TY - GEN
T1 - An open source solar power forecasting tool using PVLIB-Python
AU - Holmgren, William F.
AU - Groenendyk, Derek G.
N1 - Funding Information:
The authors gratefully acknowledge Sandia National Laboratories for the initial development of PVLIB-MATLAB and PVLIB-Python and the ongoing contributions of many others to the project. A list of PVLIB-Python contributors may be found on the GitHub repository [10] and in the online documentation [14]. The authors also gratefully acknowledge Unidata, the Siphon developers, and the NCEP, NWS, and other NOAA personnel that create, develop, and provide access to the weather models discussed above. WFH thanks the Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Postdoctoral Research Award for support.
Publisher Copyright:
© 2017 IEEE.
PY - 2017
Y1 - 2017
N2 - We describe an open-source PV power forecasting tool based on the PVLIB-Python library. The tool allows users to easily retrieve standardized weather forecast data relevant to PV power modeling from NOAA/NCEP/NWS models including the GFS, NAM, RAP, HRRR, and the NDFD. A PV power forecast can then be obtained using the weather data as inputs to the comprehensive modeling capabilities of PVLIB-Python. Standardized, open source, reference implementations of forecast methods using publicly available data may help advance the state-of-the-art of solar power forecasting.
AB - We describe an open-source PV power forecasting tool based on the PVLIB-Python library. The tool allows users to easily retrieve standardized weather forecast data relevant to PV power modeling from NOAA/NCEP/NWS models including the GFS, NAM, RAP, HRRR, and the NDFD. A PV power forecast can then be obtained using the weather data as inputs to the comprehensive modeling capabilities of PVLIB-Python. Standardized, open source, reference implementations of forecast methods using publicly available data may help advance the state-of-the-art of solar power forecasting.
KW - Forecasting
KW - Performance modeling
KW - PV modeling
KW - Software
UR - http://www.scopus.com/inward/record.url?scp=85048480035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048480035&partnerID=8YFLogxK
U2 - 10.1109/PVSC.2017.8366167
DO - 10.1109/PVSC.2017.8366167
M3 - Conference contribution
AN - SCOPUS:85048480035
T3 - 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
SP - 1777
EP - 1780
BT - 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE Photovoltaic Specialist Conference, PVSC 2017
Y2 - 25 June 2017 through 30 June 2017
ER -