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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 5 Issue 5, July-August 2021
@ IJTSRD | Unique Paper ID – IJTSRD
Comparative Studies of the Measured and
Values of Global Solar Radiation for
Nigeria
Nwokoye,
Department of Physics and Industrial Physics
ABSTRACT
This study was aimed at utilizing the monthly mean values of
global solar radiation, sunshine hours, rainfall, wind speed,
atmospheric pressure and cloud cover to develop an empirical
equation for estimation global solar radiation on a horizontal
surface for Awka (6.2 °N, 7.0^°E) for
2013). The regression constants were obtained using regression
analysis and the predicted values of global solar radiation
calculated. The measured values of glo
compared with the predicted using different models. The result
showed that the deviations were minimal. Validation of the results
was tested using MBE, RMSE and MPE. The values of R and R2
were also determined for each model. Of al
parameters: sunshine hours, rainfall, wind speed, atmospheric
pressure and cloud cover used in this study only sunshine hours
was found to have a direct correlation with global solar radiation.
Result obtained show that all the model
good agreement with the measured global solar radiation
considering their MBE, RMSE and MPE values. However,
considering the RMSE, models 5 and 6 gave better predictions of
R which indicate that about 94.8% of variation in the mont
mean solar radiation on a horizontal surface can be accounted for
by the models. Therefore, either model 5 or model 6 can be used
for predicting global solar radiation for Awka and other locations
with similar climate conditions.
KEYWORDS: Solar radiation, sunshine hours, wind speed and root
mean square error
1. INTRODUCTION
Energy certainly is vital in development of the
society. There exists a direct correlation between
the development of a country and its consumption
of energy (Mohammad, 2013). The quantity of
solar energy that reaches the surface of the earth per
hour is greater than quantity used by the Earth’s
population over an entire year and of all the energy
sources available, solar is perhap
promising (Brown, 1988).
Clearly, solar energy is a resource of the future. It is
an ideal, alternative source of energy, abundant and
inexhaustible (Bolaji, 2005). Solar energy is a
renewable resource and is environmentally friendly
Unlike fossil fuels that are only found in selected
regions of the world, it is available just about
International Journal of Trend in Scientific Research and Development (IJTSRD)
August 2021 Available Online: www.ijtsrd.com e
IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug
Comparative Studies of the Measured and Predicted
Values of Global Solar Radiation for Awka,
using Selected Seven Models
Nwokoye, A. O. C.; Mbadugha, A. O.
Department of Physics and Industrial Physics, Nnamdi Azikiwe University,
This study was aimed at utilizing the monthly mean values of
global solar radiation, sunshine hours, rainfall, wind speed,
atmospheric pressure and cloud cover to develop an empirical
solar radiation on a horizontal
surface for Awka (6.2 °N, 7.0^°E) for nine year period (2005 –
2013). The regression constants were obtained using regression
analysis and the predicted values of global solar radiation
The measured values of global solar radiation were
compared with the predicted using different models. The result
showed that the deviations were minimal. Validation of the results
was tested using MBE, RMSE and MPE. The values of R and R2
were also determined for each model. Of all these meteorological
parameters: sunshine hours, rainfall, wind speed, atmospheric
pressure and cloud cover used in this study only sunshine hours
was found to have a direct correlation with global solar radiation.
Result obtained show that all the models except model 4 were in
good agreement with the measured global solar radiation
considering their MBE, RMSE and MPE values. However,
considering the RMSE, models 5 and 6 gave better predictions of
R which indicate that about 94.8% of variation in the monthly
mean solar radiation on a horizontal surface can be accounted for
by the models. Therefore, either model 5 or model 6 can be used
for predicting global solar radiation for Awka and other locations
sunshine hours, wind speed and root
How to cite
O. C. | Mbadugha, A. O. "Comparative
Studies of the Measured and Predicted
Values of Global Solar Radiation for
Awka, Nigeria using Selected Seven
Models" Published
in International
Journal of Trend in
Scientific Research
and Development
(ijtsrd), ISSN:
2456-6470,
Volume-5 | Issue
August 2021, pp.649
www.ijtsrd.com/papers/ijtsrd43919.pdf
Copyright
International
Scientific
Journal. This
Open Access
distributed
the terms
Attribution
(http://creativecommons.org/licenses/by/4.
0)
Energy certainly is vital in development of the
society. There exists a direct correlation between
and its consumption
of energy (Mohammad, 2013). The quantity of
that reaches the surface of the earth per
used by the Earth’s
population over an entire year and of all the energy
sources available, solar is perhaps the most
Clearly, solar energy is a resource of the future. It is
an ideal, alternative source of energy, abundant and
Solar energy is a
renewable resource and is environmentally friendly.
ssil fuels that are only found in selected
regions of the world, it is available just about
everywhere on earth (Duffie and Beckman, 1994).
Because solar energy has been used by human
beings, it has been looked upon as a serious source
of energy for many years due to vast amounts of
energy that are made freely available if harnessed
by modern technology.
Solar energy is received on any surface as solar
radiation but the amount that is received by any
horizontal surface in Nigeria depends on the
geographical latitude of such surface and therefore
varies from place to place (Innocent
In many solar energy applications,
data play vital roles in areas such as in
heating, wood drying, stoves, photovoltaic and is
essential for proper prediction, design and the study
International Journal of Trend in Scientific Research and Development (IJTSRD)
e-ISSN: 2456 – 6470
Aug 2021 Page 649
Predicted
Awka,
sing Selected Seven Models
, Awka, Nigeria
cite this paper: Nwokoye, A.
