SlideShare a Scribd company logo
1 of 8
Download to read offline
International Journal of Electrical and Computer Engineering (IJECE)
Vol. 10, No. 2, April 2020, pp. 1200~1207
ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1200-1207  1200
Journal homepage: http://ijece.iaescore.com/index.php/IJECE
Effect analysis of the different channel length and depth of
photovoltaic thermal system with ∇-groove collector
Saprizal Hadisaputra1
, Muhammad Zohri2
, Bahtiar3
, Ahmad Fudholi4
1
Faculty of Science and Education, University of Mataram, Indonesia
2,3
Department of Physic Education, Universitas Islam Negeri (UIN) Mataram, Indonesia
2,4
Solar Energy Research Institute, Universiti Kebangsaan Malaysia, Malaysia
Article Info ABSTRACT
Article history:
Received May 8, 2019
Revised Oct 1, 2019
Accepted Oct 17, 2019
The converted Solar energy as electrical and thermal energy was named
photovoltaic thermal (PVT). The aim of this study is to the analysis of
different length and depth channel effect of photovoltaic thermal with
∇-groove collector by a mathematical model. The matrix inversion was used
to analyze the energy balance equation. Simulation results were conducted
below the solar intensity of 800 W/m2
and mass flow rate between 0.0069
kg/s and 0.0491 kg/s. Electrical and thermal efficiency was done to assess
the effect of different length and channel depth of PVT system with ∇-groove
collector. The effect of different length and depth of ∇-groove collector for
electrical and thermal performance is caused by changed mass flow rate.
The effect Increasing of the mass flow rate of collector increased the thermal
and electrical performance of the ∇-groove collector.
Keywords:
Depth
Electrical
Length
Mathematical model
Thermal Copyright © 2020 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Muhammad Zohri,
Department of physic education,
Universitas Islam Negeri (UIN) Mataram,
Indonesia.
Email: zohri.ukm@gmail.com
1. INTRODUCTION
Solar energy is one of renewable energy which has characteristic sanitary and harmless and
sustainable. The conversion of solar energy to thermal and electrical energy is called Photovoltaic thermal
(PVT) system. The PVT system is a combination of photovoltaic and solar collector technology. The over
heat from PV panel is removed by air as medium cooling [1]. The performance of PVT system is excessive
total energy transformation efficiency. The enactment and financial effectiveness of PVT system be
contingent of numerous scheme parameters for example collector design shape, collector dimension,
collector penetration, amount of collectors, Photovoltaic module form , glazed and unglazed collector,
focused solar intensity [2].
Many studies of the photovoltaic thermal system with collector have been done by The theoretical
and experimental assessment in last decades. Zohri et al. [3] have developed mathematical modeling of
photovoltaic thermal with v-groove. The electrical and thermal efficiency have been compared with other
design collectors. The use of v-groove was the higher efficiency than other design collectors. Zohri et al. [4]
have done energy and exergy analyses of photovoltaic thermal with fins collector with theoretical approach.
The use of fins collector is higher energy and exergy efficiency than without fins collector. Zohri et al. [5]
have done developed performances analysis of photovoltaic thermal with and without fins collector.
The energy performance of fins collector was very good than without fins collector. The theoretical approach
or mathematical model of photovoltaic thermal with and without v-groove collector have been conducted by
Zohri et al. [6]. the exergy performance results showed that using of v-groove collector be able to increase
the exergy efficiency.
Int J Elec & Comp Eng ISSN: 2088-8708 
Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra)
1201
Kumari and Babu [7] have analyzed the photovoltaic cell using the Matlab-Simulink situation with
theoretical study. The objective of this study was to the discovery of nonlinear I-V equation. The best of I-V
equation for the single-diode photovoltaic model counting the effect of the sequence and similar
confrontations was found. Aminullah et al. [8] have conducted the influence analysis of solar intensity and
combination of photovoltaic generator to power quality. The yield of dual adjusted passive sieve able to
increase voltage and current THD grid. Sharma et al. [9] have done the modeling and representing analysis of
off-grid control cohort system with photovoltaic. Mohammad et al. [10] have done theoretical approach of
photovoltaic collection by application of fuzzy logic.
Many researchers just have conducted a thermal and electrical analysis of the PVT system with
channel depth and length of collector constantly. The assessment with differences in length and a channel
depth of collectors is still very rare in determining the achievement of the PVT system. In this simulation,
a mathematical model for calculating the performance of the PVT system with ∇-groove collector is
calculated by variation of length and channel depth collector. Mathematical modeling is carried out to
develop thermal and electrical efficiency using a steady-state condition. The ∇-groove collector is
a combination of V-groove and plat plate collector. The process heat removals improved thermal efficiency
because of the extended surface of absorber collector. The purpose of this study is to determine the best of
length and depth of collector before to do the experimental investigation.
2. THEORETICAL ANALYSIS
The cross sectional view of the PVT with ∇-collector is shown in our paper [11]. It shows various
heat transfer coefficients. In order to write the energy balance equation of PVT system with ∇-collector,
the following assumptions are made as showed our in paper [12]. The steady-state equation of photovoltaic
thermal with ∇-groove collector as following
For module PV:
𝜏𝛼𝑆 − 𝑈𝑡(𝑇𝑝𝑣 − 𝑇𝑎) − ℎ 𝑐1(𝑇𝑝𝑣 − 𝑇𝑓) = ℎ 𝑟(𝑇𝑝𝑣 − 𝑇𝑏) + 𝑆𝜂 𝑝𝑣 + 𝑄∇ (1)
The channel of air:
𝑚̇ 𝐶(𝑇𝑜 − 𝑇𝑖) − ℎ 𝑐1(𝑇𝑝𝑣 − 𝑇𝑓) = ℎ 𝑐2(𝑇𝑏 − 𝑇𝑓) + 𝑄∇ (2)
The bottom plate:
ℎ 𝑟(𝑇𝑝𝑣 − 𝑇𝑏) − 𝑈𝑏(𝑇𝑏 − 𝑇𝑎) = ℎ 𝑐2(𝑇𝑏 − 𝑇𝑓) (3)
The photovoltaic thermal with ∇-groove collector uses the matrix 3 x 3 for calculating the module
PV temperature Tpv, the air temperature Tf, and bottom plate Tb using inverse matrix as following.
The completion of PVT system with ∇-groove as following,
[
(𝑈𝑡 + ℎ 𝑐1+𝑄∇ + ℎ 𝑟)
ℎ 𝑐1+𝑄∇
ℎ 𝑟
−ℎ 𝑐1 + 𝑄∇
−(ℎ 𝑐1 + ℎ 𝑐2+𝑄∇ + 𝑚̇ 𝐶)
ℎ 𝑐2
−ℎ 𝑟
ℎ 𝑐2
−(ℎ 𝑟 + ℎ 𝑐2 + 𝑈𝑏)
] [
𝑇𝑝𝑣
𝑇𝑓
𝑇𝑏
] = [
𝑈𝑡 𝑇𝑎 + 𝜏𝛼(1 − 𝜂 𝑝𝑣)𝑆
−2𝑚̇ 𝐶𝑇𝑖
−𝑈𝑏 𝑇𝑎
]
Where,
𝑄∇ = 𝑁𝐴𝑛 ℎ 𝑐 𝜂∇(𝑇𝑝𝑣 − 𝑇𝑓)
𝜂∇ = 𝑡𝑎𝑛ℎ𝑀𝐻/𝑀𝐻
𝑀 = (2ℎ 𝑐 𝑙/𝑘𝐴 𝑐𝑛)0.5
ℎ 𝑐1 = ℎ 𝑐2 = ℎ 𝑐
𝑈𝑏 =
𝑘 𝑡
𝑙 𝑡
𝑈𝑡 = (
1
ℎ 𝑤+ℎ 𝑟𝑝𝑎
)
The settlement procedure uses the iteration process. The excel program is used to calculate all
the heat transfer coefficients required in the mathematical model. The heat transfer characteristics are
calculated according to the initial estimation of temperature values. In this study, inlet air temperature,
ambient temperature, PV panel temperature and bottom plate temperature are predicted first. For PV panel
temperature is set at 30 o
C above ambient temperature. For the bottom plate temperature and the air
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207
1202
temperature is set at 20 o
C and 10 o
C above the ambient temperature. The design parameters are L = 2.4 m,
W = 0.53, 𝛼 = 0.9, 𝜏 = 0.92, 𝜀 𝑝𝑣 = 0.7, 𝜀 𝑏 = 0.9, Ta = 27, Ti = 27 o
C.
The thermal energy efficiency of PVT system is given as [13-17]
𝜂 𝑡ℎ𝑒𝑟𝑚𝑎𝑙 =
𝑚̇ 𝐶(𝑇𝑜−𝑇 𝑖)
𝐴𝑆
(4)
Where, the area of collector is A, the specific heat of air is C, mass flow rate is 𝑚̇ , solar intensity is S, and
the inlet and outlet temperature of air are Ti , To respectively.
The electrical efficiency is calculated as [18]
𝜂 𝑝𝑣 = 𝜂0[1 − 0.0045(𝑇𝑝𝑣)] (5)
The heat transfer coefficient according to Ong [19] is
ℎ 𝑤 = 2.8 + 3.3𝑉
(6)
Where, ℎ 𝑤 heat transfer coefficient due to wind and V is the wind velocity. The heat transfer coefficient from
panel cell to sky
ℎ 𝑟,𝑝𝑣𝑠 = 𝜀 𝑝𝑣 𝜎(𝑇𝑝𝑣
2
+ 𝑇𝑠𝑘𝑦
2
)(𝑇𝑝𝑣 − 𝑇𝑠𝑘𝑦) (7)
ℎ 𝑟,𝑝𝑣𝑏 =
𝜎(𝑇𝑣𝑝+𝑇 𝑏)(𝑇 𝑝𝑣
2 +𝑇𝑏
2
)
(
1
𝜀 𝑝𝑣
+
1
𝜀 𝑏
−1)
(8)
Where Ts is the sky temperature, Tpv is the photovoltaic panel temperature.
𝑇𝑠𝑘𝑦 = 0.0552𝑇𝑎
1.5
(9)
Where, 𝜀 𝑝,𝜎,𝑇𝑎, 𝑇𝑠𝑘𝑦, and 𝑇𝑝𝑣are the emissivity of panel Photovoltaic, Stefan Boltzman constant, ambient
temperature, sky temperature and panel photovoltaic temperature, respectively
The convective heat transfer coefficients are calculated as follow [20]:
ℎ =
𝑘
𝐷ℎ
𝑁𝑢 (10)
where,
𝐷ℎ =
4𝑊𝑑
2(𝑊+𝑑)
(11)
