PV power output mainly depends on solar irradiance, which is affected by various meteorological factors. Thus, it is required to predict solar irradiance in the future for the efficient operation of PV systems. In this paper we develop a novel approach for solar irradiance forecasting, in which we combine the black-box model (JIT modeling) with the physical model (GPV data). We investigate the predictive accuracy of solar irradiance over a wide controlled area of each electric power company by utilizing measured data from 44 observation points throughout Japan provided by JMA and 64 points around Kanto provided by NEDO. Finally, we propose an applied forecasting method of solar irradiance to deal with difficulties in compiling databases. We also consider the influence of different GPV default times on solar irradiance prediction.We use MSM-GPV data as the input data for JIT modeling. MSM-GPV [12, 13] is a meteorological numerical forecast model based on a physical model. It is calculated in intervals of 3 hours, and consists of hourly physical predicted values such as air pressure, temperature, cloudiness, and so on for 33 hours in advance at each node of a 5-km grid throughout Japan. We then perform prediction of the hourly integrated next-day solar irradiance by using the MSM-GPV calculated at midnight (00:00). We also per-
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