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http://dx.doi.org/10.5351/KJAS.2018.31.6.785

Solar radiation forecasting by time series models  

Suh, Yu Min (Department of Applied Statistics, Chung-Ang University)
Son, Heung-goo (Korea Power Exchange)
Kim, Sahm (Department of Applied Statistics, Chung-Ang University)
Publication Information
The Korean Journal of Applied Statistics / v.31, no.6, 2018 , pp. 785-799 More about this Journal
Abstract
With the development of renewable energy sector, the importance of solar energy is continuously increasing. Solar radiation forecasting is essential to accurately solar power generation forecasting. In this paper, we used time series models (ARIMA, ARIMAX, seasonal ARIMA, seasonal ARIMAX, ARIMA GARCH, ARIMAX-GARCH, seasonal ARIMA-GARCH, seasonal ARIMAX-GARCH). We compared the performance of the models using mean absolute error and root mean square error. According to the performance of the models without exogenous variables, the Seasonal ARIMA-GARCH model showed better performance model considering the problem of heteroscedasticity. However, when the exogenous variables were considered, the ARIMAX model showed the best forecasting accuracy.
Keywords
ARIMA; ARIMAX; seasonal ARIMA; seasonal AIRMAX GARCH; weather variables; solar radiation;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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