Estimation of Diffuse Solar Radiation for Selected Cities in Nigeria

This study proposes a multivariable model of monthly mean daily diffuse solar radiation on horizontal surfaces for three cities (Abuja, Benin City and Katsina), in Nigeria. The estimation was based on a correlation between clearance index and diffuse to global solar radiation ratio and was computed using monthly mean daily data set for global solar radiation on horizontal surfaces. The predictive efficiency of the proposed model was compared with the observed values and those believed to be universally applicable. The results suggest that the existing methods could be replaced by the developed model for a diffuse solar radiation data generation scheme.

Download Full-text

Empirical Model for Estimating Global Solar Radiation on Horizontal Surfaces for Selected Cities in the Six Geopolitical Zones in Nigeria

Journal of Control Science and Engineering ◽

10.1155/2011/356405 ◽

2011 ◽

Vol 2011 ◽

pp. 1-7 ◽

Cited By ~ 9

Author(s):

M. S. Okundamiya ◽

A. N. Nzeako

Keyword(s):

Solar Radiation ◽

Global Solar Radiation ◽

Mean Bias Error ◽

Bias Error ◽

Data Set ◽

Ambient Temperatures ◽

Performance Accuracy ◽

Daily Data ◽

Proposed Model ◽

Regression Theory

This study proposes a temperature-based model of monthly mean daily global solar radiation on horizontal surfaces for selected cities, representing the six geopolitical zones in Nigeria. The modelling was based on linear regression theory and was computed using monthly mean daily data set for minimum and maximum ambient temperatures. The results of three statistical indicators: Mean Bias Error (MBE), Root Mean Square Error (RMSE), andt-statistic (TS), performed on the model along with practical comparison of the estimated and observed data, validate the excellent performance accuracy of the proposed model.

Download Full-text

Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

Journal of Solar Energy ◽

10.1155/2016/8197389 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 7

Author(s):

Boluwaji M. Olomiyesan ◽

Onyedi D. Oyedum

Keyword(s):

Solar Radiation ◽

Comparative Study ◽

Global Radiation ◽

Statistical Error ◽

Global Solar Radiation ◽

Coefficient Of Determination ◽

Mean Bias Error ◽

Percentage Error ◽

Radiation Data ◽

Proposed Model

In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005) of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET) Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA) for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE), and coefficient of determination (R2). Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano) and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

Download Full-text

MODELOS DE ESTIMATIVA DA RADIAÇÃO FOTOSSINTETICAMENTE ATIVA GLOBAL E DIFUSA EM FUNÇÃO DA RADIAÇÃO DE ONDAS CURTAS E DO ÍNDICE DE CLARIDADE (Kt)

Irriga ◽

10.15809/irriga.2002v7n2p123-129 ◽

2002 ◽

Vol 7 (2) ◽

pp. 123-129

Author(s):

Eduardo Nardini Gomes ◽

João Francisco Escobedo

Keyword(s):

Solar Radiation ◽

Photosynthetically Active Radiation ◽

Model Development ◽

Diffuse Radiation ◽

Global Solar Radiation ◽

Clearness Index ◽

Active Radiation ◽

Diffuse Solar Radiation ◽

Proposed Model ◽

Index 2

MODELOS DE ESTIMATIVA DA RADIAÇÃO FOTOSSINTETICAMENTE ATIVA GLOBAL E DIFUSA EM FUNÇÃO DA RADIAÇÃO DE ONDAS CURTAS E DO ÍNDICE DE CLARIDADE (Kt) Eduardo Nardini GomesJoão Francisco EscobedoDepartamento de Recursos Naturais, Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, CP 237, CEP 18603-970, Botucatu – SP, Fone: (0xx14) 6802-7162 1 RESUMO O presente trabalho apresenta equações de estimativa da radiação fotossinteticamente ativa global () e difusa () em função das respectivas radiações global () e difusa () do espectro solar total, bem como a estimativa da fração PAR difusa da PAR global () em função do índice de transmissividade atmosférica ().A base de dados foi adquirida no período de 01/06/1999 a 31/09/2000 na Estação de Radiometria Solar da FCA-UNESP, Botucatu. Foram utilizados dados adicionais, diferentes dos utilizados na geração dos modelos, de forma a possibilitar uma validação adequada dos modelos propostos. UNITERMOS: radiação fotossinteticamente ativa global e difusa, transmissividade atmosférica, modelos de estimativa da radiação solar. GOMES, E.N., ESCOBEDO, J.F MODELS FOR GLOBAL AND DIFFUSE PHOTOSYNTHETICALLY ACTIVE RADIATION IN RELATION TO GLOBAL, DIFFUSE RADIATION AND CLEARNESS INDEX. 2 SUMMARY This work describes typical correlations between global solar radiation () and its global PAR component (), diffuse solar radiation () and its diffuse PAR component (), clearness index () and the diffuse PAR fraction of global PAR (). Database was recorded from June 1st 1999 to September 31st 2000 at the Solar Radiometric Station, Botucatu, SP. Additional data which are not part of the model development were used to validate each proposed model. KEYWORDS: global and diffuse photosynthetically active radiation, clearness index, estimating models.