Where, W, Dh are the width, high equivalence diameter of the channel, k is air thermal conductivity, and Nu
is Nusselt number. Nusselt numbers are given as,
for Re<2300 (laminar flow region):
𝑁𝑢 = 5.4 +
0.00190[𝑅𝑒𝑃𝑟(
𝐷ℎ
𝐿
)]
1.71
1+0.00190[𝑅𝑒𝑃𝑟(
𝐷ℎ
𝐿
)]
1.71 (12)
For 2300 < Re < 6000 (transition flow region):
𝑁𝑢 = 0.116(𝑅𝑒2/3
− 125)𝑃𝑟1/3 [1 + (
𝐷ℎ
𝐿
)
2/3
](
𝜇
𝜇 𝑤
)
0.14
(13)
For Re > 6000 (turbulent flow region):
𝑁𝑢 = 0.018𝑅𝑒0.8
𝑃𝑟0.4
(14)
Int J Elec & Comp Eng ISSN: 2088-8708 
Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra)
1203
Where, Re and Pr are the Reynolds and Prandtl number given as:
𝑅𝑒 =
𝑚̇ 𝐷ℎ
𝐴 𝑐ℎ 𝜇
(15)
𝑃𝑟 =
𝜇𝐶
𝑘
(16)
The physical properties of air are hypothetical vary linearly with temperature by Fudholi [21]:
Specific heat
𝐶 = 1.0057 + 0.000066 (𝑇 − 27) (21) (17)
Density,
𝜌 = 1.1774 − 0.00359 (𝑇 − 27) (22) (18)
Thermal conductivity
𝑘 = 0.02624 + 0.0000758 (𝑇 − 27) (23) (19)
Viscosity
𝜇 = [1.983 + 0.00184 (𝑇 − 27)]10−5 (24) (20)
The theoretical model assumes that for a short collector or less of 10 m. Then, the mean air
temperature is then equal to the arithmetic mean, where:
𝑇𝑓 =
(𝑇 𝑖+𝑇𝑜)
2
(21)
3. RESULTS AND DISCUSS
In this simulation, the thermal and electrical performance of PVT with ∇-groove has been predicted
by the mathematical model. The yield of the mathematical model is assumed steady-state condition.
The different solar radiation and mass flow rate caused different thermal and electrical performances.
The simulation studies have been done with the influence of the different collector length L and channel
depth d with mass flow rate from 0.0069 kg/s to 0.0491 kg/s and the solar intensity of 800 W/m2
.
The collector length L determined with the distance of the air channel through the collector channel during
the transfer process. Figure 1 shows the thermal efficiency versus mass flow rate with the different collector
length L. The optimum thermal efficiency is 39.05% at the mass flow rate of 0.0491 kg/s with the length
collector of 2.4 m. The minimum thermal efficiency is 30.71% with the length collector of 6 m. Generally,
the thermal efficiency increases nonlinearly to the maximum and then decrease as the collector length
increases.
Figure 2 shows the electrical efficiency versus the mass flow rate at the solar intensity of 800 W/m2
with different collector length L. The electrical efficiency results were a non-linear reduction when
the collector length L increased. The optimum electrical efficiency is 10.43% with the collector length of
2.4 m. and the minimum electrical efficiency is 10.22% with collector length of 6 m. The decrease of
electrical efficiency is due to the higher rise of photovoltaic panel temperature for lower mass flow rate when
the collector length increases.
Figure 3 shows the mass flow rate versus thermal efficiency with different channel depth d at
the solar intensity of 800 W/m2
. The collector channel depth affects the heat transfer rate from collector to
the airflow through it and consequently affects the performance of the PVT system. In this study,
the collector depth is used from 0.04 m to 0.07 m. The thermal efficiency in the collector channel depth of
0.04 m reaches about 41.89%. When the collector channel depth is 0.05 m, thermal efficiency decreases
about 38.20%. And subsequently decreased by about 32.70% when the collector channels depth is 0.07 m.
Figure 4 shows electrical efficiency versus the mass flow rate with different channel depth d at
the solar intensity of 800 W/m2
. The electrical efficiency of the PVT system changes when the channel depth
d is also changed. Electrical efficiency with mass flow rate from 0.0069 kg/s to 0.0491 kg/s about is 10.50%
at channel depth of 0.04 m. When the channel depth is 0.05 m, the electrical efficiency decrease about
10.40%. and declining electrical efficiency is until 10.27% when the depth of the collector is 0.07 m.
The reduction in electrical efficiency of the collector is due to the temperature increase of photovoltaic panel
because the channel depth d is improved
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207
1204
Figure 1. Thermal efficiency versus mass flow rate
with different collector length L (d = 0.04 m)
Figure 2. Electrical efficiency versus mass flow rate
with different collector length L (d = 0.04 m)
Figure 3. Mass flow rate versus thermal efficiency
with different channel depth d (L=2.4 m)
Figure 4. Electrical efficiency versus the mass flow
rate with different channel depth d (L = 2.4 m)
In this study, the comparison of the results with preceding theoretical or experimental studies is
valuable. Table 1 shows that the use of channel depth of 0.04 m or 0.05 m and length of 2.4 m produced
higher thermal and electrical efficiency than increase channel depth and length of the collector. The yield of
this simulation shows that this result very closed to the results by Abd-AlRaheem and Amori [22].
The change in the channel depth and length of collector have an important effect on the electrical and thermal
efficiency. The Increasing of the mass flow rate of collector increased the thermal and electrical performance
of the collector.
Table 1. The comparison with previous studies
References Parameters Efficiencies
Thermal (%) Electrical (%)
Kasaeian et al. [23] d = 0.01 - 0.05 m
𝑚̇ = 0.018 - 0.06 kg/s
15 - 31 12 – 12.4
Joshi et al. [24] d = 0.05 m
𝑚̇ = 0.05 kg/s
13.4 – 16.5 9.5 - 11
Sarhaddi et al. [25] d = 0.05 m
𝑚̇ = 0.06 kg/s
25 10
Kim et al. [26] d = 0.06 m 22 15
Tonui and Tripanagnostopoulos [27] d = 0.15 m
𝑚̇ = 0.05 kg/s
18 12
Abd-AlRaheem and Amori [22] d = 0.24 m 50 10
Present study d = 0.04 – 0.07 m
𝑚̇ = 0.0069-0.0491 kg/s
32.70 – 41.89 10.50 – 10.27
Int J Elec & Comp Eng ISSN: 2088-8708 
Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra)
1205
4. CONCLUSION
The performances of electrical and thermal efficiency with ∇-groove collector have been conducted
by a mathematical model with the difference channel depth d and length L. Optimum thermal and electrical
efficiency are 39.05 %, 10.43% respectively with the collector length L of 2.4 m. The optimum thermal and
electrical efficiency are 41.89 %, 10.50% respectively with the collector depth d of 0.04 m. The variation of
the length and depth of the collector is effected by changed mass flow rate and solar intensity. The effect
Increasing of the mass flow rate of collector increased the thermal and electrical performance of the collector.
The best of mass flow rate, length, and depth of collector is 0.0491 kg/s, 2.4 m and 0.04 m, respectively.
ACKNOWLEDGEMENTS
The authors would like to thank the Solar Energy Research Institute (SERI), University Kebangsaan
Malaysia. And this research was financially supported by Hibah KEMENRISTEKDIKTI Indonesia, and their
support is gratefully acknowledged.
REFERENCES
[1] A. Fudholi, et al., "Heat transfer and efficiency of dual channel PVT air collector: a review," International Journal
of Power Electronics and Drive System (IJPEDS), vol. 10(4), pp. 2037-2045, Dec. 2019.
[2] A. Fudholi, M. F. Musthafa, A. Ridwan, R.Yendra, Hartono, A.P.Desvina, M.K.B.M. Ali, K.Sopian, "Review of
solar photovoltaic/thermal (PV/T) air collector," International Journal of Electrical and Computer Engineering
(IJECE), vol. 1(1), pp. 126-133, 2019.
[3] M. Zohri, A. Fudholi, M. H. Ruslan, and K. Sopian, "Mathematical modeling of photovoltaic thermal PV/T system
with v-groove collector," AIP Conference Proceedings, vol. 1862, pp. 030063-1, 2017.
[4] M. Zohri, S. Hadisaputra, A. Fudholi1, "Exergy And Energy Analysis Of Photovoltaic Thermal (PVT) With And
Without Fins Collector," ARPN Journal of Engineering and Applied Sciences, vol. 13(3), pp. 803-808, 2018.
[5] M. Zohri, et al., "Photovoltaic-Thermal (PVT) System with and Without Fins Collector: Theoretical Approach,"
International Journal of Power Electronics and Drive System (IJPEDS), vol. 8(4), pp. 1756-1763, Dec. 2017.
[6] M. Zohri. Nurato, L. D. Bakti, A. Fudholi, "Exergy Assessment of Photovoltaic Thermal with V-groove Collector
Using Theoretical study," TELKOMNIKA (Telecommunication, Computing, Electronics and Control), vol. 16(2),
pp. 550-557, Apr. 2018.
[7] J. S. Kumari and Ch. S. Babu, "Mathematical modeling and simulation of photovoltaic cell using Matlab-simulink
environment," International Journal of Electrical and Computer Engineering (IJECE), vol. 2(1), pp. 26-34, 2012.
[8] O. Amirullah, A. Penangsang, Soeprijanto, "Power Quality Analysis of Integration Photovoltaic Generator to Three
Phase Grid under Variable Solar Irradiance Level," TELKOMNIKA (Telecommunication Computing Electronics
