Comparison of clear-sky models for evaluating solar forecasting skill

World Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conferen

Volumn 6, Issue , 2012, Pages 4443-4449

  Marquez, Ricardo ^a   Coimbra, Carlos F M ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; FORECASTING ALGORITHM; FORECASTING ERROR; FORECASTING MODELS; FORECASTING SKILL; PERSISTENCE MODELS; REFERENCE MODELS; SKILL METRIC; TIME HORIZONS;

MATHEMATICAL MODELS; RENEWABLE ENERGY RESOURCES;

FORECASTING;

EID: 84871596067     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Badescu, V. Modeling Solar Radiation at the Earth Surface. Springer-Verlag, Berlin Heidelberg, 2008.
2. C.M. Bishop. Neural Networks for Pattern Recognition. Oxford University Press, Greate Clarendon Street, Oxford, 1995.
3. Cao, J. and Lin, X. Study of hourly and daily solar irradiation forecast using diagonal recurrent wavelet neural networks. Energy Conversion and Management, 49 (6):1396-1406, 2008.
4. Hoff, T. E. and Perez, R. Quantifying pv power output variability. Solar Energy, 84 (10):1782-1793, 2010.
5. Lew, D. and Piwko, R. Western Wind and Solar Integration Study. Technical report, National Renewable Energy Laboratories, 2010.
6. Marquez, R. and Coimbra, C. F. M. A novel metric for evaluation of solar forecasting models, under review.
7. Marquez, R. and Coimbra, C. F. M. Forecasting of global and direct solar irradiance using stochastic learning methods, ground experiments and the NWS database. Solar Energy, 85 (5):746-756, 2011.
8. Martin, L. and Zarzalejo, L. F. and Polo, J. and Navarro, A. and Marchante, R. and Cony, M. Prediction of global solar irradiance based on time series analysis: application to solar thermal power plants energy production planning. Solar Energy, 84 (10):1772-1781, 2010.
9. Mellit, A. Artificial intelligence technique for modelling and forecasting of solar radiation data: a review. Int. J. Artif. Intell. Soft Comput., 1:52-76, 2008.
10. Perez, R. and Kivalov, S. and Schlemmer, J. and Hemker, K. and Renne, D. and Hoff, T. E. Validation of short and medium term operational solar radiation forecasts in the US. Solar Energy, 84 (5):2161-2172, 2010.
11. Rodriguez, G. D. A Utility Perspective of the Role of Energy Storage in the Smart Grid. Power and Energy Society General Meeting, 2010 IEEE, pages 1-2, 2010.
12. Sundar, V. Integration of Renewable Resources: Operational Requirements and Generation Fleet Capability at 20 percent RPS. Technical report, California Independent System Operator (CAISO), 2010.