Download Full-text

A Model for Hourly Solar Radiation Data Generation from Daily Solar Radiation Data Using a Generalized Regression Artificial Neural Network

International Journal of Photoenergy ◽

10.1155/2015/968024 ◽

2015 ◽

Vol 2015 ◽

pp. 1-13 ◽

Cited By ~ 15

Author(s):

Tamer Khatib ◽

Wilfried Elmenreich

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Solar Radiation ◽

Percentage Error ◽

Data Generation ◽

Error Statistics ◽

Radiation Data ◽

Proposed Model ◽

Artificial Neural ◽

Generalized Regression

This paper presents a model for predicting hourly solar radiation data using daily solar radiation averages. The proposed model is a generalized regression artificial neural network. This model has three inputs, namely, mean daily solar radiation, hour angle, and sunset hour angle. The output layer has one node which is mean hourly solar radiation. The training and development of the proposed model are done using MATLAB and 43800 records of hourly global solar radiation. The results show that the proposed model has better prediction accuracy compared to some empirical and statistical models. Two error statistics are used in this research to evaluate the proposed model, namely, mean absolute percentage error and root mean square error. These values for the proposed model are 11.8% and −3.1%, respectively. Finally, the proposed model shows better ability in overcoming the sophistic nature of the solar radiation data.

Download Full-text

Proposal to Refine Solar Radiation of Typical Meteorological Year Database and Evaluation on the Influence of Air-Conditioning Load

Atmosphere ◽

10.3390/atmos12040524 ◽

2021 ◽

Vol 12 (4) ◽

pp. 524

Author(s):

Jihui Yuan ◽

Kazuo Emura ◽

Craig Farnham

Keyword(s):

Solar Radiation ◽

Air Conditioning ◽

Energy Savings ◽

Energy Resource ◽

Global Solar Radiation ◽

Resource Assessment ◽

Weather Data ◽

Diffuse Solar Radiation ◽

Chinese Standard ◽

The Impact

The Typical meteorological year (TMY) database is often used to calculate air-conditioning loads, and it directly affects the building energy savings design. Among four kinds of TMY databases in China—including Chinese Typical Year Weather (CTYW), International Weather for Energy Calculations (IWEC), Solar Wind Energy Resource Assessment (SWERA) and Chinese Standard Weather Data (CSWD)—only CSWD is measures solar radiation, and it is most used in China. However, the solar radiation of CSWD is a measured daily value, and its hourly value is separated by models. It is found that the cloud ratio (diffuse solar radiation divided by global solar radiation) of CSWD is not realistic in months of May, June and July while compared to the other sets of TMY databases. In order to obtain a more accurate cloud ratio of CSWD for air-conditioning load calculation, this study aims to propose a method of refining the cloud ratio of CSWD in Shanghai, China, using observed solar radiation and the Perez model which is a separation model of high accuracy. In addition, the impact of cloud ratio on air-conditioning load has also been discussed in this paper. It is shown that the cloud ratio can yield a significant impact on the air conditioning load.

Download Full-text

Analysis of Experimental Solar Radiation Data for Osogbo, Nigeria

Fountain Journal of Natural and Applied Sciences ◽

10.53704/fujnas.v8i1.296 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Abdulhamid Yusuf ◽

Hakeem Bolarinwa ◽

Lukman Animasahun ◽

Yinusa Babatunde

Keyword(s):

Solar Radiation ◽

Global Solar Radiation ◽

Total Radiation ◽

Wet Season ◽

Annual Average ◽

Percentage Frequency ◽

Monthly Average ◽

Radiation Data ◽

Maximum Value ◽

Daily Total

An analysis of measured global solar radiation (GR) in Osogbo (7.77oN, 4.57oE, 288m) is presented in the form of hourly average, monthly average and percentage frequency distribution. The experimental data corresponds to a year data of 2017. The results reveal that the monthly average values of daily total radiation exhibit seasonal variation with maximum value in dry season month of March (16.59MJ/m2) and minimum value in wet season month of August (8.98 MJ/m2). The annual average GR value is 14.20 MJ/m2 while the annual cumulative GR is 5122 MJ/m2. The solar radiation climate of Osogbo has also been compared to those reported for a number of locations. The percentage frequency of days possessing irradiation rate greater than 15 MJ/m2 is 14 percent whereas that possessing less than 10 MJ/m2 is 61 percent. We conclude, based upon the above analysis that Osogbo is characterized by relatively low global solar radiation.