and Control), vol. 14(1), pp. 29-38, 2016.
[9] H. Sharma, N. Pal, P.K. Sadhu, "Modeling and Simulation of Off-Grid Power Generation," TELKOMNIKA
Indonesian Journal of Electrical Engineering, vol. 13(3), pp. 418- 424, 2015.
[10] N. Mohammad, M.A. Islam, T. Karim, Q.D. Hossain, "Improved solar photovoltaic array model with FLC based
maximum power point tracking," International Journal of Electrical and Computer Engineering (IJECE), vol. 2(6),
pp. 717-730, 2012.
[11] A. Fudholi, M. Zohri, G.L Jin, A. Ibrahim, C.H. Yen, M.Y. Othman, M.H. Ruslan, K. Sopian, "Energy and exergy
analyses of photovoltaic thermal collector with ∇-groove," Solar Energy, vol. 159, pp. 742-750, 2018.
[12] A. Fudholi, M. Zohri, N. S. B. Rukman, N.S. Nazri, M. Mustapha, C. H. Yen, M. Mohammad, K. Sopian, "Exergy
and sustainability index of photovoltaic thermal (PVT) air collector: A theoretical and experimental study,"
Renewable and Sustainable Energy Reviews, vol. 100, pp. 44-51, 2019.
[13] R. K. Agarwal and H. P. Garg, "Study of a Photovoltaic Thermal System Thermosyphonic Solar Water Heater
Combined With Solar Cells," Energy Convers. Manag., vol. 35(7), pp. 605–620, 1994.
[14] A. Fudholi, et al., "Performance and Cost Benefits Analysis of Double-Pass Solar Collector With and Without
Fins," Energy Conversion and Management, vol. 76, pp. 8-19, 2013.
[15] A. Fudholi, et al., "Collector Efficiency of the Double-Pass Solar Air Collectors With Fins," Proceedings of the 9th
WSEAS International Conference on System Science and Simulation in Engineering (ICOSSSE’10), Japan,
pp. 428-34, 2010.
[16] A. Fudholi, et al., "Experimental Study of the Double-Pass Solar Air Collector With Staggered Fins," Proceedings
of the 9th
WSEAS International Conference on System Science and Simulation in Engineering (ICOSSSE’10), Japan,
pp. 410-14, 2010.
[17] A. Fudholi, et al., "Performance Analysis of Photovoltaic Thermal (PVT) Water Collectors," Energy Conversion
and Management, vol. 78, pp. 641-651, 2014.
[18] R. J. Amrizal N, Chemisana D, "Hybrid photovoltaic–thermal solar collectors dynamic modeling," Appl Energy,
vol. 101, pp. 797–807, 2013.
[19] K. S. Ong, "Thermal performance of solar air heaters: Mathematical model and solution procedure," Sol. Energy,
vol. 55(2), pp. 93–109, 1995.
[20] T. T. Chow, "A review on photovoltaic/thermal hybrid solar technology," Appl. Energy, vol. 87(2), pp. 365–379,
2010.
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207
1206
[21] A. Fudholi, K. Sopian, M. Y. Othman, M. H. Ruslan, and B. Bakhtyar, "Energy analysis and improvement potential
of finned double-pass solar collector," Energy Convers. Manag., vol. 75, pp. 234–240, 2013.
[22] M.A. Abd-AlRaheem and Amori, "Field study of various air based photovoltaic/thermal hybrid solar collectors,"
Renewable Energy, vol. 63, pp. 402-414, 2014.
[23] Kasaeian, Alibakhsh, Y. Khanjari, S. Golzari, O. Mahian, and S. Wongwises, "Effects of forced convection on
the performance of a photovoltaic thermal system: An experimental study," Experimental Thermal and Fluid
Science, vol. 85, pp. 13-21, 2017.
[24] A. Joshi, et al., "Performance evaluation of a hybrid photovoltaic thermal (PV/T) (glass-toglass) system,"
International Journal of Thermal Sciences, vol. 48(1), pp. 154-164, 2009.
[25] F. Sarhaddi, et al., "An improved thermal and electrical model for a solar photovoltaic thermal (PV/T) air
collector," Applied Energy, vol. 87(7), pp. 2328-2339, 2010.
[26] Kim, J.-H., S.-H. Park, and J.-T. Kim, "Experimental Performance of a Photovoltaic-thermal Air Collector," Energy
Procedia, vol. 48, pp. 888-894, 2014.
[27] J. K. Tonui and Y. Tripanagnostopoulos, "Performance improvement of PV/T solar collectors with natural air flow
operation," Solar Energy, vol. 82, pp. 1–12, 2008.
BIOGRAPHIES OF AUTHORS
Saprizal Hadisaputra is currently a chemistry lecturer the University of Mataram, Lombok,
Indonesia. His Ph.D degree was obtained in from Austrian-Indonesian Centre for Computational
Chemistry, Universitas Gadjah Mada at 2014 in the field of Physical Chemistry/Computational
Chemistry. He took his bachelor degree of chemistry at the same university and finished his
master degree in Nanotechnology at Flinders University, Australia. He actively conducts
research in computational chemistry that focuses on the use of quantum mechanics to predict the
corrosion inhibition performance and energy storage of new materials. He published many
articles in national and international journals.
Muhammad Zohri obtained his S.Si (2009) in physics and received the Master of Science
degree in Solar Energy Research Institute from The National University of Malaysia, Malaysia
in 2017, with a thesis based on PVT system. He was appointed a Graduate Research Assistant
(GRA) under Dr. Ahmad Fudholi in Solar Energy Research Institute (SERI) in UKM Malaysia,
during his master’s degree. He worked at State Islamic University (UIN) Mataram, Indonesia.
He was a speaker at The 2nd International Symposium on Current Progress in Mathematics and
Science (2nd ISCPMS) FMIPA UI in Depok and The 4th Solar Energy Research Institute (SERI)
Colloquium 2016, in UKM Bangi, Malaysia. He has published many paper in Scopus and WoS
Index.
Bahtiar is currently a physic lecturer the State Islamic University (UIN) Mataram, Lombok,
Indonesia. His Ph.D degree was obtained in from State University of Surabaya, Indonesia at
2016 in the field of Physic education. He took his Master degree of Physic education at State
University of Yogyakarta. He actively conducts research in physic and physic education. He
published many articles in national and international journals. He was a speaker at Mathematic-
Informatics-Science-Education International-Conference (MISEIC) 2017, 2018 by FMIPA State
University of Surabaya and international Conference on Environmental and Science Education
(ICESE) 2019 by FMIPA State University of Semarang.
Ahmad Fudholi obtained his S.Si (2002) in physics. He has working experience about 4 years
(2004-2008) as Head of Physics Department at Rab University Pekanbaru, Indonesia. A. Fudholi
started his master course in Energy Technology (2005-2007) at UniversitiKebangsaan Malaysia
(UKM). After his master he became Research Assistant at UKM up to 2012. After his Ph.D
(2012) he became Postdoctoral in Solar Energy Research Institute (SERI) UKM up to 2013. He
joined the SERI as a Lecture in 2014. More than USD 304,000 research grant in 2014–2017
obtained. More than 25 M.Sc project supervised and completed. Until now, he managed to
supervise 6 Ph.D (4 main supervisor and 1 Co. supervisor), 2 Master’s student by research mode,
and 5 Master’s student by coursework mode, he was also as examiner (3 Ph.D and 1 M.Sc). His
current research focuses on renewable energy, especially energy technology. He has published
more than 100 peer-reviewed papers, which 25 papers in ISI index (20 Q1, impact factor more
than 3) and more than 48 papers in Scopus index, 10 more currently accepted manuscript, 20
more currently under review, and 2 book chapters. Addition, he has published more than 70
papers in international conferences. His total citations of 571 by 395 documents and h-index of
12 in Scopus (Author ID: 57195432490). His total citations of 1093 and h-index of 19 in google
scholar. He is appointed as reviewer of high impact journal such as Renewable and Sustainable
Energy Reviews, Energy Conversion and Management, Applied Energy, Energy and Buildings,
Int J Elec & Comp Eng ISSN: 2088-8708 
Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra)
1207
Applied Thermal Engineering, Energy, Industrial Crops and Products, etc. He is appointed as
reviewer of reputation journals such as Drying Technology, International Journal of Green
Energy, Drying Technology, Bio system Engineering, Journal of Sustainability Science and
Management, Journal of Energy Efficiency, Sains Malaysiana, Jurnal Teknologi etc. He is also
appointed as editor journals. He has received several awards such as Gold Medal Award at the
International Ibn Al-Haytham’s Al-Manazir Innovation and Invention Exhibition 2011, Silver
Medal Award at the International Technology EXPO (ITEX) 2012, Silver Medal Award at the
Malaysia Technology Expo (MTE) 2013, Bronze Medal Award at International Exposition of
Research and Invention (PECIPTA) 2011, also 2 Bronze Medal Award at PECIPTA 2017. He
was also invited as speaker: Workshop of Scientific Journal Writing; Writing Scientific Papers
Steps Towards Successful Publish in High Impact (Q1) Journals.

