응용통계연구 (The Korean Journal of Applied Statistics)

  • 제27권3호
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  • Pages.419-430
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  • 2014
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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시계열모형에 의한 전력판매량 예측

Prediction of Electricity Sales by Time Series Modelling

  • 투고 : 2014.02.10
  • 심사 : 2014.05.20
  • 발행 : 2014.06.30
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초록

전력수급의 정확한 예측은 국민들의 일상적 생활 유지, 산업활동, 그리고 국가경영을 위하여 매우 중요하다. 본 연구에서는 시계열모형화에 의해 전력판매량을 예측한다. 실제 자료분석을 통하여 입력시계열로서 냉난방도일과 개입변수로 펄스함수를 사용한 전이함수모형이 다른 시계열모형에 비해서 제곱근평균제곱오차 및 평균절대오차의 의미에서 더 우수하였다.

An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

키워드

참고문헌

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피인용 문헌

  1. Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods vol.9, pp.9, 2016, https://doi.org/10.3390/en9090727