O. C. | Mbadugha, A. O. "Comparative
Studies of the Measured and Predicted
Values of Global Solar Radiation for
Awka, Nigeria using Selected Seven
Models" Published
in International
Journal of Trend in
Scientific Research
and Development
d), ISSN:
6470,
5 | Issue-5,
August 2021, pp.649-654, URL:
www.ijtsrd.com/papers/ijtsrd43919.pdf
© 2021 by author (s) and
International Journal of Trend in
Research and Development
This is an
Access article
distributed under
of the Creative Commons
Attribution License (CC BY 4.0)
http://creativecommons.org/licenses/by/4.
everywhere on earth (Duffie and Beckman, 1994).
Because solar energy has been used by human
beings, it has been looked upon as a serious source
y years due to vast amounts of
energy that are made freely available if harnessed
Solar energy is received on any surface as solar
radiation but the amount that is received by any
horizontal surface in Nigeria depends on the
cal latitude of such surface and therefore
varies from place to place (Innocent et al., 2015).
solar energy applications, solar radiation
in areas such as in solar water
heating, wood drying, stoves, photovoltaic and is
tial for proper prediction, design and the study
IJTSRD43919
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 650
of energy systems to be installed in that geographic
location. The basic need for the knowledge of the
quantity of solar radiation that can be received and
transformed into useful energy at a given time
interval at a given geographical place or region led
to the need for measuring and maintaining solar
radiation data (Munawwar, 2002).
This measurement of data for a given location can
be obtained by the use of an instrumentsuch as
pyranometer. Due to high cost, maintenance, and
calibration requirement of solar radiation measuring
equipment the stations measuring solar radiation is
sparse in Nigeria (Chineke, 2007).Thus Researchers
in this country, in order to overcome this defect, use
theoretical value of meteorological data toestimate
the global solar radiation with the help of some
models incorporating the available meteorological
parameters as input. The resultant correlation may
then be used for locations of similar meteorological
characteristics (Meduguet al., 2011).
Several models have been used to predict amount of
solar radiation in some places using various
meteorological parameters such as (Okonkwo and
Nwokoye, 2014)
This paper aims at using some solar parameters for
a period of nine year (2005 – 2013), as an
independent variable for the Angstrom-type
correlation, to generate empirical equations for
predicting global solar radiation inAwka Nigeria.
The predicted solar radiation data obtained from
study will be tested for error using the RMSE, MBE
and MPE to compare the measured with the
predicted values. The model with highest value of
Rwill be recommended for predicting global solar
radiation for Awka.
2. METHODLOGY
The most commonly method used in this study was
based on correlation in predicting linear relation
between monthly mean global solar radiation and
clearness index developed by Angstrom (1924) and
modified by Prescott (1940). The Angstrom-
Prescott regression model which forms the basis of
most models used in this study was given by Iqbal
(1983); Ahmads and Tiwari (2010); Gadiwal et al.,
(2013) as:
= a +b ( ) (1)
Hmis the measured inmJ/m2
/day. Ho is the monthly
mean extraterrestrial solar radiation on a horizontal
surface is computed from
Ho = ×13673	× 10 E o 	 	 +
(2)
(Duffie and Beckmann, (1994); Nwokoye (2006),
Okonkwo and Nwokoye (2014).
where
o = 1+0.033cos
	 !
"
# (3)
=23.45 sin 360(
' !
"
)# (4)
(Cooper (1969); Salima and Chavula (2012)
Ws =cos-1)−+, 	+, - (5)
is the latitude of the location in question.
The dn is the characteristic day length for each
month of the year from 1st January to 31st
December (365 days) or (366 days for a leap year).
It is also called Julian day of the month. It was
calculated for fifteen day of the month according to
Iqbal (1983), Duffie and Beckmann (1991) and
Okonkwo and Nwokoye (2014).
The sunshine duration/hours (n) is a
climatologically indicator in a given period for a
given location on Earth. It is a clear indicator of
cloudiness of a place. Sunshine duration is
measured in hours (hrs).
Mean daylength, N for horizontal surface is the
number of hours of sunshine or darkness within 24
hours in a given day. For this study it was
calculated using equation given by(Duffie and
Beckmann (1994) and Umohet al., (2014).
N = "
Ws = "
)−+, .	+, - (6)
Sunshine fraction (n/N) is the ratio of sunshine
duration to the corresponding values of mean day
length. It has no unit. The ‘a’and‘b’ are regression
constants which are determined using a computer
statistical software program, (IBM SPSS 21).The
clearness index, KT is ratio of measured solar
radiation calculated solar radiation. This was
obtained using the equation of this form as:
KT =
Observation showed that clearness index had high
values in clear atmospheres and low values in
cloudy atmosphere and vice-versa.
In this work, the monthly values of sunshine hours,
atmospheric pressure, wind speed, rainfall and
cloud cover are obtained from Nigerian
Meteorological Agency (NIMET), Awka while the
measured solar radiation data used are the one
given by Okonkwo and Nwokoye (2012).
The data covered a period of nine years (2005-
2013) for rainfall, wind speed, cloud cover and
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 651
atmospheric pressure and six years (2008-2013) for
sunshine hours/duration.
3. STATISTICAL METHODS
Satistical test methods used to determine the
proposed models of solar radiation in this
studyinclude, Root Mean Square Error (RMSE),
Mean Bias Error (MBE), Mean Percentage Error
(MPE), Correlation of determination (R2
) and
Coefficient of correlation, (R).
Root Mean Square Error
It is always positive and a low RMSE is desirable.
The RMSE may be computed from the following
equation, Akpabio and Etuk, (2013).
RMSE = [∑ (Hipred - Hi meas)2
/n] ½
(8)
Mean Bias Error
The ideal value of the MBE is zero.. It was
recommended that a zero value for MBE is ideal
Iqbal, (1983). The MBE is given by,
MBE = [∑ (Hi pred – Hi meas]/n (9)
Mean Percentage Error
MPE = [	)/H01234 − H056278/ /H012348 ] /n ] x100
(10)
(Akpabio and Etuk, (2013); Okonkwo and
Nwokoye (2014).
whereHipred and Himeas are the ith predicted and
measured values respectively of solar radiation. n is
the total number of observations.