More Related Content

What's hot

Gas turbine exergy analysis
Gas turbine exergy analysisGas turbine exergy analysis
Gas turbine exergy analysisravi801
 
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM Mellah Hacene
 
Novel technique for maximizing the thermal efficiency of a hybrid pv
Novel technique for maximizing the thermal efficiency of a hybrid pvNovel technique for maximizing the thermal efficiency of a hybrid pv
Novel technique for maximizing the thermal efficiency of a hybrid pveSAT Journals
 
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion System
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion SystemDynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion System
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion SystemIJRES Journal
 
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE Mellah Hacene
 
Performance analysis of partially covered photovoltaic thermal (pvt) water co...
Performance analysis of partially covered photovoltaic thermal (pvt) water co...Performance analysis of partially covered photovoltaic thermal (pvt) water co...
Performance analysis of partially covered photovoltaic thermal (pvt) water co...eSAT Journals
 
Paper id 27201445
Paper id 27201445Paper id 27201445
Paper id 27201445IJRAT
 
Energy cost savings based on the UPS
Energy cost savings based on the UPS Energy cost savings based on the UPS
Energy cost savings based on the UPS IJECEIAES
 
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector iMentor Education
 
Novel technique for maximizing the thermal efficiency
Novel technique for maximizing the thermal efficiencyNovel technique for maximizing the thermal efficiency
Novel technique for maximizing the thermal efficiencyeSAT Publishing House
 
Multi-objective based economic environmental dispatch with stochastic solar-w...
Multi-objective based economic environmental dispatch with stochastic solar-w...Multi-objective based economic environmental dispatch with stochastic solar-w...
Multi-objective based economic environmental dispatch with stochastic solar-w...IJECEIAES
 
Influence Types of Startup on Hydrothermal Scheduling
Influence Types of Startup on Hydrothermal SchedulingInfluence Types of Startup on Hydrothermal Scheduling
Influence Types of Startup on Hydrothermal SchedulingTELKOMNIKA JOURNAL
 
96 manuscript-579-1-10-20210211
96  manuscript-579-1-10-2021021196  manuscript-579-1-10-20210211
96 manuscript-579-1-10-20210211Mellah Hacene
 

What's hot (20)

Gas turbine exergy analysis
Gas turbine exergy analysisGas turbine exergy analysis
Gas turbine exergy analysis
 
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
 
J010337176
J010337176J010337176
J010337176
 
Novel technique for maximizing the thermal efficiency of a hybrid pv
Novel technique for maximizing the thermal efficiency of a hybrid pvNovel technique for maximizing the thermal efficiency of a hybrid pv
Novel technique for maximizing the thermal efficiency of a hybrid pv
 
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion System
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion SystemDynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion System
Dynamic Simulation of a Hybrid Solar and Ocean Thermal Energy Conversion System
 
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE
SIMULATION OF A MATHEMATICAL MODEL OF A WIND TURBINE
 
Performance analysis of partially covered photovoltaic thermal (pvt) water co...
Performance analysis of partially covered photovoltaic thermal (pvt) water co...Performance analysis of partially covered photovoltaic thermal (pvt) water co...
Performance analysis of partially covered photovoltaic thermal (pvt) water co...
 
Paper id 27201445
Paper id 27201445Paper id 27201445
Paper id 27201445
 
1
11
1
 
Energy cost savings based on the UPS
Energy cost savings based on the UPS Energy cost savings based on the UPS
Energy cost savings based on the UPS
 
1901.08661
1901.086611901.08661
1901.08661
 
274 iitb 274 corrected
274 iitb 274 corrected274 iitb 274 corrected
274 iitb 274 corrected
 
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector
CFD Analysis of a Heat Collector Element in a Solar Parabolic Trough Collector
 
Novel technique for maximizing the thermal efficiency
Novel technique for maximizing the thermal efficiencyNovel technique for maximizing the thermal efficiency
Novel technique for maximizing the thermal efficiency
 
Multi-objective based economic environmental dispatch with stochastic solar-w...
Multi-objective based economic environmental dispatch with stochastic solar-w...Multi-objective based economic environmental dispatch with stochastic solar-w...
Multi-objective based economic environmental dispatch with stochastic solar-w...
 
01_A Study of Heat Exchanger Produces Hot Water from Air Conditioning Incorp...
01_A Study of Heat Exchanger Produces Hot Water from Air Conditioning  Incorp...01_A Study of Heat Exchanger Produces Hot Water from Air Conditioning  Incorp...
01_A Study of Heat Exchanger Produces Hot Water from Air Conditioning Incorp...
 
Influence Types of Startup on Hydrothermal Scheduling
Influence Types of Startup on Hydrothermal SchedulingInfluence Types of Startup on Hydrothermal Scheduling
Influence Types of Startup on Hydrothermal Scheduling
 
L1303038388
L1303038388L1303038388
L1303038388
 
96 manuscript-579-1-10-20210211
96  manuscript-579-1-10-2021021196  manuscript-579-1-10-20210211
96 manuscript-579-1-10-20210211
 
22057 44311-1-pb
22057 44311-1-pb22057 44311-1-pb
22057 44311-1-pb
 

Similar to Effect of channel length and depth on PVT system efficiency

Indoor and outdoor investigation comparison of photovoltaic thermal air colle...
Indoor and outdoor investigation comparison of photovoltaic thermal air colle...Indoor and outdoor investigation comparison of photovoltaic thermal air colle...
Indoor and outdoor investigation comparison of photovoltaic thermal air colle...journalBEEI
 
Impact of solar radiation and temperature levels on the variation of the seri...
Impact of solar radiation and temperature levels on the variation of the seri...Impact of solar radiation and temperature levels on the variation of the seri...
Impact of solar radiation and temperature levels on the variation of the seri...eSAT Journals
 
Experiment study of water based photovoltaic-thermal (PV/T) collector
Experiment study of water based photovoltaic-thermal (PV/T) collectorExperiment study of water based photovoltaic-thermal (PV/T) collector
Experiment study of water based photovoltaic-thermal (PV/T) collectorIJECEIAES
 
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...IJAAS Team
 
Use of Nanofluids to increase the efficiency of solar panels
Use of Nanofluids to increase the efficiency of solar panelsUse of Nanofluids to increase the efficiency of solar panels
Use of Nanofluids to increase the efficiency of solar panelsvarungoyal98
 
Solar photovoltaic/thermal air collector with mirrors for optimal tilts
Solar photovoltaic/thermal air collector with mirrors for  optimal tiltsSolar photovoltaic/thermal air collector with mirrors for  optimal tilts
Solar photovoltaic/thermal air collector with mirrors for optimal tiltsIJECEIAES
 
Simulation of solar intensity in performance of flat
Simulation of solar intensity in performance of flatSimulation of solar intensity in performance of flat
Simulation of solar intensity in performance of flateSAT Publishing House
 
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...IJECEIAES
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentIJERD Editor
 
