A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

Abstract

This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the 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 show that, they are in accordance with the actual data.