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Energy Conversion and Management 155 (2018) 324–343
Contents lists available at ScienceDirect
Energy Conversion and Management
journal homepage: www.elsevier.com/locate/enconman
Experimental investigation of cooling photovoltaic (PV) panels using (TiO2)
nanofluid in water -polyethylene glycol mixture and (Al2O3) nanofluid in
water- cetyltrimethylammonium bromide mixture
MARK
⁎
Munzer.S.Y. Ebaida, , Ayoup.M. Ghrairb, Mamdoh Al-Busoulc
a
b
c
Mechanical Engineering Department, Philadelphia University, Amman, Jordan
Royal Scientific Society, Water, and Environment Center, Amman, Jordan
Mechanical Engineering Department, Applied Balqa University, Amman, Jordan
A R T I C L E I N F O
A B S T R A C T
Keywords:
Nanofluid (Al2O3–water)
Nanofluid (TiO2–water)
Concentration
Efficiency
Power
Cooling of photovoltaic (PV) panels was investigated experimentally outdoors using two nanofluids and water as
a cooling medium for volume flow rate ranging from 500 to 5000 mL/min at concentrations (0.01 wt.%, 0.05 wt.
%, and 0.1 wt.%) under different radiation intensity. Two types of nanofluids were used, namely Al2O3 in water
-polyethylene glycol mixture at pH 5.7, and TiO2 in water- cetyltrimethylammonium bromide mixture at pH 9.7,
respectively. The cooling of PV panel required incorporating a heat exchanger of aluminium rectangular cross
section at its back surface to accommodate different volume flow rate of the cooling medium aforementioned.
The system was tested under climate conditions of Jerash-Jordan. Determination of flow characteristics; friction
factor, f and product of friction factor Reynolds number, of TiO2, Al2O3 nanofluids and water as a cooling
medium were investigated. Also, a f Re comparison of the temperature between the cooled PV cell and without
cooling for volume flow rate ranging from 500 to 5000 mL/min was presented. Results showed that the nanofluid cooled PV cell in both types caused higher decrease in the average PV cell temperature compared with
the cooled cell with water and without cooling. In addition, Al2O3 nanofluid showed better performance than
TiO2 nanofluid. Furthermore, experimental results showed that higher concentration of nanofluid produces a
better cooling effect of the PV cell for all the studied range of volume flow rate. Also, electrical analysis of power
and efficiency showed that TiO2 nanofluid gives better performance for the studied range of volume flow rate
and concentrations compared with water cooling and without cooling.
1. Introduction
It is well known that global warming and climate change was caused
by greenhouse gas emissions whereby a high percentage of emissions is
due to burning fossil fuels. To reduce the environmental impacts of these
gases, photovoltaic (PV) technology can be considered an ideal solution.
However, one of the main problems which limit the extensive use of PV
systems is the rising in temperature of PV panels. Overheating of a PV
module decreases performance of output power by 0.4–0.5% per 1°C over
its rated temperature (which in most cases is 25 degrees C). This is why the
concept of “cooling of PV” has become so important [1,2]. An effective
way of improving efficiency and reducing the rate of thermal degradation
of a PV module is by reducing the operating temperature of its surface.
This can be achieved by either by using conventional method of cooling by
water and air with natural or forced convection or by what is called nanofluid which was introduced by Choi and Estman [3] in 1995.
⁎
Many researchers have proposed various techniques of water
cooling to reduce PV surface temperature, and improve the performance of PV systems. Among them is the work done by Krauter [4] in
which a thin film of water nozzles running over the surface panel was
utilized. It was noticed that water decreased cell temperature up to
22°C and electrical yield by 10.3%. Odeh and Behnia [5] used water
trickling method on the upper surface of the PV panel and obtained an
increase of about 15% in system output at peak radiation conditions.
Hosseini et al. [6] carried out an experimental study to compare the
performance of a PV system combined with a cooling system with
conventional PV. The results showed that combined system yielded
higher power output and efficiency compared to the conventional one.
Royne and Dey [7] used the technique of jet impingement cooling
devices for arrays of densely packed PV cells. Their results showed that
using this technique had only a weak effect on the electrical output of
the photovoltaic system compared with the effect of changing the
Corresponding author.
E-mail addresses: [email protected] (M.S.Y. Ebaid), [email protected] (A.M. Ghrair), [email protected] (M. Al-Busoul).
http://dx.doi.org/10.1016/j.enconman.2017.10.074
Received 25 July 2017; Received in revised form 24 October 2017; Accepted 25 October 2017
Available online 10 November 2017
0196-8904/ © 2017 Elsevier Ltd. All rights reserved.
Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
Nomenclature
Pin
Pout
Re
Q̇
um
Vnp
VT
Wch
Symbols
A
Apv
Cp, nf
Cp, np
Cp, bf
Dh
Gt
Hch
ISC
Imax
kn, eff
kbf
knp
mnp
P
P
Pmax
cross section of heat exchanger channel
photovoltaic cell area
specific heat of nanofluid
specific heat of nanoparticles
specific heat of base fluid
hydraulic diameter of heat exchanger channel
solar irradiation
height of heat exchanger channel
short circuit current
maximum current
effective thermal conductivity of nanofluid
thermal conductivity of basefluid
thermal conductivity of nanoparicles
mass of nanoparticles
wetted perimeter
power
maximum power
power input of the PV cell
power output of the PV cell
Reynolds number
fluid flow rate
mean velocity of flow
volume of nanoparticles
total volume of mixture
width of heat exchanger channel
Greek letters
ρ
ρnf
ρbf
ρnp
μ
μnp
ν
νnp
ϕ
density
density of nanofluid
density of base fluid
density of nanoparticles
dynamic viscosity
viscosity of nanoparticles
kinematic viscosity
kinematic viscosity of nanofluid
volume fraction of nanoparticles
dispersion. The measurements showed a clear effect of the particle size
and method of dispersion. Xie et al. [26] measured the thermal conductivity of aqueous Al2O3 nanofluids with even smaller particles
(1.2–302 nm). They also observed the effect of particle size in addition
to the effect of the base solution. Murshed et al. [27], who measured
the thermal conductivity of aqueous solutions of spherical and cylindrically shaped TiO2 nanoparticles, found that 15 nm-sized spherical
particles show slightly less enhancement than 10 × 40 nm rods, which
showed an enhancement of 33% for a volume fraction of 5%. However,
the enhancement was far more than that predicted by the HamiltonCrosser model. Same researchers [28] developed a combined model for
the effective thermal conductivity. Wang et al. [29] proposed a fractal
model predicts well the trend for variation of the effective thermal
conductivity with dilute suspension of nanoparticles, and fits successfully with our experimental data for 50 nm CuO particles suspension in
deionized water when/ < 0:5%. The calculated result also shows that
the predictive calculation of effective thermal conductivity is complicated. Further work would be needed, especially for metallic nanoparticles inclusion. Similar results were obtained by other researchers
[30–32].
Many researchers carried out different reviews on nanofluids characteristics, heat transfer and properties. Zhou et al. [33] presented a
review on development of nanofluid preparation and characterization.
Lee et al. [34] carried out a review of thermal conductivity data, mechanics and models for nanofluids while Ghamdi et al. [35] was related to of nanofluid stability properties and characterization in stationary conditions. On the same context Fan and Wang [36] presented
a review of heat conduction in nanofluids while Vajjha and Dass [37]
work was a review and analysis on influence of temperature and concentration of nanofluids on thermophysical properties, heat transfer
and pumping power. Reviews of thermophysical characteristics of nanofluids and heat transfer were carried out by [38–40].
The influence of nanofluid on different solar thermal applications
was investigated by many researchers. One of these applications is the
solar collector whereby several papers were found in the literature.