Coefficient of determination (R2
) AND
Coefficient of correlation(R) were determined
using software programme.
Table1 showed that the highest and lowest rainfall
occurred in August and November respectively.
This was expected since August is characterized by
heavy rainfall .It was also observed that sunshine
fraction was highest in November while the lowest
value occurred in August. This is attributed to the
highest and lowest values of clearness index
obtained for these months, respectively. This again
is expected since according to Augustine and
Nnabuchi (2010), and Okonkwo and Nwokoye
(2014). Again, it was observed that the global solar
radiation was highest in November while the lowest
value occurred in August. Table 2 showed the 7
proposed models for this study while Table 3
displayed the regression constants obtained for each
models.
From the Table 4, it was observed that the values of
the global solar radiation predicted by models 1, 2,
5, 6 and 7 were related to the measured values. The
values predicted by models were either highly
overestimated or underestimated except model 4.
This again was reflected in Table 5, where the MBE
and RMSE values were lowest for all the models 1,
2, 3, 5, 6 and 7. Also the MPE values for these
models were low with the exception of model 4
which indicates overestimation.
Model 4 had the highest MBE, RMSE though with
low MPE values was the worst performed model.
Models 1, 2, 5, 6 and 7 were adequately for
predicting global solar radiation in Awka. Model 4
overestimated the global solar radiation in the
months except December while the other models
either slightly overestimated or slightly
underestimated the global solar radiation.
Therefore, models 5 and 6 were the best models for
Awka.
Table1: Monthly mean solar radiation and solar parameters for Awka, Nigeria (2005 -2013)
Month
9
(hrs)
:
(hrs)
9/:
<
(octas
)
</=
>?
(mm)
@
A
(m/s)
Bm
(mJ/m2
/day)
Bo
(mJ/m2
/
day)
CDm	=
Bm/BO
BP
(mJ/m
2
/day)
KTp=
Hp
/Ho
January 5.080 11.680 0.435 6.870 0.0687 0.800 24.330 9.720 18.320 33.590 0.545 18.94 0.56
February 6.220 11.800 0.527 6.370 0.064 0.800 29.030 9.520 20.010 35.730 0.560 20.28 0.57
March 6.830 11.960 0.488 6.450 0.065 1.790 29.080 8.110 19.980 37.370 0.534 20.71 0.55
April 5.520 12.140 0.455 5.780 0.058 4.820 30.130 8.920 19.820 37.630 0.527 19.85 0.53
May 4.620 12.280 0.376 4.590 0.046 5.260 30.860 7.870 18.880 38.700 0.488 19.59 0.51
June 3.830 12.360 0.310 4.740 0.047 6.110 30.030 7.780 18.250 35.720 0.511 17.27 0.48
July 3.410 12.330 0.277 3.030 0.030 8.080 29.920 9.070 16.470 35.950 0.458 16.54 0.46
August 2.870 12.200 0.235 2.720 0.027 9.000 30.020 9.820 14.960 36.930 0.405 16.24 0.44
September 3.770 12.030 0.313 3.560 0.036 8.070 28.900 8.410 15.720 37.260 0.422 17.60 0.47
October 5.230 11.860 0.441 2.790 0.028 5.700 28.640 6.830 18.760 36.080 0.520 18.88 0.52
November 7.740 11.710 0.661 2.010 0.020 0.500 27.770 5.400 20.140 34.010 0.592 20.54 0.60
December 5.420 11.650 0.465 5.650 0.057 1.200 23.410 7.820 19.220 32.970 0.583 18.37 0.56
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 652
Table 2 shows the various models used
S/N Models
1. =a+ b (n/N)
2. =a+ b(n/N) - c (n/N)2
3. = a + b (c/C) + c (RF)
4. = a + b (n/N) + c (RF)
5. = a + b (RF) + c (W) + d (A)
6. = a + b (n/N) +c (RF) +d(W)
7. = a + b(n/N) +c (A) +d (W)
The M
Nm is monthlymean measured solar radiation, M
Nois monthly mean calculated solar radiation, O/P
N is
monthly mean sunshine fraction, Qis monthly mean atmospheric pressure, /C is monthly mean cloudiness
index, RS is monthly mean rainfall, and is the monthly mean wind speed.
Results and discussions
Table 3 shows Regression equations, (models 1-7) obtained in this study
1. = 0.331 + 0.435 (n/n)
2. = 0.205 + 1.062 (n/N) – 0.723 (n /N)2
3. = 0.615 - 0.488 (C/C	) – 0.019 (RF)
4. = 0.500 + 0.156 (n/N) - 0.012(RF)
5. = 0.676 - 0.016 (RF) − 0.011(w) + 0.000 (A)
6. = 0.663 + 0.008(n/N) - 0.016 (RF) -0.010(w)
7. = 0.547 + 0.384 (n/N)- 0.007(A) – 0.001 (w)
Table 4: Monthly mean measured and predicted values of global solar radiation
Month Hm H1 H2 H3 H4 H5 H6 H7
Jan 18.32 18.37 18.61 19.02 19.34 18.69 18.71 18.73
Feb 20.01 20.02 20.15 20.30 20.75 19.95 19.98 19.18
Mar 19.98 20.29 20.59 20.48 21.39 20.86 20.82 19.53
Apr 19.82 19.90 20.26 18.49 21.12 18.84 18.83 18.88
May 18.88 19.14 19.44 18.90 21.21 19.55 19.47 18.10
Jun 18.25 16.64 16.60 16.82 19.15 17.60 17.50 16.00
Jul 16.47 16.22 15.94 15.83 18.95 16.07 16.01 15.63
Aug 14.96 16.00 15.32 15.64 19.16 15.66 15.61 15.41
Sep 15.72 17.41 17.39 16.31 19.85 16.92 16.85 17.01
Oct 18.76 18.86 19.22 17.63 20.11 18.39 18.29 18.37
Nov 20.14 21.04 20.10 20.25 20.48 20.70 20.62 20.44
Dec 19.22 17.59 17.89 18.58 18.80 18.32 18.77 18.26
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 653
Table 5: Statistical Error Indicators of the Models.
MODEL MBE RMSE MPE R R2
= a + b (n/N) 0.0801 2.2936 -0.6343 0.7740
0.599
= a + b(n/N) - c(n/N)2
-1.4696 2.3312 -0.5507 0.816 0.6659
= a + b(c/C) + c(RF) -0.1899 2.3248 0.9216 0.930 0.864
= a + b(n/N) + c(RF) 1.6480 5.9520 -9.6857 0.935 0.874
= a + b(RF) + c(W) + d(A) 0.1270 2.0872 -0.8169 0.948 0.889
= a + b(n/N) +c(RF) +d(W) 0.0776 2.0853 -0.5403 0.948 0.899
= a + b(n/N) +c(A) +d(W) -0.4159 2.8612 2.0695 0.912 0.832
4. CONCLUSION
The monthly mean global solar radiation, sunshine
hours, rainfall, wind speed, cloud cover) had been
employed to develop the Angstrom-Prescott type
equations (models) had successfully obtained a
model for estimated global solar radiation for Awka
Nigeria.
Result obtained show that all the models except
model 4 were in good agreement with the measured
global solar radiation and gave very good results in
predicting global solar radiation, considering their
MBE, RMSE and MPE values. However,
considering the RMSE, models 5 and 6 gave better
predictions of R which indicate that about 94.8% of
variation in the monthly mean solar radiation on a
horizontal surface can be accounted for by the
models. Therefore, either model 5 or model 6 could
be used for predicting global solar radiation for
Awka.
ACKNOWLEDGEMENTS
We wish to acknowledge the management and staff
of Nigerian Meteorological Agency, Awka for
supplying the solar parameters required for this
study.
REFERENCES
[1] Akpabio, L. E., Udo S. O., Etuk S. E. (2004),
Empirical Correlation of Global Solar
Radiation with Meteorological Data for Onne,
Nigeria, Turkish Journal of Physics, 28: 222-
227.
[2] Angstrom, A. (1924), Solar and Terrestrial
Radiation, Quarterly Journal of
RoaylMeteorogical Society, 50, 121-125.
[3] Arinze, E. A. and Obi, S. E. (1985) Solar
Energy Availability and Prediction in
Northern Nigeria,
[4] Global Solar Radiation with Hours of Bright
Sunshine in Turkey, Energy 34 (4):485–501.
[5] Bolaji, B. O. (2005), Development and
Performance, Evaluation of a Box-type
Absorber solar Air Collector for crop drying,
Journal of food and Technology 3(4): 595.
[6] Brown, E. W. (1988), An Introduction to
Solar Energy, Academic Press, Newyork,
655pp.
[7] Chineke, T. C. (2007), A Comparison of three
Empirical Models for Estimating Solar
Radiation in Nigeria. African Journal of
Sciences and Technology, Series A 11: 45-48.
[8] Cooper, P. I. (1969), The Absorption of
Radiation in Solar Stills, Solar Energy, 12:
333-346.
[9] Duffie, J. A. and Beckman, W. A. (1994),
Solar Engineering of Thermal Processes, John
Wiley, New York, U. S. A. 2nd Edn. pp. 234-
367.
[10] Ekpe, J. E. and Nnabuchi, M. N. (2012), Solar
Radiation in Onitsha. A Correlation with
Average Temperature, Nigeria Journal of
Solar Energy, 2(6):65-69
[11] Falayi, E. O and A. B. Rabiu, 2012. Solar
Radiation and Information for Renewable
Energy Energy, 2(4/5): 401–404.
[12] Iqbal, M. (1983), An Introduction to Solar
Radiation, Academic Press Canada, pp 91 -
94.
[13] Medugu, D. W. and Yakubu, D. (2011),
Estimation of the Mean Monthly Global Solar
Radiation in Yola, Nigeria using Angstrom
Model Advances in Applied Science,
Reaserch 2(2): 414-421.
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 654
[14] Mohammed Arif, S. B. (2013), Estimation of
Solar Radiation: An Empirical Model for
Bangladesh, Ilum Engineering Journal, 14
(1): 101-117.
[15] Muneer, T; Younes, S; and Munawar, S.
(2007), Discourses on Solar Radiation
Modeling, Renewable and Sustainable Energy
Reviews, 11 (4): 551-602.
[16] Nwokoye, A. O. C. (2006), Solar Energy
Technology, other Alternative Energy
Resources and Environmental Sciences, Rex
Charles and Patrick Lt, Nimo, 426pp.
[17] Okonkwo, G. N. and Nwokoye, A. O. C.
(2012), Solar Radiation Analysis and
Temperature Profiles of Thermosyphon Solar
Water Heater at Awka, Nigeria, Advances in
Natural and Applied Sciences, 6(2): 185 -194.
[18] Okonkwo, G. N. and Nwokoye, A. O. C.
(2014), Relationship between Global Solar
Radiation and Sunshine Hour Duration for
Bida in Nigeria, International Journal of
Renewable and Sustainble Energy, 3(2):43-
46.
