Solar radiation prediction based on recurrent neural networks trained by Levenberg-Marquardt backpropagation learning algorithm

2012 IEEE PES Innovative Smart Grid Technologies, ISGT 2012

Volumn , Issue , 2012, Pages

  Zhang, Nian ^a   Behera, Pradeep K ^a  

^a UNIVERSITY OF THE DISTRICT OF COLUMBIA   (United States)

Author keywords

backpropagation learning algorithm; neural networks; Solar radiation prediction; time series prediction

Indexed keywords

AUTOCORRELATION FUNCTION ANALYSIS; BACKPROPAGATION LEARNING ALGORITHM; HYBRID POWER SYSTEMS; LEVENBERG-MARQUARDT; MEAN SQUARED ERROR; NEURAL NETWORK STRUCTURES; POWER GENERATION INDUSTRIES; PREDICTIVE MODELS; RADIATION PREDICTION; RENEWABLE ENERGY INDUSTRIES; STAND ALONE PHOTOVOLTAIC SYSTEM; STRONG GROWTH; TIME SERIES PREDICTION;

ARTIFICIAL INTELLIGENCE; ERROR ANALYSIS; FORECASTING; FOSSIL FUELS; LEARNING ALGORITHMS; NEURAL NETWORKS; RECURRENT NEURAL NETWORKS; REGRESSION ANALYSIS; SMART POWER GRIDS; SOLAR POWER GENERATION; SUN; TIME SERIES;

SOLAR RADIATION;

EID: 84860860444     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISGT.2012.6175757     Document Type: Conference Paper

References (28)

