Behavior Prediction Algorithm of Solar Radiation and Temperature in Cajicá, Colombia

Nicolas Fernando Marrugo, Dario Amaya, Olga Ramos

Abstract


The meteorological variables prediction such as solar radiation, temperature and humidity, is a process that has taken a major relevance in the last years, due to the impact of this variables in energetic systems, especially those that use renewable sources. This article has as objective, design and develop a prediction algorithm using artificial intelligence to determine the future behavior of solar radiation and temperature in Cajicá, Colombia. Initially were used the campus meteorological station of UMNG (Nueva Granada Military University), to validate the data collected by the NASA web application POWER (Prediction of Worldwide Energy Resource), data will be used for characterizing these variables. Obtaining as a result, a patterns prediction tool of increase, decrease or constancy of solar radiation and temperature, that be able to support the development of energetic projects based on the use of renewable sources.

Total Views: 92

Keywords


Artificial Intelligence algorithm, solar energy, solar radiation, temperature

Full Text:

PDF

References


M. Bolinger, R. Wiser, and G. Fitzgerald, “An Overview of Investments by State Renewable Energy Funds in Large-Scale Renewable Generation Projects,” Electr. J., vol. 18, no. 1, pp. 78–84, January 2005.

S. Sperati, S. Alessandrini, P. Pinson, and G. Kariniotakis, “The ‘Weather Intelligence for Renewable Energies’ Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation,” Energies, vol. 8, no. 9, pp. 9594–9619, 2015.

J. L. Oviedo-Salazar, M. H. Badii, A. Guillen, and O. L. Serrato, “Historia y Uso de Energías Renovables History and Use of Renewable Energies,” Daena Int. J. Good Conscience, vol. 10, no. 1, pp. 1–18, 2015.

O. C. Juan Francisco, “La contribución de las energías renovables al desarrollo económico, social y medioambiental,” Universidad de Extremadura, 2015.

Jefry Mora, Nicolas Marrugo, and Dario Amaya, “Study and comparison of silicon and AlGaAs for the development of tandem solar cells,” Energy Educ. Sci. Technol., vol. 33, no. 6, pp. 2887–2896, September 2015.

P. j. Tavner, D. M. Greenwood, M. W. G. Whittle, R. Gindele, S. Faulstich, and B. Hahn, “Study of weather and location effects on wind turbine failure rates,” Wind Energy, vol. 16, no. 2, pp. 175–187, March 2013.

E. K. Rensheng Chen, “An hourly solar radiation model under actual weather and terrain conditions: A case study in Heihe river basin,” Energy, vol. 32, no. 7, pp. 1148–1157, 2007.

J. Twidell and T. Weir, Renewable Energy Resources. Routledge, 2015.

F. O. Hocaoĝlu, Ö. N. Gerek, and M. Kurban, “A Novel 2-D Model Approach for the Prediction of Hourly Solar Radiation,” in Computational and Ambient Intelligence, F. Sandoval, A. Prieto, J. Cabestany, and M. Graña, Eds. Springer Berlin Heidelberg, 2007, pp. 749–756.

A. Mellit, M. Menghanem, and M. Bendekhis, “Artificial neural network model for prediction solar radiation data: application for sizing stand-alone photovoltaic power system,” in Power Engineering Society General Meeting, 2005. IEEE, 2005, pp. 40–44.

R. Munzhedzi and A. B. Sebitosi, “Redrawing the solar map of South Africa for photovoltaic applications,” Renew. Energy, vol. 34, no. 1, pp. 165–169, January 2009.

Oscar Ulises Preciado Olvera and David Morillón Gálvez, “BIOSOL: Software para el estudio del bioclima, control solar e iluminación natural,” presented at the IV Conferencia Latino Americana de Energía Solar (IV ISES_CLA), Lima - Perú, 2010, vol. 1.

W. S. Chandler, C. H. Whitlock, and J. Paul W. Stackhouse, “NASA Climatological Data for Renewable Energy Assessment,” J. Sol. Energy Eng., vol. 126, no. 3, pp. 945–949, July 2004.

D. Peterson and J. Wang, “A sub-pixel-based calculation of fire radiative power from MODIS observations: 2. Sensitivity analysis and potential fire weather application,” Remote Sens. Environ., vol. 129, pp. 231–249, February 2013.

S. Hernández R, E. Gómez V, R. A, and D. F, “Outstanding evaluation of radiation emitted by the sun as a power supplysystem for a pico-satellite "CUBESAT,” Tecnura, vol. 16, no. 31, pp. 19–32, January 2012.

B. Palencia, S. Ernesto, P. Cubillos, and C. Andrés, “Administración de la información de alertas diarias del IDEAM a través del diseño de un sistema de información con una base de datos OLTP y un almacén de datos,” 2014.

H. Mohamed Ismail, H. K. Ng, C. W. Queck, and S. Gan, “Artificial neural networks modelling of engine-out responses for a light-duty diesel engine fuelled with biodiesel blends,” Appl. Energy, vol. 92, pp. 769–777, April 2012.


Refbacks

  • There are currently no refbacks.


Online ISSN: 1309-0127

www.ijrer.org

ijrereditor@gmail.com; ilhcol@gmail.com;

IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Thomson Reuters)