[19] Prescott, J. A. (1940), Evaporation from a
Water Surface in Relation to Solar Radiation,
Transportation R. Soc. S. Australia 64: 114-
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[20] Salima, G. G. and Chavula, M. S. (2012),
Determining Angstrom Constants for
Estimating Solar Radiation in Malawi,
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[21] Umoh, M., Udo S. O. and Udoakah Y. N.
(2014), Estimating Global Solar Radiation on
Horizontal Surface from Sunshine Hours over
Porth Harcourt Nigeria Journal of Electrical
and Electronics Engineering Research, 6 (1):1
– 5.

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Comparative Studies of the Measured and Predicted Values of Global Solar Radiation for Awka, Nigeria using Selected Seven Models

  • 1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume 5 Issue 5, July-August 2021 @ IJTSRD | Unique Paper ID – IJTSRD Comparative Studies of the Measured and Values of Global Solar Radiation for Nigeria Nwokoye, Department of Physics and Industrial Physics ABSTRACT This study was aimed at utilizing the monthly mean values of global solar radiation, sunshine hours, rainfall, wind speed, atmospheric pressure and cloud cover to develop an empirical equation for estimation global solar radiation on a horizontal surface for Awka (6.2 °N, 7.0^°E) for 2013). The regression constants were obtained using regression analysis and the predicted values of global solar radiation calculated. The measured values of glo compared with the predicted using different models. The result showed that the deviations were minimal. Validation of the results was tested using MBE, RMSE and MPE. The values of R and R2 were also determined for each model. Of al parameters: sunshine hours, rainfall, wind speed, atmospheric pressure and cloud cover used in this study only sunshine hours was found to have a direct correlation with global solar radiation. Result obtained show that all the model good agreement with the measured global solar radiation considering their MBE, RMSE and MPE values. However, considering the RMSE, models 5 and 6 gave better predictions of R which indicate that about 94.8% of variation in the mont mean solar radiation on a horizontal surface can be accounted for by the models. Therefore, either model 5 or model 6 can be used for predicting global solar radiation for Awka and other locations with similar climate conditions. KEYWORDS: Solar radiation, sunshine hours, wind speed and root mean square error 1. INTRODUCTION Energy certainly is vital in development of the society. There exists a direct correlation between the development of a country and its consumption of energy (Mohammad, 2013). The quantity of solar energy that reaches the surface of the earth per hour is greater than quantity used by the Earth’s population over an entire year and of all the energy sources available, solar is perhap promising (Brown, 1988). Clearly, solar energy is a resource of the future. It is an ideal, alternative source of energy, abundant and inexhaustible (Bolaji, 2005). Solar energy is a renewable resource and is environmentally friendly Unlike fossil fuels that are only found in selected regions of the world, it is available just about International Journal of Trend in Scientific Research and Development (IJTSRD) August 2021 Available Online: www.ijtsrd.com e IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug Comparative Studies of the Measured and Predicted Values of Global Solar Radiation for Awka, using Selected Seven Models Nwokoye, A. O. C.; Mbadugha, A. O. Department of Physics and Industrial Physics, Nnamdi Azikiwe University, This study was aimed at utilizing the monthly mean values of global solar radiation, sunshine hours, rainfall, wind speed, atmospheric pressure and cloud cover to develop an empirical solar radiation on a horizontal surface for Awka (6.2 °N, 7.0^°E) for nine year period (2005 – 2013). The regression constants were obtained using regression analysis and the predicted values of global solar radiation The measured values of global solar radiation were compared with the predicted using different models. The result showed that the deviations were minimal. Validation of the results was tested using MBE, RMSE and MPE. The values of R and R2 were also determined for each model. Of all these meteorological parameters: sunshine hours, rainfall, wind speed, atmospheric pressure and cloud cover used in this study only sunshine hours was found to have a direct correlation with global solar radiation. Result obtained show that all the models except model 4 were in good agreement with the measured global solar radiation considering their MBE, RMSE and MPE values. However, considering the RMSE, models 5 and 6 gave better predictions of R which indicate that about 94.8% of variation in the monthly mean solar radiation on a horizontal surface can be accounted for by the models. Therefore, either model 5 or model 6 can be used for predicting global solar radiation for Awka and other locations sunshine hours, wind speed and root How to cite O. C. | Mbadugha, A. O. "Comparative Studies of the Measured and Predicted Values of Global Solar Radiation for Awka, Nigeria using Selected Seven Models" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue August 2021, pp.649 www.ijtsrd.com/papers/ijtsrd43919.pdf Copyright International Scientific Journal. This Open Access distributed the terms Attribution (http://creativecommons.org/licenses/by/4. 