Assembled Methods for the Prediction of the Incident GHI over the City of Puno in Sloped Solar Panels
Read ArticleDate of Conference
July 18-22, 2022
Published In
"Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions"
Location of Conference
Boca Raton
Authors
Loayza-Pizarro, Fernando
Nuñez-Medrano, Yuri
Abstract
In this work we apply the Assembled Machine Learning methods for the estimation of the incident GHI on a 30° Sloped Solar Panel, their performances will be compared with the Simple Regression ML methods. The Bagging Ensemble and Extra Trees optimized methods obtained better performances using the evaluation metrics MSE and R2. Due to data limitations, preprocessing was performed to obtain the GHI of the surfaces inclined at 30° in order to use it as a target.