TY  - JOUR
T1  - Hourly Day Ahead Solar Irradiance Forecasting Model in LabVIEW Using Cloud Cover Data
AU  - Ceylan, Oğuzhan
AU  - Starke, Michael
AU  - Irminger, Phil
AU  - Ollis, Ben
AU  - King, Dan
AU  - Tomsovic, Kevin
PY  - 2016
DA  - September
JF  - IU-Journal of Electrical & Electronics Engineering
PB  - İstanbul University-Cerrahpasa
WT  - DergiPark
SN  - 1303-0914
SP  - 2047
EP  - 2054
VL  - 16
IS  - 2
LA  - en
AB  - This paper applies a regression based numerical method for hourly forecasting photovoltaic power output. This methodology uses a historical dataset composed of irradiance, azimuth, zenith angle and time of day information. A developed forecast program from this methodology pulls publicly available cloud cover forecast data for the following day and uses a numerical regression based method for fitting the data. Using publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results are compared to actual collected data.
KW  - solar forecasting
KW  - numerical regression
KW  - LabVIEW
UR  - https://dergipark.org.tr/en/pub/iujeee/issue//259642
L1  - https://dergipark.org.tr/en/download/article-file/226119
ER  -