Among these is the work carried out by Luo et al. [41] in which they
prepared nanofluids by dispersing and oscillating TiO2, Al2O3, Ag, Cu,
SiO2, graphite nanoparticles, and carbon nanotubes into Texatherm oil
to study the performance of a DAC solar collector. Their results showed
that the use of nanofluid in solar collector can improve the outlet
temperature and efficiency. Rahman et al. [42] performed a numerical
study for a triangular shape solar collector with nanofluids TiO2, Al2O3
average temperature of the cells. Hence it was concluded that liquid jet
impingement would be a promising method for dissipating heat efficiently from densely packed cells. Abdolzadeh and Ameri [8] found
out that spraying water over the front of PV cells improved the performance of a PV system, while Nizetic et al. [9] reported that better
performance could be achieved by spraying water on the front and back
surfaces of a PV panel. However, Bahaidarah et al. [10] used water
cooling on the back surface and front surface to evaluate performance
of PV module by using EES software. They found that the EES results for
surface cooling; the cell temperature was 35°C whereas 37.8°C for noncooling. In the contrast, for the back surface cooling; the cell temperature was 25.9°C with cooling whereas 42.8°C for non-cooling. A
similar work by Azadeh [11] showed that the electrical power output
and efficiency increased noticeably by cooling the PV cells with a thin
film of water. Rosa et al. [12] and Tina et al. [13] carried out work to
study the behaviour of PV panel submerged in water. Both observed an
average increase in the electrical efficiency. Furushima and Nawata
[14] used a cooling siphonage device for enhancing the performance of
a PV power generation system. In the same context, many researchers
[15–19] and [20–23] have investigated the effect of water and air based
cooling, respectively, on the performance of hybrid photo voltaic
thermal units of PV/T systems. From the analysis of the above mentioned articles, it is clear that cooling leads to an improvement in the
performance of PV systems.
The thermal conductivity of nanofluids is much improved when
compared with usual suspensions. The enhancement of the thermal
conductivity of nanofluids over that of the base fluid is often a few
times better than what would have been given by micrometer-sized
suspensions. Lee et al. [24] presented conductivity measurements on
fluids that contained Al2O3 and CuO nanoparticles in water and ethylene glycol. The results clearly indicated that the thermal conductivity
enhancement of the Al2O3 and CuO nanofluids were high. They used
volume fractions of only 1–5%. The enhancement was higher when
ethylene glycol was the base fluid. An enhancement of 20% was observed at 4% volume fraction of CuO. The enhancement when water
was the base fluid was lower but still substantial, with 12% enhancement at 3.5% CuO, and 10% enhancement with 4% Al2O3. Wang et al.
[25] also measured the thermal conductivity of CuO–water and
Al2O3–water nanofluid but their particle size was smaller (23 nm for
CuO and 28 nm for Al2O3). They also measured the nanofluids with
ethylene glycol and engine oil (Pennzoil10W-30) as the base fluids. The
measurements showed a clear effect of the particle size and method of
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Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
that the addition of less than 2% Al2O3 nanoparticles significantly increases the specific heat of Hitec metal at low temperatures. Kabeel
et al. [55] used Al2O3 nanoparticles with water inside a single basin
solar still. Their results showed that using nanofluids improves the solar
still water productivity by about 116% and 76% with and without
operating the vacuum fan. The authors attributed this increment to the
increase of evaporation rate inside the still. Also, Kabeel et al. [56]
investigated a small unit for water desalination coupled with nanofluid-based (Cu/water) solar collector as a heat source. They authors
reported that the water cost can be decreased from 16.43 to 11.68 $/m3
at concentration ϕ = 5%. Al-Nimr et al. [57] presented a mathematical model to describe the effects of using silver-water nanofluid on the
thermal performance of a shallow solar pond (SSP) and showed that the
energy stored in the nanofluid pond is about 216% more than the energy stored in the brine pond. Liu et al. [58] experimentally showed
that the solar collector integrated with open thermosyphon has a much
better collecting performance compared to the collector with concentric
tube and its efficiency could be improved by using CuO/water nanofluid as the working fluid as well. Their results showed that the maximumand mean values of the collecting efficiency of the collector with
open thermosyphon using nanofluids increased 6.6% and 12.4%, respectively. Singh et al. [59] used Cu metallic nanoparticles to improve
the thermophysical properties of organic heat transfer fluids used in
concentrated solar power. Elmir et al. [60] carried out a numerical
simulation cooling a solar cell by forced convection in the presence of a
nanofluid while Zeinali et al. [61] studied numerically convective heat
transfer of Al2O3/water, Co/water and Cu/water nanofluids through
square cross-section duct in laminar flow.
Also, many papers in the literature have discussed analytically,
numerically and experimentally the performance of hybrid PVT
(photo voltaic thermal units) systems using different base nanofluids
(Al2O3/water, CuO/water, Cu/water, silica/water, SiO2/water) for
cooling. Michael and Iniyan [62] reported that due to the inherent
drawback of lower efficiencies per unit area of solar PV module and
solar water heater, copper oxide–water (CuO/H2O) nanofluid was
used to improve performance. Experimentally, they observed that the
nanofluid made a significant improvement in the thermal performance
compared to water. Ghadiri et al. [63] studied the effects of ferrofluids as a coolant on the overall efficiency of a PVT (photovoltaic
thermal systems). They used distilled water as a base fluid and a nanoferrofluid (Fe3O4-water) with 1% and 3% concentrations by weight
(wt.%). Experiments were performed indoor conditions under two
constant solar radiations (1100 W/m2 and 600 W/m2). The results
showed that by using a 3 wt.% ferrofluid, the overall efficiency of the
system improved by 45%. Xu and Kleinstreuer [64] studied new
designs of dual concentration photovoltaic–thermal (CPV/T) systems
that provide both electrical and thermal energy, while reducing solar
cell material usage via optical techniques. The results showed that
using nanofluids improves electrical and total efficiencies of the
system, especially when using silicon solar cells. Sardarabadi et al.
[65] performed experiments to study the effects of using SiO2/water
nanofluid as a coolant on the thermal and electrical efficiencies of a
photovoltaic thermal (PV/T) system. It was observed that the thermal
efficiency of the PV/T collector for the two cases of 1 and 3 wt.% of
silica/water nanofluid increased 7.6% and 12.8%, respectively.
However, in recent years, there has been an increasing interest in
investigations about the effects of different cooling nanofluids on PV
cells performance. Among these studies, the work carried out by
Karami and Rahimi [66] in which they studied the cooling performance of channels (straight and helical) by water-based nanofluids
containing small concentrations of Boehmite (AlOOHxH2O) for the PV
cell. Results showed that the nanofluid performs better than water and
caused higher decrease in the average PV cell temperature. Efficiencies were about 39.70% and 53.76% for 0.1 wt.% at flow rate of
80 ml/min and electrical efficiency about 20.57% and 37.67% for
straight and helical channel, respectively.
and Cu in water. Results showed 24.28% improvement for Gr number
= 106 at 10% volume fraction of copper particles. Also, the convective
heat transfer performance is better when the solid volume fraction is
kept at 0.05 or 0.08. Faizal et al. [43] investigated the thermal performance of nanofluid solar collector using CuO, SiO2, TiO2 and Al2O3
nanofluids water based. Results confirmed that higher density and
lower specific heat of nanofluids offers higher thermal efficiency than
water and therefore can reduce the solar collector area about 25.6%,
21.6%, 22.1% and 21.5% for CuO, SiO2, TiO2 and Al2O3 nanofluids.
Environmental damage cost is also lower with the nanofluid based solar
collector. Parvin et al. [44] numerically investigated the effects of the
nanoparticle volume fraction (ϕ = 0%, 1%, 3%, 5% and 7%) and the
Reynolds number (Re = 200, 400, 600, 800 and 1000) on the temperature distribution, rate of entropy generation, and collector efficiency. The working fluid was incompressible Cu-water nanofluid under
a laminar regime. Their findings showed that increasing the particles
concentration raises the fluid viscosity and decreases the Reynolds
number and consequently decreases heat transfer.
Ladjevardi et al. [45] numerically studied the effects of using nanofluid (graphite/water) on the performance of a solar collector considering the different diameter and volume fractions of graphite nanoparticles. Their numerical results showed that nanofluid collector
thermal efficiency increases about 88% compared with the pure water
collector with the inlet temperature of 313 K. It also can be increased to
227% with the inlet temperature of 333 K. Hordy et al. [46] used multi
walled carbon nanotubes (MWCNTs) in water, ethylene glycol, propylene glycol. They examined both the long-term and high-temperature
stability of CNT nanofluids for use in direct solar absorption. This study
reported a quantitative demonstration of the high temperature and
long-term stability of ethylene glycol and propylene glycol-based
MWCNT nanofluids for solar thermal collectors. Said et al. [47] experimentally investigated the thermal conductivity, viscosity and
pressure drop of water, ethylene glycol (EG) and EG + H2O (60:40)based Al2O3 (13 nm) nanofluids. Their results showed that nanofluids
pressure drop at a low concentration flowing in a solar collector is
slightly higher than the base fluid. Liu et al. [48] experimentally investigated the feasibility of using the grapheme (GE)/ionic liquid 1hexyl-3-methylimidazolium
tetrafluoroborate.
