CUED Publications database

A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications

Paletta, Q and Lasenby, J A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications. (Unpublished)

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Abstract

Improving irradiance forecasting is critical to further increase the share of solar in the energy mix. On a short time scale, fish-eye cameras on the ground are used to capture cloud displacements causing the local variability of the electricity production. As most of the solar radiation comes directly from the Sun, current forecasting approaches use its position in the image as a reference to interpret the cloud cover dynamics. However, existing Sun tracking methods rely on external data and a calibration of the camera, which requires access to the device. To address these limitations, this study introduces an image-based Sun tracking algorithm to localise the Sun in the image when it is visible and interpolate its daily trajectory from past observations. We validate the method on a set of sky images collected over a year at SIRTA's lab. Experimental results show that the proposed method provides robust smooth Sun trajectories with a mean absolute error below 1% of the image size.

Item Type: Article
Uncontrolled Keywords: cs.CV cs.CV cs.LG
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 30 Jan 2021 21:03
Last Modified: 03 Jun 2021 05:33
DOI: