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Open AccessArticle

Solar Panel Tilt Angle Optimization Using Machine Learning Model: A Case Study of Daegu City, South Korea

Graduate School of Information, Yonsei University, Seoul 03722, Korea
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Energies 2020, 13(3), 529; https://doi.org/10.3390/en13030529
Received: 26 December 2019 / Revised: 13 January 2020 / Accepted: 15 January 2020 / Published: 21 January 2020
(This article belongs to the Section Solar Energy and Photovoltaic Systems)
Finding optimal panel tilt angle of photovoltaic system is an important matter as it would convert the amount of sunlight received into energy efficiently. Numbers of studies used various research methods to find tilt angle that maximizes the amount of radiation received by the solar panel. However, recent studies have found that conversion efficiency is not solely dependent on the amount of radiation received. In this study, we propose a solar panel tilt angle optimization model using machine learning algorithms. Rather than trying to maximize the received radiation, the objective is to find tilt angle that maximizes the converted energy of photovoltaic (PV) systems. Considering various factors such as weather, dust level, and aerosol level, five forecasting models were constructed using linear regression (LR), least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine (SVM), and gradient boosting (GB). Using the best forecasting model, our model showed increase in PV output compared with optimal angle models. View Full-Text
Keywords: solar panel; machine learning; solar irradiance solar panel; machine learning; solar irradiance
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Kim, G.Y.; Han, D.S.; Lee, Z. Solar Panel Tilt Angle Optimization Using Machine Learning Model: A Case Study of Daegu City, South Korea. Energies 2020, 13, 529.

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