@inproceedings{c16b41975ca84b5ea9fe14818cea3154,
title = "Short-term PV power forecasts based on a real-time irradiance monitoring network",
abstract = "We built an irradiance sensor network that we are now using to make operational, real-time, intra-hour forecasts of solar power at key locations. We developed reliable irradiance sensor hardware platforms to enable these sensor network forecasts. Using 19 of the 55 irradiance sensors we have throughout Tucson, we make retrospective forecasts of 26 days in April and evaluate their performance. We find that that our network forecasts outperform a persistence model for 1 to 28 minute time horizons as measured by the root mean squared error. The sensor hardware, our network forecasting method, error statistics, and future improvements to our forecasts are discussed.",
keywords = "data analysis, forecasting, real-time systems, sensors, solar energy",
author = "Lorenzo, \{Antonio T.\} and Holmgren, \{William F.\} and Michael Leuthold and Kim, \{Chang Ki\} and Cronin, \{Alexander D.\} and Betterton, \{Eric A.\}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 40th IEEE Photovoltaic Specialist Conference, PVSC 2014 ; Conference date: 08-06-2014 Through 13-06-2014",
year = "2014",
month = oct,
day = "15",
doi = "10.1109/PVSC.2014.6925212",
language = "English (US)",
series = "2014 IEEE 40th Photovoltaic Specialist Conference, PVSC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "75--79",
booktitle = "2014 IEEE 40th Photovoltaic Specialist Conference, PVSC 2014",
}