0) Energy certainly is vital in development of the society. There exists a direct correlation between and its consumption of energy (Mohammad, 2013). The quantity of that reaches the surface of the earth per used by the Earth’s population over an entire year and of all the energy sources available, solar is perhaps the most Clearly, solar energy is a resource of the future. It is an ideal, alternative source of energy, abundant and Solar energy is a renewable resource and is environmentally friendly. ssil fuels that are only found in selected regions of the world, it is available just about everywhere on earth (Duffie and Beckman, 1994). Because solar energy has been used by human beings, it has been looked upon as a serious source of energy for many years due to vast amounts of energy that are made freely available if harnessed by modern technology. Solar energy is received on any surface as solar radiation but the amount that is received by any horizontal surface in Nigeria depends on the geographical latitude of such surface and therefore varies from place to place (Innocent In many solar energy applications, data play vital roles in areas such as in heating, wood drying, stoves, photovoltaic and is essential for proper prediction, design and the study International Journal of Trend in Scientific Research and Development (IJTSRD) e-ISSN: 2456 – 6470 Aug 2021 Page 649 Predicted Awka, sing Selected Seven Models , Awka, Nigeria cite this paper: Nwokoye, A. O. C. | Mbadugha, A. O. "Comparative Studies of the Measured and Predicted Values of Global Solar Radiation for Awka, Nigeria using Selected Seven Models" Published in International Journal of Trend in Scientific Research and Development d), ISSN: 6470, 5 | Issue-5, August 2021, pp.649-654, URL: www.ijtsrd.com/papers/ijtsrd43919.pdf © 2021 by author (s) and International Journal of Trend in Research and Development This is an Access article distributed under of the Creative Commons Attribution License (CC BY 4.0) http://creativecommons.org/licenses/by/4. everywhere on earth (Duffie and Beckman, 1994). Because solar energy has been used by human beings, it has been looked upon as a serious source y years due to vast amounts of energy that are made freely available if harnessed Solar energy is received on any surface as solar radiation but the amount that is received by any horizontal surface in Nigeria depends on the cal latitude of such surface and therefore varies from place to place (Innocent et al., 2015). solar energy applications, solar radiation in areas such as in solar water heating, wood drying, stoves, photovoltaic and is tial for proper prediction, design and the study IJTSRD43919
  • 2. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 650 of energy systems to be installed in that geographic location. The basic need for the knowledge of the quantity of solar radiation that can be received and transformed into useful energy at a given time interval at a given geographical place or region led to the need for measuring and maintaining solar radiation data (Munawwar, 2002). This measurement of data for a given location can be obtained by the use of an instrumentsuch as pyranometer. Due to high cost, maintenance, and calibration requirement of solar radiation measuring equipment the stations measuring solar radiation is sparse in Nigeria (Chineke, 2007).Thus Researchers in this country, in order to overcome this defect, use theoretical value of meteorological data toestimate the global solar radiation with the help of some models incorporating the available meteorological parameters as input. The resultant correlation may then be used for locations of similar meteorological characteristics (Meduguet al., 2011). Several models have been used to predict amount of solar radiation in some places using various meteorological parameters such as (Okonkwo and Nwokoye, 2014) This paper aims at using some solar parameters for a period of nine year (2005 – 2013), as an independent variable for the Angstrom-type correlation, to generate empirical equations for predicting global solar radiation inAwka Nigeria. The predicted solar radiation data obtained from study will be tested for error using the RMSE, MBE and MPE to compare the measured with the predicted values. The model with highest value of Rwill be recommended for predicting global solar radiation for Awka. 2. METHODLOGY The most commonly method used in this study was based on correlation in predicting linear relation between monthly mean global solar radiation and clearness index developed by Angstrom (1924) and modified by Prescott (1940). The Angstrom- Prescott regression model which forms the basis of most models used in this study was given by Iqbal (1983); Ahmads and Tiwari (2010); Gadiwal et al., (2013) as: = a +b ( ) (1) Hmis the measured inmJ/m2 /day. Ho is the monthly mean extraterrestrial solar radiation on a horizontal surface is computed from Ho = ×13673 × 10 E o + (2) (Duffie and Beckmann, (1994); Nwokoye (2006), Okonkwo and Nwokoye (2014). where o = 1+0.033cos ! " # (3) =23.45 sin 360( ' ! " )# (4) (Cooper (1969); Salima and Chavula (2012) Ws =cos-1)−+, +, - (5) is the latitude of the location in question. The dn is the characteristic day length for each month of the year from 1st January to 31st December (365 days) or (366 days for a leap year). It is also called Julian day of the month. It was calculated for fifteen day of the month according to Iqbal (1983), Duffie and Beckmann (1991) and Okonkwo and Nwokoye (2014). The sunshine duration/hours (n) is a climatologically indicator in a given period for a given location on Earth. It is a clear indicator of cloudiness of a place. Sunshine duration is measured in hours (hrs). Mean daylength, N for horizontal surface is the number of hours of sunshine or darkness within 24 hours in a given day. For this study it was calculated using equation given by(Duffie and Beckmann (1994) and Umohet al., (2014). N = " Ws = " )−+, . +, - (6) Sunshine fraction (n/N) is the ratio of sunshine duration to the corresponding values of mean day length. It has no unit. The ‘a’and‘b’ are regression constants which are determined using a computer statistical software program, (IBM SPSS 21).The clearness index, KT is ratio of measured solar radiation calculated solar radiation. This was obtained using the equation of this form as: KT = Observation showed that clearness index had high values in clear atmospheres and low values in cloudy atmosphere and vice-versa. In this work, the monthly values of sunshine hours, atmospheric pressure, wind speed, rainfall and cloud cover are obtained from Nigerian Meteorological Agency (NIMET), Awka while the measured solar radiation data used are the one given by Okonkwo and Nwokoye (2012). The data covered a period of nine years (2005- 2013) for rainfall, wind speed, cloud cover and
  • 3. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 651 atmospheric pressure and six years (2008-2013) for sunshine hours/duration. 3. STATISTICAL METHODS Satistical test methods used to determine the proposed models of solar radiation in this studyinclude, Root Mean Square Error (RMSE), Mean Bias Error (MBE), Mean Percentage Error (MPE), Correlation of determination (R2 ) and Coefficient of correlation, (R). Root Mean Square Error It is always positive and a low RMSE is desirable. The RMSE may be computed from the following equation, Akpabio and Etuk, (2013). RMSE = [∑ (Hipred - Hi meas)2 /n] ½ (8) Mean Bias Error The ideal value of the MBE is zero.. It was recommended that a zero value for MBE is ideal Iqbal, (1983). The MBE is given by, MBE = [∑ (Hi pred – Hi meas]/n (9) Mean Percentage Error MPE = [ )/H01234 − H056278/ /H012348 ] /n ] x100 (10) (Akpabio and Etuk, (2013); Okonkwo and Nwokoye (2014). whereHipred and Himeas are the ith predicted and measured values respectively of solar radiation. n is the total number of observations. Coefficient of determination (R2 ) AND Coefficient of correlation(R) were determined using software programme. Table1 showed that the highest and lowest rainfall occurred in August and November respectively. This was expected since August is characterized by heavy rainfall .It was also observed that sunshine fraction was highest in November while the lowest value occurred in August. This is attributed to the highest and lowest values of clearness index obtained for these months, respectively. This again is expected since according to Augustine and Nnabuchi (2010), and Okonkwo and Nwokoye (2014). Again, it was observed that the global solar radiation was highest in November while the lowest value occurred in August. Table 2 showed the 7 proposed models for this study while Table 3 displayed the regression constants obtained for each models. From the Table 4, it was observed that the values of the global solar radiation predicted by models 1, 2, 5, 6 and 7 were related to the measured values. The values predicted by models were either highly overestimated or underestimated except model 4. This again was reflected in Table 5, where the MBE and RMSE values were lowest for all the models 1, 2, 3, 5, 6 and 7. Also the MPE values for these models were low with the exception of model 4 which indicates overestimation. Model 4 had the highest MBE, RMSE though with low MPE values was the worst performed model. Models 1, 2, 5, 6 and 7 were adequately for predicting global solar radiation in Awka. Model 4 overestimated the global solar radiation in the months except December while the other models either slightly overestimated or slightly underestimated the global solar radiation. Therefore, models 5 and 6 were the best models for Awka. Table1: Monthly mean solar radiation and solar parameters for Awka, Nigeria (2005 -2013) Month 9 (hrs) : (hrs) 9/: < (octas ) </= >? (mm) @ A (m/s) Bm (mJ/m2 /day) Bo (mJ/m2 / day) CDm = Bm/BO BP (mJ/m 2 /day) KTp= Hp /Ho January 5.080 11.680 0.435 6.870 0.0687 0.800 24.330 9.720 18.320 33.590 0.545 18.94 0.56 February 6.220 11.800 0.527 6.370 0.064 0.800 29.030 9.520 20.010 35.730 0.560 20.28 0.57 March 6.830 11.960 0.488 6.450 0.065 1.790 29.080 8.110 19.980 37.370 0.534 20.71 0.55 April 5.520 12.140 0.455 5.780 0.058 4.820 30.130 8.920 19.820 37.630 0.527 19.85 0.53 May 4.620 12.280 0.376 4.590 0.046 5.260 30.860 7.870 18.880 38.700 0.488 19.59 0.51 June 3.830 12.360 0.310 4.740 0.047 6.110 30.030 7.780 18.250 35.720 0.511 17.27 0.48 July 3.410 12.330 0.277 3.030 0.030 8.080 29.920 9.070 16.470 35.950 0.458 16.54 0.46 August 2.870 12.200 0.235 2.720 0.027 9.000 30.020 9.820 14.960 36.930 0.405 16.24 0.44 September 3.770 12.030 0.313 3.560 0.036 8.070 28.900 8.410 15.720 37.260 0.422 17.60 0.47 October 5.230 11.860 0.441 2.790 0.028 5.700 28.640 6.830 18.760 36.080 0.520 18.88 0.52 November 7.740 11.710 0.661 2.010 0.020 0.500 27.770 5.400 20.140 34.010 0.592 20.54 0.60 December 5.420 11.650 0.465 5.650 0.057 1.200 23.410 7.820 19.220 32.970 0.583 18.37 0.56
