New Temperature Dependent Models for Estimating Global Solar Radiation across the Coastal Climatic Zone of Nigeria

Akpootu, D. O.; Tijjani, Bashir; Gana, Usman M.

doi:10.31695/ijasre.2019.33523

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…The phase space construction which represents the state of any real-world systems taking into consideration the dynamics emanating from the set of its state variable is plotted in Fig.(3). The PSR for the four regions between 2005-2016 were plotted using equation (14). The phase plots motions exhibit random-like and concentrated points at the center which indicates evidence of chaos.…”

Section: Resultsmentioning

confidence: 99%

Chaotic Signatures and Global Solar Radiation model estimate over Nigeria, a Tropical region

Adelakun

2020

Preprint

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Abstract. In a tropical region like Nigeria, accurate estimation and chaotic signatures of global solar radiation (Rs) are essential to the design of solar energy utilization systems in PV technology companies and one of the plant growth determinants in Agriculture. The Rs model is a function of solar declination angle, temperature difference, and relative humidity. In this paper, the daily re-analyzed atmospheric data obtained from the archive of ERA-Interim was used to estimate the nonlinear Global Solar radiation model and investigated chaotic signatures across the tropical climatic regions of Nigeria. The well-known statistical tools were used to analyze the chosen meteorological parameters and the correlation was found to be perfect, close with low values of RMSE across the selected regions over Nigeria. For proper modeling and prediction of the underlying dynamics, the extensive chaotic measures of phase space reconstruction using recurrence plots and recurrence quantification analyses are also presented, analyzed and discussed with the appropriate choice of embedded dimension, m, and time delay τ. The radiant energy from the sun is one of the most available and renewable resources across the season in a tropical region like Nigeria. The information, therefore, suggests how vital the solar irradiance can be useful in Agriculture and Photovoltaic technology companies. Based on the scarcely gauged of global solar radiation (GSR) at meteorological stations in developing countries. This demand necessitates a better understanding of the underlying dynamics for better prediction mostly by the nonlinear Global Solar radiation model estimate and chaotic signature measurement. The optimum usage of meteorological parameters such as solar radiation, relative humidity and temperature difference needs further studies, using RPs and RQA measures. However, several data such as rainfall data, geomagnetic data, ionospheric data, wind speed data etc obtained from different parts of the world have been estimated with several models and applied to RQA measures for better prediction and modeling. Using RPs and RQA, features due to external effects such as harmattan and intertropical discontinuity (ITD) on solar radiation data in this tropical region were uniquely identified. Meanwhile, the inverse characteristic behavior of solar radiation and relative humidity were vividly maintained. The results show a very low value of RMSE while the value of R2 is very closed to 1, which depicts a good prediction for all locations. However, the highest values of both SSE and RMSE, as well as the lowest value of R2 were observed in kano station, which indicates high solar irradiance location. The RPs reviewed the observed clusters points around the parallel diagonal lines with short segments, which implies the presence of chaos. Additional complex measure, the RQA also shows that the solar radiation during the dry season of the months has lower values of Lmax, determinism and entropy, and higher values during the wet season of the months.

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Section: Resultsmentioning

confidence: 99%

Chaotic Signatures and Global Solar Radiation model estimate over Nigeria, a Tropical region

Adelakun

2020

Preprint

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“…The magnitudes of RMSE values are useful to identify model performance but not of under or overestimation by individual model [23]. The peak value for RMSE is zero or 0.0≤ RMSE [24] is given by the equation [25][26][27][28][29][30][31][32][33]:…”

Section: Root Mean Square Error (Rmse)mentioning

confidence: 99%

A Comparative Study for Estimating Reference Evapotranspiration Models over Kano, Nigeria

Abdulsalam,

Akpootu,

Aliyu

et al. 2023

JENRR

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The major factor faced by Agricultural activities is water scarcity. Water is very essential in Agricultural activities (plantation), crop acquires water naturally by precipitation and subsurface moisture, when the supply of water is inadequate for crop use, mostly results to irrigation. This present study estimates and compares six various universally accepted models for estimating reference evapotranspiration (ET0) for Kano situated in the Sahelian climatic zone of Nigeria using measured meteorological parameters of monthly average daily global solar radiation, sunshine hour, wind speed, minimum and maximum temperatures and relative humidity covering a period of thirty one years (1988 – 2018). Four different statistical validation indices of Root Mean Square Error (RMSE), Mean Bias Error (MBE), Mean Absolute Error (MAE) and coefficient of correlation (R) were carried out to test the accuracy of the evaluated models. The result indicated that high value of ETo was found in the month of April with 10.0256 mm/day for Kano and a low value was found to be in August with 5.0804 mm/day for Kano. The Blaney – Morin Nigeria model was found more accurate for Kano with RMSE, MBE, MAE and R values as 1.5078 mm/day, -1.4634 mm/day, 1.4634 mm/day and 0.9790 respectively.

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New Models for Estimation of Diffuse Solar Radiation Using Meteorological Parameters for Benin, Nigeria

Salifu,

Hamza,

Akpootu

et al. 2024

FJS

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In this comprehensive study, an extensive 22-year dataset (2001-2022) for Benin (Latitude 6.32 oN, Longitude 5.10 oE and 77.80 m above sea level) were obtained from the National Aeronautic Space Administration (NASA) website. The datasets comprises of the monthly average daily global solar radiation, diffuse solar radiation, relative humidity, atmospheric pressure, wind speed, and mean temperature, was utilized to develop 19 new models for estimating diffuse solar radiation. These models were categorized into five distinct groups: modified Page, Liu and Jordan models; clearness index and one-variable models; two-variable models; three-variable models, and a four-variable model. These models were statistically evaluated using a set of five validation indices—Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t-test, and the coefficient of determination (R²). The study identified the most effective models in each category. Equation 28b from the modified Page, Liu and Jordan category, Equation 28f from the clearness index and one-variable models, Equation 28j from the two-variable models, and Equation 28o from the three-variable models category were found to be the best-performing models. A comparative assessment of these performed models revealed that the quadratic regression model (Equation 28b) stood out as the most suitable for accurately estimating diffuse solar radiation in Benin. This implies that the developed model equation 28b can be used to estimate the diffuse solar radiation for Benin and locations with similar climatic conditions

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New Temperature Dependent Models for Estimating Global Solar Radiation across the Coastal Climatic Zone of Nigeria

Cited by 4 publications

References 8 publications

Chaotic Signatures and Global Solar Radiation model estimate over Nigeria, a Tropical region

Chaotic Signatures and Global Solar Radiation model estimate over Nigeria, a Tropical region

A Comparative Study for Estimating Reference Evapotranspiration Models over Kano, Nigeria

New Models for Estimation of Diffuse Solar Radiation Using Meteorological Parameters for Benin, Nigeria

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