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Techno-economical lifetime assessment of power transformers rated over 50 MVA using artificial intelligence models

机译:使用人工智能模型评估额定功率超过50 MVA的电力变压器的技术经济寿命

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摘要

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.
机译:电力变压器是电力系统中最有价值和最关键的部分。因此,准确,详细地评估变压器的技术和经济(技术经济)状况对于确保其可靠运行至关重要。在这项研究中,为了评估电力变压器的总体状况,将从技术寿命指数(TI)和经济寿命指数(EI)获得的总体状况指数(OI)进行定义。 OI指数提供了一种评估资产总体状况的实用工具,将操作观察,现场检查,现场和实验室测试以及对投资以及运营和维护成本的分析结果组合为一个整体指数。自适应神经模糊推理系统模型用于评估TI,而模糊逻辑模型用于EI评估。研究了额定功率超过50 MVA的大型电力变压器,这些变压器在网络中变得越来越重要。这些模型是使用170个变压器油特性和溶解气体分析的实验现场数据集以及经济数据(例如运营和维护成本)开发的。结果证明,该模型可用于有效评估电力变压器的技术经济寿命。

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