Download Full-text

An Intelligent Memory Model for Short-Term Prediction: An Application to Global Solar Radiation Data

Trends in Applied Intelligent Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-13033-5_61 ◽

2010 ◽

pp. 596-605

Author(s):

Llanos Mora-Lopez ◽

Juan Mora ◽

Michel Piliougine ◽

Mariano Sidrach-de-Cardona

Keyword(s):

Solar Radiation ◽

Global Solar Radiation ◽

Memory Model ◽

Short Term ◽

Radiation Data ◽

Intelligent Memory ◽

Term Prediction ◽

Short Term Prediction

Download Full-text

Multistep-Ahead Solar Radiation Forecasting Scheme Based on the Light Gradient Boosting Machine: A Case Study of Jeju Island

Remote Sensing ◽

10.3390/rs12142271 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2271 ◽

Cited By ~ 2

Author(s):

Jinwoong Park ◽

Jihoon Moon ◽

Seungmin Jung ◽

Eenjun Hwang

Keyword(s):

Solar Radiation ◽

Global Solar Radiation ◽

Jeju Island ◽

Gradient Boosting ◽

Probabilistic Forecasting ◽

Training Time ◽

Light Gradient ◽

Proposed Model ◽

Gradient Boosting Machine ◽

Time Problem

Smart islands have focused on renewable energy sources, such as solar and wind, to achieve energy self-sufficiency. Because solar photovoltaic (PV) power has the advantage of less noise and easier installation than wind power, it is more flexible in selecting a location for installation. A PV power system can be operated more efficiently by predicting the amount of global solar radiation for solar power generation. Thus far, most studies have addressed day-ahead probabilistic forecasting to predict global solar radiation. However, day-ahead probabilistic forecasting has limitations in responding quickly to sudden changes in the external environment. Although multistep-ahead (MSA) forecasting can be used for this purpose, traditional machine learning models are unsuitable because of the substantial training time. In this paper, we propose an accurate MSA global solar radiation forecasting model based on the light gradient boosting machine (LightGBM), which can handle the training-time problem and provide higher prediction performance compared to other boosting methods. To demonstrate the validity of the proposed model, we conducted a global solar radiation prediction for two regions on Jeju Island, the largest island in South Korea. The experiment results demonstrated that the proposed model can achieve better predictive performance than the tree-based ensemble and deep learning methods.

Download Full-text

Parametrization of Models and Use of Estimated Global Solar Radiation Data in the Irrigated Rice Yield Simulation

Revista Brasileira de Meteorologia ◽

10.1590/0102-7786332003 ◽

2018 ◽

Vol 33 (2) ◽

pp. 238-246

Author(s):

João Rodrigo de Castro ◽

Santiago Vianna Cuadra ◽

Luciana Barros Pinto ◽

João Marcelo Hoffmann de Souza ◽

Marcos Paulo dos Santos ◽

...

Keyword(s):

Solar Radiation ◽

Air Temperature ◽

Rice Yield ◽

Simulation Models ◽

Global Solar Radiation ◽

Empirical Models ◽

Potential Yield ◽

Irrigated Rice ◽

Radiation Data ◽

The Impact

Abstract The objective of this study was to evaluate the use of estimated global solar radiation data in the simulations of potential yield of irrigated rice. Global solar radiation was estimated by four empirical models, based on air temperature, and a meteorological satellite derivated. The empirical models were calibrated and validated for 10 sites, representative of the six rice regions of the State of Rio Grande do Sul - Brazil. To evaluate the impact of the radiation estimates on irrigated rice yield simulations, the CERES-Rice model, calibrated for four cultivars, was used. The estimates of global solar radiation of the empirical models based on the air temperature showed deviations, from the observed values, of 20 to 30% and the estimated by satellite deviations of more than 30%. The global solar radiation data estimated by the Hargreaves and Samani, Donatelli and Campbell and derived satellite (PowerNasa) type air temperature-based empirical models can be used as input data in simulation models of crop growth, development and productivity of irrigated rice.

Download Full-text