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T system in India
Solar Energy 170 (2018) 618–632
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Modelling and experimental analysis of a seasonally tracked V-trough PV/T system in India ⁎
Hasan Baiga, Ruchita Janib, Bhupendra K. Markamb, Subarna Maitib, , Tapas K. Mallicka, a b
T
⁎
Environmental and Sustainability Institute, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK PDEC, CSIR-Central Salt and Marine Chemicals Research Institute, G.B. Marg, Bhavnagar 364002, Gujarat, India
A R T I C LE I N FO
A B S T R A C T
Keywords: Desalination FEA PV/T Simulation V-Trough
Hybrid PV/Thermal (PV/T) systems can generate both electrical and thermal energy simultaneously. These systems are already finding interesting applications in the fields of desalination, sensible heating/cooling and other allied industrial processes. An effective way to further improve the overall system efficiency is by using VTrough’s to concentrate incoming sunlight and enhance the power output from these systems. In this work, we study the performance of a V-Trough PV/T system connected to a reverse osmosis plant in India. A coupled optical, electrical, and thermal model is presented and validated by experiments. The optical analysis was carried out while including the variations in suns altitude and zenith angle over the day. The impact of the variable inlet water temperature with time is included in the model. The performance of a V-Trough PV/T system is compared with a standard PV system. An average increase of 35% was observed in the electrical power output from the V-Trough PV/T system as compared to the conventional one, with the maximum being 63%. Using the water circulation, an average of 778 BTU/m2 of thermal energy was extracted from the V-Trough PV/T system. A maximum temperature difference of 5.2 °C was observed in the feed water at the system outlet, this accounted for a maximum 1/3rd of the total energy recovery when using the V-Trough PV/T system. Feeding heated water to the RO unit in the PV-RO system helped in significantly increasing the quantity and quality of the permeate obtained from the system. A parametric study of the effect of varying mass flow rate on the performance of the system is also discussed.
1. Introduction India is geographically well placed on the earth's solar belt (40° S–40° N) having 250–300 sunny days in a year with most of the regions receiving an average annual global horizontal radiation amounting 1800–2000 kWh/m2. However, this huge solar potential remains untapped due to the associated deployment costs and alternative land usage. The power generation using solar energy has reached a cumulative of 13 GW till date and is planned to increase to 175 GW by 2021 (MNRE, 2018). The photovoltaic systems are essentially limited by their efficiency (currently reported maximum efficiency) up to 26% (Green et al., 2018) making it an expensive power generating source in developing countries like India. Applications are sought where we can employ the PV systems with other technologies making it cost-effective and environment-friendly at the same time. Solar concentration is an effective route towards increasing the output from typical Si solar panels, (Baig and Mallick, 2011; Swanson, 2000; Maiti, et al.,2012). Baig et al. highlights the effective routes that could help increase the power output of silicon cells using concentrators ⁎
and draws attention to how they can be used as an alternative to reduce consumption of expensive silicon-based materials and couple it with low cost concentrators. However, it tends to reduce the reliability of the system due to the hot spots formed by the non-uniform illumination on both single and multi-junction solar cells and the temperature rise caused by this ultimately reduces the efficiency of the system and increases the cost of electric power produced by such systems, these effects can be minimised by improving the design procedure adopted for making them (Baig et al., 2012). Employing suitable cooling mechanisms (Chemisana and Rosell, 2013) and utilising the excess heat generated from the system can prove to be a suitable method to increase the overall performance of the system and reduce the overall cost. A review of different mechanisms that can be employed has been showcased recently (Michael et al., 2015). The excess heat from the PV panels can be utilised as a source of low grade thermal energy and these hybrid systems can be utilised for generating the electrical power and hot water at the same time (Baig et al., 2013; Kumar et al., 2015, Kern and Russell, 1978; Kandilli, 2013). Adding solar concentration to such systems (CPV/T) will further increase the overall energy output because
Corresponding authors. E-mail addresses: [email protected] (H. Baig), [email protected] (B.K. Markam), [email protected] (S. Maiti), [email protected] (T.K. Mallick).
https://doi.org/10.1016/j.solener.2018.06.018 Received 13 December 2017; Received in revised form 5 April 2018; Accepted 4 June 2018 0038-092X/ © 2018 Elsevier Ltd. All rights reserved.
