which show the difference between normal and abnormal condition of the transformers.

Determining the current prevailing conditions in the transformer is still a challenge and an attempt is made for meeting the same challenge. In this paper a novel system based on fuzzy logic is developed which considers thermal, electrical and mechanical conditions prevailing in the transformer and gives the critical status of the transformer at an aggregate. The developed system also facilitates to give the critical condition of Paper thermal, Oil thermal, Partial discharge, Electrical arching, Dissolved gas analysis(DGA), Break down voltage and sweep frequency response analysis(SFRA) individually so that corresponding preventive measures can be taken by the technologists. This system consists of 10 fuzzy logic controllers whose connections are made by considering technical conditions and reasons, the corresponding rule bases of these fuzzy logic controllers were developed by considering various standards and experience of TIFAC CORE in NIT-Hamirpur. This fuzzy logic based system is tested for various transformers and found that it is highly précised in classifying the critical statues of any transformer as well as all identifying the current prevailing conditions.

All the manufacturers of power transformer give the anticipated life of their product in terms of certain numbers of years. Some power transformers may fail earlier than their stipulated life, while some of them even may cross their limit of recommended age and they are still in working status. But the transformers which are in working condition after their completion of expected age or near to complete their expected age, normally need more care and precautions. For this, some important tests are involved more often in a regular fashion to determine the health status. These tests include moisture level determination in paper insulation, moisture level in oil insulation, BDV, flash point, acidity, tan delta (dissipation factor) measurement and IFT etc. and adopt the recommendation and precautionary action to avoid major faults. In this report, a survey of three power transformers (21 year old) of HPSEBL, Shimla has been performed on the basis of DIRANA (Dielectric Response Analyzer) wherein details related to its paper insulation moisture diagnostics have been taken as preventive measure to safeguard the equipment.

Power transformer is one of the most prominent equipment in the area of power sector. Increasing power demand at world level requires manufacturing of large number of oil immersed power transformer. With increase in size and MVA rating of power transformer, the chances of failure also increases simultaneously. Cost of replacement of whole transformer is much more enough compared to regular condition monitoring of transformer. In this paper, efforts are made to analyse the core magnetization effects in low frequency range for high voltage, low voltage and tertiary voltage winding. In low frequency range, core magnetization inductance is dominant over winding inductance and hence responsible for magnetization effect. There is lot of irregularities for resonance amplitude at resonance frequency for SFRA signature, which indicates core magnetization effect. A case study has been presented in this paper for 315 MVA rating transformer through design based interpretation techniques.

Condition monitoring and diagnostic playing important role in estimating remnant Life of power transformer. Concentration of furan content in transformer oil can be a promising factor for indirect measurement of the aging of transformer insulation. The oil gets contaminated mainly due to prolonged operation and ageing. The present research paper introduces Adaptive Neuro Fuzzy inference system (ANFIS) technique to correlate furanic compounds obtained by High Performance Liquid Chromatography (HPLC) test to remnant life of the power transformer. The results are obtained by conducting HPLC test at TIFAC-CORE lab, NIT Hamirpur on thirteen samples of Power transformer oil taken from Himachal State Electricity Board Ltd, Shimla (India). DOI: http://dx.doi.org/10.11591/ijece.v4i4.5567