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In recent years, reduction of greenhouse gas emissions has been a serious issue throughout the world. The Japanese Government aims to reduce 25% of the emissions in 1990 by 2020. Eco-cities which effectively use renewable energy sources attract an attention in order to attain this goal. A smart energy town project in Honjyo, Japan has been conducted by making use of renewable energy sources. Above all, photovoltaic (PV) generators are expected to play a key role in this project. In addition, PV generators are expected to be installed in the residential and commercial areas due to ease of its installation. However, unstable power output from PV generation causes negative impacts on power quality of distribution networks. Therefore, prediction of PV output is indispensable to operate networks properly. In this paper, we propose a method to predict a day-ahead solar radiation and output power of PV generation in specific areas. Furthermore, the predicted solar radiation is corrected using the on-line measured actual data. As a result, the correction of a day-ahead prediction proposed here reduces errors of daily solar radiation by around 34% .

Connective Day-Ahead Prediction of Solar Radiation based on Online Measurements