Asset Management Through Effective Transformer Diagnostics & Condition Monitoring Nor Asiah Binti Muhamad & Nouruddeen Bashir Institute of High Voltage and High Current (IVAT) FKE, Universiti Teknologi Malaysia Johor Bahru, Malaysia norasiah@fke.utm.my nour@fke.utm.my Abubakar Abdullkareem Suleiman National Agency for Science and Engineering Infrastructure (NASENI), Abuja, Nigeria aabubakarsule@yahoo.ca Ali Saeed Alghamdi Technical and Vocational Training Corporation, Secondary and Vocational Institute, 21413 Jeddah, KSA sar_dont2004@hotmail.com Abstract—Power transformers are the most critical and important equipment in the power sector. It links power generation, transmission and distribution. There is a huge investment required to acquire or replace them and when they fail, huge losses are incurred in terms of assets, revenue and customer good will. This huge financial burden due to sudden losses of power transformers can be minimized through effective condition monitoring and diagnostics. This paper presents a computer program developed to interpret the condition of power transformers by the analyzing the dissolved gases. The computer program developed using C-Sharp (C#) language under WINDOWS operating system is used to assess four different methods of Dissolved Gas Analysis (DGA) technique to predict the condition of the transformer so as to improve the accuracy of the interpretation. The result shows an increase in the fault- analysis classification of these DGA methods by up to 20%. Keywords- Asset Management; Transformer; Condition Monitoring; Rogers Ratio; IEC Ratio; Duval Triangle; Key Gas I. INTRODUCTION The power transformer is the most critical and important equipment in the chain of power generation, transmission and distribution as shown in the fig. 1. From the figure, it can clearly be noticed to be the only recurring equipment and so its economic and social value cannot be over emphasized. Figure 1. Schematic diagram of power generation to delivery chain Therefore to ensure the reliability and guarantee the availability of power, effective management of the power transformer is necessary. The management of the power transformer will have economic, social and environment implications. Effective asset management will elongate equipment life, its reliability and thus improve and optimize business profitability [1]. The management of power transformer is essentially through monitoring and maintenance while it is circuit. In the power transformer, the degradation of the oil is identified as one of the major reasons of transformer failures [2]. This is because the insulation materials degrade at higher temperatures in the presence of oxygen and moisture causing thermal stress which affects electrical, chemical, and physical properties of the oil [3]. The insulating materials of the power transformer is mainly oil and paper and their degradation will produce hydrocarbon gases that include Methane (CH 4 ), Hydrogen (H 2 ), Ethane (C 2 H 6 ), Ethylene (C 2 H 4 ), Acetylene (C 2 H 2 ) [4]. Dissolve Gas Analysis (DGA) is one of the most well established condition monitoring assessment techniques developed to diagnose the fault condition on oil filled insulation transformers. Though the testing of transformer oil for dissolved gases started around 1956 with the Buchholz relay trigger in transformers, modern methods are available for DGA analysis. The methods utilise proportional quantities of the gases to indirectly interpret partial discharges, hot points, arcing, combustion, aging and overheating; thus aiming to detect incipient failures that could end the transformer life. There are more than 6 known different methods of DGA fault interpretation technique and so there is the likelihood that they may vary in their interpretations and each of the known techniques has its own method of assessing the condition of transformer. The results from either of this assessment method vary from each other and so there may be an elusive conclusion on the condition of the transformer. A combination of all or some of the assessment techniques will make the DGA more accurate interpretation. In view of the foregoing, this paper presents a computer program that is developed to combine four DGA techniques to interpret the same data obtained from any power transformer 2012 IEEE International Conference on Power and Energy (PECon), 2-5 December 2012, Kota Kinabalu Sabah, Malaysia 978-1-4673-5019-8/12/$31.00 ©2012 IEEE 212