Mobile QR Code QR CODE : The Transactions P of the Korean Institute of Electrical Engineers
The Transactions P of the Korean Institute of Electrical Engineers

Korean Journal of Air-Conditioning and Refrigeration Engineering

ISO Journal TitleTrans. P of KIEE
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    Korea Citation Index(KCI)

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  3. 2015-09(Vol.64 No.03)
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Title Development of Daily PV Power Forecasting Models using ELM
Authors 이창성(Lee, Chang-Sung) ; 지평식(Ji, Pyeong-Shik)
DOI https://doi.org/10.5370/KIEEP.2015.64.3.164
Page pp.164-168
ISSN 1229-800X
Keywords PV power ; Forecasting model ; ELM ; Neural networks
Abstract Due to the uncertainty of weather, it is difficult to construct an accurate forecasting model for daily PV power generation. It is very important work to know PV power in next day to manage power system. In this paper, correlation analysis between weather and power generation was carried out and daily PV power forecasting models based on Extreme Learning Machine(ELM) was presented. Performance of district ELM model was compared with single ELM model. The proposed method has been tested using actual data set measured in 2014.