Development of Short-term Solar Irradiance Forecasting Model Using ARIMA and Seasonal ARIMA in Daejeon

DongHee Kim; YooJung Kim; ChangKi Kim; HyunGoo Kim; YungSeop Lee

doi:10.7836/kses.2022.42.6.105

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2022 Vol.42, Issue 6 Preview Page Next Page

Research Article

Development of Short-term Solar Irradiance Forecasting Model Using ARIMA and Seasonal ARIMA in Daejeon ARIMA와 SARIMA 시계열 분석기법을 이용한 대전지역 초단시간 일사량 선행예보모델 구축

30 December 2022. pp. 105-114

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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.

Keywords

Solar irradiance

Time series analysis

Auto-regressive integrated moving average

Seasonal ARIMA

Short-term solar irradiance forecasting

키워드

일사량

시계열 분석

ARIMA

SARIMA

초단시간 일사량 예보

References

The Center of New & Renewable Energy in Korea Energy Agency, Renewable Energy Supply Statistics in 2020, 2022. https://www.knrec.or.kr/biz/pds/statistic/view.do?no=120. last accessed on the 1^st September 2022.

Suh, Y. -M., Son, H., and Kim, S., Solar Radiation Forecasting by Time Series Models, The Korean Journal of Applied Statistics, Vol. 31, No. 6, pp. 785-799, 2018, https://doi.org/10.5351/KJAS.2018.31.6.785. 10.5351/KJAS.2018.31.6.785

Kim, S., A Study on Solar Irradiance Forecasting with Weather Variables, The Korean Journal of Applied Statistics, Vol. 30, No. 6, pp. 1005-1013, 2017, https://doi.org/10.5351/KJAS.2017.30.6.1005. 10.5351/KJAS.2017.30.6.1005

El Alani, O., Abraim, M., Ghennioui, H., Ghennioui, A., Ikenbi, I., and Dahr, F. E., Short Term Solar Irradiance Forecasting Using Sky Images based on a Hybrid CNN-MLP Model, Energy Reports, Vol. 7, pp. 888-900. 2021, https://doi.org/10.1016/j.egyr.2021.07.053. 10.1016/j.egyr.2021.07.053

Lee, D. -H., Jung, A. -H., Kim, J. -Y., Kim, C. -K., Kim., H. -G., and Lee, Y. -S., Solar Power Generation Forecast Model Using Seasonal ARIMA, Journal of The Korean Solar Energy Society, Vol. 39, No. 3, pp. 59-66, 2019, https://doi.org/10.7836/kses.2019.39.3.059. 10.7836/kses.2019.39.3.059

Jung, A. -H., Lee, D. -H., Kim, J. -Y., Kim, C. -K., Kim, H. -G., and Lee, Y. -S., Regional Photovoltaic Power Forecasting Using Vector Autoregression Model in South Korea, Energies, Vol. 15, No. 21, 7853, 2022, https://doi.org/10.3390/en15217853. 10.3390/en15217853

Cavanaugh, J. E., Unifying the Derivations for the Akaike and Corrected Akaike Information Criteria, Statistics & Probability Letters, Vol. 33, No. 2, pp. 201-208, 1997, https://doi.org/10.1016/S0167-7152(96)00128-9. 10.1016/S0167-7152(96)00128-9

Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 42
No :6
Pages :105-114
Received Date : 2022-09-19
Revised Date : 2022-10-14
Accepted Date : 2022-11-10
DOI :https://doi.org/10.7836/kses.2022.42.6.105

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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