energies Article Fuzzy Logic Approach to Dissolved Gas Analysis for Power Transformer Failure Index and Fault Identification Nitchamon Poonnoy 1 , Cattareeya Suwanasri 1, * and Thanapong Suwanasri 2   Citation: Poonnoy, N.; Suwanasri, C.; Suwanasri, T. Fuzzy Logic Approach to Dissolved Gas Analysis for Power Transformer Failure Index and Fault Identification. Energies 2021, 14, 36. https://dx.doi.org/10.3390/en14010036 Received: 12 November 2020 Accepted: 20 December 2020 Published: 23 December 2020 Publisher’s Note: MDPI stays neu- tral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2020 by the authors. Li- censee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). 1 Department of Electrical and Computer Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok (KMUTNB), Bangkok 10800, Thailand; nitchamon.p@fte.kmutnb.ac.th 2 Department of Electrical and Software Systems Engineering, The Sirindhorn International Thai-German Graduate School of Engineering (TGGS), KMUTNB, Bangkok 10800, Thailand; thanapong.s.epe@tggs-bangkok.org * Correspondence: cattareeya.s@eng.kmutnb.ac.th; Tel.: +66-851-410-072 Abstract: This research focuses on problem identification due to faults in power transformers during operation by using dissolved gas analysis such as key gas, IEC ratio, Duval triangle techniques, and fuzzy logic approaches. Then, the condition of the power transformer is evaluated in terms of the percentage of failure index and internal fault determination. Fuzzy logic with the key gas approach was used to calculate the failure index and identify problems inside the power transformer. At the same time, the IEC three-gas ratio and Duval triangle are subsequently applied to confirm the problems in different failure types covering all possibilities inside the power transformer. After that, the fuzzy logic system was applied and validated with DGA results of 244 transformers as reference cases with satisfactory accuracy. Two transformers were evaluated and practically confirmed by the investigation results of an un-tanked power transformer. Finally, the DGA results of a total of 224 transformers were further evaluated by the fuzzy logic system. This fuzzy logic is a smart, accurate tool for automatically identifying faults occurring within transformers. Finally, the recommendation of maintenance strategy and time interval is proposed for effective planning to minimize the catastrophic damage, which could occur with the power transformer and its network. Keywords: dissolved gas analysis; Duval triangle; key gas method; IEC 60599; power transformer; total dissolved combustible gases 1. Introduction The power transformer is a key component in power transmission and distribution systems. During operation, it might be deteriorated by both normal and abnormal con- ditions, including overloading, aging, and degradation of paper-oil insulation, internal arcing and partial discharge (PD), short circuit, etc. Survey results [1] show damages within power transformers including on-load tap changer (OLTC), winding and iron core, bushing, tank, and other related damages. Therefore, to prevent failure and to maintain the power transformer in the satisfactorily working condition, several traditional and nontraditional diagnostic methods have been performed to assess the condition [2,3]. The traditional diagnostic methods are dissolved gas analysis, oil quality, power factor testing, winding resistance measurement, turn ratio, and thermography, while the nontraditional diagnostic methods are partial discharge measurement, dielectric spectroscopy, frequency response analysis, tap changer monitoring, and internal temperature measurement. After obtaining the test results from various diagnostic methods mentioned above, the data has been further evaluated to assess the condition of the power transformer, mainly based on health index value by applying a scoring and weighting algorithm [4]. However, this traditional health index determination has some drawbacks because it requires many test results from transformer electrical tests and oil diagnostics to complete the evaluation Energies 2021, 14, 36. https://dx.doi.org/10.3390/en14010036 https://www.mdpi.com/journal/energies