A Recurrent S_CMAC_GBF Based Estimation for Global Solar Radiation from Environmental Information

In recent years, from Europe to worldwide, installing Photovoltaic (PV) systems become a trend. The installing is not only increasing in larger systems but also in power plants. When the total installation capacity is getting enlarged, the power allocation and scheduling is getting more important. The prediction of the solar radiation is very important to PV system power generation, and PV power generation has effects on the power allocation, scheduling and the stability of the power net. This paper provides an efficient solar radiation prediction model, and it is useful to predict an installed PV system power generation or to evaluate a to-be-installed grid-connected system. The most effective factor of PV system stability is the solar radiation; it affects a PV system's voltage and current. Therefore, base on Recurrent S_CMAC_GBF, this project utilizes the easier measurable meteorological parameters to estimate the solar radiation to accurately calculate PV system's annual power generation. This research applied the information of the sunshine duration, relative humidity and temperature in Taiwan Taipei from 1998 to 2009 to verify the feasibility and accuracy of the developed model.