They
observed
15.2%–22.9% enhancement in thermal conductivity using 0.06% volume graphene in the temperature range from 25 to 200°C. Their results
showed that GE is a better nanoadditive for nanofluids than other
carbon materials and metal nanoparticles. Saidur et al. [49] investigated the effects of different parameters on the efficiency of a lowtemperature nanofluid based direct absorption solar collector (DAC)
with water and aluminium nanoparticles. Their results revealed that
Aluminium/water nanofluid with 1% volume fraction improves the
solar absorption considerably. They found that the effect of particle size
on the optical properties of nanofluid is minimal, but in order to have
Rayleigh scattering the size of nanoparticles should be less than 20 nm.
Work on other solar thermal applications such as flat plate solar collector using nanofluid was carried out by Said et al. [50]. They found
that nanofluids with single wall carbon nanotubes (SWCNTs) in a flat
plate solar collector could reduce the entropy generation by 4.34% and
enhance the heat transfer coefficient by 15.33%. Yousefi et al. [51,52]
studied the effect of Al2O3 (15 nm) and MWCNT (10–30 nm) water
nanofluid on the efficiency of a flat plate solar collector experimentally.
The weight fractions of the nanoparticles were 0.2% and 0.4%, and the
experiments were performed with and without Triton X-100 as surfactant. Their findings showed that the surfactant presence in the nanofluid extremely affects solar collector’s efficiency. Sokhansefat et al.
[53] numerically investigated the heat transfer enhancement for Al2O3/
synthetic oil nanofluid with concentrations up to 5% in a parabolic
trough collector tube at different operational temperatures and found
that Nanofluid enhanced convective heat transfer coefficient. Ho et al.
[54] investigated the use of alumina nanoparticles in doped molten
Hitec (a nitrate salt) in concentrating solar power systems. They found
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Yun and Qunzhi [67] used a film of MgO/water nanofluid with
different concentrations of 0.02%, 0.06% and 0.1% by weight, on top of
silicon photovoltaic cells in order to absorb extra heat from the cells.
They investigated the effects of the nanofluid film thickness on the
output power of solar cells. They found that an increase of the film
thickness or the concentration of the nanofluid reduces the thermal and
electrical efficiencies at a constant solar radiation. In another study, a
simple passive cooling system with cotton wick structures developed for
standalone flat PV modules was investigated by Chandrasekhar et al.
[68]. The thermal and electrical performance of flat PV module with
cooling system consisting of cotton wick structures in combination with
water, Al2O3/water and CuO/water nanofluids were investigated experimentally. The experimental results showed that the cell temperature, maximum power output and efficiency all increased when using
cotton wick structure in combination with nanofluids. Bearing in mind
the strategic location of Jordan in the sun Belt with more than 300
sunny days per year and the scarcity of water (3rd country in the world
in water scarcity), moreover, Jordan depends almost totally on imported energy carrier. All of these sectors make it necessary to use PV
systems in power generation.
From the literature review, it has been found that a lot of research
progress has been addressed to cooling system such as solar systems,
hybrid PVT systems using water, air and water based nanofluids or liquid based nanofluids. For PV cells cooling using nanofluids, papers
were scarce in the open literature regarding experimental work being
carried out outdoors whereby the solar irradiation is varying with time
in order to get more realistic results. Moreover, the type of nanoparticles mixture used in this current work is different as surfactants
were added to nanofluid in order to lower surface tension of mixture
and increase immersion of particles and stability. Hence, the work in
this paper was motivated. In this regard, the objective of the current
work is to investigate experimentally the effect of two types nanofluids
water based (Al2O3/water-mixture, TiO2/water-mixture) used for
cooling on cell temperature, efficiency, maximum power output and
compare the results with water and without water cooling, respectively.
Also, different concentration of nanofluid by weight and different volume flow rate were conducted to study the effect on the PV performance.
2.2. Equipment and instruments
The equipment and instruments used in the experimental setup are
presented in Fig. 4 as follows:
i. Mono-crystalline silicon PV cell of 50 W power output as shown in
Fig. 4a.
ii. Air Cooled Heat Exchanger as shown in Fig. 4b.
iii. Centrifugal pumps, Pedrollo type as shown in Fig. 4c of power
0.5HP, head 23m, and flow rate 10–80 L/min.
iv. Flowmeter as shown in Fig. 4d of working pressure; (MPa) ≤ 0.6,
and accuracy; ± 5% .
v. Digital multimeter as shown in Fig. 4e of DC voltage range from
200mV to 500V and accuracy of ± 1.0% + 2 . Also, DC current
range from 2000µA to 10A and accuracy ± (1.0% + 2).
vi. Solar power meter as shown in Fig. 4f of range 2000 W/m2 and
accuracy; ± 10%W/m2 .
vii. K-type thermocouples as shown in Fig. 4g of range; –270 to
1260°C, limits of error; ± 1.1 °C
viii. Data logger as shown in Fig. 4h of range from −40 to 1350 °C, and
accuracy ± 0.1%
In an attempt to investigate the effect of different configurations of
channels on the performance of the PV cell, the fluid flow channels can
be arranged in different geometries depending on the heat dissipation
requirement. In this study, a straight Aluminium rectangular channel is
considered as shown in Fig. 5, and two of them are used in this current
work.
In order to achieve high accuracy, a computer numerical control
(CNC) machine was used as shown in Fig. 5a to etch particular design
on a Plexiglas aluminium plate with a thickness of 10 mm. The straight
design contains 23 parallel channels with a hydraulic diameter of 4.1
mm which was fabricated from aluminium material of dimensions of
24.5 cm in length, 5 mm in width and 3.5 mm in depth. All channels
have an identical rectangular entrance cross section. Moreover, in the
design just mentioned, appropriate provisions are made for coolant
inlet and outlet locations as shown in Fig. 5b.
It should be noted that the experiments have been conducted for
various volume flow rate ranging from 500 to 5000 mL/min under
different radiation intensity to observe the effect of cooling on the
performance parameters of PV cell. At the first stage, the flow rate was
adjusted at a desirable amount by measuring outlet flow using a flow
meter. Consequently, enough time about 30 min was given to the
2. Proposed experimental rig
2.1. Experimental rig description
The proposed experimental rig setup as shown in Fig. 1 was constructed on the roof of Mechanical Engineering Department at Philadelphia University to ensure that all PV modules working under the
same operating conditions (i.e. solar irradiation intensity, ambient
temperature, wind speed and dust content). The rig as shown in the
schematic diagram Fig. 2 consists of three mono-crystalline silicon
photovoltaic modules with an active area of 18 mm by 50 mm whereby
two aluminium rectangular heat exchangers were placed on the back
surface of PV modules. Heat sink material were added to ensure that a
good contact between the aluminium heat exchanger and the back
surface of the PV cell. Two circulating centrifugal pumps were used to
circulate the cooling fluids under consideration from the two 15L insulated tank that is used as an accumulator and they are connected by
PVC pipes to the system. Two air cooling heat exchangers were installed
to cool the cooling fluid. 12 K-type thermocouples were fitted at different positions across the PV cell are shown in Fig. 3 to measure the PV
surface temperature. Two flow meters were attached at the outlet of
centrifugal pumps Equipments such as solar power meter, digital multimeter and data logger were used to measure solar irradiation intensity, inlet and outlet fluid temperature of the PV module, respectively. Detailed description of the component and instruments used in
the rig setup is presented in the following Section 2.2.
Fig. 1. Actual experimental setup.
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M.S.Y. Ebaid et al.
Fig. 2. Schematic diagram of the proposed experimental setup.
temperature, inlet and outlet flow temperatures through the heat exchanger, and current and voltage values were recorded.