Photovoltaic thermal hybrid solar system for
Photovoltaic thermal hybrid solar system forPhotovoltaic thermal hybrid solar system for
Photovoltaic thermal hybrid solar system foreSAT Publishing House
 
Photovoltaic thermal hybrid solar system for residential applications
Photovoltaic thermal hybrid solar system for residential applicationsPhotovoltaic thermal hybrid solar system for residential applications
Photovoltaic thermal hybrid solar system for residential applicationseSAT Journals
 
Solar Module Modeling, Simulation And Validation Under Matlab / Simulink
Solar Module Modeling, Simulation And Validation Under Matlab / SimulinkSolar Module Modeling, Simulation And Validation Under Matlab / Simulink
Solar Module Modeling, Simulation And Validation Under Matlab / SimulinkIJERA Editor
 
Performance of low-cost solar radiation logger
Performance of low-cost solar radiation loggerPerformance of low-cost solar radiation logger
Performance of low-cost solar radiation loggerIJECEIAES
 
comparative analysis of solar photovoltaic thermal (pvt) water and solar
comparative analysis of solar photovoltaic thermal (pvt) water and solarcomparative analysis of solar photovoltaic thermal (pvt) water and solar
comparative analysis of solar photovoltaic thermal (pvt) water and solarIJCMESJOURNAL
 
Experimental Investigation Of Active Cooling Of Photovoltaic Cells
Experimental Investigation Of Active Cooling Of Photovoltaic CellsExperimental Investigation Of Active Cooling Of Photovoltaic Cells
Experimental Investigation Of Active Cooling Of Photovoltaic Cellsguest741138
 
06 6377 9057-1-pb
06 6377 9057-1-pb06 6377 9057-1-pb
06 6377 9057-1-pbIAESIJEECS
 
Dg3211151122
Dg3211151122Dg3211151122
Dg3211151122IJMER
 
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...IRJET Journal
 

Similar to Effect of channel length and depth on PVT system efficiency (20)

GSA TUNED HIGH EXERGY IN PV ARRAY
GSA TUNED HIGH EXERGY IN PV ARRAYGSA TUNED HIGH EXERGY IN PV ARRAY
GSA TUNED HIGH EXERGY IN PV ARRAY
 
Indoor and outdoor investigation comparison of photovoltaic thermal air colle...
Indoor and outdoor investigation comparison of photovoltaic thermal air colle...Indoor and outdoor investigation comparison of photovoltaic thermal air colle...
Indoor and outdoor investigation comparison of photovoltaic thermal air colle...
 
Impact of solar radiation and temperature levels on the variation of the seri...
Impact of solar radiation and temperature levels on the variation of the seri...Impact of solar radiation and temperature levels on the variation of the seri...
Impact of solar radiation and temperature levels on the variation of the seri...
 
Experiment study of water based photovoltaic-thermal (PV/T) collector
Experiment study of water based photovoltaic-thermal (PV/T) collectorExperiment study of water based photovoltaic-thermal (PV/T) collector
Experiment study of water based photovoltaic-thermal (PV/T) collector
 
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...
Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: A...
 
Use of Nanofluids to increase the efficiency of solar panels
Use of Nanofluids to increase the efficiency of solar panelsUse of Nanofluids to increase the efficiency of solar panels
Use of Nanofluids to increase the efficiency of solar panels
 
Solar photovoltaic/thermal air collector with mirrors for optimal tilts
Solar photovoltaic/thermal air collector with mirrors for  optimal tiltsSolar photovoltaic/thermal air collector with mirrors for  optimal tilts
Solar photovoltaic/thermal air collector with mirrors for optimal tilts
 
Simulation of solar intensity in performance of flat
Simulation of solar intensity in performance of flatSimulation of solar intensity in performance of flat
Simulation of solar intensity in performance of flat
 
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector:...
 
40220130406011 2-3-4
40220130406011 2-3-440220130406011 2-3-4
40220130406011 2-3-4
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and Development
 
Photovoltaic thermal hybrid solar system for
Photovoltaic thermal hybrid solar system forPhotovoltaic thermal hybrid solar system for
Photovoltaic thermal hybrid solar system for
 
Photovoltaic thermal hybrid solar system for residential applications
Photovoltaic thermal hybrid solar system for residential applicationsPhotovoltaic thermal hybrid solar system for residential applications
Photovoltaic thermal hybrid solar system for residential applications
 
Solar Module Modeling, Simulation And Validation Under Matlab / Simulink
Solar Module Modeling, Simulation And Validation Under Matlab / SimulinkSolar Module Modeling, Simulation And Validation Under Matlab / Simulink
Solar Module Modeling, Simulation And Validation Under Matlab / Simulink
 
Performance of low-cost solar radiation logger
Performance of low-cost solar radiation loggerPerformance of low-cost solar radiation logger
Performance of low-cost solar radiation logger
 
comparative analysis of solar photovoltaic thermal (pvt) water and solar
comparative analysis of solar photovoltaic thermal (pvt) water and solarcomparative analysis of solar photovoltaic thermal (pvt) water and solar
comparative analysis of solar photovoltaic thermal (pvt) water and solar
 
Experimental Investigation Of Active Cooling Of Photovoltaic Cells
Experimental Investigation Of Active Cooling Of Photovoltaic CellsExperimental Investigation Of Active Cooling Of Photovoltaic Cells
Experimental Investigation Of Active Cooling Of Photovoltaic Cells
 
06 6377 9057-1-pb
06 6377 9057-1-pb06 6377 9057-1-pb
06 6377 9057-1-pb
 
Dg3211151122
Dg3211151122Dg3211151122
Dg3211151122
 
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...
Piezoelectric Thermo-Acoustic Refrigeration System with Peltier Module Energy...
 

More from IJECEIAES

Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...IJECEIAES
 
Prediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionPrediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionIJECEIAES
 
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...IJECEIAES
 
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...IJECEIAES
 
Improving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningImproving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningIJECEIAES
 
Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...IJECEIAES
 
Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...IJECEIAES
 
Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...IJECEIAES
 
Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...IJECEIAES
 
A systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyA systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyIJECEIAES
 
Agriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationAgriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationIJECEIAES
 
Three layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceThree layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceIJECEIAES
 
Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...IJECEIAES
 
Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...IJECEIAES
 
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...IJECEIAES
 
Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...IJECEIAES
 
On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...IJECEIAES
 
Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...IJECEIAES
 
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...IJECEIAES
 
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...IJECEIAES
 

More from IJECEIAES (20)

Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...
 
Prediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionPrediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regression
 
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
 
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
 
Improving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningImproving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learning
 
Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...
 
Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...
 
Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...
 
Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...
 
A systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyA systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancy
 
Agriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationAgriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimization
 
Three layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceThree layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performance
 
Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...
 
Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...
 
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
 
Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...
 
On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...
 
Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...
 
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
 
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
 

Recently uploaded

chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learningmisbanausheenparvam
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )Tsuyoshi Horigome
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfAsst.prof M.Gokilavani
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...asadnawaz62
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2RajaP95
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort servicejennyeacort
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfAsst.prof M.Gokilavani
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...VICTOR MAESTRE RAMIREZ
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLDeelipZope
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSCAESB
 
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...VICTOR MAESTRE RAMIREZ
 
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...Soham Mondal
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerAnamika Sarkar
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxk795866
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 

Recently uploaded (20)

chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
 
Design and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdfDesign and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdf
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
 
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...
VICTOR MAESTRE RAMIREZ - Planetary Defender on NASA's Double Asteroid Redirec...
 
