ARIMA와 SARIMA 시계열 분석기법을 이용한 대전지역 초단시간 일사량 선행예보모델 구축
Development of Short-term Solar Irradiance Forecasting Model Using ARIMA and Seasonal ARIMA in Daejeon
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초록
Solar irradiance is a major meteorological factor affecting solar energy generation. In this study, we develop a short-term solar irradiance forecasting model with a high time resolution to accurately predict the amount of solar energy generated and apply it to the real-time energy trade market. Two types of irradiance (Global Horizontal Irradiance and Direct Normal Irradiance) data observed at Daejeon, South Korea, are predicted using two time series analysis models (the ARIMA model, which does not consider seasonality, and SARIMA model which considers seasonality), which we compared to determine the model that is better suited to performing predictions. Comparing the prediction errors from 15 to 120 minutes, using RMSE and nRMSE as evaluation indices, GHI was better predicted using the ARIMA model from 15 to 75 minutes, while the SARIMA model performed better from 90 to 120 minutes. For DNI, the ARIMA model showed higher accuracy than the SARIMA model during the entire prediction period.
Abstract
Solar irradiance is a major meteorological factor affecting solar energy generation. In this study, we develop a short-term solar irradiance forecasting model with a high time resolution to accurately predict the amount of solar energy generated and apply it to the real-time energy trade market. Two types of irradiance (Global Horizontal Irradiance and Direct Normal Irradiance) data observed at Daejeon, South Korea, are predicted using two time series analysis models (the ARIMA model, which does not consider seasonality, and SARIMA model which considers seasonality), which we compared to determine the model that is better suited to performing predictions. Comparing the prediction errors from 15 to 120 minutes, using RMSE and nRMSE as evaluation indices, GHI was better predicted using the ARIMA model from 15 to 75 minutes, while the SARIMA model performed better from 90 to 120 minutes. For DNI, the ARIMA model showed higher accuracy than the SARIMA model during the entire prediction period.
참고문헌 (7)
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