Temperature points
(red spots)
3. Preparation of nanofluids
3.1. Preparation of nanofluids (TiO2 and Al2O3)
Nanoparticles, the additives of nanofluids, play an important role in
changing the thermal transport properties of cooling fluids. Two types
of nanoparticles (Al2O3 and TiO2) have been used in the nanofluids
preparation. Al2O3 nanoparticles were obtained from Dequssa Company
(Germany) and TiO2 nanoparticles were obtained from EVNANO
Advanced Chemical Materials Co., China. Three different concentrations Al2O3 nanofluids (0.01%, 0.05%, and 0.10%) by weight and three
different concentrations TiO2 nanofluids (0.01%, 0.05%, and 0.1%) by
weight using distilled water as a matrix were prepared. The nanoparticles were directly mixed with the base liquid and thoroughly
stirred for 1 h. Nanoparticles were dispersed in distilled water using
powerful probe ultrasonic processor (UP400S, Hielscher, Germany) for
Fig. 3. PV cell surface with 12 K-type thermocouples positions.
system to reach the steady state conditions. At this stage, 12 readings of
surface temperature of the PV cell using thermocouples were recorded
at different positions. Also, solar radiation intensity, ambient
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Fig. 4. Equipment and instruments used in the experimental setup.
(a) PV cell module
(b) Air cooled heat
(c) Centrifugal pumps
(d) Flow meter
(e) Digital multimeter
(g) K-type thermocouples
(f) Solar power meter
(h) Data logger
1 h. Cooling jacket was utilized to prevent temperature elevation of
nanofluid during the sonication process.
overcoming the attractive forces between particles. Therefore, the stability of nano-fluids was investigated at various pH and suitable surfactant.
3.2. Stability of nanofluids
3.2.1. pH control of nanofluids
Electrostatic stabilization can be achieved when charges accumulate
at the surface of particles have zeta potential values more than 30 mV
or less than −30 mV. Under such circumstances no agglomeration
occurs. Ionic strength and pH influence on electrostatic stabilization;
when pH is far from the isoelectric point, agglomeration is inhibited,
Sonication process of the nanofluids was not enough to have stable
dispersion and prevent the long term agglomeration of nanoparticles.
Aggregation of nanoparticles in cooling-fluid can lose their potential to
transfer heat. Aggregation of nanoparticles could be avoided by
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Fig. 5. Aluminium rectangular heat exchanger.
Coolant inlet
and outlet
(a) Aluminium rectangular channel
(b) Fabricated aluminium channel
under fabrication
with coolant inlet and outlet
Nia et al. [69]. Each concentration of the Al2O3 and TiO2 nano-fluids
were prepared at six different pH values. The stability of the nano-fluids
was monitored for several days on shelf as shown in Figs. 6 and 7. Tests
showed that the decrease or increment of agglomeration was obtained
by changing pH.
4.2. Nanofluid properties parameters
3.3. Ultrasonic agitation
ρnf = (1−φ)ρ bf + φρnp
After preparation of nanofluids, agglomeration might occur over the
time which results in fast sedimentation of nanoparticles due to the
enhancement of downward body force. Using the Ultrasonic vibration
instrument for about 1 h to utilize high energy of cavitation for
breaking clusters into particles.
where ρ bf : density of base fluid, φ : volume fraction of nanoparticles, and
ρnp : Density of nanoparticles
i. The density of a nanofluid
Density of a nanofluid is based on the classical theory of two-phase
mixture given in [73,74].
ii. Mass of nanoparticle is defined as
mnp = 0.001φρnp → φ =
3.4. Addition of surfactants
φ=
0.001 ρnp
(2)
Vnp
VT
and φ =
ρnf −ρ bf
ρ b−ρ bf
(3)
where: Vnp:Volume of nanoparticle and VT: Total volume of mixture
iv. Specific heat of nanofluid is given by [75] as:
Cp, nf = (1−φ) Cp, bf + φ Cp, np
(4)
v. Dynamic and kinematic viscosity of nanofluid is defined as
μ n f = (1 + 2.5 φ) × μ b f ,νn f =
4. Parameters used in the calculations
μn f
ρn f
(5)
vi. Effective thermal conductivity of nanofluid is reported [76] as:
The parameters used for the calculations in this current work are
three types:
(kbf −knf ) + 2φ (kp−knf ) ⎤
kn, eff = knf × ⎡
⎢
(k
⎣ bf + 2knf )−φ (kbf −knf ) ⎥
⎦
4.1 Fluid flow parameters
(6)
4.3. Solar cell performance parameters
These are the mean velocity defined as um =
defined as Dh =
mnp
iii. Volume fraction of nanoparticle is defined as:
Surfactants can be defined as chemical compounds added to nanoparticles in order to lower surface tension of liquids and increase immersion of particles. In a stabilized dispersion large molecules such as
polymers and surfactants, adsorbed on to the surface of particles prevent re-agglomeration on long term Nia et al. [69]. Two types of surfactant have been utilized for water base fluid of Al2O3 and TiO2 nanoparticles. The best stabilization results of nano-fluids at long term
condition were achieved by addition of 0.1g Cetyltrimethylammonium
Bromide for each 1litre of Al2O3 nanofluid Sakamoto et al. [70] at pH
5.7 and 4g of Polyethylene Glycol for 1g of TiO2 nanoparticles Deiss
et al. [71] at pH 9.7 as shown in Fig. 8. A companion of the optimum
cooling–fluid pH level and the suitable surfactant type and concentration led to stabilized nano-fluid for long term.
Number defined as Re =
(1)
ρ um Dh
μ
=
um Dh
ν
Q̇
,
WchHch
Reynolds
i. The power produced by the cell is given by [77].
[72], and hydraulic diameter
P= (ISC × VOC) × FF
4A
P
330
(7)
Energy Conversion and Management 155 (2018) 324–343
Friction factor ( f )
M.S.Y. Ebaid et al.
Friction factor ( f )
(a)
Friction factor ( f )
(b)
(c)
Fig. 6. Variation of friction factor with Reynolds number for TiO2 and Al2O3 nanofluids of
concentration (a) 0.1 wt.%, (b) 0.01 wt.%, (c) 0.05 wt.% and for water calculated at 13.00
afternoon.
where, P : power produced by the solar cell, ISC : short circuit current,
VOC : open circuit voltage and FF : fill factor .
The cell generates the maximum power Pmax at a maximum voltage
Vmax and maximum current Imax , It is convenient to define the Fill Factor
FF by:
FF =
Pmax
I
× Vmax
= max
ISC × VOC
ISC × VOC
Fig. 7. Variation of f Re roduct with Reynolds number for TiO2 and Al2O3 nanofluids of
concentration (a) 0.1 wt.%, (b) 0.01 wt.%, (c) 0.05 wt.% and for water calculated at 13.00
afternoon.
(8)
The percentage of the increase of the generated power, which is a dimensionless parameter, is defined as follows: [78].
%Pmax,increase =
Pcooling−Pwithout cooling
Pwithout cooling
× 100%
ii. Efficiency of PV cell
Efficiency is defined as the ratio of energy output from the solar cell
to input energy from the sun as reported by [77,78] and it represents
the performance of the solar cell itself. The efficiency depends on the
spectrum of the incident sunlight, intensity of the incident sunlight, the
temperature of the solar cell. η, ηmax and %ηmax, increase are defined as
follows:
Fig. 8. Distribution of daily measurements of solar irradiance for all experiments.
η=
331
Pout
I × VOC ×FF
= SC
Pin
Apv × Gt
(9)
Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
Table 1
Experimental measurements were recorded on 12/10/2016 using nanofluid TiO2 water mixture based of concentration 0.1 wt.% with flow rate of 5000 mL/min .
Time
QRad
(W ⧹ m2)
Tamb (°C)
Q̇
(mL ⧹ min)
Tin (°C)
Tout
(°C)
ΔT
(°C)
Tavg
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
352
527
680
768
830
811
600
471
21
23.5
25.9
29
32.1
33
31.3
29.9
5000
5000
5000
5000
5000
5000
5000
5000
28.2
28.9
29.1
31.5
32.5
31.6
31.2
29.8
32.1
31.8
30.5
34.6
36.8
35.3
33.2
30.8
3.9
2.9
1.4
3.1
4.3
3.7
2
1
33.63
36.50
39.10
40.42
42.35
42.26
39.88
35.99
Tavg
(Top)
(Bottom)
33.23
36.83
37.65
38.04
40.13
39.55
39.58
35.30
Tavg
(°C)
Voc
(V)
Isc
(A)
33.43
36.67
38.38
39.23
41.24
40.90
39.73
35.65
20.5
20.6
20.7
20.7
20.7
20.6
20.4
20.5
1.1
1.63
2.15
2.3
2.45
2.3
1.7
1.28
Tavg (°C)
Voc
(V)
Isc
(A)
Table 2
Experimental measurements were recorded on 12/10/2016 using water with volume flow rate of 5000 mL/min .
