# Nanofluid-Powered Dual-Fluid Photovoltaic/Thermal (PV/T) System: Comparative Numerical Study

^{1}

^{2}

^{*}

## Abstract

**:**

^{®}and ANSYS FLUENT

^{®}software, respectively. An experimental validation of the numerical models was performed using the results from the published study. Additionally, to identify the optimal nanofluid type for the PV/T collector, metal oxide nanoparticles (CuO, Al

_{2}O

_{3}, and SiO

_{2}) with different concentrations were dispersed in the base fluid (water). The results revealed that the CuO nanofluid showed the highest thermal conductivity and the best thermal stability compared to the other two nanofluids evaluated herein. Furthermore, the influence of CuO nanofluid in combination with air on the heat transfer enhancement is investigated under different flow regions such as laminar, transition, and turbulent. Using a CuO nanofluid plus air and water plus air the total equivalent efficiency was found to be 90.3% and 79.8%, respectively. It is worth noting that the proposed models could efficiently simulate both single and dual-fluid PV/T systems even under periods of fluctuating irradiance.

## 1. Introduction

## 2. Collector Design

## 3. Mathematical Model

#### 3.1. PV Plate

#### 3.2. Absorber Tube

_{2}O

_{3}nanoparticles [20], the Nusselt number can be calculated as follows:

#### 3.3. Back Plate

## 4. CFD Model

#### 4.1. Numerical Scheme

^{−3}and 10

^{−6}, respectively. To enhance the solution stability and to accelerate the convergence rate, the under relaxation factors were precisely taken. The temperature condition and fluid flow rate in the parallel tubes can be considered as being the same; the model is therefore limited to the vicinity of a single tube [26,27].

#### 4.2. Boundary Conditions and Grid Study

^{2}was taken into account. Due to the opaque top surface of the PV/T collector, a fixed heat flux was applied as a thermal boundary condition instead of using a solar ray tracing algorithm, because the solar load model’s ray tracing algorithm in FLUENT does not include the internals such as the heat gain for a model having an opaque rooftop [30].

## 5. Results and Discussion

#### 5.1. Model Validation

#### 5.2. Results Derived from Mathematical Model

_{2}O

_{3}), copper oxide (CuO), and silicon dioxide (SiO

_{2}). Table 4 shows the thermo-physical properties of the metal oxide nanoparticles used in this study [32,33,34]. The influence of the nanoparticle concentrations on the collector’s performance is investigated by considering important thermo-physical properties such the viscosity and thermal conductivity. As depicted in Figure 4, the viscosity ratio and thermal conductivity ratio increase with the increasing nanoparticle concentration. However, the highest percentage increase in the thermal conductivity was found with the CuO nanofluid, followed by the Al

_{2}O

_{3}, and SiO

_{2}nanofluids. The optimal concentration for the available nanoparticles in the base fluid (water) is around 0.75%; beyond this point, the aggregation of the nanoparticles and thermal diffusivity increased significantly. One of the reasons that the CuO nanofluid affords the highest heat transfer performance is that it has a lower specific heat and a slightly higher thermal conductivity compared to the aforementioned nanofluids. Based on the preceding outcomes, the CuO nanoparticles with a concentration of 0.75% in water are selected and employed as an optimal nanofluid throughout the rest of this study.

^{2}day) and ambient temperature (21.47 °C). When the nanofluid flow rate is set to vary between 0.005 kg/s and 0.030 kg/s at a fixed air flow rate of 0.055 kg/s, the total equivalent efficiency of the PVT collector was increased to 79.8% and 90.3% with water plus air, and with nanofluid plus air, respectively. It is noted that at the lowest nanofluid flow rate of 0.005 kg/s, the total equivalent efficiency was found to be as low as 82.6%, while under similar operating conditions using water plus air, the minimum value was 73.7%. The results show that when the fluids are operated simultaneously, a reasonably good total equivalent efficiency is achievable even at a low mass flow rate. In comparison with water plus air, the total equivalent efficiency of the PV/T system using nanofluid plus air as the dual-fluid was found to be approximately 10% higher. This can be attributed to the thermophysical properties of the nanofluid being sufficiently great to enhance the heat transfer behavior and thus increase the rate of heat removal from the PV module.