1. International Energy Agency, "World Energy Outlook 2009 Edition," ISBN 978-92-64-06130-9, 2009.
2. T. Appenzeller, "End of Cheap Oil," National Geographic, June 2004. http://ngm.nationalgeographic.com/ngm/0406/feature5/fulltext.html.
3. US Energy Information Administration, "Energy and Environment Explained: Greenhouse Gases," http://tonto.eia.doe.gov/energyexplained/ index.cfm?page=environment-about-ghg.
4. The American Solar Energy Society and Management Information Services, Inc., "Defining, Estimating, and Forecasting the Renewable Energy and Energy Efficiency Industries in the U.S and in Colorado," December 2008.
5. A. Mellit, M. Benghanem, A. Hadj, A. Guessoum, K. Moulai, "Neural Network Adaptive Wavelets for Sizing of Stand-Alone Photovoltaic Systems," Proceedings of the 2nd International IEEE Conference on Intelligent Systems, vol. 1, pp. 365-370, 2004.
6. N. Amjady, "Short-Term Hourly Load Forecasting Using Time-Series Modeling with Peak Load Estimation Capability," IEEE Transactions on Power Systems, vol. 16, no. 4, pp. 798-805, 2001.
7. T. Zhu, S. R. Shaw, S. B. Leeb, "Transient Recognition Control for Hybrid Fuel Cell Systems," IEEE Transactions on Energy Conversion, vol. 21, no. 1, pp. 885-896, 2006.
8. S. Haykins, Neural Networks: A Comprehensive Foundation, Second Edition, Prentice Hall, 1998.
9. H. Zhou, W. Sun, D Liu, J. Zhao, N. Yang, "The Research of Daily Total Solar-Radiation and Prediction Method of Photovoltaic Generation Based on Wavelet- Neural Network," 2011 Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1-5, 2011.
10. G. Capizzi, F. Bonanno, C. Napoli, "A Wavelet Based Prediction of Wind and Solar Energy for Long-Term Simulation of Integrated Generation Systems," 2010 International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM), pp. 586-592, 2010.
11. F. Deng, G. Su, C. Liu, Z. Wang, "Prediction of Solar Radiation Resources in China Using the LS-SVM Algorithms," 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE), vol. 5, pp. 31-35, 2010.
12. S. Cao, "Total Daily Solar Irradiance Prediction using Recurrent Neural Networks with Determinants," 2010 Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1-4, 2010.
13. S. M. Ruffing, G. K. Venayagamoorthy, "Short to Medium Range Time Series Prediction of Solar Irradiance Using an Echo State Network," 15th International Conference on Intelligent System Applications to Power Systems (ISAP '09), pp. 1-6, 2009.
14. A. Mellit, A. H. Arab, N. Khorissi, H. Salhi, "An ANFIS-Based Forecasting for Solar Radiation Data from Sunshine Duration and Ambient Temperature," IEEE Power Engineering Society General Meeting, pp. 1-6, 2007.
15. E. M. Crispim, P. M. Ferreira, A. E. Ruano, "Solar Radiation Prediction Using RBF Neural Networks and Cloudiness Indices," International Joint Conference on Neural Networks (IJCNN '06), pp. 2611-2618, 2006.
16. A. Ghanbarzadeh, A. R. Noghrehabadi, E. Assareh, M. A. Behrang, "Solar Radiation Forecasting Based on Meteorological Data Using Artificial Neural Networks," The seventh IEEE International Conference on Industrial Informatics, pp. 227-231, 2009.
17. L. El Chaar, L. A. Lamont, M. Karkoub, "Modeling Climate Parameters for Renewable Energy Applications in the UAE Using Neural Networks," CIGRE/IEEE PES Joint Symposium on Integration of Wide-Scale Renewable Resources Into the Power Delivery System, pp. 1-10, 2009.
18. D. Paul, S. N. Mandal, D. Mukherjee, S. Chaudhuri, "Artificial Neural Network Modeling for Efficient Photovoltaic System Design," International Conference on Advanced Computer Theory and Engineering, pp. 50-56, 2008.
19. A. Mellit, M. Menghanem, M. Bendekhis, "Artificial Neural Network Model for Prediction Solar Radiation Data: Application for Sizing Stand-Alone Photovoltaic Power System," IEEE Power Engineering Society General Meeting, vol. 1, pp. 40-44, 2005.
20. J. Wu, C. Chan, J. Loh, F. Choo, L. H. Chen, "Solar Radiation Prediction Using Statistical Approaches," 7th International Conference on Information, Communications and Signal Processing (ICICS 2009), pp. 1-5, 2009.
21. D. K. Barrow, S.F. Crone, N. Kourentzes, "An Evaluation of Neural Network Ensembles and Model Selection for Time Series Prediction," 2010 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2010.
22. N.A. Barker, C.J. Myers, H. Kuwahara, Learning Genetic Regulatory Network Connectivity from Time Series Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 1, pp. 152-165, 2011.
23. A. Rodan, P. Tino, "Minimum Complexity Echo State Network," IEEE Transactions on Neural Networks, vol. 22, no.1, pp. 131-144, 2011.
24. X. Cai, N. Zhang, G. K. Venayagamoorthy, and D. C. Wunsch, II, Time Series Prediction with Recurrent Neural Networks Trained by a Hybrid PSO-EA Algorithm, Neurocomputing, vol. 70, no. 13-15, pp. 2342-2353, 2007.
25. X. Cai, N. Zhang, G.K. Venayagamoorthy, D.C. Wunsch II, "Time Series Prediction with Recurrent Neural Networks Using Hybrid PSO-EA Algorithm," INNS-IEEE International Joint Conference on Neural Networks (IJCNN), vol. 2, Budapest, Hungary, pp. 1647-1652, 2004.
26. Artificial Neural Network & Computational Intelligence Forecasting Competition in 2006, 2008, and 2010. http://www.neural-forecasting-competition. com/
27. A. Lendasse, E. Oja and O. Simula, M. Verleysen, Time Series Prediction Competition: The CATS Benchmark, INNS-IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1615-1620, 2004.
28. M.T. Hagan and M. Menhaj, "Training Feed-Forward Networks with the Marquardt Algorithm," IEEE Transactions on Neural Networks, vol. 5, no. 6, pp. 989-993, 1994.