Time
QRad
(W ⧹ m2)
Tamb
(°C)
Q̇ (mL ⧹ min)
Tin
(°C)
Tout
(°C)
ΔT
(°C)
Tavg
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
352
527
680
768
830
811
600
471
21
23.5
25.9
29
32.1
33
31.3
29.9
5000
5000
5000
5000
5000
5000
5000
5000
28.3
29.1
30.5
32.7
33.8
32.4
31.6
31.1
29.6
30.8
31.9
33.9
35.1
34.3
32.4
31.7
1.3
1.7
1.4
1.2
1.3
1.9
0.8
0.6
35.35
39.33
41.12
41.33
45.29
41.59
41.46
36.04
35.76
39.64
41.72
41.96
43.94
42.03
40.63
36.48
35.55
39.49
41.42
41.65
44.62
41.81
41.04
36.26
20.3
20.5
20.5
20.5
20.5
20.4
20.2
20.3
1.08
1.59
2.14
2.29
2.43
2.26
1.68
1.27
Tavg
Tavg (°C)
Voc
(V)
Isc
(A)
37.97
43.66
47.72
49.35
53.49
51.28
47.53
39.07
20.1
20
19.7
19.9
19.9
19.7
19.7
20.1
1.07
1.59
2.13
2.27
2.44
2.28
1.67
1.27
(Top)
Tavg
(Bottom)
Table 3
Experimental measurements were recorded on 12/10/2016 for without cooling panel.
Time
QRad
(W ⧹ m2)
Tamb
(°C)
Q̇ (mL ⧹ min)
Tin
(°C)
Tout
(°C)
ΔT
(°C)
Tavg
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
352
527
680
768
830
811
600
471
21
23.5
25.9
29
32.1
33
31.3
29.9
5000
5000
5000
5000
5000
5000
5000
5000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
37.39
41.91
47.20
48.72
51.72
50.92
46.18
38.78
(Top)
(Bottom)
38.55
45.41
48.24
49.98
55.26
51.64
48.87
39.37
Table 4
Properties of TiO2 nanofluid for different masses of TiO2 nanoparticles.
Mass TiO2
kg
Volume fraction of nanoparticles
φ
Volume of nanoparticles Vnp
Density of nanoparticles
ρnf
Dynamic viscosity
μ nf
Effective thermal conductivity
k eff
0.01 (0.1) wt.%
0.005 (0.05) wt.%
0.001 (0.01) wt.%
0.002365
0.001182
0.000236
0.023640662
0.011820331
0.002364066
1003.6
999.82
996.76
0.000802716
0.000800358
0.000798472
0.6265
0.6197
0.6143
Table 5
Properties of Al2O3 nanofluid for different masses of Al2O3 nanoparticles.
Mass Al2O3
(kg)
Volume fraction of nanoparticles
φ
Volume of nanoparticles
Vnp
Density of nanoparticles
ρnf
Dynamic viscosity
μ nf
Effective thermal conductivity
k eff
0.01
(0.1) wt.%
0.005
(0.05) wt.%
0.001
(0.01) wt.%
0.002571
0.02571
1003.43
0.000803129
0.6590
0.001285
0.0129
999.72
0.000800564
0.6357
0.0002571
0.00256
996.74
0.000798513
0.6175
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Tsurface (C)
Fig. 9. Average distributions of daily measurements of solar irradiance for all experiments.
60
58
56
54
52
50
48
46
44
42
40
38
36
TiO2 0.1 wt.%
TiO2 0.05 wt.%
TiO2 0.01 wt.%
water
without cooling
0
1000 2000 3000 4000 5000 6000
Flow Rate (mL/min)
Tsurface (C)
(a)
60
58
56
54
52
50
48
46
44
42
40
38
36
TiO2 0.1 wt.%
TiO2 0.05 wt.%
TiO2 0.01 wt.%
water
Fig. 11. Variation of average PV cell surface temperature with flow rates of TiO2, Al2O3
and water relative to reference temperature (no cooling) calculated at 13:00: (a) 0.1 wt.
%, (b) 0.05 wt.%, and (c) 0.01 wt.%.
without cooling
0
1000 2000 3000 4000 5000 6000
Flow Rate (mL/min)
ηmax =
(b)
Fig. 10. Variation of the average PV cell surface temperature with flow rate for (a) TiO2
nanofluid and (b) Al2O3 nanofluid of different concentrations (0.01, 0.05, and 0.1 wt.%)
calculated at 13.00 afternoon..
Pmax
I
× Vmax
= max
Pin
Apv × Gt
% ηmax, increase =
(10)
ηnanofluid cooling −ηwithout cooling
ηwithout cooling
(11)
4.4. Power-hydraulic performance parameter
It can be defined to compare the performance of variable concentrations as given by [79]:
Table 6
Percentage of PV cell surface temperature decrease at different flow rates and for various
working fluid as a cooling medium calculated at 13:00 afternoon.
% PV cell surface temperature
decrease relative to water
(TiO2)
% PV cell surface temperature
decrease relative to water
(Al2O3)
min)
0.1 wt.%
0.05 wt.
%
0.01 wt.
%
0.1 wt.%
0.05 wt.
%
0.01 wt.
%
500
1000
2000
3000
4000
5000
9.66%
10.36%
9.94%
10.14%
10.02%
11.20%
7.08%
8.61%
9.03%
8.54%
7.69%
8.01%
4.92%
5.90%
5.86%
5.69%
5.33%
5.36%
11.37%
12.77%
12.89%
12.69%
13.54%
13.83%
8.36%
9.94%
11.01%
10.64%
9.61%
9.25%
6.09%
7.06%
7.59%
7.36%
7.48%
8.06%
Volume
flow rate
(Q̇ )|
Power hydraulic performance =
%Pmax, increase
where,f :friction factor
f 1/3
(12)
5. Experimental procedure
(mL ⧹
In this current work, several experiments were carried out using two
types of nanofluids (TiO2 and Al2O3) at different flow rates ranging
from (500 to 5000) mL/min with different concentration by weight
(0.1, 0.05, 0.01 wt.%) water based as well as water as a cooling
medium. The required measurements for all experiments were Q rad ,
Tamb ,Q̇, Tin, Tout, Tsurface , VOC and ISC , and they were recorded during the
day from 9.00am to 16.00pm. It should be noted that several surface
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Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
(b) Variation of efficiency with time of
(a) Variation of power with time of TiO2
TiO2 at concentration 0.1 wt.% and
water
at concentration 0.1 wt.% and water
(d) Variation of current with voltage of
(c) Variation of PV cell surface temperature
TiO2 at concentration 0.1 wt.% and
water
with time of TiO2 at concentration
0.1wt.% and water
(e) Variation of Q
rad with time of TiO 2 at
concentration 0.1 wt.% and water
Fig. 12. Electrical and thermal performance of PV cell with time at flow rate 5000 mL/min .
cell temperatures were recorded at different positions (Fig. 3) using
digital multimeter in order to have more accurate experimental readings. The description of the experimental work is presented hereafter.
Tables 1–3, respectively. Same procedure for the other five experiments
was followed for flow rates (500, 1000, 2000, 3000, and 4000), mL/min
and same data measurements were recorded.
5.1. Experiment work (1) using TiO2 water mixture based nanofluid of
concentration 0.1 wt.%
5.2. Experimental work part (2) using TiO2 and Al2O3 water mixture based
nanofluids used as a cooling medium
Experimental work (1) was carried out using TiO2 water mixture
based nanofluid with flow rate of 5000 ml ⧹ min at concentration 0.1 wt.
%, and water for cooling PV cells. The required experimental measurements were recorded for TiO2 water mixture, water and without cooling
for the three PV cells. A sample of the recorded readings is presented in
Experimental work part (2) was carried out using TiO2 and Al2O3
water mixture based nanofluids as a cooling medium for two flow rates
of 500 and 3000 mL/min at different concentrations of 0.05, 0.01 and
0.1 wt.%. Same experimental measurements were recorded for TiO2
and Al2O3 and also without cooling for the three PV cells, respectively.
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M.S.Y. Ebaid et al.
