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The Forecasting Power Energy Demand by Applying Time Dependent Sensitivity between Temperature and Power Consumption KCI 등재

시간대별 기온과 전력 사용량의 민감도를 적용한 전력 에너지 수요 예측

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한국산업경영시스템학회지 (Journal of Society of Korea Industrial and Systems Engineering)
한국산업경영시스템학회 (Society of Korea Industrial and Systems Engineering)
초록

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.

목차
1. 서 론
 2. 온도 변화에 따른 단기간 전력 사용량 예측을 위한 모형
  2.1 파워 스펙트럼(Power Spectrum) 분석
  2.2 시간대별 온도와 전력 사용량의 관련성 분석
  2.3 온도를 고려한 전력수요 예측 모형
 3. 실험결과
 4. 요약 및 결론
 References
저자
  • Jinho Kim(Dept. of Industrial and Systems Engineering, Kongju National University) | 김진호
  • Chang-Yong Lee(Dept. of Industrial and Systems Engineering, Kongju National University) | 이창용 Corresponding Author