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Sustainability 2017, 9(4), 482; doi:10.3390/su9040482

A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting

1
Department of Mathematics, University of Texas at San Antonio, San Antonio, TX 78249, USA
2
Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA
3
CPS Energy, San Antonio, TX, 78205, USA
4
Merrick & Company, San Antonio, TX 78258, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Tomonobu Senjyu
Received: 31 December 2016 / Revised: 15 March 2017 / Accepted: 17 March 2017 / Published: 23 March 2017
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
View Full-Text   |   Download PDF [4087 KB, uploaded 23 March 2017]   |  

Abstract

With increasing use of photovoltaic (PV) power generation by utilities and their residential customers, the need for accurate intra-hour and day-ahead solar irradiance forecasting has become critical. This paper details the development of a low cost all-sky imaging system and an intra-hour cloud motion prediction methodology that produces minutes-ahead irradiance forecasts. The SkyImager is designed around a Raspberry Pi single board computer (SBC) with a fully programmable, high resolution Pi Camera, housed in a durable all-weather enclosure. Our software is written in Python 2.7 and utilizes the open source computer vision package OpenCV. The SkyImager can be configured for different operational environments and network designs, from a standalone edge computing model to a fully integrated node in a distributed, cloud-computing based micro-grid. Preliminary results are presented using the imager on site at the National Renewable Energy Laboratory (NREL) in Golden, CO, USA during the fall of 2015 under a variety of cloud conditions. View Full-Text
Keywords: solar forecasting; global horizontal irradiance; single board computer; optical flow; cloud motion vectors; ray tracing; micro-grid solar forecasting; global horizontal irradiance; single board computer; optical flow; cloud motion vectors; ray tracing; micro-grid
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Richardson, W.; Krishnaswami, H.; Vega, R.; Cervantes, M. A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting. Sustainability 2017, 9, 482.

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