Machine learning-based statistical testing hypothesis for fault detection in photovoltaic systems
Abstract
In this paper, we consider a machine learning approach merged with statistical testing hypothesis for enhanced fault detection performance in photovoltaic (PV) systems. The developed method makes use of a machine learning based Gaussian process regression (GPR) technique as a modeling framework, while a generalized likelihood ratio test (GLRT) chart is applied to detect PV system faults. The developed GPR-based GLRT approach is assessed using...
Paper Details
Title
Machine learning-based statistical testing hypothesis for fault detection in photovoltaic systems
Published Date
Sep 1, 2019
Journal
Volume
190
Pages
405 - 413
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