A review of solar energy modeling techniques

Solar radiation data provide information on how much of the sun's energy strikes a surface at a location on the earth during a particular time period. These data are needed for effective research in solar-energy utilization. Due to the cost of and difficulty in solar radiation measurements and these data are not readily available, alternative ways of generating these data are needed. In this paper, a review is made on the solar energy modeling techniques which are classified based on the nature of the modeling technique. Linear, nonlinear, artificial intelligence models for solar energy prediction have been considered in this review. The outcome of the review showed that the sunshine ratio, ambient temperature and relative humidity are the most correlated coefficients to solar energy.

[1]  Viorel Badescu,et al.  A new kind of cloudy sky model to compute instantaneous values of diffuse and global solar irradiance , 2002 .

[2]  Mireia Diez,et al.  Solar radiation incident on tilted surfaces in Burgos, Spain: Isotropic models , 1995 .

[3]  A. Rabl,et al.  The average distribution of solar radiation-correlations between diffuse and hemispherical and between daily and hourly insolation values , 1979 .

[4]  A. A. El-Sebaii,et al.  Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia , 2010 .

[5]  Kamaruzzaman Sopian,et al.  Modeling of solar energy for Malaysia using artificial neural networks , 2011 .

[6]  Athanasios Sfetsos,et al.  Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques , 2000 .

[7]  A. Hepbasli,et al.  Determination of the optimum tilt angle of solar collectors for building applications , 2007 .

[8]  C. Justus,et al.  Estimation of daily and monthly direct, diffuse and global solar radiation from sunshine duration measurements , 1984 .

[9]  A. Q. Malik,et al.  Optimum tilt angle and orientation for solar collector in Brunei Darussalam , 2001 .

[10]  J. Hay Calculation of monthly mean solar radiation for horizontal and inclined surfaces , 1979 .

[11]  A. A. Trabea Analysis of solar radiation measurements at Al-Arish area, North Sinai, Egypt , 2000 .

[12]  Saleh M. Al-Alawi,et al.  An ANN-based approach for predicting global radiation in locations with no direct measurement instrumentation , 1998 .

[13]  Theo Chidiezie Chineke,et al.  Equations for estimating global solar radiation in data sparse regions , 2008 .

[14]  Kamal Skeiker,et al.  OPTIMUM TILT ANGLE AND ORIENTATION FOR SOLAR COLLECTORS IN SYRIA , 2009 .

[15]  Adel Mellit,et al.  Radial Basis Function Network-based prediction of global solar radiation data: Application for sizing of a stand-alone photovoltaic system at Al-Madinah, Saudi Arabia , 2010 .

[16]  Mohamed Mohandes,et al.  Estimation of global solar radiation using artificial neural networks , 1998 .

[17]  W. Beckman,et al.  Evaluation of hourly tilted surface radiation models , 1990 .

[18]  Weibin Ma,et al.  Estimating monthly average daily diffuse solar radiation with multiple predictors: A case study , 2011 .

[19]  Shen Weixiang,et al.  Design of standalone photovoltaic system at minimum cost in Malaysia , 2008, 2008 3rd IEEE Conference on Industrial Electronics and Applications.

[20]  M. Ranjan,et al.  Solar resource estimation using artificial neural networks and comparison with other correlation models , 2003 .

[21]  Gilles Notton,et al.  PREDICTING HOURLY SOLAR IRRADIATIONS ON INCLINED SURFACES BASED ON THE HORIZONTAL MEASUREMENTS: PERFORMANCES OF THE ASSOCIATION OF WELL-KNOWN MATHEMATICAL MODELS , 2006 .

[22]  Kamaruzzaman Sopian,et al.  Optimization of a PV/wind micro-grid for rural housing electrification using a hybrid iterative/genetic algorithm: Case study of Kuala Terengganu, Malaysia , 2012 .

[23]  Emanuele Calabrò,et al.  Determining optimum tilt angles of photovoltaic panels at typical north-tropical latitudes , 2009 .