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Nomenclature a AreaPV Cw hext I IL IO L ṁ Qth RS Rsh S Tamb Tin Tout TPV U V Vwind Qs Cp F
Fx Fy Fz g k ksi
ideality factor area of the PV panel (m2) specific heat of water (J/kg K) external heat transfer coefficient (W/m2 K) current under load condition (A) light generated current (A) diode reverse saturation current (A) characteristic length scale (m) mass flow rate of incoming water (kg/s) amount of energy removed by the heat exchanger (J/kg K) series resistance (Ω) shunt resistance (Ω) absorbed solar radiation (W/m2) ambient temperature (K) inlet water temperature (K) outlet water temperature (K) temperature of the PV layer (K) characteristic velocity (m/s) voltage under load condition (V) wind velocity (m/s) amount of heat generated by volume of PV layer (W/m3) heat capacity (J/kg K) volume force (N /m3)
p T TPV-surface Td u, v, w
body force in x direction (N/m3) body force in y direction (N/m3) body force in z direction (N/m3) acceleration due to gravity (m/s2) turbulent kinetic energy (J/kg) thermal conductivity of the thin layer (silicon-Si) (W/ m2 K) pressure (Pa) feed water temperature (°C) temperature of the PV (°C) temperature at the surface having a thickness of d in mm (°C) components of the velocity (m/s)
Greek symbols γPV ε ηn ηel θ μ μT ρ
temperature coefficient (%/°C of temperature) turbulent dissipation rate (J kg s) nominal efficiency electrical efficiency of the panel tilt angle (°) dynamic viscosity (Pa s) turbulent viscosity (m2/s) density (kg/m3)
atmospheric conditions as inputs were presented recently. An energy assessment method incorporating the effects of shading on a low concentrating photovoltaic system with PV panels, with and without bypass diodes was recently presented by (Tina and Ventura, 2015). Finite element simulation was used to carry out simulation of PV (Usama Siddiqui et al., 2012) and PV/T (Siddiqui and Arif, 2013) systems in order to study the heat transfer phenomenon taking place in them, however very little has been published on the detailed modelling of VTrough based CPV/T systems. Zhou et al. recently presented the finite element analysis of a PV module where they evaluated the thermal and electrical performance of a PV system and its dependence on ambient temperature and wind velocities (Zhou et al., 2015). The impact of the flow and its configuration on a PV/T system was investigated by (Naewngerndee et al., 2011), they found that the number of strings used is inversely proportional to the quality of the flow distribution and the best performance can be obtained by using fewer strings in the horizontal direction. PV/T systems have found their applications in several process applications, they have been used for space heating and domestic hot water supply (Rommel et al., 2015). A V-Trough based water purification and power generation were presented recently (Qin et al., 2015). Results showed that the electrical output was more than double compared to a non-concentrating system. In remote locations, such small-scale solar photovoltaic powered Reverse Osmosis (RO) desalination systems can be utilised to provide potable water for its residents. The temperature of water supplied to an RO desalination unit influences the performance of the quality and quantity of permeate obtained. Employing CPV/T technologies for such systems can be used for increasing the temperature of the water supplied to such RO based system’s feed water (Vyas et al., 2015) while still increasing the electrical output. The objective of the current work was to develop a coupled multiphysics model using ray tracing and finite element methods capable of predicting the performance of the V-Trough based PV/T system. Results obtained using the optical analysis are utilised to evaluate the thermal and electrical performance of the system. Impact of adding the thermal heat exchange system to the existing plant is evaluated. The model is experimentally validated, and shortcomings identified. Atmospheric
it not only concentrates direct but also diffused radiations quite effectively (Baig et al., 2013). Several designs of such systems have been developed in the past few years based on the desired application (Sharaf and Orhan, 2015). Use of flat mirrors placed at an angle (V-Trough) to boost the performance of solar collectors is a well-established methodology (Tabor, 1966; Seitel, 1975; Pucar and Despic, 2002; Broman and Mirrors, 1984). These systems require occasional tracking and can work much effectively even if the position of the mirrors is changed once a month. The V-Trough walls can be used for light concentration as well as heat dissipation from the solar cells (Solanki et al., 2008) which is an effective way of improving the performance if we do not intend to utilise the excess heat generated. Results show that the temperature of the PV cell remains the same when placed under concentration whilst using this design. Andersen et al. characterized the natural convection heat transfer phenomena experimentally in a V-Trough system (Anderson, 2013). It was found that the parameters could be predicted extending a relationship described earlier (Iyican et al., 1980) for a Rayleigh number range of 2 × 103–5 × 107. Recently, Baig et