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Implementation of Adaptive Neuro-Fuzzy Inference System in Fault Location Estimation

机译:自适应神经模糊推理系统在故障位置估计中的实现

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This paper proposed a new scheme using hybrid intelligent technique that combines artificial neural network and fuzzy inference system. This technique, known as Adaptive Neuro-Fuzzy Inference System (ANFIS) has associated with the advantage of wavelet transform as a pattern recognition method. The algorithm used to identify the type of fault either single line to ground, double line, double line to ground or three phase occur on a power transmission line. Other than that, this scheme is capable to analyze the fault location without the knowledge of line parameters. A power clustering algorithm called Gustafson Kessel is implemented for better performance. Alternative Transient Program/Electromagnetic Transient Program (ATP/EMTP) is used for simulation purposes and Matlab for further analysis. Outcomes indicated that the scheme is efficient and has a high percentage of accuracy.
机译:提出了一种基于混合智能技术的人工神经网络与模糊推理系统相结合的新方案。这种称为自适应神经模糊推理系统(ANFIS)的技术具有将小波变换作为模式识别方法的优势。用于识别故障类型的算法是在输电线路上发生单线接地,双线故障,双线接地故障还是三相故障。除此之外,该方案能够在不知道线路参数的情况下分析故障位置。为实现更好的性能,实施了一种称为Gustafson Kessel的功率聚类算法。替代暂态程序/电磁暂态程序(ATP / EMTP)用于仿真目的,而Matlab用于进一步分析。结果表明该方案是有效的,并且具有很高的准确性百分比。

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