Publisher : The Korean Institute of Electrical Engineers
DOI : 10.5370/KIEEP.2015.64.4.246
Title & Authors
Development of PV Power Prediction Algorithm using Adaptive Neuro-Fuzzy Model Lee, Dae-Jong; Lee, Jong-Pil; Lee, Chang-Sung; Lim, Jae-Yoon; Ji, Pyeong-Shik;
Solar energy will be an increasingly important part of power generation because of its ubiquity abundance, and sustainability. To manage effectively solar energy to power system, it is essential part In this paper, we develop the PV power prediction algorithm using adaptive neuro-fuzzy model considering various input factors such as temperature, solar irradiance, sunshine hours, and cloudiness. To evaluate performance of the proposed model according to input factors, we performed various experiments by using real data.
PV power;Prediction model;ANFIS;Data selection;
A. Molki, "Dust affects solar cell efficiency," Physics Education, Vol. 45, pp. 456-458, 2010.
C. H. Henry, "Limiting efficiencies of ideal single and multiple energy gap terrestrial solar cells," J. App. Phys. Vol. 51, pp. 4494, 1980.
J. Hedstrom, J. Kessler, M. Ruckh, K. O. Velthaus, Hans-Werner Schock, "ZnO/CdS/CuInSe2 thin-film Solar cells with improved performance," Applied Physics Letters, Vol. 62, No. 6, pp. 597-599, 1993.
S. R. Kurtz. D. Myers. T. Townsend, C. Whitaker, A. Maish, R. Hulstrom, K. Emery, "Outdoor rating conditions for photovoltaic modules and systems," Solar Energy Materials & Solar Cells, Vol. 62, pp. 379-391, 2000.
D. R. Myers, S. R. Kurtz, C. Whitaker, T. Townsend, "Preliminary Investigations of Outdoor Meteorological Broadband and Spectral Conditions for Evaluating Photovoltaic Modules and systems," Program and Proceedings : NCPV Program Review Meeting 2000, pp. 16-19, 2000.
C. S. Chin, A. Babu, W. McBride, "Design, modeling and testing of a standalone single axis active solar tracker using MATLAB/Simulink," Renewable Energy, vol. 36, no. 11, pp. 3075-3090, 2011.
Y. S. Heo, J. G. Kim, B. M. Kwon, H. J. Song, "Prediction and Analysis of Photovoltaic Modules's Output using MATLAB," Journal of academia-industrial technology, Vol. 11, No. 8, pp. 2963-2967, 2010.
Modeling and fault diagnosis of a photovoltaic systems," Electrial Power Research, Vol. 78, No. 1, pp. 97-105, 2008.
Hyun Cheol Cho, "A Study on Dynamic Modeling of Photovoltaic Power Generator Systems using Probability and Statistics Theories," The Transactions of the Korean Institute of Electrical Engineers, vol. 61, no. 7, pp. 1007-1013, 2012.
H. C. Cho, Y. J. Jung, "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.
J. J. Song, Y. S. Jeong S. H. Lee, "Analysis of prediction model for solar power generation," Journal of Digital Convergence, Vol. 12, No. 3, pp. 243-248, 2014.
Kim Kwang-Deuk, "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
J. S. R. Jang, "ANFIS:Adaptive-network-based fuzzy inference system," IEEE Trans. on Systems, Man and Cybernetics, Vol. 23, No. 3, pp. 665-685, 1993.