al. performed the optical analysis of a reflective Compound Parabolic Concentrator (CPC) based PV/T system designed for similar application in Saudi Arabia (Baig et al., 2013). The system was later experimentally studied and evaluated (Li et al., 2015). It was found that the PV-CPC design helps reducing the solar cell temperature and produces hot water simultaneously. Li et al. developed and tested an air-gap-lens-walled compound parabolic concentrator incorporated with the photovoltaic/ thermal system (ALCPC-PV/T) with the geometrical concentration ratio of 2.4× designed for building integration (Li et al., 2015). The thermal efficiency of the ALCPC-PV/T system was found to be 52.0%, but the electrical efficiency was found very low having a value of 6.6%. Numerical methods have been employed for evaluating the performance of such systems (Huang et al., 2001; Amrizal et al., 2013) and have been validated using experiments. Rao et al. developed an algorithm to assess the contribution of solar energy on a horizontal receiver by plane booster mirrors (Narasimha Rao et al., 1993). Results showed that placing a south facing mirror is the best choice for boosting the energy outputs, especially at lower solar altitudes. A model (Reis et al., 2010) to describe the performance of V-Trough systems in terms of the module temperature, power output and energy yield using the 619
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heat exchanger connected to the PV panel. However, it was important to understand the physical phenomenon occurring due to the inclination angle and the flow rate of water a model to optimise the overall performance. A direct contact type heat exchanger system was arranged behind the panel where water can be circulated from one end and extracted from another. Previous research (Vyas et al., 2015) suggests that there is a notable increase in the output permeate from a reverse osmosis unit if there is a rise in feed water temperature (up to a certain limit i.e. 40 °C) which is given as inlet to the RO unit. Thus, the heated water received after cooling of PV panels can be supplied as feed water to the RO unit for desalination purposes. To analyse such a complex system where we have optical reflectors, electricity generating PV modules and water heating technologies coupled together we need to break down each analysis separately and couple them together to evaluate the overall performance of the system. In the present study, we have isolated a single unit of PV panel along with a V-Trough and cooling system and compared its performance against a similar PV panel placed next to it under similar environmental conditions to estimate the benefit obtained by using such a system. The experimental set up was constructed on the terrace of Solar Energy Lab of CSMCRI, Bhavnagar. Fig. 2 shows the experimental setup and the parameters being monitored in the system. The water was circulated in the heat exchanger behind the PV panel using a diaphragm pump and the flow rate was maintained at 1.5 LPM. The heat exchanger connected behind the PV panel simply consisted of a tray of a 2 mm GI sheet arranged along with each PV panel. Measurements were carried out in 30-minute intervals. The thermal images of the PV panel were taken using the Testo Thermal Imager 876.
parameters like ambient temperature and wind speed affecting the system performance are analysed for their impact on the PV module temperature and the water outlet temperature. The model can be extended to evaluate the impact of different boundary conditions including both the environmental, geometrical design and incoming flow rates of the water used for cooling the system.
2. System description In the present study, we consider a community scale Solar powered Reverse Osmosis desalination plant located at the rooftop of Solar Energy Lab, CSMCRI Bhavnagar, Gujarat (Latitude and Longitude of 21.45° N and 72.08° E respectively) is shown in Fig. 1. The plant consists of two different V-trough PV arrays (one PV and the other PV/T) connected in the opposite directions that provide electrical energy and low-grade thermal energy for carrying out the desalination using the Reverse osmosis plant. Both were used to run the RO system, the heated water from the PV/T system was used at the inlet of the RO plant. The PV/T array having 8 modules sloped at an angle of 20° facing south. The V-Trough mirrors are placed at inclinations which can be changed depending on the time of the year. The system also consists of 8 PV panels with V-Trough without any energy recovery system. The main objective of this system was to increase the power output obtained through each panel using V-Trough whilst reducing the number of panels required for operating the setup. This was done by placing Aluminium reflectors in V- Trough alignment in a North-South direction to increase the amount of solar intensity falling on the PV panel. The increased intensity of solar radiation helped in improving the electrical output and increased the temperature of the water leaving the
Fig. 1. Schematic of the V-trough PV/T system connected to an RO desalination unit. 620
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Fig. 2. Experimental setup showing different parameters being measured.
