Proceedings of the SAREK Conference (대한설비공학회:학술대회논문집)
- 2009.06a
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- Pages.940-945
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- 2009
Development of the DB-Based Energy Demand Prediction System Urban Community Energy Planning
광역도시 에너지계획단계에서의 DB기반 에너지수요예측 시스템 개발
- Kong, Dong-Seok (Graduate School of Architectural Engineering, University of Seoul) ;
- Lee, Sang-Mun (Korea Institute of Construction Materials) ;
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Lee, Byung-Jeong
(Architectural Engineering, University of Seoul)
;
- Huh, Jung-Ho (Department of Computer Science, University of Seoul)
- Published : 2009.06.25
Abstract
Energy planning for hybrid energy system is important to increase the flexibility in the urban community and national energy systems. Expected maximum loads, load profiles and yearly energy demands are important input parameters to plan for the technical and environmental optimal energy system for a planning area. The method for energy demand prediction has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. This method can produce 10% of errors hourly load profile from individual building to urban community. As the results of this paper, energy demand prediction system has been developed based on simulink.
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