@inproceedings{aed7819f2c3149bebcfde87f1dc41be3,
title = "Comparing and integrating solar forecasting techniques",
abstract = "The SunCast Solar Power Forecasting System is comprised of various models to predict the short term solar resource from 15 min through 168 hours. It leverages surface and satellite observations in building both physically-based as well as artificial intelligence nowcasting models. It also employs numerical weather prediction models, including an enhanced version of the Weather Research and Forecasting model, WRF-Solar. This paper compares the various techniques and describes how they are integrated to provide a seamless probabilistic power forecast.",
author = "Haupt, \{Sue Ellen\} and Branko Kosovic and Tara Jensen and James Cowie and Pedro Jimenez and Gerry Wiener",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 44th IEEE Photovoltaic Specialist Conference, PVSC 2017 ; Conference date: 25-06-2017 Through 30-06-2017",
year = "2017",
doi = "10.1109/PVSC.2017.8366162",
language = "English",
series = "2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2368--2371",
booktitle = "2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017",
address = "United States",
}