3.1. Optical analysis
The solar radiation incident on the PV panel was measured using a Kipp and Zonen CM4 High-Temperature pyranometer. The sensitivity of the instrument was 4–10 μV W−1 m−2 and response time was < 8 s. The IV curve of the solar panel was measured with the help of Autosys PV Array tester-SAT10030ACH2. The atmospheric conditions during all experiments were recorded using AWS 3001K-13-2 Virtual Electronics Weather station which has an inbuilt anemometer and capable of recording ambient temperature, relative humidity, wind speed and wind direction. The temperature of the water at the inlet and exit of the heat exchanger are measured using K-type thermocouples.
An optical analysis was performed to evaluate the incoming solar radiation on the PV panels using ray tracing methods. The PV panels are fixed at a slope of 20° facing south and the reflectors are tilted at −9° and 63° from the vertical plane as shown in Fig. 4. The position of the reflectors can be varied to suit the experimental setup which could be changing over the period of the year. To understand the effects of both the azimuth and zenith angle a model as shown in Fig. 5 was developed. A V-trough PV/T system was modelled along with the north and south side reflectors. It is important to note that the reflectors are modelled extending on both the sides of the PV panel to include the lateral concentration effects caused by adjacent systems in both the directions. In the present analysis, the trajectory of the sun for a given day can be determined in terms of its zenith and azimuth angle with the use of MIDC SOLPOS calculator (Mcadams, 1954). At a given time instance, total reflected power, received by the PV panel array was determined using the ray tracing method. The integration of these values was then performed over the time interval from sunrise to sunset to get the total solar energy received by the PV panel array. The optical properties of the reflector play an important role in the determination of the solar radiation incident on the PV panel. Anodized aluminium sheets were used in the experimental setup, whose reflectivity was determined using PerkinElmer UV–Vis-NIR spectrophotometer based at the Environment & Sustainability Institute, Penryn, the UK as shown in Fig. 6. Additionally, the standard AM1.5G solar spectrum used in the optical model and the silicon solar cell quantum efficiency are also represented. The incident angles of solar radiation on the aperture were calculated for a specified day using the MIDC SOLPOS calculator. The
3. Computational model To perform the numerical analysis of this system we have adopted a detailed procedure as highlighted in Fig. 3. Input parameters like the solar radiation based on the time of the day, the reflectivity of the mirrors, and absorption of PV are utilised. Based on this, ray tracing is carried out to estimate the amount of solar radiation incident on the PV panels as a function of time. Once this is estimated the energy conversion to electrical power is modelled and the dissipated heat from the PV module to thermal energy is estimated simultaneously. This is then introduced in the thermo-fluid model of the PV/T device to estimate the solar cell temperature under steady state conditions. Initially, a steady state analysis is carried out to obtain an initial solution for the system. On convergence, this becomes the initial solution for the transient thermo-fluid model. The temperature of the PV in the heat transfer model is interlinked with the thermo-fluid model of the heat exchanger. This is then finally utilised to estimate the electrical and thermal performance of the PV/T system. The outlet temperature of the water is then evaluated using which the thermal efficiency of the system can be estimated. 621
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Fig. 3. Detailed procedure used for the analysis of the V- trough system.
function of the zenith and azimuth angle. Based on the day and time of the year the position of the source could be modelled. Rays emanating from the source are incident on the reflectors and the PV panel. Some rays directly reach the PV panel and the rest arrive via reflection from the adjoining mirror surfaces. The angular variation of the reflectors can also be changed in the model if needed for evaluation during a different period of the year.
variation of the azimuth and altitude corresponding to 22 January 2016 is shown in Fig. 7. The sun’s azimuth position changes between 155° and 250°, the altitude/elevation angle varies between 6° and 50°. It is important to establish the variation of both these angles as it enables an approximate location of the sun when performing the optical analysis of the system. An accurate estimation of the solar position minimises the error between the model and the experiments. The optical analysis of the V-trough CPV unit was performed using ray tracing method. The geometry was modelled in Solid works and subsequently evaluated using the commercial ray tracing software. This gives much flexibility in analysing the optical performance as we can input the optical properties as a function of the wavelengths. In the present study, we have used the standard AM1.5 G spectrum for the source and the reflectivity as a function of the wavelength as shown in Fig. 6. The setup for the ray tracing is shown in Fig. 8. A circular light source representing the sun is chosen to produce one million collimated rays with a flux of 1000 W/m2. The position of the source is made a
3.2. Electrical model Typically, a five-parameter model (Lo Brano et al., 2010) is used to estimate the parameters and the I-V curve determining the electrical performance of the PV panel. It is important to note that the electrical performance is dependent on the operating PV temperature which is coupled with the thermal analysis of the system. Eq. (1) can be utilised to predict the I-V characteristic of this system at a fixed temperature and solar radiation. 622
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incident on the PV panel is converted into the electrical energy and the rest of energy is dissipated in the form of heat to the surroundings and to the water flowing behind the PV panel. The heat is dissipated to the surroundings in the form of radiation and convection losses from the front and side surfaces. Convection losses occur on the back side of the heat exchanger which have been modelled assuming a constant heat transfer coefficient. When solar energy is incident on a PV panel then only a portion of it is converted into electricity, part of it is lost to the surroundings and the remaining goes into heating the water in the heat exchanger behind the PV panel, so the energy balance can be expressed using Eq. (2).
