Simulation Dataset of Partial Shading and Fault of a Photovoltaic Module

Published: 17 August 2022| Version 1 | DOI: 10.17632/3fr92f4xy9.1


Micro-autonomous or remotely controlled drones are getting popular for search and rescue missions during natural or human-made disasters. A photovoltaic-based power source is ideal for prolonging the flight time and multi-role ability of the drone. However, during various lighting conditions and adverse operating conditions, the PV panels' performance can deteriorate and adversely affect micro-autonomous performance. Hence, a dataset for 10 GaAs/Ge Single Junction PV cells by Spectrolab is presented. The dataset is generated using python and LTSpice at various temperatures, configurations, lighting conditions, and open/short circuit faults. For modeling PV cells, 2-diode based equivalent circuit model is used. The dataset is generated using LTSpice and Python.



California State University Fullerton


Photovoltaics, Machine Learning, Spice, Energy Conversion