3D cloud detection and tracking system for solar forecast using multiple sky imagers

Abstract

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. This information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system's ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can (1) robustly detect clouds and track layers, and (2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

A review on the recent progress made on solar photovoltaic in selected countries of sub-Saharan Africa

“…The panels perform at lower power quality depending on climate conditions (e.g. cloud drift [22,23], wind speed [24] etc.). It is also necessary to clean the panel from dust and dirt to ensure that the maximum power could be generated from the panels [25,26].…”

Short-Range Forecasting for Energy

“…For solar radiation, we often use a "smart persistence" where we expect the cloud cover to stay the same, but recognize that the solar angle will change. For solar energy, sky imaging traces cloud conditions in real time, which allows us to use motion vectors derived from image processing succeeding images, or if there is a co-located wind profiler, one can project the cloud motion for (Kleissl 2010;Chu et al 2013;Nguyen and Kleissl 2014;Peng et al 2015). Cloud imager-based forecasts are effective for about 15-30 minutes.…”

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

“…Some sky imager forecasts use a single camera and successive evaluation of cloud location, speed, and projection. Integrated threedimensional (3D) forecast systems have been developed more recently (Peng et al 2015;Oberländer et al 2015).…”