[24]  Jesús Polo,et al.  Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index , 2005 .

[25]  Jorge Aguilera,et al.  An application of the multilayer perceptron: Solar radiation maps in Spain , 2005 .

[26]  J. Olseth,et al.  Modelling slope irradiance at high latitudes , 1986 .

[27]  E. Arcaklioğlu,et al.  Use of artificial neural networks for mapping of solar potential in Turkey , 2004 .

[28]  K. Sopian,et al.  Estimates of monthly average daily global solar radiation in Malaysia , 1992 .

[29]  Jan F. Kreider,et al.  Solar energy handbook , 1981 .

[30]  G. Mihalakakou,et al.  The total solar radiation time series simulation in Athens, using neural networks , 2000 .

[31]  Z. Şen,et al.  Simple models of solar radiation data for northwestern part of Turkey , 2001 .

[32]  Zekai Şen,et al.  Fuzzy algorithm for estimation of solar irradiation from sunshine duration , 1998 .

[33]  H.M.S. Hussein,et al.  Performance evaluation of photovoltaic modules at different tilt angles and orientations , 2004 .

[34]  Himangshu Ranjan Ghosh,et al.  Determining seasonal optimum tilt angles, solar radiations on variously oriented, single and double axis tracking surfaces at Dhaka , 2010 .

[35]  Soteris A. Kalogirou,et al.  Methodology for predicting sequences of mean monthly clearness index and daily solar radiation data in remote areas: Application for sizing a stand-alone PV system , 2008 .

[36]  Kadir Bakirci,et al.  Models of solar radiation with hours of bright sunshine: A review , 2009 .

[37]  M. Benghanem Optimization of tilt angle for solar panel: Case study for Madinah, Saudi Arabia , 2011 .

[38]  F. S. Tymvios,et al.  Comparative study of Ångström's and artificial neural networks' methodologies in estimating global solar radiation , 2005 .

[39]  R. Tang,et al.  Optimal tilt-angles for solar collectors used in China , 2004 .

[40]  Yong Q. Tian,et al.  Estimating solar radiation on slopes of arbitrary aspect , 2001 .

[41]  M. Kacira,et al.  Determining optimum tilt angles and orientations of photovoltaic panels in Sanliurfa, Turkey , 2004 .

[42]  Hamdy K. Elminir,et al.  Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models , 2007 .

[43]  Joseph A. Jervase,et al.  Solar radiation estimation using artificial neural networks , 2002 .

[44]  Kamaruzzaman Sopian,et al.  Modeling of Daily Solar Energy on a Horizontal Surface for Five Main Sites in Malaysia , 2011 .

[45]  S. Tuller,et al.  The relationship between diffuse, total and extra terrestrial solar radiation , 1976 .

[46]  Serm Janjai,et al.  A new model for computing monthly average daily diffuse radiation for Bangkok , 1996 .

[47]  Isaac N. Itodo,et al.  A model for determining the global solar radiation for Makurdi, Nigeria , 2011 .

[48]  Michael H. Unsworth,et al.  The angular distribution and interception of diffuse solar radiation below overcast skies , 1980 .

[49]  S. Iniyan,et al.  A review of energy models , 2006 .

[50]  S. Alam,et al.  Computation of beam solar radiation at normal incidence using artificial neural network , 2006 .

[51]  M. Al-Akhras,et al.  Optimizing the tilt angle of solar collectors , 2002 .

[52]  P. Koronakis,et al.  On the choice of the angle of tilt for south facing solar collectors in the Athens basin area , 1986 .

[53]  D. Fadare Modelling of solar energy potential in Nigeria using an artificial neural network model , 2009 .

[54]  Liu Yang,et al.  Solar radiation modelling using ANNs for different climates in China , 2008 .

[55]  Yousef A.G. Abdalla,et al.  Global and diffuse solar radiation in Doha (Qatar) , 1985 .

[56]  Zafer Aslan,et al.  Study of hourly solar radiation data in Istanbul , 1995 .