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

• 발행기관: 한국산업경영시스템학회
• 저자명: Jinho Kim Chang-Yong Lee
• 간행물 정보: 『산업경영시스템학회지』제42권 제1호, 129~136쪽, 전체 8쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2019.03.28

영문 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

3. 실험결과

4. 요약 및 결론

키워드

Time Series Power Energy Consumption Temperature Exponential Smoothing Foreca