Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

Abstract

A method for intra-hour, sub-kilometer cloud forecasting and irradiance nowcasting using a groundbased sky imager at the University of California, San Diego is presented. Sky images taken every 30 seconds were processed to determine sky cover using a clear sky library and sunshine parameter. From a two-dimensional cloud map generated from coordinate-transformed sky cover, cloud shadows at the surface were estimated. Limited validation on four partly cloudy days showed that (binary) cloud conditions were correctly nowcast 70% of the time for a network of six pyranometer ground stations spread out over an area of 2 km 2. Cloud motion vectors were generated by cross-correlating two consecutive sky images. Cloud locations up to five minutes ahead were forecasted by advection of the two-dimensional cloud map. Cloud forecast error increased with increasing forecast horizon due to high cloud cover variability over the coastal site.

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

“…2, 3b, c for illustrations of these angles), and changes in aerosol properties. This lead to the development of clear-sky libraries (CSL) (Shields et al, 1993;Chow et al, 2011) to express clearsky RBR values under any condition. CSL are constructed by binning pixel values from clear-sky images into matrices as a function of θ 0 (Fig.…”

“…RBR successfully differentiates clear sky from thin clouds and to a more limited extent thick clouds, but the RBR has not been applied to differentiate τ c . It is also difficult to apply the RBR method in the circumsolar region as thick dark clouds have lower RBRs than clear sky (Chow et al, 2011). In fact we will demonstrate in this paper through radiative transfer modeling (Sect.…”

“…Physics-based solar forecasting using whole-sky imagery requires geolocating clouds in the sky images, estimating their optical depth, motion, and dynamics (Chow et al, 2011). To estimate a cloud's optical depth (τ c ), the most advanced methods separate the image into clear sky, thin cloud, and thick cloud and assign a τ c to each of these groups.…”

“…To estimate a cloud's optical depth (τ c ), the most advanced methods separate the image into clear sky, thin cloud, and thick cloud and assign a τ c to each of these groups. To distinguish thin and thick clouds, the red-blue ratio (RBR) (or a function of RBR) has been used as the default method (Koehler et al, 1991;Shields et al, 1993;Chow et al, 2011;Ghonima et al, 2012;Roy et al, 2001). It is defined as the ratio of the signal from the red channel to the signal from the blue channel.…”

Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks

“…Physical models use spatial equations for wind speed at the locations of each turbine, and then predict wind power with theoretical or measured power curves [10]. Statistical models aggregate measured or forecasted meteorological variables and develop a relationship between the variables and the output power.…”