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Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

Recently, for the purpose of utilizing renewable energy in a community, interactive electricity power networks, such as smart grid, have received much attention. In those electricity power networks, the technologies for maintain the balance of electricity demand and supply in a limited area become more important. Installing photovoltaic system can be effective for supplying electricity in a limited area at the peak load time, but PV output depends on weather conditions. Thus we propose to combine PV power generation with demand response program. We simulate interchange PV power with demand response program in a residential community. Some numerical results, which demonstrate the validity of the proposed method, will be presented.