(b) Variation of efficiency with time of
(a) Variation of power with time of TiO2
TiO2 at concentration 0.1 wt.% and
water
at concentration 0.1 wt.% and water
(d) Variation of current with voltage of
(c) Variation of PV cell surface temperature
TiO2 at concentration 0.1 wt.% and
water
with time of TiO2 at concentration0.1wt.%
and water
(e) Variation of Qrad with time of TiO2 at
concentration 0.1 wt.% and water
Fig. 13. Electrical and thermal performance of PV cell with time at flow rate 4000 mL/min .
6. Results and discussions
volume of nanoparticlesVnp, and dynamic viscosity μ nf of nanofluid are
calculated using the relevant parameter in Section 4. Likewise for the
thermal conductivity k eff of nanofluid. The results of calculations for
TiO2 and Al2O3 nanofluids with different concentrations by weight (0.1,
0.05, 0.01 wt.%) are all tabulated in Tables 4 and 5.
6.1. Fluid flow characteristics determination
6.1.1. Properties of nanofluids
The initial TiO2 nano-fluid is stable at pH higher than 5.7. A decrease in the pH of the colloid lead to coagulation and subsequent
precipitation of the aggregates. Addition of polyethylene glycol (PG) to
the TiO2 nano-fluid at pH 9.7 led to colloidal stability for long term.
According to Deiss et al. [71] the polymer adsorbed on the particle
surface increases the repulsive forces that prevent particles aggregation.
The initial Al2O3 nano-fluid is stable at pH less than 7.9. An increase in
the pH of the colloid lead to coagulation and subsequent precipitation
of the aggregates. Addition of surfactant (Cetyltrimethylammonium
Bromide (CTAB)) to the Al2O3 nano-fluid at pH 5.7 led to colloidal
stability for long term.
In order to determine the properties of nanofluids used in the experimental work, density ρnf , the volume fraction of nanoparticles φ ,
6.1.2. Flow characteristics determination of the cooling medium
Based on the related parameters given in Section 4, the required
properties of the nanofluid cooling medium (TiO2, Al2O3)-fluid base
water mixture in the studied range of fluid flow rates and concentrations are determined. The mean fluid velocity um is calculated based on
volumetric fluid flow rate Q̇ and cross-sectional area of a single channel
Wch × Hch as well as Reynolds number Re . The values of friction factor f
are calculated using Moody Chart calculator software based on Re and
relative roughness of the aluminum cooling channel (r). The calculated
values of f and f Re of Al2O3, TiO2-fluid base water mixture of concentrations (0.1, 0.05, 0.01 wt.%), and water used as a cooling medium
are presented in Figs. 6 and 7.
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M.S.Y. Ebaid et al.
(a) Variation of power with time of TiO2
(b) Variation of efficiency with time of
at concentration 0.1 wt.% and water
TiO2 at concentration 0.1 wt.% and
water
(c) Variation of PV cell surface temperature
(d) Variation of current with voltage of
with time of TiO2 at concentration
0.1wt.% and water
TiO2 at concentration 0.1 wt.% and
water
(e) Variation of Qrad with time of TiO2 at
concentration 0.1 wt.% and water
Fig. 14. Electrical and thermal performance of PV cell with time at flow rate 3000mL/min..
constant for the laminar flow and changes considerably for the turbulent flow as shown in Fig. 7a–c. This agrees with the work carried out
for laminar flow by Karrimi and Rahimi [66].
It is observed from Fig. 6a–c that the trends of variation of f with Re
are similar for both TiO2 and Al2O3 nanofluids at concentrations (0.01,
0.05%, 0.1 wt.%), and for water at the studied range of flow rate
(500–5000) mL/min . Also, it is noticed that there is a sharp decrease in
f up to Re = 2088, then a sudden increase of f up to Re ⩽ 4177. In this
region, the flow can be considered transient, after that f starts to decrease again. This behaviour is attributed to the change in flow from
laminar toward turbulent flow. Therefore, it can be deduced that for
various fluid flow rates less or equal to 1000 ml/min, the laminar flow
prevails while for flow rate higher than 1000 mL/min ,turbulent flow
exists. Also, it is observed that the change of f is relatively small for Re
⩾ 4177 (turbulent region) compared with the laminar flow region.
These results are in good agreement with those obtained by Nikuradse
[80]. To confirm the flow regime type, it is found that f Re product is
6.2. Solar irradiance distribution
Solar irradiance values were measured per day for each experiment
from 9.00 to 16:00 h using solar power meter. The experimental results
are plotted as shown in Fig. 8. It can be seen that the distribution of
daily measurements of solar irradiance for all experiments is a bell
shape with maximum solar irradiance occurs at 13:00 afternoon
(750 W/m2), while minimum values (400 W/m2) occurred at 9:00 and
16:00 h, respectively. These values are in full agreement with those
reported by the ministry of Energy and Mineral Resources for north
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M.S.Y. Ebaid et al.
(a) Variation of power with time of TiO2
of concentration 0.1 wt.% and water
(b) Variation of efficiency with time of
TiO2 of concentration 0.1 wt.% and
water
(c) Variation of PV cell surface temperature
with time of TiO2 at concentration 0.1
wt.% and water
(d) Variation of current with voltage of
TiO2 at concentration 0.1 wt.% and
water
(e) Variation of Qrad with time of TiO2 at
concentration 0.1 wt.% and water
Fig. 15. Electrical and thermal performance of PV cell with time at flow rate 2000 mL/min .
5000) mL/min , and at different concentrations (0.01, 0.05, 0.1 wt.%)
for both TiO2 and Al2O3 nanofluids, the PV cell surface temperatures
were measured for each hour at 12 different selected positions by Ktype thermocouples (Fig. 3). The curves of the calculated average surface temperature of the PV cell using TiO2 and Al2O3 nanofluids as a
cooling medium at the studied flow rates and concentrations relative to
the water mixture base fluid, and without cooling, are depicted Fig. 10
based on experimental readings recorded at 13:00 afternoon.It can be
seen from Fig. 10a and b, by using TiO2 and Al2O3 nanofluids and water
as a cooling medium, that Al2O3 produces the best cooling effect when
compared TiO2 nanofluid and water, while water produces the worst
cooling effect at the studied range of flow rates and concentrations for
all flow rates and concentrations. This is due to the higher effective
thermal conductivity of Al2O3 than TiO2 and water (see Tables 4 and 5).
region of Jerash-Jordan where Philadelphia University is located. Also,
it can be deduced that the difference in the measured solar irradiance
values for the 12 experiments is due to the variation in solar radiation
during the running days of the experiments, and it is relatively small.
An average distribution of solar irradiance for all experiments is calculated and the results are depicted in Fig. 9.
6.3. Thermal performance analysis of PV cell when subjected to cooling
medium and no cooling
6.3.1. The effect of cooling medium TiO2, Al2O3 nanofluids and water and
without cooling on PV cell surface temperature
In order to investigate the variation of the average surface temperature of the PV cell at different fluid flow rates ranging from (500 to
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M.S.Y. Ebaid et al.
(b) Variation of efficiency with time of
(a) Variation of power with time of TiO2
TiO2 at concentration 0.1 wt.% and
water
at concentration 0.1 wt.% and water
(d) Variation of current with voltage of
(c) Variation of PV cell surface temperature
TiO2 at concentration 0.1 wt.% and
water
with time of TiO2 at concentration 0.1
wt.% and water
(e) Variation of Qrad with time of TiO2 at
concentration 0.1 wt.% and water
Fig. 16. Electrical and thermal performance of PV cell with time at flow rate 1000 mL/min .
TiO2 and Al2O3 nanofluids gives better cooling performance than low
concentration ones (0.01, 0.05 wt.%). The reason for that was explained
by a qualitative analysis suggested by Ding et al. [81]. But this point
still required further investigations to determine the optimum value of
wt.% concentration for different nanofluids.
The best and the second best values recorded for the average PV cell
surface temperature at all concentrations were 39.1, 40.4, 42.0 and
40.0, 41.1, 43.2 at flow rate of 5000 mL/min of TiO2 and Al2O3 nanofluids, respectively. This is due to the fact that higher flow rates of
cooling fluids produce higher cooling effect as expected. Also, to study
the effect of concentration of the two nanofluids as a cooling medium
on the average PV cell surface temperature. Fig. 10a and b illustrate
that the best and worst cooling effects occur at nanofluid concentrations
of 0.1 wt.% and 0.01 wt.% for both Al2O3 ad TiO2 respectively, and this
is reflected on the PV cell surface temperature. Moreover, it may be
shown from the figures that increasing wt.% concentration of nanofluids leads a corresponding increasing in cooling effect. It could be
concluded that here that higher concentration (i.e. 0.1 wt.%) of both
6.3.2. Comparison of TiO2 and Al2O3 nanofluids relative to water as a
cooling medium as a%PV cell surface temperature decrease
In order to compare the level of cooling by nanofluids relative to the
base fluid (water), the decrease percentage of average PV cell surface
temperature is calculated, which is as follows:
The absolute% PV cell surface temperature decrease relative to base
fluid (water)
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M.S.Y. Ebaid et al.