⎡ RateofHeatloss ⎤ ⎡ RateofSolarEnergy ⎤ = ⎢ fromallthesurfaces ⎥ ⎣ AvailableonSolarPanel ⎦ ⎢ oftheSolarPanel ⎥ ⎣ ⎦ RateofHeatTransferfrom ⎤ +⎡ PVtothewater ⎣ ⎦ RateofElectrical ⎤ +⎡ ⎢ ⎥ EnergyProduced ⎣ ⎦
Fig. 4. Angular position of the mirrors during the study.
I = IL−Io ⎡exp ⎛ ⎝ ⎣
V + IRs V + IRs ⎞−1⎤− a Rsh ⎠ ⎦
(2)
To formulate the problem using finite element method, the geometry of the given dimensions was created as per the system specifications as shown in Fig. 10. The PV panel is modelled with all the different layers whose thermophysical properties used (Siddiqui and Arif, 2013) are shown in Table 1. The basic PV module consists of five layers of materials namely: glass, ethyl vinyl acetate as an encapsulant, silicon, second layer of encapsulant and Tedlar. While the PV/T module consists of an added heat exchanger made of GI metal sheet attached along with the panel that could store water in it for circulation purpose. There are two PVC pipes also attached to the PV/T system that acts as inlet and outlet points for water circulation. The heat exchanger placed behind the PV panel is constructed in the form of a simple rectangular tray made using galvanized iron whose thickness is 2 mm and bonded directly behind the PV panel with an inlet and exit pipe. Depending on the flow rate of the incoming water we can have laminar or turbulent fluid flow occurring inside the heat exchanger. Turbulence accounts for the additional localised random effects such as eddies and vortices at small length and timescales. This behaviour is characterised by a dimensionless number called the Reynolds Number.
(1)
where I and V represent the current and voltage respectively under load condition. The electrical circuit requires that five parameters be known, and they are light generated current (IL), diode reverse saturation current (I0), series resistance (Rs), shunt resistance (Rsh), ideality factor (a). The five parameters in the model are obtained using I-V characteristics of a module at reference condition supplied by the manufacturer and other known PV characteristics. Here values for Rs and Rsh are considered at the module level. 3.3. Thermo-fluid model A thermo-fluid model was developed to examine the heat transfer processes occurring in the system. The incoming solar radiation on the panel is converted to electricity and rejected to its surroundings via different heat transfer mechanisms as shown in Fig. 9. The incident solar radiation gets concentrated from the V-trough where it experiences reflection losses. A part of the concentrated solar radiation
Fig. 5. Schematic of the optical analysis method used to estimate the solar radiation received by the PV panel. 623
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Fig. 6. Reflectance of the anodized aluminium sheet used as a reflector, the silicon quantum efficiency and the standard AM1.5G solar spectrum used in the optical model.
Fig. 7. Variation of the solar azimuth and altitude on the test date, equinox, and solstice.
ρ∇∙ (u) = 0
The Reynolds number is a ratio of the inertial and viscous forces acting on the fluid and is determined using the Eq. (3).
ρUL Re = μ
(5)
The transport equation for the turbulent kinetic energy k and the dissipation rate of turbulence energy, ε are shown in Eqs. (6), (7).
(3)
μ ρ (u∙∇) k = ∇∙ ⎡ ⎛μ + T ⎞ ∇k ⎤ + Pk−ρ ∊ ⎢⎝ σk ⎠ ⎥ ⎣ ⎦
(6)
μ ε ε2 ρ (u∙∇) ε = ∇∙ ⎡ ⎛μ + T ⎞ ∇∊⎤ + Cε1 ρk −Cε 2 ρ , ε = e p ⎢⎝ ⎥ σ k k c ⎠ ⎦ ⎣
(7)
⎜
where ρ is the density, µ is the dynamic viscosity, U is the characteristic velocity, and L is the characteristic length scale. The Reynolds Averaged Navier Stokes (RANS) equations were solved using the k-ε model to compute the turbulent fluid flow occurring in the water in the heat exchanger. The momentum and continuity Eqs. (4), (5) used are shown below for steady state conditions.
