@inproceedings{c5dfbf48a3724f5ea77492978bc7f9f9,
title = "Diagnose Algorithm and Fault Characterization for Photovoltaic Arrays: A Simulation Study",
abstract = "The performance of photovoltaic installation is highly affected by faults in single modules. Faults in photovoltaic arrays are difficult to detect, locate and diagnose due to the way in which modules are configured. Given that photovoltaic arrays are formed by modules in series, a fault in a single module affects the whole system. Therefore, the technology to detect and diagnose faults inside solar arrays is emerging, the present paper proposes several expressions that help to detect and diagnose failures using a proposed algorithm. The expressions were obtained by an inductive approach based on the analysis of simulation cases where different faults were tested. The array model used for the simulation was built in Spice software based on the five-parameter model of a solar module.",
keywords = "Modelling faults, PV fault diagnosis, Simulation",
author = "Murillo-Soto, {Luis D.} and Carlos Meza",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 13th International Conference of the IMACS TC1 Committee, ELECTRIMACS 2019 ; Conference date: 21-05-2019 Through 23-05-2019",
year = "2020",
doi = "10.1007/978-3-030-37161-6_43",
language = "Ingl{\'e}s",
isbn = "9783030371609",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer",
pages = "567--582",
editor = "Walter Zamboni and Giovanni Petrone",
booktitle = "ELECTRIMACS 2019 - Selected Papers - Volume 1",
}