(b) Variation of efficiency with time of
(a) Variation of power with time of TiO2
at concentration 0.1 wt.% and water
TiO2 at concentration 0.1 wt.% and
water
(c) Variation of PV cell surface temperature
(d) Variation of current with voltage of
with time of TiO2 at concentration 0.1
wt.% and water
TiO2 at concentration 0.1 wt.% and
water
(e) Variation of Q
rad with time of TiO 2 at
concentration 0.1 wt.% and water
Fig. 17. Electrical and thermal performance of PV cell with time at flow rate 500 mL/min .
Tnano fluid cooling−Twater cooling
Table 7
Maximum PV power increase at different flow rates for TiO2, water as a cooling medium
relative to no cooling calculated at 13:00 afternoon.
Volume flow
rate (Q̇ )
Maximum power output of PV cell
at
% Power output increase of PV
cell relative to no cooling
TiO2
Water
No cooling
TiO2
Water
35.64
36.59
36.64
36.59
35.67
37.90
35.42
35.63
35.50
35.63
34.74
37.23
34.12
34.01
34.60
34.83
33.66
35.20
4.45%
7.59%
5.58%
5.05%
5.97%
7.67%
3.81%
4.76%
2.68%
2.30%
3.20%
5.77%
Twater cooling
The results of calculation are presented in Table 6. Firstly, it can be
observed that Al2O3 nanofluid achieves higher values of% PV cell surface temperature decrease relative to base fluid (water mixture) than
TiO2 nanofluid. Secondly, the% PV cell surface temperature decrease
relative to base fluid (water mixture) than TiO2 nanofluid increases
with the increase of flow rates and concentrations. This illustrates that
higher values of concentrations and flow rates are favourable to achieve
a better cooling effect and hence better thermal and electrical performance of PV cell. Based on the above, it can be noticed that the biggest
% PV decrease in surface cell temperature relative to water is 13.83%
(mL ⧹ min)
500
1000
2000
3000
4000
5000
× 100%
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Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
concentrations, the decrease of average PV cell surface temperature
relative to the reference temperature (without cooling) variation with
flow rates and concentrations is presented in Fig. 11a–c. It can be deduced that heat transfer using Al2O3 nanofluid is the best among the
other two working fluids TiO2 nanofluid and water, respectively for all
concentrations and flow rates considered. Also, for a given concentration of Al2O3, TiO2 nanofluids, and water, there is a sharp rise in PV cell
surface temperature reduction compared with no cooling and this increases with flow rates. This is reasonable because heat transfer increases as flow rate increases. In addition to that, the flow changes from
laminar to turbulent which in its rule cause an increase in internal
convection heat transfer coefficient and as a result improve cooling.
Quantatively, to compare the amount of the PV cell surface drop in
temperature by using the three cooling fluids three cooling fluids relative to no cooling, cooling with water showed the lowest values of
temperature difference for all flow rates considered, and the maximum
difference value using cooling water is (Twithout cooling−Tcooling = 12) water
and occurs at flow rate 5000 L/min . However, Al2O3 nanofluid showed
the highest values of temperature difference and the maximum difference value is (Twithout cooling−Tcooling = 18) Al2O3 at flow rate 5000 L/min,
and occurs at 0.1 wt.% concentration. For the other two concentration
of 0.05 wt.% and 0.01 wt.% of Al2O3 nanofluid, the temperature difference occurs at about 16.1 °C and 15.7 °C , respectively. For the TiO2
nanofluid, again the maximum temperature difference values occur at
flow rate 5000 L/min, and the values for 0.1 wt.%, 0.05 wt.% and
0.05 wt.% are around 16.8 °C , 15.7 °C and 14.2 °C , respectively. This is
expected and is due to the fact that Al2O3 nanofluid has a better effective thermal conductivity than TiO2 nanofluid and water as shown in
Tables 4 and 5.
Table 8
Percentage of PV efficiency increase at different flow rates for TiO2, water as a cooling
medium relative to no cooling calculated at 11:00 afternoon.
Volume flow
rate (Q̇ )
Maximum%efficiency of PV cell
% Efficiency increase of PV cell
relative to no cooling
TiO2
Water
No
cooling
TiO2
Water
14.01
14.66
14.00
13.95
14.16
14.38
13.53
14.16
13.51
13.40
13.74
14.17
13.26
13.68
12.71
13.14
13.40
13.56
0.75%
0.5%
1.29%
0.81%
0.76%
0.82%
0.27%
0.48%
0.8%
0.26%
0.34%
0.61%
(mL ⧹ min)
500
1000
2000
3000
4000
5000
Table 9
Maximum PV cell surface temperature at different flow rates for TiO2, water as a cooling
me medium relative to no cooling calculated at 11:00 afternoon.
Volume flow
rate (Q̇ )
Maximum PV cell surface
temperature
% PV cell surface temperature
decrease (worst case) relative to no
cooling
TiO2
Water
No
cooling
TiO2
Water
42.13
41.98
40.55
42.99
44.08
41.24
46.03
44.74
43.66
45.30
45.38
44.62
54.88
53.98
55.88
57.24
58.33
53.49
23.23%
22.22%
27.43%
24.90%
24.43%
22.90%
16.13%
17.12%
21.87%
20.86%
22.20%
16.58%
(mL ⧹ min)
500
1000
2000
3000
4000
5000
6.4. Electrical performance analysis of PV cell when subjected to TiO2
nanofluid of concentration 0.1 wt.%, water and without cooling at different
flow rates
Table 10
Current voltage (I-V) characteristics at different flow rates for TiO2, water as a cooling me
medium relative to no cooling calculated at 13:00 afternoon.
Volume
flow rate
(Q̇ )
PV cell voltage and current
%PV voltage andcurrent
increase (worst case) relative
to no cooling
TiO2 nanofluid cooling medium at a concentration 0.1 wt.% and for
different flow rates (500–5000) mL/min is selected in this investigation
as a case study to show the effects on the power and efficiency of the PV
cells. In order to determine electrical performance (i.e. power and efficiency) of the PV cells when subjected to TiO2 nanofluid, water as a
cooling medium and without cooling, the Fill Factor FF, power and
efficiency of the PV are calculated, respectively based on the parameters given in Section 4.3. The result of calculations is discussed
hereafter.
The set of graphs for the parameters of power, efficiency, solar irradiance measurements, PV cell surface temperature, and I-V characteristics for TiO2 nanofluid of 0.1 wt.% concentration, water as a
cooling medium and without cooling are drawn against time at the
studied range of flow rates (500–5000) mL/min as shown in
Figs. 12–17. Generally, it can be deduced from this set of figures that
the trends of the aforementioned parameters variation with time are all
almost similar. However, TiO2 nanofluid of concentration 0.1 wt.%
produces, as expected, the best results of power, efficiency, reduction in
(mL ⧹
min)
500
1000
2000
3000
4000
5000
TiO2
Water
No cooling
TiO2
Water
Voc
Isc
Voc
Isc
Voc
Isc
Voc
Isc
Voc
Isc
20.6
20.6
20.6
20.4
20.3
20.7
2.35
2.43
2.38
2.40
2.34
2.45
20.2
20.2
20.3
20.2
20.3
20.5
2.28
2.36
2.34
2.36
2.38
2.43
19.7
19.7
19.7
19.5
19.5
19.9
2.25
2.31
2.32
2.35
2.31
2.40
4.59%
4.59%
4.59%
4.62%
4.10%
4.02%
4.44
5.20
1.7
0.42
1.30
0.41
2.54
2.54
2.54
3.59
4.10
3.02
1.33
2.16
0.86
0.43
3.03
1.25
and occurs at concentration 0.1 wt.% of Al2O3 nanofluid, while the
minimum value is 4.92% and occurs at concentration 0.01 wt.% of TiO2
nanofluid.
In order to have a better understanding of how different working
fluids perform as a cooling medium with various flow rates and
Table 11
Uncertainty of measurements.
