Open AccessTechno‐economical lifetime assessment of power transformers rated over 50 MVA using artificial intelligence models
Author(s) -
ZeinoddiniMeymand Hamed,
Vahidi Behrooz
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.0480
Subject(s) - transformer , reliability engineering , computer science , engineering , electrical engineering , voltage
Power transformers are some of the most valuable and critical elements of power systems. Therefore, accurate and detailed assessment of technical and economical (techno‐economical) condition of the transformers is absolutely important to ensure its reliable operation. In this study, in order to assess the overall condition of the power transformers, an overall condition index (OI) obtained from technical lifetime index (TI) and economical lifetime index (EI) will be defined. The OI index, which provides a practical tool to assess the overall condition of the asset, combines the results of operating observations, field inspections, site and laboratory testing, and analysis of investment and operating and maintenance costs into an overall index. An adaptive neuro‐fuzzy inference system model is used to assess the TI, and a fuzzy logic model is used for EI evaluation. Large power transformers rated over 50 MVA, which are more critical and important in the network, are investigated. The models are developed using 170 experimental field datasets of transformer oil characteristics and dissolved gas analysis, and economical data such as operating and maintenance costs. The results prove that the models can be used to effectively assess the techno‐economical lifetime of power transformers.