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptx
 
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 

Effect of channel length and depth on PVT system efficiency

  • 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 2, April 2020, pp. 1200~1207 ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1200-1207  1200 Journal homepage: http://ijece.iaescore.com/index.php/IJECE Effect analysis of the different channel length and depth of photovoltaic thermal system with ∇-groove collector Saprizal Hadisaputra1 , Muhammad Zohri2 , Bahtiar3 , Ahmad Fudholi4 1 Faculty of Science and Education, University of Mataram, Indonesia 2,3 Department of Physic Education, Universitas Islam Negeri (UIN) Mataram, Indonesia 2,4 Solar Energy Research Institute, Universiti Kebangsaan Malaysia, Malaysia Article Info ABSTRACT Article history: Received May 8, 2019 Revised Oct 1, 2019 Accepted Oct 17, 2019 The converted Solar energy as electrical and thermal energy was named photovoltaic thermal (PVT). The aim of this study is to the analysis of different length and depth channel effect of photovoltaic thermal with ∇-groove collector by a mathematical model. The matrix inversion was used to analyze the energy balance equation. Simulation results were conducted below the solar intensity of 800 W/m2 and mass flow rate between 0.0069 kg/s and 0.0491 kg/s. Electrical and thermal efficiency was done to assess the effect of different length and channel depth of PVT system with ∇-groove collector. The effect of different length and depth of ∇-groove collector for electrical and thermal performance is caused by changed mass flow rate. The effect Increasing of the mass flow rate of collector increased the thermal and electrical performance of the ∇-groove collector. Keywords: Depth Electrical Length Mathematical model Thermal Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Muhammad Zohri, Department of physic education, Universitas Islam Negeri (UIN) Mataram, Indonesia. Email: zohri.ukm@gmail.com 1. INTRODUCTION Solar energy is one of renewable energy which has characteristic sanitary and harmless and sustainable. The conversion of solar energy to thermal and electrical energy is called Photovoltaic thermal (PVT) system. The PVT system is a combination of photovoltaic and solar collector technology. The over heat from PV panel is removed by air as medium cooling [1]. The performance of PVT system is excessive total energy transformation efficiency. The enactment and financial effectiveness of PVT system be contingent of numerous scheme parameters for example collector design shape, collector dimension, collector penetration, amount of collectors, Photovoltaic module form , glazed and unglazed collector, focused solar intensity [2]. Many studies of the photovoltaic thermal system with collector have been done by The theoretical and experimental assessment in last decades. Zohri et al. [3] have developed mathematical modeling of photovoltaic thermal with v-groove. The electrical and thermal efficiency have been compared with other design collectors. The use of v-groove was the higher efficiency than other design collectors. Zohri et al. [4] have done energy and exergy analyses of photovoltaic thermal with fins collector with theoretical approach. The use of fins collector is higher energy and exergy efficiency than without fins collector. Zohri et al. [5] have done developed performances analysis of photovoltaic thermal with and without fins collector. The energy performance of fins collector was very good than without fins collector. The theoretical approach or mathematical model of photovoltaic thermal with and without v-groove collector have been conducted by Zohri et al. [6]. the exergy performance results showed that using of v-groove collector be able to increase the exergy efficiency.
  • 2. Int J Elec & Comp Eng ISSN: 2088-8708  Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra) 1201 Kumari and Babu [7] have analyzed the photovoltaic cell using the Matlab-Simulink situation with theoretical study. The objective of this study was to the discovery of nonlinear I-V equation. The best of I-V equation for the single-diode photovoltaic model counting the effect of the sequence and similar confrontations was found. Aminullah et al. [8] have conducted the influence analysis of solar intensity and combination of photovoltaic generator to power quality. The yield of dual adjusted passive sieve able to increase voltage and current THD grid. Sharma et al. [9] have done the modeling and representing analysis of off-grid control cohort system with photovoltaic. Mohammad et al. [10] have done theoretical approach of photovoltaic collection by application of fuzzy logic. Many researchers just have conducted a thermal and electrical analysis of the PVT system with channel depth and length of collector constantly. The assessment with differences in length and a channel depth of collectors is still very rare in determining the achievement of the PVT system. In this simulation, a mathematical model for calculating the performance of the PVT system with ∇-groove collector is calculated by variation of length and channel depth collector. Mathematical modeling is carried out to develop thermal and electrical efficiency using a steady-state condition. The ∇-groove collector is a combination of V-groove and plat plate collector. The process heat removals improved thermal efficiency because of the extended surface of absorber collector. The purpose of this study is to determine the best of length and depth of collector before to do the experimental investigation. 2. THEORETICAL ANALYSIS The cross sectional view of the PVT with ∇-collector is shown in our paper [11]. It shows various heat transfer coefficients. In order to write the energy balance equation of PVT system with ∇-collector, the following assumptions are made as showed our in paper [12]. The steady-state equation of photovoltaic thermal with ∇-groove collector as following For module PV: 𝜏𝛼𝑆 − 𝑈𝑡(𝑇𝑝𝑣 − 𝑇𝑎) − ℎ 𝑐1(𝑇𝑝𝑣 − 𝑇𝑓) = ℎ 𝑟(𝑇𝑝𝑣 − 𝑇𝑏) + 𝑆𝜂 𝑝𝑣 + 𝑄∇ (1) The channel of air: 𝑚̇ 𝐶(𝑇𝑜 − 𝑇𝑖) − ℎ 𝑐1(𝑇𝑝𝑣 − 𝑇𝑓) = ℎ 𝑐2(𝑇𝑏 − 𝑇𝑓) + 𝑄∇ (2) The bottom plate: ℎ 𝑟(𝑇𝑝𝑣 − 𝑇𝑏) − 𝑈𝑏(𝑇𝑏 − 𝑇𝑎) = ℎ 𝑐2(𝑇𝑏 − 𝑇𝑓) (3) The photovoltaic thermal with ∇-groove collector uses the matrix 3 x 3 for calculating the module PV temperature Tpv, the air temperature Tf, and bottom plate Tb using inverse matrix as following. The completion of PVT system with ∇-groove as following, [ (𝑈𝑡 + ℎ 𝑐1+𝑄∇ + ℎ 𝑟) ℎ 𝑐1+𝑄∇ ℎ 𝑟 −ℎ 𝑐1 + 𝑄∇ −(ℎ 𝑐1 + ℎ 𝑐2+𝑄∇ + 𝑚̇ 𝐶) ℎ 𝑐2 −ℎ 𝑟 ℎ 𝑐2 −(ℎ 𝑟 + ℎ 𝑐2 + 𝑈𝑏) ] [ 𝑇𝑝𝑣 𝑇𝑓 𝑇𝑏 ] = [ 𝑈𝑡 𝑇𝑎 + 𝜏𝛼(1 − 𝜂 𝑝𝑣)𝑆 −2𝑚̇ 𝐶𝑇𝑖 −𝑈𝑏 𝑇𝑎 ] Where, 𝑄∇ = 𝑁𝐴𝑛 ℎ 𝑐 𝜂∇(𝑇𝑝𝑣 − 𝑇𝑓) 𝜂∇ = 𝑡𝑎𝑛ℎ𝑀𝐻/𝑀𝐻 𝑀 = (2ℎ 𝑐 𝑙/𝑘𝐴 𝑐𝑛)0.5 ℎ 𝑐1 = ℎ 𝑐2 = ℎ 𝑐 𝑈𝑏 = 𝑘 𝑡 𝑙 𝑡 𝑈𝑡 = ( 1 ℎ 𝑤+ℎ 𝑟𝑝𝑎 ) The settlement procedure uses the iteration process. The excel program is used to calculate all the heat transfer coefficients required in the mathematical model. The heat transfer characteristics are calculated according to the initial estimation of temperature values. In this study, inlet air temperature, ambient temperature, PV panel temperature and bottom plate temperature are predicted first. For PV panel temperature is set at 30 o C above ambient temperature. For the bottom plate temperature and the air
  • 3.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207 1202 temperature is set at 20 o C and 10 o C above the ambient temperature. The design parameters are L = 2.4 m, W = 0.53, 𝛼 = 0.9, 𝜏 = 0.92, 𝜀 𝑝𝑣 = 0.7, 𝜀 𝑏 = 0.9, Ta = 27, Ti = 27 o C. The thermal energy efficiency of PVT system is given as [13-17] 𝜂 𝑡ℎ𝑒𝑟𝑚𝑎𝑙 = 𝑚̇ 𝐶(𝑇𝑜−𝑇 𝑖) 𝐴𝑆 (4) Where, the area of collector is A, the specific heat of air is C, mass flow rate is 𝑚̇ , solar intensity is S, and the inlet and outlet temperature of air are Ti , To respectively. The electrical efficiency is calculated as [18] 𝜂 𝑝𝑣 = 𝜂0[1 − 0.0045(𝑇𝑝𝑣)] (5) The heat transfer coefficient according to Ong [19] is ℎ 𝑤 = 2.8 + 3.3𝑉 (6) Where, ℎ 𝑤 heat transfer coefficient due to wind and V is the wind velocity. The heat transfer coefficient from panel cell to sky ℎ 𝑟,𝑝𝑣𝑠 = 𝜀 𝑝𝑣 𝜎(𝑇𝑝𝑣 2 + 𝑇𝑠𝑘𝑦 2 )(𝑇𝑝𝑣 − 𝑇𝑠𝑘𝑦) (7) ℎ 𝑟,𝑝𝑣𝑏 = 𝜎(𝑇𝑣𝑝+𝑇 𝑏)(𝑇 𝑝𝑣 2 +𝑇𝑏 2 ) ( 1 𝜀 𝑝𝑣 + 1 𝜀 𝑏 −1) (8) Where Ts is the sky temperature, Tpv is the photovoltaic panel temperature. 𝑇𝑠𝑘𝑦 = 0.0552𝑇𝑎 1.5 (9) Where, 𝜀 𝑝,𝜎,𝑇𝑎, 𝑇𝑠𝑘𝑦, and 𝑇𝑝𝑣are the emissivity of panel Photovoltaic, Stefan Boltzman constant, ambient temperature, sky temperature and panel photovoltaic temperature, respectively The convective heat transfer coefficients are calculated as follow [20]: ℎ = 𝑘 𝐷ℎ 𝑁𝑢 (10) where, 𝐷ℎ = 4𝑊𝑑 2(𝑊+𝑑) (11) Where, W, Dh are the width, high equivalence diameter of the channel, k is air thermal conductivity, and Nu is Nusselt number. Nusselt numbers are given as, for Re<2300 (laminar flow region): 𝑁𝑢 = 5.4 + 0.00190[𝑅𝑒𝑃𝑟( 𝐷ℎ 𝐿 )] 1.71 1+0.00190[𝑅𝑒𝑃𝑟( 𝐷ℎ 𝐿 )] 1.71 (12) For 2300 < Re < 6000 (transition flow region): 𝑁𝑢 = 0.116(𝑅𝑒2/3 − 125)𝑃𝑟1/3 [1 + ( 𝐷ℎ 𝐿 ) 2/3 ]( 𝜇 𝜇 𝑤 ) 0.14 (13) For Re > 6000 (turbulent flow region): 𝑁𝑢 = 0.018𝑅𝑒0.8 𝑃𝑟0.4 (14)
