Sun-tracking imaging system for intra-hour DNI forecasts

Yinghao Chu, Mengying Li, Carlos F.M. Coimbra

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)

Abstract

A Sun-tracking imaging system is implemented for minimizing circumsolar image distortion for improved short-term solar irradiance forecasts. This sky-imaging system consists of a fisheye digital camera mounted on an automatic solar tracker that follows the diurnal pattern of the Sun. The Sun is located at the geometric center of the sky images where the fisheye distortion is minimized. Images from this new system provide more information about the circumsolar sky cover, which provides critical information for intra-hour solar forecasts, particularly for direct normal irradiance. An automatic masking algorithm has been developed to separate the sky area from ground obstacles and the image edges for each image that is collected. Then numerical image features are extracted from the segmented sky area and are used as exogenous inputs to MultiLayer Perceptron (MLP) models for direct normal irradiance forecasts. Sixty-seven days of irradiance and image measurements are used to train, optimize, and assess the MLP-based forecast models for solar irradiance. The results show that the MLP forecasts based on the newly proposed sky-imaging system significantly outperform the reference models in terms of statistical metrics and forecast skill, particularly for shorter horizons, achieving forecast skills 18%-50% higher than the skills of a reference MLP-based model that is based on a zenith-pointed, stationary sky-imaging system.

Original languageEnglish
Pages (from-to)792-799
Number of pages8
JournalRenewable Energy
Volume96
DOIs
Publication statusPublished - 1 Oct 2016

Keywords

  • Sky imaging
  • Solar forecasting
  • Stochastic learning
  • Sun-tracking

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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