Short-term fluctuations of solar power output via cloud shadows are one of the factors causing difficulty in predicting the output of solar power generation. In this paper, the short-term fluctuations of solar power output are analyzed using a discrete Fourier transform, short-time Fourier transform, and continuous wavelet transform. Based on the frequency analysis results, the necessity for short-term predictions are presented. It was found that continuous wave conversion is most suitable for the analysis of non-stationary waveforms such as the output of solar power generation. From the scalogram obtained by the continuous wavelet transform of the output power waveform of solar power generation, the frequency band corresponding to the short-term fluctuation was determined. The short-term fluctuation time was calculated by applying envelope processing to the absolute values of the spectral intensity in the frequency band, and it accounted for ~29% of the annual solar power generation time. Therefore, it was clear that approximately 29% of the annual solar power generation time requires a power generation prediction interval as fast as the floating speed of cloud shadows.
In order to maintain the power generation performance of photovoltaic power generation systems, it is common to compare the actual energy yield with the estimated energy yield calculated from the measured solar irradiation in the same location. If there is no on-site measured data of the solar irradiation, it can be estimated from the total global horizontal irradiation measured at 48 JMA sites in Japan. However, in order to use the data which measured at closer points, the sunshine hours measured at 687 AMeDAS sites in addition to JMA sites are also available in Japan. This paper verified the validity of the conversion formula of the hourly integrated sunshine hours into the global horizontal irradiation and updated it with the latest data. Finally, this study propose the model which convert sunshine hours into the global horizontal irradiation: the model can select the optimum coefficient in nationwide and in each solar radiation climatic province which is added in order to maintain simplicity and improve accuracy.
In our previous report, we evaluated the outside air load reduction effect of the natural energy ventilation system by roof thermal collection and earth tube of house located in the city of Fujisawa (Kanagawa Prefecture). In this report, we evaluated the outside air load reduction effect, surveyed the electric power consumption and predicted energy self-sufficiency rate of wooden house located in the city of Kasukabe (Saitama Prefecture). The results the outside air load of this system is about 36 % reduction compared to the case without system. In addition, the annual electric power consumption of the measured house was 6,796 kWh/year, and the energy self-sufficiency rate with the introduction of solar power generation and electricity storage system reached 81.1% at 5 kW of solar power generation. It was expected that energy independence would be possible by reducing the outside air load of this system, optimizing of control conditions for switching, or energy conservation behavior by residents.