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Temperature Effects on the Industrial Electricity Usage

산업별 전력수요의 기온효과 분석

  • 김인무 (성균관대학교 경제학부) ;
  • 이용주 (영남대학교 경제금융학부) ;
  • 이성로 (한국가스공사 경영연구소) ;
  • 김대용 (한국개발연구원(KDI) 국제개발협력센터 자문협력팀)
  • Received : 2016.02.15
  • Accepted : 2016.06.15
  • Published : 2016.06.30

Abstract

This paper, using AMR (Automatic Meter Reading) electricity data accurately measured in real time, analyses the characteristics and patterns of temperature effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated temperature response function and the temperature effect, we categorize the whole industry into two groups: one group with sharp temperature effect and the other with weak temperature effect. Furthermore, the industry group with sharp temperature effect is classified into a summer peak industry group and a winter peak industry group, based on the estimates of the temperature response function. These empirical results carry practical policy implications on the real time electricity demand management.

본 논문은 실시간으로 측정되는 자동원격검침(AMR) 전력수요량을 사용하여 산업별 전력수요의 기온효과에 대한 특성과 패턴을 분석하였다. AMR 전력사용량의 시계열적 특징으로부터 장기 추세효과와 중기 기온효과 그리고 단기 특수일 효과로 구성되는 공적분 모형을 구축하고, 기온효과를 연속적인 기온반응함수를 통하여 분석하기 위하여 기온반응함수를 푸리에 플렉서블 폼(Fourier Flexible Form; FFF) 비선형 함수로 추정하였다. 추정 결과 도출된 기온반응함수와 기온효과를 통하여 기온효과가 뚜렷하게 나타나는 서비스업군과 기온효과가 미약하게 나타나는 제조업군으로 구분하였다. 그리고 기온효과가 뚜렷하게 나타나는 서비스업군을 기온반응함수의 추정치에 근거하여 여름피크 산업과 겨울피크 산업으로 구분하였다. 이러한 실증분석 결과는 산업별, 계절별 전력수요관리정책 수립에 정책적 기초를 제공한다. 또한 실시간으로 측정되는 AMR 전력수요량 분석이라는 점에서 시차의 발생없이 신속하게 전력수요관리에 반영될 수 있다는 의미가 있다.

Keywords

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