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Dr. Walter Richardson
Department of Mathematics, College of Sciences, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA

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Research Keywords & Expertise

0 Smart Grid
0 EDGE COMPUTING
0 SOLAR FORECASTING
0 Internet-of-Things
0 All-sky imaging

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Journal article
Published: 17 February 2019 in Applied Sciences
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Increasing photovoltaic (PV) generation in the world’s power grid necessitates accurate solar irradiance forecasts to ensure grid stability and reliability. The University of Texas at San Antonio (UTSA) SkyImager was designed as a low cost, edge computing, all-sky imager that provides intra-hour irradiance forecasts. The SkyImager utilizes a single board computer and high-resolution camera with a fisheye lens housed in an all-weather enclosure. General Purpose IO pins allow external sensors to be connected, a unique aspect is the use of only open source software. Code for the SkyImager is written in Python and calls libraries such as OpenCV, Scikit-Learn, SQLite, and Mosquito. The SkyImager was first deployed in 2015 at the National Renewable Energy Laboratory (NREL) as part of the DOE INTEGRATE project. This effort aggregated renewable resources and loads into microgrids which were then controlled by an Energy Management System using the OpenFMB Reference Architecture. In 2016 a second SkyImager was installed at the CPS Energy microgrid at Joint Base San Antonio. As part of a collaborative effort between CPS Energy, UT San Antonio, ENDESA, and Universidad de La Laguna, two SkyImagers have also been deployed in the Canary Islands that utilize stereoscopic images to determine cloud heights. Deployments at three geographically diverse locations not only provided large amounts of image data, but also operational experience under very different climatic conditions. This resulted in improvements/additions to the original design: weatherproofing techniques, environmental sensors, maintenance schedules, optimal deployment locations, OpenFMB protocols, and offloading data to the cloud. Originally, optical flow followed by ray-tracing was used to predict cumulus cloud shadows. The latter problem is ill-posed and was replaced by a machine learning strategy with impressive results. R2 values for the multi-layer perceptron of 0.95 for 5 moderately cloudy days and 1.00 for 5 clear sky days validate using images to determine irradiance. The SkyImager in a distributed environment with cloud-computing will be an integral part of the command and control for today’s SmartGrid and Internet of Things.

ACS Style

Walter Richardson; David Cañadillas; Ariana Moncada; Ricardo Guerrero-Lemus; Les Shephard; Rolando Vega-Avila; Hariharan Krishnaswami. Validation of All-Sky Imager Technology and Solar Irradiance Forecasting at Three Locations: NREL, San Antonio, Texas, and the Canary Islands, Spain. Applied Sciences 2019, 9, 684 .

AMA Style

Walter Richardson, David Cañadillas, Ariana Moncada, Ricardo Guerrero-Lemus, Les Shephard, Rolando Vega-Avila, Hariharan Krishnaswami. Validation of All-Sky Imager Technology and Solar Irradiance Forecasting at Three Locations: NREL, San Antonio, Texas, and the Canary Islands, Spain. Applied Sciences. 2019; 9 (4):684.

Chicago/Turabian Style

Walter Richardson; David Cañadillas; Ariana Moncada; Ricardo Guerrero-Lemus; Les Shephard; Rolando Vega-Avila; Hariharan Krishnaswami. 2019. "Validation of All-Sky Imager Technology and Solar Irradiance Forecasting at Three Locations: NREL, San Antonio, Texas, and the Canary Islands, Spain." Applied Sciences 9, no. 4: 684.

Journal article
Published: 23 March 2017 in Sustainability
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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.

ACS Style

Walter Richardson; Hariharan Krishnaswami; Rolando Vega; Michael Cervantes. A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting. Sustainability 2017, 9, 482 .

AMA Style

Walter Richardson, Hariharan Krishnaswami, Rolando Vega, Michael Cervantes. A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting. Sustainability. 2017; 9 (4):482.

Chicago/Turabian Style

Walter Richardson; Hariharan Krishnaswami; Rolando Vega; Michael Cervantes. 2017. "A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting." Sustainability 9, no. 4: 482.