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: mebaid2@philadelphia.edu.jo (M.S.Y. Ebaid), ayoup.ghrair@rss.jo (A.M. Ghrair), m_ai_busoul@yahoo.com (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 325 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 326 Energy Conversion and Management 155 (2018) 324–343 M.S.Y. Ebaid et al. 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. 327 Energy Conversion and Management 155 (2018) 324–343 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 328 Energy Conversion and Management 155 (2018) 324–343 M.S.Y. Ebaid et al. 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 329 Energy Conversion and Management 155 (2018) 324–343 M.S.Y. Ebaid et al. 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 332 Energy Conversion and Management 155 (2018) 324–343 M.S.Y. Ebaid et al. 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 333 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. 334 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 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. 335 Energy Conversion and Management 155 (2018) 324–343 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 336 Energy Conversion and Management 155 (2018) 324–343 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 337 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 0.1 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) 338 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 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% 339 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 Energy Conversion and Management 155 (2018) 324–343 M.S.Y. Ebaid et al. 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