Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 30455

Select areas to restrict search in scientific publication database:
Forecasting Direct Normal Irradiation at Djibouti Using Artificial Neural Network
In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.
Digital Object Identifier (DOI):


[1] Gauri, S., Safiatou, A. N. and Mohamed, Y. S. “Renewable Readiness Assessement: Djibouti”, International Renewable Energy Agency, IRENA (2015).
[2] Abdourazak, A. K., Abderafi, S., Zejli, D. and Ibrahim, I. A. “Potentialities of using linear Fresnel technology for solar energy development in Djibouti”, In Renewable and Sustainable Energy Conference. IRSEC 2014, IEEE International, 2014, pp. 672-675, IEEE.
[3] Koca, A., Oztop, H. F., Varol, Y. and Koca, G. O. “Estimation of solar irradiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey”, Expert Systems with Applications, 38, 2011, pp. 8756-8762.
[4] Fadare, D. A. “Modelling of solar energy potential in Nigeria using an artificial neural network model”, Applied Energy, 86, 2009, pp. 1410-1422.
[5] Dorvloa, A. S. S., Jervase, J. A. and Al-Lawati, A. “Solar irradiation estimation using artificial neural networks”, Applied Energy, 71, 2002, pp. 307-319.
[6] Amit, K. Y. and Chandel, S. S. “Solar radiation prediction using Artificial Neural Network techniques: A review”, Renewable and Sustainable Energy Reviews, 33, 2014, pp. 772-781.
[7] Md. Shafiqul, I., Md. Monirul, K. and Nafis, K. “Artificial Neural Networks based Prediction of Insolation on Horizontal Surfaces for Bangladesh”, Procedia Technology, 10, 2013, pp. 482-491.
[8] Ermis, K., Midilli, A., Dincer, I. and Rosen, M. A. “Artificial neural network analysis of world green energy use”, Energy Policy, 35, 2007, pp. 1731-1743.
[9] GPS Coordinates and Google Map, “”. Accessed on 12/2015.
[10] Solar and Wind Energy Resource Assessment (SWERA), DNI DLR (Germain Aerospace Centre) high Resolution, “”. Accessed on 12/2015.
[11] Ouammi, A., Zejli, D., Dagdougui, H. and Benchrifa, R. “Artificial neural network analysis of Moroccan solar potential”, Renewable and Sustainable Energy Reviews, 16(7), 2012, pp. 4876-4889.
[12] Mubiri, J. “Predicting total solar irradiation values using artificial neural networks”, Renewable Energy, 33(10), 2008, pp. 2329-2332.
[13] Ouammi, A., Sacile, R., Zejli, D., Mimet, A. and Benchrifa, R. “Sustainability of a wind power plant: application to different Moroccan sites”, Energy, 35, 2010, pp. 4226-4236.
[14] Adnan S., Erol A. and Mehmet O. “Estimation of solar potential in Turkey by artificial neural networks using meteorological and geographical data”, Energy Conversion and Management, 45(18-19), 2004, pp. 3033-3052.
[15] Fernando R. M., Enio B. P. and Ricardo A. G. “Solar radiation forecastion using Artificial Neural Networks”, International Journal of Energy Science, 2(6), 2012, pp. 217-227.
Vol:14 No:05 2020Vol:14 No:04 2020Vol:14 No:03 2020Vol:14 No:02 2020Vol:14 No:01 2020
Vol:13 No:12 2019Vol:13 No:11 2019Vol:13 No:10 2019Vol:13 No:09 2019Vol:13 No:08 2019Vol:13 No:07 2019Vol:13 No:06 2019Vol:13 No:05 2019Vol:13 No:04 2019Vol:13 No:03 2019Vol:13 No:02 2019Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007