Abstract—Forecasting of the solar irradiance and load demand are essential for system level control and components coordination in the supervisory controller of an off-grid hybrid energy system. This paper presents the analysis of the predictions for solar irradiance and load demand using two different Single Exponential Smoothing forecasting approaches. Both approaches perform prediction based on hourly basis. The first approach uses the current day data while the other uses the previous day data. Comparison between the two approaches is carried out, and the forecast results show that the Single Exponential Smoothing forecast models utilizing the previous day data achieved higher accuracy as compared to the one using the previous hour data.
Index Terms—Prediction model, single exponential smoothing, renewable energy.
The authors are with the Department of Electrical and Computer Engineering Curtin University Australia (e-mail:peiyi.lim@postgrad.curtin.edu.au, c.v.nayar@curtin.edu.au).
Cite: P. Y. Lim and C. V. Nayar, "Solar Irradiance and Load Demand Forecasting based on Single Exponential Smoothing Method," International Journal of Engineering and Technology vol. 4, no. 4, pp. 451-455, 2012.
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