Spice Simulated Solar Panel Dataset for Machine Learning Applications
Description
The dataset is generated using LTSpice, where a Photovoltaics (PV) module consisting of 10 PV cells is connected in various electrical configurations and shading conditions. Due to the size of the dataset, it is ideal for training students and researchers to perform regression and classification tasks, such as predicting power output or categorizing shading levels. Due to its compact size, for educational purposes, no specialized GPU or cloud computing space is required for training students.
Files
Steps to reproduce
The dataset can be reproduced using the PV cells model provided in [1]. The electrical characteristics can be analyzed and modeled by configuring the PV cells in various series and parallel combinations and operating them under different temperatures. Reference: [1] L. Castañer and S. Silvestre, "Electrical Characteristics of the Solar Cell," in Modelling Photovoltaic Systems Using PSpice®, John Wiley & Sons, Ltd, pp. 41-75, 2006.