Abstract
Forecasting solar radiation has recently become the focus of numerous researchers due to the growing interest in green energy. This study aims to develop a seasonal auto-regressive integrated moving average (SARIMA) model to predict the daily and monthly solar radiation in Seoul, South Korea based on the hourly solar radiation data obtained from the Korean Meteorological Administration over 37 years (1981–2017). The goodness of fit of the model was tested against standardized residuals, the autocorrelation function, and the partial autocorrelation function for residuals. Then, model performance was compared with Monte Carlo simulations by using root mean square errors and coefficient of determination (R2) for evaluation. In addition, forecasting was conducted by using the best models with historical data on average monthly and daily solar radiation. The contributions of this study can be summarized as follows: (i) a time series SARIMA model is implemented to forecast the daily and monthly solar radiation of Seoul, South Korea in consideration of the accuracy, suitability, adequacy, and timeliness of the collected data; (ii) the reliability, accuracy, suitability, and performance of the model are investigated relative to those of established tests, standardized residual, autocorrelation function (ACF), and partial autocorrelation function (PACF), and the results are compared with those forecasted by the Monte Carlo method; and (iii) the trend of monthly solar radiation in Seoul for the coming years is analyzed and compared on the basis of the solar radiation data obtained from KMS over 37 years. The results indicate that (1,1,2) the ARIMA model can be used to represent daily solar radiation, while the seasonal ARIMA (4,1,1) of 12 lags for both auto-regressive and moving average parts can be used to represent monthly solar radiation. According to the findings, the expected average monthly solar radiation ranges from 176 to 377 Wh/m2.
Highlights
Symmetry 2019, 11, 240 the Korean government to achieve the vision of sustainable development and energy security as well as follow policies that combine energy, environment, economy, and society in aspect of solar energy are abundant available in South Korea [3]
This study aims to build a time series auto-regressive integrated moving average (ARIMA) model to forecast daily and monthly solar radiation in Seoul, South Korea, based on the hourly solar radiation data obtained from the Korean
A solar radiation forecasting method, whichwhich needsneeds to be as as possible, possible, is needed to help policy makers frame strong policies, by understanding the is needed to help policy makers frame strong policies, by understanding the overall overall perspective of solar radiation in consideration of the strength, weakness, opportunities, and perspective of solar radiation in consideration of the strength, weakness, opportunities, and challenges challenges associated with the predictions
Summary
Renewable energy is considered as one of the most promising solutions to achieve sustainable development and energy security. Renewable natural resources such as solar radiation that enable. Symmetry 2019, 11, 240 the Korean government to achieve the vision of sustainable development and energy security as well as follow policies that combine energy, environment, economy, and society in aspect of solar energy are abundant available in South Korea [3]. The Korean government has sought to diversify its energy sources by increasing the dependence on renewable energy sources to enhance energy security and protect the environment [4,5]. The strategic vision of the energy sector in South Korea aims to increase the contribution of renewable energy to the total generated power. Solar energy will increase in particular to 14.2% of total energy production by 2035 [6]
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