  • 4. Int J Elec & Comp Eng ISSN: 2088-8708  Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra) 1203 Where, Re and Pr are the Reynolds and Prandtl number given as: 𝑅𝑒 = 𝑚̇ 𝐷ℎ 𝐴 𝑐ℎ 𝜇 (15) 𝑃𝑟 = 𝜇𝐶 𝑘 (16) The physical properties of air are hypothetical vary linearly with temperature by Fudholi [21]: Specific heat 𝐶 = 1.0057 + 0.000066 (𝑇 − 27) (21) (17) Density, 𝜌 = 1.1774 − 0.00359 (𝑇 − 27) (22) (18) Thermal conductivity 𝑘 = 0.02624 + 0.0000758 (𝑇 − 27) (23) (19) Viscosity 𝜇 = [1.983 + 0.00184 (𝑇 − 27)]10−5 (24) (20) The theoretical model assumes that for a short collector or less of 10 m. Then, the mean air temperature is then equal to the arithmetic mean, where: 𝑇𝑓 = (𝑇 𝑖+𝑇𝑜) 2 (21) 3. RESULTS AND DISCUSS In this simulation, the thermal and electrical performance of PVT with ∇-groove has been predicted by the mathematical model. The yield of the mathematical model is assumed steady-state condition. The different solar radiation and mass flow rate caused different thermal and electrical performances. The simulation studies have been done with the influence of the different collector length L and channel depth d with mass flow rate from 0.0069 kg/s to 0.0491 kg/s and the solar intensity of 800 W/m2 . The collector length L determined with the distance of the air channel through the collector channel during the transfer process. Figure 1 shows the thermal efficiency versus mass flow rate with the different collector length L. The optimum thermal efficiency is 39.05% at the mass flow rate of 0.0491 kg/s with the length collector of 2.4 m. The minimum thermal efficiency is 30.71% with the length collector of 6 m. Generally, the thermal efficiency increases nonlinearly to the maximum and then decrease as the collector length increases. Figure 2 shows the electrical efficiency versus the mass flow rate at the solar intensity of 800 W/m2 with different collector length L. The electrical efficiency results were a non-linear reduction when the collector length L increased. The optimum electrical efficiency is 10.43% with the collector length of 2.4 m. and the minimum electrical efficiency is 10.22% with collector length of 6 m. The decrease of electrical efficiency is due to the higher rise of photovoltaic panel temperature for lower mass flow rate when the collector length increases. Figure 3 shows the mass flow rate versus thermal efficiency with different channel depth d at the solar intensity of 800 W/m2 . The collector channel depth affects the heat transfer rate from collector to the airflow through it and consequently affects the performance of the PVT system. In this study, the collector depth is used from 0.04 m to 0.07 m. The thermal efficiency in the collector channel depth of 0.04 m reaches about 41.89%. When the collector channel depth is 0.05 m, thermal efficiency decreases about 38.20%. And subsequently decreased by about 32.70% when the collector channels depth is 0.07 m. Figure 4 shows electrical efficiency versus the mass flow rate with different channel depth d at the solar intensity of 800 W/m2 . The electrical efficiency of the PVT system changes when the channel depth d is also changed. Electrical efficiency with mass flow rate from 0.0069 kg/s to 0.0491 kg/s about is 10.50% at channel depth of 0.04 m. When the channel depth is 0.05 m, the electrical efficiency decrease about 10.40%. and declining electrical efficiency is until 10.27% when the depth of the collector is 0.07 m. The reduction in electrical efficiency of the collector is due to the temperature increase of photovoltaic panel because the channel depth d is improved
  • 5.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207 1204 Figure 1. Thermal efficiency versus mass flow rate with different collector length L (d = 0.04 m) Figure 2. Electrical efficiency versus mass flow rate with different collector length L (d = 0.04 m) Figure 3. Mass flow rate versus thermal efficiency with different channel depth d (L=2.4 m) Figure 4. Electrical efficiency versus the mass flow rate with different channel depth d (L = 2.4 m) In this study, the comparison of the results with preceding theoretical or experimental studies is valuable. Table 1 shows that the use of channel depth of 0.04 m or 0.05 m and length of 2.4 m produced higher thermal and electrical efficiency than increase channel depth and length of the collector. The yield of this simulation shows that this result very closed to the results by Abd-AlRaheem and Amori [22]. The change in the channel depth and length of collector have an important effect on the electrical and thermal efficiency. The Increasing of the mass flow rate of collector increased the thermal and electrical performance of the collector. Table 1. The comparison with previous studies References Parameters Efficiencies Thermal (%) Electrical (%) Kasaeian et al. [23] d = 0.01 - 0.05 m 𝑚̇ = 0.018 - 0.06 kg/s 15 - 31 12 – 12.4 Joshi et al. [24] d = 0.05 m 𝑚̇ = 0.05 kg/s 13.4 – 16.5 9.5 - 11 Sarhaddi et al. [25] d = 0.05 m 𝑚̇ = 0.06 kg/s 25 10 Kim et al. [26] d = 0.06 m 22 15 Tonui and Tripanagnostopoulos [27] d = 0.15 m 𝑚̇ = 0.05 kg/s 18 12 Abd-AlRaheem and Amori [22] d = 0.24 m 50 10 Present study d = 0.04 – 0.07 m 𝑚̇ = 0.0069-0.0491 kg/s 32.70 – 41.89 10.50 – 10.27
  • 6. Int J Elec & Comp Eng ISSN: 2088-8708  Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra) 1205 4. CONCLUSION The performances of electrical and thermal efficiency with ∇-groove collector have been conducted by a mathematical model with the difference channel depth d and length L. Optimum thermal and electrical efficiency are 39.05 %, 10.43% respectively with the collector length L of 2.4 m. The optimum thermal and electrical efficiency are 41.89 %, 10.50% respectively with the collector depth d of 0.04 m. The variation of the length and depth of the collector is effected by changed mass flow rate and solar intensity. The effect Increasing of the mass flow rate of collector increased the thermal and electrical performance of the collector. The best of mass flow rate, length, and depth of collector is 0.0491 kg/s, 2.4 m and 0.04 m, respectively. ACKNOWLEDGEMENTS The authors would like to thank the Solar Energy Research Institute (SERI), University Kebangsaan Malaysia. And this research was financially supported by Hibah KEMENRISTEKDIKTI Indonesia, and their support is gratefully acknowledged. REFERENCES [1] A. Fudholi, et al., "Heat transfer and efficiency of dual channel PVT air collector: a review," International Journal of Power Electronics and Drive System (IJPEDS), vol. 10(4), pp. 2037-2045, Dec. 2019. [2] A. Fudholi, M. F. Musthafa, A. Ridwan, R.Yendra, Hartono, A.P.Desvina, M.K.B.M. Ali, K.Sopian, "Review of solar photovoltaic/thermal (PV/T) air collector," International Journal of Electrical and Computer Engineering (IJECE), vol. 1(1), pp. 126-133, 2019. [3] M. Zohri, A. Fudholi, M. H. Ruslan, and K. Sopian, "Mathematical modeling of photovoltaic thermal PV/T system with v-groove collector," AIP Conference Proceedings, vol. 1862, pp. 030063-1, 2017. [4] M. Zohri, S. Hadisaputra, A. Fudholi1, "Exergy And Energy Analysis Of Photovoltaic Thermal (PVT) With And Without Fins Collector," ARPN Journal of Engineering and Applied Sciences, vol. 13(3), pp. 803-808, 2018. [5] M. Zohri, et al., "Photovoltaic-Thermal (PVT) System with and Without Fins Collector: Theoretical Approach," International Journal of Power Electronics and Drive System (IJPEDS), vol. 8(4), pp. 1756-1763, Dec. 2017. [6] M. Zohri. Nurato, L. D. Bakti, A. Fudholi, "Exergy Assessment of Photovoltaic Thermal with V-groove Collector Using Theoretical study," TELKOMNIKA (Telecommunication, Computing, Electronics and Control), vol. 16(2), pp. 550-557, Apr. 2018. [7] J. S. Kumari and Ch. S. Babu, "Mathematical modeling and simulation of photovoltaic cell using Matlab-simulink environment," International Journal of Electrical and Computer Engineering (IJECE), vol. 2(1), pp. 26-34, 2012. [8] O. Amirullah, A. Penangsang, Soeprijanto, "Power Quality Analysis of Integration Photovoltaic Generator to Three Phase Grid under Variable Solar Irradiance