응용통계연구 (The Korean Journal of Applied Statistics)

  • 제30권6호
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  • Pages.1005-1013
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  • 2017
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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기상변수를 활용한 일사량 예측 연구

A study on solar irradiance forecasting with weather variables

  • 김삼용 (응용통계학과, 중앙대학교)
  • Kim, Sahm (Department of Applied Statistics, Chung-Ang University)
  • 투고 : 2017.10.17
  • 심사 : 2017.10.28
  • 발행 : 2017.12.31
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초록

본 연구에서는 태양광 발전량 예측에 필요한 일사량을 예측하기 위해 다양한 기상변수를 활용한 다중회귀, ARIMA, ARIMAX 모형을 사용하여 각 모형의 예측 성능을 비교하고자 한다. 예측에 사용된 변수와 시계열 모형에 대해 소개하고, 실제 일사량 예측에 적용하여 일사량을 예측한 결과 운량, 기온, 습도, 대기권 밖 일사량을 활용한 ARIMAX 모형의 성능이 가장 우수하였다.

In this paper, we investigate the performances of time series models to forecast irradiance that consider weather variables such as temperature, humidity, cloud cover and Global Horizontal Irradiance. We first introduce the time series models and show that regression ARIMAX has the best performance with other models such as ARIMA and multiple regression models.

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참고문헌

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