Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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The Forecasting Power Energy Demand by Applying Time Dependent Sensitivity between Temperature and Power Consumption

시간대별 기온과 전력 사용량의 민감도를 적용한 전력 에너지 수요 예측

  • Kim, Jinho (Dept. of Industrial and Systems Engineering, Kongju National University) ;
  • Lee, Chang-Yong (Dept. of Industrial and Systems Engineering, Kongju National University)
  • 김진호 (공주대학교 산업시스템공학과) ;
  • 이창용 (공주대학교 산업시스템공학과)
  • Received : 2019.01.21
  • Accepted : 2019.02.20
  • Published : 2019.03.31
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Abstract

In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

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