Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Electricity forecasting model using specific time zone

특정 시간대 전력수요예측 시계열모형

  • Shin, YiRe (Wise institute, Hankuk University of Foreign Studies) ;
  • Yoon, Sanghoo (Department of Computer Science and Statistics, Daegu University)
  • 신이레 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 윤상후 (대구대학교 전산통계학과)
  • Received : 2016.02.25
  • Accepted : 2016.03.25
  • Published : 2016.03.31
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Abstract

Accurate electricity demand forecasts is essential in reducing energy spend and preventing imbalance of the power supply. In forcasting electricity demand, we considered double seasonal Holt-Winters model and TBATS model with sliding window. We selected a specific time zone as the reference line of daily electric demand because it is least likely to be influenced by external factors. The forecasting performance have been evaluated in terms of RMSE and MAPE criteria. We used the observations ranging January 4, 2009 to December 31 for testing data. For validation data, the records has been used between January 1, 2012 and December 29, 2012.

정확한 전력수요 예측은 에너지 소비를 줄이고 전력수급의 불균형을 방지한다. 본 연구는 외부요인의 영향을 가장 적게 받는 특정 시간대의 일 단위 전력 수요량을 참조선 (reference line)으로 한 시계열모형을 세우고자 한다. 고려된 시계열모형은 슬라이딩 창을 이용한 이중 계절성 Holt-Winters 모형과 TBATS 모형이다. 시계열모형의 모수는 2009년 1월 4일부터 2011년 12월 31일까지 자료를 이용하여 추정되었으며, 2012년 1월 1일부터 2012년 12월 29일까지의 각 모형의 전력수요량을 예측하여 성능을 비교하였다. RMSE와 MAPE를 통해 예측 성능을 비교한 결과 TBATS 모형의 성능이 우수하였다.

Keywords

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