Estimating Solar Irradiance on Tilted Surface with Arbitrary Orientations and Tilt Angles

Author:

Cheng Hsu-Yung,Yu Chih-Chang,Hsu Kuo-Chang,Chan Chi-Chang,Tseng Mei-Hui,Lin Chih-Lung

Abstract

Photovoltaics modules are usually installed with a tilt angle to improve performance and to avoid water or dust accumulation. However, measured irradiance data on inclined surfaces are rarely available, since installing pyranometers with various tilt angles induces high costs. Estimating inclined irradiance of arbitrary orientations and tilt angles is important because the installation orientations and tilt angles might be different at different sites. The goal of this work is to propose a unified transfer model to obtain inclined solar irradiance of arbitrary tilt angles and orientations. Artificial neural networks (ANN) were utilized to construct the transfer model to estimate the differences between the horizontal irradiance and the inclined irradiance. Compared to ANNs that estimate the inclined irradiance directly, the experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy. Moreover, the trained model can successfully estimate inclined irradiance with tilt angles and orientations not included in the training data.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)

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