Distributed storage system big data mining based on HPC Application- A solar photovoltaic forecasting system practice

Information

Volumn 15, Issue 9, 2012, Pages 3749-3755

  Fu, Jia ^a   Chen, Zhenghong ^a   Wang, Junchao ^b,c   He, Mingqiong ^a   Wang, Jianzong ^c  

^a Meteorological Service Center of Hubei Province   (China)

^b Wuhan Research Institute of Rainstorm   (China)

^c HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Big data; High Performance computing; Neural network; Photovoltaic forecasting

Indexed keywords

EID: 84864975150     PISSN: 13434500     EISSN: 13448994     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (10)

1. European Photovoltaic Industry association Report. Solar Generation Solar generation 6[R]. EPIA, 2011, pp. 1-200
2. Bofinger S, Heilscher G. 2004. Solar radiation forecast based on ECMWF and model output statistics. Technical Report ESA/ENVISOLAR, AO/l-4364/03/I-IW, EOEPEOMD.
3. Ensenius J S, Cotton GF. 1981. The development and testing of automated solar energy forecasts based on the model output statistics (MOS) Technique. Proc. 1st Workshop on Terrestrial Solar Resource Forecasting and on the Use on Satellites for Terrestrial Solar Resource Assessment, Newark, American Solar Energy Society.
4. Lorenz E, Remund J, Müller S, et al. Benchmarking of different approaches to forecast solar irradiance. 24th European Photovoltaic Solar Energy Conference, 2009, pp. 1-10.
5. Aguilar J D, Perez P J, Almonacid G, et al. 2005. Average Power of a Photovoltaic Gridconnected System. 21th. European Solar Energy Conference, pp. 1-4.
6. Almonacid F, Rus C, Pérez P J, et al. 2009. Estimation of the energy of a PV generator using artificial neural network. Renewable Energy, 34 (12): pp.2743-2750.
7. European Photovoltaic Industry Association (EPIA). 2011. Solar photovoltaic electricity empowering the world. 1-100
8. Intergovernmental Panel on Climate Change (IPCC) . 2007. IPCC Fourth Assessment Report (AR4). Cambridge: Cambridge University Press.
9. Kudo M, Nozaki Y, Endo H, et al. 2009.Forecasting electric power generation in a photovoltaic power system for an energy network. Electrical Engineering in Japan, 167 (4): pp. 16-23
10. U.S. Energy Information Administration (EIA). International Energy Outlook 2010. pp. 1-32