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http://dx.doi.org/10.5370/KIEEP.2013.62.4.169

Development of Daily Peak Power Demand Forecasting Algorithm using ELM  

Ji, Pyeong-Shik (한국교통대 전기공학과)
Kim, Sang-Kyu (한국교통대 전기공학과)
Lim, Jae-Yoon (대덕대학교 전기과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.62, no.4, 2013 , pp. 169-174 More about this Journal
Abstract
Due to the increase of power consumption, it is difficult to construct an accurate prediction model for daily peak power demand. It is very important work to know power demand in next day to manage and control power system. In this research, we develop a daily peak power demand prediction method based on Extreme Learning Machine(ELM) with fast learning procedure. 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
ELM; Neural networks; Peak power; Power demand;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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