Abdelhadi Aouaichia

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

Submitted: 19 February 2025 You are already at the latest version In this paper, a new methodology for fault detection and diagnosis in photo- 1 voltaic systems is proposed. This method employs a novel Euclidean distance-based tree algorithm to classify various considered faults.Unlike the decision tree, which requiresthe use of the Gini index to split the data, this algorithm mainly relies on computing distances between an arbitrary point in the space and the entire dataset.