Level," TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 14(1), pp. 29-38, 2016. [9] H. Sharma, N. Pal, P.K. Sadhu, "Modeling and Simulation of Off-Grid Power Generation," TELKOMNIKA Indonesian Journal of Electrical Engineering, vol. 13(3), pp. 418- 424, 2015. [10] N. Mohammad, M.A. Islam, T. Karim, Q.D. Hossain, "Improved solar photovoltaic array model with FLC based maximum power point tracking," International Journal of Electrical and Computer Engineering (IJECE), vol. 2(6), pp. 717-730, 2012. [11] A. Fudholi, M. Zohri, G.L Jin, A. Ibrahim, C.H. Yen, M.Y. Othman, M.H. Ruslan, K. Sopian, "Energy and exergy analyses of photovoltaic thermal collector with ∇-groove," Solar Energy, vol. 159, pp. 742-750, 2018. [12] A. Fudholi, M. Zohri, N. S. B. Rukman, N.S. Nazri, M. Mustapha, C. H. Yen, M. Mohammad, K. Sopian, "Exergy and sustainability index of photovoltaic thermal (PVT) air collector: A theoretical and experimental study," Renewable and Sustainable Energy Reviews, vol. 100, pp. 44-51, 2019. [13] R. K. Agarwal and H. P. Garg, "Study of a Photovoltaic Thermal System Thermosyphonic Solar Water Heater Combined With Solar Cells," Energy Convers. Manag., vol. 35(7), pp. 605–620, 1994. [14] A. Fudholi, et al., "Performance and Cost Benefits Analysis of Double-Pass Solar Collector With and Without Fins," Energy Conversion and Management, vol. 76, pp. 8-19, 2013. [15] A. Fudholi, et al., "Collector Efficiency of the Double-Pass Solar Air Collectors With Fins," Proceedings of the 9th WSEAS International Conference on System Science and Simulation in Engineering (ICOSSSE’10), Japan, pp. 428-34, 2010. [16] A. Fudholi, et al., "Experimental Study of the Double-Pass Solar Air Collector With Staggered Fins," Proceedings of the 9th WSEAS International Conference on System Science and Simulation in Engineering (ICOSSSE’10), Japan, pp. 410-14, 2010. [17] A. Fudholi, et al., "Performance Analysis of Photovoltaic Thermal (PVT) Water Collectors," Energy Conversion and Management, vol. 78, pp. 641-651, 2014. [18] R. J. Amrizal N, Chemisana D, "Hybrid photovoltaic–thermal solar collectors dynamic modeling," Appl Energy, vol. 101, pp. 797–807, 2013. [19] K. S. Ong, "Thermal performance of solar air heaters: Mathematical model and solution procedure," Sol. Energy, vol. 55(2), pp. 93–109, 1995. [20] T. T. Chow, "A review on photovoltaic/thermal hybrid solar technology," Appl. Energy, vol. 87(2), pp. 365–379, 2010.
  • 7.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1200 - 1207 1206 [21] A. Fudholi, K. Sopian, M. Y. Othman, M. H. Ruslan, and B. Bakhtyar, "Energy analysis and improvement potential of finned double-pass solar collector," Energy Convers. Manag., vol. 75, pp. 234–240, 2013. [22] M.A. Abd-AlRaheem and Amori, "Field study of various air based photovoltaic/thermal hybrid solar collectors," Renewable Energy, vol. 63, pp. 402-414, 2014. [23] Kasaeian, Alibakhsh, Y. Khanjari, S. Golzari, O. Mahian, and S. Wongwises, "Effects of forced convection on the performance of a photovoltaic thermal system: An experimental study," Experimental Thermal and Fluid Science, vol. 85, pp. 13-21, 2017. [24] A. Joshi, et al., "Performance evaluation of a hybrid photovoltaic thermal (PV/T) (glass-toglass) system," International Journal of Thermal Sciences, vol. 48(1), pp. 154-164, 2009. [25] F. Sarhaddi, et al., "An improved thermal and electrical model for a solar photovoltaic thermal (PV/T) air collector," Applied Energy, vol. 87(7), pp. 2328-2339, 2010. [26] Kim, J.-H., S.-H. Park, and J.-T. Kim, "Experimental Performance of a Photovoltaic-thermal Air Collector," Energy Procedia, vol. 48, pp. 888-894, 2014. [27] J. K. Tonui and Y. Tripanagnostopoulos, "Performance improvement of PV/T solar collectors with natural air flow operation," Solar Energy, vol. 82, pp. 1–12, 2008. BIOGRAPHIES OF AUTHORS Saprizal Hadisaputra is currently a chemistry lecturer the University of Mataram, Lombok, Indonesia. His Ph.D degree was obtained in from Austrian-Indonesian Centre for Computational Chemistry, Universitas Gadjah Mada at 2014 in the field of Physical Chemistry/Computational Chemistry. He took his bachelor degree of chemistry at the same university and finished his master degree in Nanotechnology at Flinders University, Australia. He actively conducts research in computational chemistry that focuses on the use of quantum mechanics to predict the corrosion inhibition performance and energy storage of new materials. He published many articles in national and international journals. Muhammad Zohri obtained his S.Si (2009) in physics and received the Master of Science degree in Solar Energy Research Institute from The National University of Malaysia, Malaysia in 2017, with a thesis based on PVT system. He was appointed a Graduate Research Assistant (GRA) under Dr. Ahmad Fudholi in Solar Energy Research Institute (SERI) in UKM Malaysia, during his master’s degree. He worked at State Islamic University (UIN) Mataram, Indonesia. He was a speaker at The 2nd International Symposium on Current Progress in Mathematics and Science (2nd ISCPMS) FMIPA UI in Depok and The 4th Solar Energy Research Institute (SERI) Colloquium 2016, in UKM Bangi, Malaysia. He has published many paper in Scopus and WoS Index. Bahtiar is currently a physic lecturer the State Islamic University (UIN) Mataram, Lombok, Indonesia. His Ph.D degree was obtained in from State University of Surabaya, Indonesia at 2016 in the field of Physic education. He took his Master degree of Physic education at State University of Yogyakarta. He actively conducts research in physic and physic education. He published many articles in national and international journals. He was a speaker at Mathematic- Informatics-Science-Education International-Conference (MISEIC) 2017, 2018 by FMIPA State University of Surabaya and international Conference on Environmental and Science Education (ICESE) 2019 by FMIPA State University of Semarang. Ahmad Fudholi obtained his S.Si (2002) in physics. He has working experience about 4 years (2004-2008) as Head of Physics Department at Rab University Pekanbaru, Indonesia. A. Fudholi started his master course in Energy Technology (2005-2007) at UniversitiKebangsaan Malaysia (UKM). After his master he became Research Assistant at UKM up to 2012. After his Ph.D (2012) he became Postdoctoral in Solar Energy Research Institute (SERI) UKM up to 2013. He joined the SERI as a Lecture in 2014. More than USD 304,000 research grant in 2014–2017 obtained. More than 25 M.Sc project supervised and completed. Until now, he managed to supervise 6 Ph.D (4 main supervisor and 1 Co. supervisor), 2 Master’s student by research mode, and 5 Master’s student by coursework mode, he was also as examiner (3 Ph.D and 1 M.Sc). His current research focuses on renewable energy, especially energy technology. He has published more than 100 peer-reviewed papers, which 25 papers in ISI index (20 Q1, impact factor more than 3) and more than 48 papers in Scopus index, 10 more currently accepted manuscript, 20 more currently under review, and 2 book chapters. Addition, he has published more than 70 papers in international conferences. His total citations of 571 by 395 documents and h-index of 12 in Scopus (Author ID: 57195432490). His total citations of 1093 and h-index of 19 in google scholar. He is appointed as reviewer of high impact journal such as Renewable and Sustainable Energy Reviews, Energy Conversion and Management, Applied Energy, Energy and Buildings,
  • 8. Int J Elec & Comp Eng ISSN: 2088-8708  Effect analysis of the different channel length and depth of photovoltaic … (Saprizal Hadisaputra) 1207 Applied Thermal Engineering, Energy, Industrial Crops and Products, etc. He is appointed as reviewer of reputation journals such as Drying Technology, International Journal of Green Energy, Drying Technology, Bio system Engineering, Journal of Sustainability Science and Management, Journal of Energy Efficiency, Sains Malaysiana, Jurnal Teknologi etc. He is also appointed as editor journals. He has received several awards such as Gold Medal Award at the International Ibn Al-Haytham’s Al-Manazir Innovation and Invention Exhibition 2011, Silver Medal Award at the International Technology EXPO (ITEX) 2012, Silver Medal Award at the Malaysia Technology Expo (MTE) 2013, Bronze Medal Award at International Exposition of Research and Invention (PECIPTA) 2011, also 2 Bronze Medal Award at PECIPTA 2017. He was also invited as speaker: Workshop of Scientific Journal Writing; Writing Scientific Papers Steps Towards Successful Publish in High Impact (Q1) Journals.