4.6 Article

Shadow camera system for the generation of solar irradiance maps

Journal

SOLAR ENERGY
Volume 157, Issue -, Pages 157-170

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2017.05.074

Keywords

Shadow camera system; Solar forecasting; Integration of renewable energies

Categories

Funding

  1. European Union's Horizon programme [654984]
  2. European Union's FP7 programme [608623]

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Highly spatially and temporally resolved solar irradiance maps are of special interest for predicting ramp rates and for optimizing operations in solar power plants. Irradiance maps with lead times between 0 and up to 30 min can be generated using all-sky imager based nowcasting systems or with shadow camera systems. Shadow cameras provide photos of the ground taken from an elevated position below the clouds. In this publication, we present a shadow camera system, which provides spatially resolved Direct Normal Irradiance (DNI), Global Horizontal Irradiance (GHI) and Global Tilted Irradiance (GTI) maps. To the best of our knowledge, this is the first time a shadow camera system is achieved. Its generated irradiance maps have two purposes: (1) The shadow camera system is already used to derive spatial averages to benchmark all-sky imager based nowcasting systems. (2) Shadow camera systems can potentially provide spatial irradiance maps for plant operations and may act as nowcasting systems. The presented shadow camera system consists of six cameras taking photos from the top of an 87 m tower and is located at the Plataforma Solar de Almeria in southern Spain. Out of six photos, an orthonormalized image (orthoimage) is calculated. The orthoimage under evaluation is compared with two reference orthoimages. Out of the three orthoimages and one additional pyranometer and pyrheliometer, spatially resolved irradiance maps (DNI, GHI, GTI) are derived. In contrast to satellites, the shadow camera system uses shadows to obtain irradiance maps and achieves higher spatial and temporal resolutions. The preliminary validation of the shadow camera system, conducted in detail on two example days (2015-09-18, 2015-09-19) with 911 one-minute averages, shows deviations between 4.2% and 16.7% root mean squared errors (RMSE), 1.6% and 7.5% mean absolute errors (MAE) and standard deviations between 4.2% and 15.4% for DNI maps calculated with the derived approach. The GHI maps show deviations below 10% RMSE, between 2.1% and 7.1% MAE and standard deviations between 3.2% and 7.9%. Three more days (2016-05-11, 2016-09-01, 2016-12-09) are evaluated, briefly presented and show similar deviations. These deviations are similar or below all-sky imager based nowcasts for lead time zero minutes. The deviations are small for photometrically uncalibrated, low-cost and off-the-shelf surveillance cameras, which is achieved by a segmentation approach. (C) 2017 The Author(s). Published by Elsevier Ltd.

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