  • 4. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 652 Table 2 shows the various models used S/N Models 1. =a+ b (n/N) 2. =a+ b(n/N) - c (n/N)2 3. = a + b (c/C) + c (RF) 4. = a + b (n/N) + c (RF) 5. = a + b (RF) + c (W) + d (A) 6. = a + b (n/N) +c (RF) +d(W) 7. = a + b(n/N) +c (A) +d (W) The M Nm is monthlymean measured solar radiation, M Nois monthly mean calculated solar radiation, O/P N is monthly mean sunshine fraction, Qis monthly mean atmospheric pressure, /C is monthly mean cloudiness index, RS is monthly mean rainfall, and is the monthly mean wind speed. Results and discussions Table 3 shows Regression equations, (models 1-7) obtained in this study 1. = 0.331 + 0.435 (n/n) 2. = 0.205 + 1.062 (n/N) – 0.723 (n /N)2 3. = 0.615 - 0.488 (C/C ) – 0.019 (RF) 4. = 0.500 + 0.156 (n/N) - 0.012(RF) 5. = 0.676 - 0.016 (RF) − 0.011(w) + 0.000 (A) 6. = 0.663 + 0.008(n/N) - 0.016 (RF) -0.010(w) 7. = 0.547 + 0.384 (n/N)- 0.007(A) – 0.001 (w) Table 4: Monthly mean measured and predicted values of global solar radiation Month Hm H1 H2 H3 H4 H5 H6 H7 Jan 18.32 18.37 18.61 19.02 19.34 18.69 18.71 18.73 Feb 20.01 20.02 20.15 20.30 20.75 19.95 19.98 19.18 Mar 19.98 20.29 20.59 20.48 21.39 20.86 20.82 19.53 Apr 19.82 19.90 20.26 18.49 21.12 18.84 18.83 18.88 May 18.88 19.14 19.44 18.90 21.21 19.55 19.47 18.10 Jun 18.25 16.64 16.60 16.82 19.15 17.60 17.50 16.00 Jul 16.47 16.22 15.94 15.83 18.95 16.07 16.01 15.63 Aug 14.96 16.00 15.32 15.64 19.16 15.66 15.61 15.41 Sep 15.72 17.41 17.39 16.31 19.85 16.92 16.85 17.01 Oct 18.76 18.86 19.22 17.63 20.11 18.39 18.29 18.37 Nov 20.14 21.04 20.10 20.25 20.48 20.70 20.62 20.44 Dec 19.22 17.59 17.89 18.58 18.80 18.32 18.77 18.26
  • 5. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 653 Table 5: Statistical Error Indicators of the Models. MODEL MBE RMSE MPE R R2 = a + b (n/N) 0.0801 2.2936 -0.6343 0.7740 0.599 = a + b(n/N) - c(n/N)2 -1.4696 2.3312 -0.5507 0.816 0.6659 = a + b(c/C) + c(RF) -0.1899 2.3248 0.9216 0.930 0.864 = a + b(n/N) + c(RF) 1.6480 5.9520 -9.6857 0.935 0.874 = a + b(RF) + c(W) + d(A) 0.1270 2.0872 -0.8169 0.948 0.889 = a + b(n/N) +c(RF) +d(W) 0.0776 2.0853 -0.5403 0.948 0.899 = a + b(n/N) +c(A) +d(W) -0.4159 2.8612 2.0695 0.912 0.832 4. CONCLUSION The monthly mean global solar radiation, sunshine hours, rainfall, wind speed, cloud cover) had been employed to develop the Angstrom-Prescott type equations (models) had successfully obtained a model for estimated global solar radiation for Awka Nigeria. Result obtained show that all the models except model 4 were in good agreement with the measured global solar radiation and gave very good results in predicting global solar radiation, considering their MBE, RMSE and MPE values. However, considering the RMSE, models 5 and 6 gave better predictions of R which indicate that about 94.8% of variation in the monthly mean solar radiation on a horizontal surface can be accounted for by the models. Therefore, either model 5 or model 6 could be used for predicting global solar radiation for Awka. ACKNOWLEDGEMENTS We wish to acknowledge the management and staff of Nigerian Meteorological Agency, Awka for supplying the solar parameters required for this study. REFERENCES [1] Akpabio, L. E., Udo S. O., Etuk S. E. (2004), Empirical Correlation of Global Solar Radiation with Meteorological Data for Onne, Nigeria, Turkish Journal of Physics, 28: 222- 227. [2] Angstrom, A. (1924), Solar and Terrestrial Radiation, Quarterly Journal of RoaylMeteorogical Society, 50, 121-125. [3] Arinze, E. A. and Obi, S. E. (1985) Solar Energy Availability and Prediction in Northern Nigeria, [4] Global Solar Radiation with Hours of Bright Sunshine in Turkey, Energy 34 (4):485–501. [5] Bolaji, B. O. (2005), Development and Performance, Evaluation of a Box-type Absorber solar Air Collector for crop drying, Journal of food and Technology 3(4): 595. [6] Brown, E. W. (1988), An Introduction to Solar Energy, Academic Press, Newyork, 655pp. [7] Chineke, T. C. (2007), A Comparison of three Empirical Models for Estimating Solar Radiation in Nigeria. African Journal of Sciences and Technology, Series A 11: 45-48. [8] Cooper, P. I. (1969), The Absorption of Radiation in Solar Stills, Solar Energy, 12: 333-346. [9] Duffie, J. A. and Beckman, W. A. (1994), Solar Engineering of Thermal Processes, John Wiley, New York, U. S. A. 2nd Edn. pp. 234- 367. [10] Ekpe, J. E. and Nnabuchi, M. N. (2012), Solar Radiation in Onitsha. A Correlation with Average Temperature, Nigeria Journal of Solar Energy, 2(6):65-69 [11] Falayi, E. O and A. B. Rabiu, 2012. Solar Radiation and Information for Renewable Energy Energy, 2(4/5): 401–404. [12] Iqbal, M. (1983), An Introduction to Solar Radiation, Academic Press Canada, pp 91 - 94. [13] Medugu, D. W. and Yakubu, D. (2011), Estimation of the Mean Monthly Global Solar Radiation in Yola, Nigeria using Angstrom Model Advances in Applied Science, Reaserch 2(2): 414-421.
  • 6. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD43919 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 654 [14] Mohammed Arif, S. B. (2013), Estimation of Solar Radiation: An Empirical Model for Bangladesh, Ilum Engineering Journal, 14 (1): 101-117. [15] Muneer, T; Younes, S; and Munawar, S. (2007), Discourses on Solar Radiation Modeling, Renewable and Sustainable Energy Reviews, 11 (4): 551-602. [16] Nwokoye, A. O. C. (2006), Solar Energy Technology, other Alternative Energy Resources and Environmental Sciences, Rex Charles and Patrick Lt, Nimo, 426pp. [17] Okonkwo, G. N. and Nwokoye, A. O. C. (2012), Solar Radiation Analysis and Temperature Profiles of Thermosyphon Solar Water Heater at Awka, Nigeria, Advances in Natural and Applied Sciences, 6(2): 185 -194. [18] Okonkwo, G. N. and Nwokoye, A. O. C. (2014), Relationship between Global Solar Radiation and Sunshine Hour Duration for Bida in Nigeria, International Journal of Renewable and Sustainble Energy, 3(2):43- 46. [19] Prescott, J. A. (1940), Evaporation from a Water Surface in Relation to Solar Radiation, Transportation R. Soc. S. Australia 64: 114- 118. [20] Salima, G. G. and Chavula, M. S. (2012), Determining Angstrom Constants for Estimating Solar Radiation in Malawi, International Journal of Geosciences, 3: 391- 397. [21] Umoh, M., Udo S. O. and Udoakah Y. N. (2014), Estimating Global Solar Radiation on Horizontal Surface from Sunshine Hours over Porth Harcourt Nigeria Journal of Electrical and Electronics Engineering Research, 6 (1):1 – 5.