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http://dx.doi.org/10.5370/KIEEP.2014.63.3.189

Development of Daily Peak Power Demand Forecasting Algorithm with Hybrid Type composed of AR and Neuro-Fuzzy Model  

Park, Yong-San (한국교통대학교 대학원 전기공학과)
Ji, Pyeong-Shik (한국교통대 전기공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.63, no.3, 2014 , pp. 189-194 More about this Journal
Abstract
Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method based on hybrid type composed of AR and Neuro-Fuzzy model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.
Keywords
Power demand; Hybrid model; AR; ANFIS;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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