Characterization of the intraday variability regime of solar irradiation of climatically distinct locations

Solar Energy

Volumn 125, Issue , 2016, Pages 99-110

  Lauret, Philippe ^a   Perez, Richard ^b   Mazorra Aguiar, Luis ^c   Tapachès, Emeric ^a   Diagne, Hadja Maimouna ^a   David, Mathieu ^a  

^a UNIVERSITÉ DE LA RÉUNION   (France)

^b STATE UNIVERSITY OF NEW YORK   (United States)

^c UNIVERSITY OF LAS PALMAS DE GRAN CANARIA   (Spain)

Author keywords

Model; NWP model; Solar irradiation; Solar resource; Variability

Indexed keywords

IRRADIATION; LOCATION; MODELS; SOLAR RADIATION;

CLOUD FORMATION; NWP MODEL; SIMPLE MODELING; SOLAR IRRADIATION; SOLAR RESOURCES; STANDARD DEVIATION; VARIABILITY; WEATHER EVENTS;

CLIMATE MODELS;

CLEAR SKY; CLIMATE MODELING; CLOUD; EMPIRICAL ANALYSIS; IRRADIATION; OROGRAPHY; SOLAR RADIATION;

EID: 84951807638     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2015.11.032     Document Type: Article

References (29)

1. Badosa J., Haeffelin M., Chepfer H. Scales of spatial and temporal variation of solar irradiance on reunion Tropical Island. Sol. Energy 2013, 88:42-56.
2. Bird, R.E., Hulstrom, R.L., 1981. Simplified the clear sky model for direct and diffuse insolation on horizontal surfaces. In: Technical Report No. SERI/TR-642-761, Golden, CO, Solar Energy Research Institute.
3. Coimbra C.F.M., Kleissl J., Marquez R. Overview of solar forecasting methods and a metric for accuracy evaluation. Solar Energy Forecasting and Resource Assessment 2013, 171-194. Elsevier. J. Kleissl (Ed.).
4. Dambreville, R., 2014. Prévision du rayonnement solaire global par télédétection pour la gestion de la production d'énergie photovoltaïque. PhD thesis, Université de Grenoble.
5. Diagne, H.M., 2015. Gestion intelligente du réseau électrique Réunionnais. Prévision de la ressource solaire en milieu insulaire. PhD thesis, Université de La Réunion.
6. Hansen, T., 2007. Utility solar generation valuation methods, USDOE Solar America Initiative Progress Report. Tucson Electr. Power, Tucson, AZ.
7. Huang J., Troccoli A., Coppin P. An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records. Renew. Energy 2014, 72:195-202.
8. Ineichen P. Comparison of eight clear sky broadband models against 16 independent data banks. Sol. Energy 2006, 80:468-478.
9. Ineichen P. A broadband simplified version of the SOLIS clear sky model. Sol. Energy 2008, 82:758-762.
10. ISIS, 2010.
11. Kang B.O., Tam K.S. A new characterization and classification method for daily sky conditions based on ground-based solar irradiance measurement data. Sol. Energy 2013, 94:102-118.
12. Kang B.O., Tam K.S. New and improved methods to estimate day-ahead quantity and quality of solar irradiance. Appl. Energy 2015, 13:240-249.
13. Lave M., Kleissl J., Arias-Castro E. High-frequency irradiance fluctuations and geographic smoothing. Sol. Energy 2012, 86:2190-2199.
14. Lenox, C., Nelson, L., 2010. Variability comparison of large-scale photovoltaic systems across diverse geographic climates. In: 25th European Photovoltaic Solar Energy Conference, 6-10 September, Valencia, Spain.
15. Marcos J., Marroyo L., Lorenzo E., Alvira D., Izco E. Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model. Prog. Photovolt. Res. Appl. 2011, 19:218-227.
16. Mazorra Aguiar, L., Díaz, F., Montero, G., Montenegro, R., 2010. Typical Meteorological Year (TMY) Evaluation for Power Generation in Gran Canaria Island. In: 25th European Photovoltaic Solar Energy Conference, 6-10 September, Valencia, Spain.
17. Mills A., Ahlstrom M., Brower M., Ellis A., George R., Hoff T., Kroposki B., Lenox C., Nicholas M., Stein J., Wan Y.W. Understanding Variability and Uncertainty of Photovoltaics for Integration with the Electric Power System 2010, Lawrence Berkeley Natl. Lab.
18. Murata A., Yamaguchi H., Otani K. A method of estimating the output fluctuation of many photovoltaic power generation systems dispersed in a wide area. Electr. Eng. Jpn. 2009, 166:9-19.
19. Perez R., Hoff T. Solar resource variability. Solar Energy Forecasting and Resource Assessment 2013, 133-148. Elsevier. J. Kleissl (Ed.).
20. Perez R., Ineichen P., Seals R., Michalsky J., Stewart R. Modeling daylight availability and irradiance components from direct and global irradiance. Sol. Energy 1990, 44:271-289.
21. Perez R., Kivalov S., Schlemmer J., Hemker K., Hoff T. Parameterization of site-specific short-term irradiance variability. Sol. Energy 2011, 85:1343-1353.
22. Perez R., Lorenz E., Pelland S., Beauharnois M., Van Knowe G., Hemker K., Heinemann D., Remund J., Müller S.C., Traunmüller W., Steinmauer G., Pozo D., Ruiz-Arias J.A., Lara-Fanego V., Ramirez-Santigosa L., Gaston-Romero M., Pomares L.M. Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe. Sol. Energy 2013, 94:305-326.
23. Perez, R., David, M., Hoff, T., Kivalov, S., Kleissl, J., Lauret, P., Perez, M., 2015. Spatial and temporal variability of solar energy. Foundations and Trends in Renewable Energy (forthcoming).
24. Perpiñán O., Marcos J., Lorenzo E. Electrical power fluctuations in a network of DC/AC inverters in a large PV plant: relationship between correlation, distance and time scale. Sol. Energy 2013, 88:227-241.
25. Reno, M.J., Stein, J.S., 2013. Using cloud classification to model solar variability. ASES National Solar Conference, April 16-20, 2013, Baltimore, Maryland.
26. Sengupta M., Keller J. PV ramping in a distributed generation environment: a study using solar measurements. IEEE Photovolt. Spec. Conf. 2011, 586-589.
27. Stein, J.S., Hansen, C.W., Reno, M.J., 2012. The variability index: a new and novel metric for quantifying irradiance and PV output variability. World Renewable Energy Forum, 13-17 May 2012, Denver, Colorado.
28. SURFRAD Network, 2010. Monitoring Surface Radiation in the Continental United States.http://www.esrl.noaa.gov/gmd/grad/surfrad/index.html.
29. Van Haaren R., Morjaria M., Fthenakis V. Empirical assessment of short-term variability from utility-scale solar PV plants. Prog. Photovol. Res. Appl. 2014, 22:548-559.