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In order to predict Solar Power with a lead time of 30 min, a network of pairs of hemispheric sky-cameras are installed in the vicinity of Solar PV installations. Images are collected every 30s. Then corrected for orientation and geometric distortion. Triangulation of cloud edges as seen from the two cameras in each pair gives cloud heights limited to two distinct cloud layers. Tracking of cloud edges in successive images gives wind speed and direction in those two cloud layers and from that the ability to predict what areas will be shaded in the near term future.
The code is written in python and requires at least version 3.5. It requires the following packages which were installed with the anaconda3 package manager conda .
Plan to put these into a package install script
Separation of Privileges
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- groupadd nowcast useradd nowcast
Set up developer (with github id) with sudo privileges to run commands as user nowcast.
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- umask 002 sudo -u nowcast mkdir -p ~nowcast/code sudo chmod g+ws ~nowcast/code cd ~nowcast/code git clone https://github.com/BNL-NowCasting/SolarForecasting # or if git already setup, to get latest updates git pull
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- cd ~nowcast/run cp ~nowcast/code/SolarForecasting/downloader/image_downloader.conf.dist image_downloader_{SITE-CODE}.conf
Edit conf file to update directory paths. Make sure destination directories (cachepath, latest, imagepath, and logpath, etc., see :doc:`DataTree`) in conf file are writable by user nowcast.
image_downloader.py