#### 5.3. Results Derived from CFD Model

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Nomenclature

$M$ | mass (kg) |

$C$ | specific heat (J/kg °C) |

$T$ | temperature (°C) |

$A$ | surface area (m^{2}) |

${h}_{wind}$ | heat transfer coefficient due to wind (W/m^{2} °C) |

${h}_{p\infty}$ | convection heat transfer coefficient between PV & ambient air (W/m^{2} °C) |

${h}_{pt}$ | conduction heat transfer coefficient between PV & tube (W/m^{2} °C) |

${h}_{pa}$ | convection heat transfer coefficient between PV & inside air (W/m^{2} °C) |

${h}_{pb}$ | radiation heat transfer coefficient between PV & back panel (W/m^{2} °C) |

${h}_{tn}$ | convection heat transfer coefficient between tube & nanofluid (W/m^{2} °C) |

${h}_{ta}$ | convection heat transfer coefficient between tube & inside air (W/m^{2} °C) |

${h}_{ab}$ | convection heat transfer coefficient between back panel & inside air (W/m^{2} °C) |

$E$ | electrical energy (W) |

$P$ | packing factor |

$G$ | solar radiation (W/m^{2}) |

$k$ | thermal conductivity (W/m °C) |

${u}_{a}$ | wind velocity (m/s) |

$W$ | width or spacing (m) |

$x$ | distance (m) |

${D}_{i}$ & ${D}_{o}$ | tube inner & outer diameters |

$Nu$ | Nusselt number |

$Re$ | Reynolds number |

$Pr$ | Prandtl number |

$\mathrm{\u1e41}$ | mass flow rate (kg/s) |

Greek | |

$\alpha $ | absorptivity |

$\mathsf{\u014b}$ | efficiency |

${\mathsf{\u014b}}_{PVT}$ | total equivalent efficiency |

${\beta}_{r}$ | solar cell temperature coefficient (l/K) |

$\epsilon $ | emissivity |

$\sigma $ | Stefan-Boltzman constant $\left({\mathrm{W}\text{}\mathrm{m}}^{-2}{\mathrm{K}}^{-4}\right)$ |

$\varphi $ | volume concentration of nanoparticles |

Subscripts | |

$p$ | PV plate |

$t$ | absorber tube |

$n$ | nanofluid |

$a$ | inside air |

$b$ | back panel |

$\infty $ | ambient air |

$e$ | electrical |

$r$ | reference |

$n,o$ & $n,in$ | nanofluid outlet & inlet |

$a,o$ & $a,in$ | air outlet & inlet |

$th$ | thermal |

$c$ | collector |

$pp$ | power plant |

$np$ | nanoparticles |

$bf$ | base fluid |

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**Figure 1.**Dual fluid PV/T collector: (

**a**) exploded view, and (

**b**) cross-section view considering a single pipe.

**Figure 3.**The simulated results by model against experimentally measured data from a previous study.

**Figure 4.**Variations of viscosity and thermal conductivity ratios with increasing concentrations of CuO, Al

_{2}O

_{3}, and SiO

_{2}nanoparticles in pure water.

**Figure 5.**The predicted efficiencies of the PV/T efficiency at the independent mode of fluid operation: (

**a**) stagnant CuO nanofluid; and (

**b**) stagnant air.

**Figure 6.**The daily predicted PV module temperature using different fluids and modes of fluid operations.

**Figure 7.**The predicted fluids temperature rise against variable: (

**a**) nanofluid mass flow rate, and (

**b**) water mass flow rate at fixed air flow rate (0.055 kg/s).

**Figure 8.**The variations of the heat transfer coefficient for different mass flow rates at absorber temperatures of (

**a**) 55 °C, (

**b**) 75 °C, and (

**c**) 95 °C.

**Figure 9.**The PV module temperature (K) distribution under the independent mode of fluid operation (

**a**) with water only, and (

**b**) with nanofluid only.

**Figure 10.**The PV module temperature (K) distribution under the simultaneous mode of fluid operation (

**a**) with water plus air, and (

**b**) with nanofluid plus air.

**Figure 11.**Variations of dual-fluid PV/T thermal efficiencies under the simultaneous fluid mode against a variable nanofluid flow rate at a fixed air flow rate (0.055 kg/s).

**Figure 12.**Variations of dual-fluid PV/T under simultaneous fluid mode against a variable water flow rate at a fixed air flow rate (0.055 kg/s).

