Browse > Article
http://dx.doi.org/10.5370/KIEEP.2015.64.3.164

Development of Daily PV Power Forecasting Models using ELM  

Lee, Chang-Sung (Dept. of Electrical Engineering Korea National University of Transportatio)
Ji, Pyeong-Shik (Dept. of Electrical Engineering Korea National University of Transportatio)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.64, no.3, 2015 , pp. 164-168 More about this Journal
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.
Keywords
PV power; Forecasting model; ELM; Neural networks;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
연도 인용수 순위
1 G. B. Huang, Q. Y. Zhu, and C. K. Siew, "Extreme learning machine: theory and applications," Neurocomputing, Vol. 70, No. 1-3, pp. 489-501, 2006.   DOI   ScienceOn
2 D. Serre, Matrices : Theory and Application, New York, Springer-Verlag, 2002.
3 M. Y. Kim, D. G. Lim, J. H. Lee, "A Status and Prospects of e PV Industry", The proceedings of KIEE, Vol. 62, No. 11, pp. 29-32, 2013.
4 J. H. Kim, "A PV Technology and industrial condition", Optical Science and Technology, ETRI, Vol. 6, No. 1, pp. 3-8, 2012.
5 K. D. King, "The Development of the Short-Term Predict Model for Solar Power Generation,"Journal of the Korean Solar Energy Society, Vol. 33, No. 6, pp. 62-69, 2013.   DOI   ScienceOn
6 D. K. Jo, Y. H. Kang, "A Detail Survey of Horizontal Global Radiation and Cloud Cover for the Installation of Solar Photovoltaic System in Korea", Journal of the Korean Solar Energy Society, Vol. 30, No. 3, pp. 2-9, 2010.
7 C. C. Hyun, J. J. Young, "Probabilistic Modeling of Photovoltaic Power Systems with Big Learning Data Sets,"Journal of Korean Institute of Intelligent Systems, Vol. 23, No. 5, pp. 412-417, 2013.   DOI   ScienceOn
8 W. C. Cha, J. H. Park, U. R. Cho, and J. C. Kim, "A study on Solar Power Generation Efficiency Emprical Analysis according to Temperature and Wind speed", The Transactions of the Korean Institute of Electrical Engineers, Vol. 64P, No. 1, pp. 1-6, 2015.   DOI
9 J. W. Ko, N. R. Yun, Y. K. Min, T. H. Jung, C. S. Won, H. K. Ahn, "Prediction of Output Power for PV Module with Tilted Angle and Structural Design", The Transactions of the Korean Institute of Electrical Engineers Vol. 62, No. 3, pp. 371-375, 2013.   DOI   ScienceOn
10 D. K. Jo, C. Y. Yun, K. D. Kim, Y. H. Kang, "A Detail Survey of Horizontal Global Radiation and Hours of Bright Sunshine for the Installation of Solar Photovoltaic System in Korea", Journal of the Korean Solar Energy Society, Vol. 31, No. 3, pp. 48-56, 2011.   DOI
11 D. K. Jo, C. Y. Yun, K. D. Kim, Y. H. Kang, "A Study on the Estimating Solar Radiation Using Hours of Bright Sunshine for the Installation of Photovoltaic System in Korea", Journal of the Korean Solar Energy Society, Vol. 31, No. 4, pp. 72-79, 2011.   DOI
12 J. M. Won, G. Y. Doe, N. R. Heo, "Predict Solar Radiation According to Weather Report", Journal of Navigation and Port Research, Vol. 35, No. 5, pp. 387-392, 2011.   DOI   ScienceOn
13 G. B. Huang, Q. Y. Zhu, and C. K. Siew, "Extreme learning machine: a new learning scheme of feedforward neural networks," in Proc. 2004 IEEE Int. Conf. Neural Networks, Vol. 2, pp. 985-990, 2004.