Estimating solar irradiance on tilted surface with arbitrary orientations and tilt angles

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

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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.

Original languageEnglish
Article number1427
JournalEnergies
Volume12
Issue number8
DOIs
StatePublished - 13 Apr 2019

Keywords

  • Artificial neural networks
  • Inclined solar irradiance
  • Photovoltaics

Fingerprint

Dive into the research topics of 'Estimating solar irradiance on tilted surface with arbitrary orientations and tilt angles'. Together they form a unique fingerprint.

Cite this