Cell Type | Mono-Crystalline Silicon |
---|---|

Open circuit voltage | 38.1 V |

Short circuit current | 9.27 A |

Maximum power point | 31.6 V & 8.23 A |

PV module [14] | Length & width | 1.62 m & 0.98 m |

Absorptivity (${\alpha}_{p}$) | 0.9 | |

Emissivity (${\epsilon}_{p}$) | 0.88 | |

Specific heat (${C}_{p}$) | 900 J/(kg·K) | |

Temperature coefficient (${\beta}_{r}$) | 0.0045/°C | |

Reference PV panel temperature | 298.15 K | |

Absorber tube | Inner diameter (${D}_{i}$) | 0.008 m |

Thickness (${\delta}_{t}$) | 0.0012 m | |

Specific heat (${C}_{t}$) | 903 J/(kg·K) | |

Density (${\rho}_{t}$) | 2702 kg/m^{3} | |

No. of tubes | 9 | |

Tube spacing | 0.11 m | |

Material | Copper | |

Back panel | Density (${\rho}_{b}$) | 20 kg/m^{3} |

Specific heat (${C}_{b}$) | 670 J/(kg·K) | |

Thermal conductivity (${K}_{b}$) | 0.034 W/(m·K) | |

Nanoparticles used | CuO, Al_{2}O_{3}, and SiO_{2} | - |

Other fluids used | Water & air | - |

Number of Elements | PV Module Temperature (°C) | |||
---|---|---|---|---|

Water | Nanofluid | Water + Air | Nanofluid + Air | |

781,430 | 57.46 | 56.18 | 50.69 | 46.65 |

903,638 | 59.35 | 57.47 | 51.55 | 48.42 |

1,060,023 | 60.16 | 58.73 | 52.39 | 47.44 |

1,437,673 | 59.87 | 57.92 | 52.23 | 47.37 |

Metal Oxides or Additive | Chemical Formula | Properties | ||
---|---|---|---|---|

Specific Heat (J/kg·K) | Thermal Conductivity (W/m.K) | Density (kg/m^{3}) | ||

Copper oxide | CuO | 551 | 32.9 | 6310 |

Aluminum oxide | Al_{2}O_{3} | 773 | 30 | 3890 |

Silicon dioxide | SiO_{2} | 730 | 1.5 | 2650 |

Nanofluid or Water Flow Rate (kg/s) | Fixed Air Flow Rate (kg/s) | Daily Solar Radiation (MJ/m^{2} day) | Ambient Temperature (°C) | Total Equivalent Efficiency (%) | ||
---|---|---|---|---|---|---|

PV without Cooling | Water Plus Air | Nanofluid Plus Air | ||||

0.005 | 0.055 | 23.25 | 21.47 | 31.5 | 73.7 | 82.6 |

0.01 | 0.055 | 23.25 | 21.47 | - | 75.1 | 85.2 |

0.015 | 0.055 | 23.25 | 21.47 | - | 76.6 | 87.4 |

0.02 | 0.055 | 23.25 | 21.47 | - | 78.4 | 88.7 |

0.025 | 0.055 | 23.25 | 21.47 | - | 79.1 | 89.5 |

0.03 | 0.055 | 23.25 | 21.47 | - | 79.8 | 90.3 |

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**MDPI and ACS Style**

Hussain, M.I.; Kim, J.-H.; Kim, J.-T.
Nanofluid-Powered Dual-Fluid Photovoltaic/Thermal (PV/T) System: Comparative Numerical Study. *Energies* **2019**, *12*, 775.
https://doi.org/10.3390/en12050775

**AMA Style**

Hussain MI, Kim J-H, Kim J-T.
Nanofluid-Powered Dual-Fluid Photovoltaic/Thermal (PV/T) System: Comparative Numerical Study. *Energies*. 2019; 12(5):775.
https://doi.org/10.3390/en12050775

**Chicago/Turabian Style**

Hussain, M. Imtiaz, Jin-Hee Kim, and Jun-Tae Kim.
2019. "Nanofluid-Powered Dual-Fluid Photovoltaic/Thermal (PV/T) System: Comparative Numerical Study" *Energies* 12, no. 5: 775.
https://doi.org/10.3390/en12050775