Parameter
Mean velocity (um)
Reynolds number
(Re)
Power (P)
Efficiency (η)
Minimum uncertainty
Uum
um
URe
Re
UP
P
Uη
η
=
=
=
=
⎛
⎝
U Q̇ 2
Q̇
⎞ =
⎠
Uρ 2
ρ
Maximum uncertainty
Uμ 2
μ
Uum 2
um
( ) +( ) +( )
UFF 2
FF
Uum
um
(0.06)2 = 0.06%
UI 2
I
=
(0.1)2 + (0.06)2 + (0.1)2 = 0.154%
( ) + ( ) + ( ) = (0.04) + (0.012) + (0.0014)
( ) + ( ) + ⎛⎝ ⎞⎠ = (0.042) + (0.1) + (0.011)
Up 2
p
UA
A
2
UV
V
UQrad
Qrad
2
2
2
2
2
2
340
URe
Re
= 0.042%
UP
P
= 0.109%
Uη
η
=
=
=
=
⎛
⎝
U Q̇ 2
Q̇
⎞ =
⎠
Uρ 2
ρ
(0.6)2 = 0.6%
Uμ 2
μ
Uum 2
um
( ) +( ) +( )
UFF 2
FF
UI 2
I
=
(0.1)2 + (0.6)2 + (0.1)2 = 0.616%
( ) + ( ) + ( ) = (0.04) + (0.03) + (0.0015)
( ) + ( ) + ⎛⎝ ⎞⎠ = (0.05) + (0.1) + (0.025)
Up 2
p
UA
A
2
UV
V
UQrad
Qrad
2
2
2
2
2
= 0.05%
2
= 0.115%
Energy Conversion and Management 155 (2018) 324–343
M.S.Y. Ebaid et al.
0.1 wt.% concentration achieves as expected the best voltage and current values compared with water and without cooling as shown in
Table 10. However, the average percentage improvement of voltage Voc
and current Isc compared with no cooling is for TiO2 nanofluid (4.42%
and 2.25%) and water (3.06% and 1.5%), respectively (See Table 10).
PV cell surface temperature, and I-V characteristics when compared
with water and without cooling for all flow rates considered. It should
be stated here that increasing the flow rates achieves a better cooling
effect, consequently better performance regarding power and efficiency. Detailed discussion of each parameter will be presented hereafter.
7. Uncertainty analysis
6.4.1. Power output analysis of PV cell with time
Figs. 12a–17a illustrates the hourly power output of the PV cell with
time at different flow rates for the three cases considered (TiO2 nanofluid, water, and without cooling). It can be observed that the variation
is a bell shape as expected. However, the maximum power output occurred at 13:00 afternoon regardless of any flow rate considered. These
maximum values of power output for TiO2 nanofluid and water, and
without cooling for the respective flow rate range 500–5000mL/min are
presented in Table 7. Furthermore, the percentage increase in power
output relative to no cooling is presented. It should be noted here that
as flow rate increase, power output should increase. However, this is
not the case here and the reason for that is due to the variation of solar
irradiance values Qrad measured during the running of the experiment
as shown in Figs. 12a–17a. The average increase in PV cell power
output for TiO2 nanofluid and water relative to no cooling are 6.05%
and 3.75%, respectively. Such improvement is attributed to the enhanced cooling of tested PV cells, which results in lower temperatures
and thus higher power output.
An uncertainty analysis was performed for the instrumentations
used in the experimental work and the related physical quantities to
assess the error in measurements. The uncertainties of physical quantities such as mean velocity, Reynolds number, power and efficiency
were estimated following the standard procedure [82,83]. The uncertainty evaluation of these quantities is presented in Table 11.
8. Conclusion
An experimental investigation of cooling PV cells of 50W power
output was carried out using water and two types of nanofluids namely;
Titanium Oxide (TiO2) nanofluid in Water-Polyethylene Glycol mixture
and aluminum Oxide (Al2O3) nanofluid in Water-Cetyltrimethyl
Ammonium Bromide mixture of different concentrations (0.01, 0.05,
0.1 wt.%), respectively. The work was done for various flow rate ranging from 500 to 5000mL/min.
The system was tested under climate conditions of Jerash-Jordan.
Fluid determination characteristics and electrical performance of the
system were studied and analyzed. Based on the experimental results
obtained, the following conclusions are presented:
6.4.2. Efficiency analysis of PV cell with time
The hourly efficiency of PV cell with time is depicted in
Figs. 12b–17b. It can be observed from these figures that the highest
values of efficiency occurred at 11:00am (Table 8) and dropped down
near mid-noon while the PV power output increases near mid-noon as
shown in Figs. 12a–17a. However, the best values among the three
cases considered are when using TiO2 nanofluid, 0.1 wt.% concentration. The explanation for such behaviour is that obtained efficiency is
affected by the PV surface temperature while the power output is directly proportional to the Qrad. Also, it can be observed that maximum
power of PV cell occurs 13:00 afternoon and this should not necessarily
correspond to a maximum efficiency for the reason mentioned earlier.
The average increase in PV cell efficiency for TiO2 nanofluid and water
relative to no cooling are 0.82% and 0.48%, respectively which shows
that nanofluid cooling increases the efficiency by 50%. It should be
noted here that the discrepancies in the efficiency curves as seen from
Figs. 12b–16b can be attributed to the variation of the recorded ambient temperature Tamb values during the time of running the experiments.
a. Fluid flow characteristics of cooling medium (TiO2, Al2O3) fluid
base water mixture and pure water was determined for the studied
flow rate range 500–5000mL/min.. It was found that two flow types
exists; laminar flow prevails up to a flow rate less or equal to 1000
mL/min , while turbulent flow exists for a flow rate above that. This
was confirmed by the f Re product values of flow.
b. It was noticed that, the presence of nanoparticles, has a big effect on
decreasing the average PV cell surface temperature compared with
that of pure water. Also, the results showed that the temperature
reduction is a function of nanoparticle weight fraction and flow rate,
which means that an increase in the concentration and flow rate
would reduce the PV cell surface temperature. Furthermore, Al2O3
nanofluid, for all concentrations and flow rates considered in this
study, achieves the best reduction in PV cell surface temperature
compared with that of TiO2 nanofluid and water
c. The effect of temperature difference (Twithout cooling-Tmedium cooling)
variation of working fluids as a cooling medium with flow rates and
concentration was investigated. It was found that with the increase
of flow rate and concentration, the temperature difference (Twithout
cooling-Tmedium cooling) is increased. Also, it was found that at the same
flow rate, the (Twithout cooling-Tmedium cooling) was increased with an
increase in solar irradiance and reduced with increase in ambient
temperature.
d. Power and efficiency of cooled PV cell is enhanced compared with
no cooling. However, power and efficiency is increased with the
increase of concentration and flow rate in the studied range. Best
results were achieved for Al2O3 nanofluid at the concentration and
flow rates considered.
6.4.3. PV cell surface temperature analysis with time
Figs. 12c–1717c and Figs. 12e–17e illustrates the hourly PV cell
surface temperature and solar irradiance variation with time, respectively at different flow rates for the three cases considered (TiO2 nanofluid, 0.1 wt.% concentration, water, and without cooling). It can be
observed that the highest PV cell surface temperature (the worst values)
occurred at 13:00 pm which corresponds to maximum Qrad and ambient
temperature, respectively. Lowest values occurred at the morning at
9:00am and 16:00pm, respectively. This confirmed the effect of Qrad
and Tamb on PV cell surface temperature. Furthermore, TiO2 nanofluid
showed the lowest values. It can be concluded from Table 9 that the
average percentage improvement on PV cell surface temperature for the
worst case (at 13:00pm) are 24.19% and 19.13% relative to no cooling,
respectively. This proves the importance of cooling the PV cell using
nanofluid or water.⧹
Acknowledgement
The authors would like to express their gratitude and appreciation
to Philadelphia University higher administration and to the Faculty of
Research and Higher Studies for their continuous support. Also, would
like to extend their deepest thanks to the Royal Scientific Society (RSS)
for their assistance and support throughout the project.
6.4.4. Current voltage (I-V) characteristics of PV cell analysis with time
Current voltage (I-V) characteristics as shown in Figs. 12d–Fig. 17d
illustrates the trends of variation of current with voltage for various
flow rates for the worst case. It can be deduced that TiO2 nanofluid,
341
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