ρ (u∙∇) u = ∇∙ [−pI + (μ + μT )(∇u + (∇u)T )] + F
⎜
⎟
⎟
Where the production term (Pk) is expressed as Eq. (8).
2 2 Pk = μT (∇u: (∇u + (∇u)T )− (∇∙u)2)− ρk∇∙u 3 3
(4) 624
(8)
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Fig. 8. Ray tracing of the system.
μT = ρCμ
k2 ε
(9)
The parameters Cε1 = 1.44, Cε2 = 1.92, Cµ = 0.09, σk = 1.0, σε = 1.3 are model constants. To incorporate the effects of gravity, a volume force (F) must be added to the Turbulent Flow, k-epsilon Interface as shown in the Eqs. (10)–(14). In the case where the module is flat (tilt angle 0°), the Volume Force of gravity is defined using the expression,
Fx = Fy = 0
(10)
Fz = −ρn g
(11)
Fig. 10. Schematic of the cross-section of the model used for thermo-fluid analysis of the PV/T system.
However, this changes with the change of the inclination of the system to
Fig. 9. Different thermal interactions occurring on the PV/T system. 625
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The energy transport equation used to model the heat transfer is expressed in Eqs. (15), (16)
Table 1 Thermo-physical properties of the different layers of the PV/T system. Layer
Thermal conductivity (W/m K)
Density (Kg/ m3)
Specific heat (J/Kg K)
Thickness (m)
Glass EVA 1 PV Cell EVA 2 Tedlar Water
1.8 0.35 148 0.35 0.2 0.667
3000 960 2330 960 1200 992.22
500 2090 677 2090 1250 4179
0.003 0.0005 0.000225 0.0005 0.0001 0.045
ρCp u∙∇T + ∇∙q = Q + Qp + Q vd
(15)
q = −k∇T
(16)
where Qvd accounts for the viscous dissipation effects and Qp is the pressure work term which is both negligible in the present study. The PV panel has several layers as shown in Table 1. For modelling thin layers, the following Eqs. (17)–(20) are applied, where ks is the layer thermal conductivity, Qs is layer internal heat source, i is the layer number and ds is the layer thickness
Table 2 Fluid flow boundary conditions.
∇∙ t qs = Qsi
(17)
No
Region
Boundary condition
qs = −ksi ∇t Ts
(18)
1
Wall condition, u·n = 0
Tu = (Ts )L = 0
(19)
2
External surface the heat exchanger Water inlet velocity
Td = (Ts )L = ds
(20)
3 4
Outlet Volumetric force
Velocity derived from the flowrate, u = uin Zero pressure, p0 = 0 Derived from bousinessq approximation
The solar radiation incident on the PV panel is converted to electrical and thermal power. Both these quantities are a function of the solar cell temperature (Tpv).
Table 3 Thermal boundary conditions.
Qs =
No
Region
Boundary condition
1
The external surface of the PV
2
The external surface of the heat exchanger Water outflow Water inlet temperature PV surface
Temperature Tamb, Convective heat transfer coefficient, ho Temperature Tamb, Convective heat transfer coefficient, hb −n·q = 0 Temperature, Ti Heat generation, Q
3 4 5
(1−ηel ) × S × Areapv Volumepv
(21)
where ηel is the electrical efficiency of the PV that can be defined as a function of the average PV temperature, nominal efficiency ηn and the temperature coefficient γpv as
ηel = ηn (1−γPV (TPV −25))
(22)
Fx = −ρn g cosθ
(12)
Fy = 0
(13)
Further effects of optical reflection which is the ratio of the solar transmittance at different angles to the normal incidence have been ignored in this study due to its minimal impact. The Tpv is the temperature of the PV layer, which is a function of the cooling rate and is coupled to the fluid flow heat transfer interface. The amount of energy removed by the heat exchanger Qth can be estimated using the equation
Fz = −ρn g cosθsinθ
(14)
̇ w (Tout −Tin ) Qth = mc
To model the temperature of the water and the solid domains the energy model is coupled to the fluid flow. To model the added dispersion of heat, transfer due to turbulence the Kays-Crawford turbulence heat transfer model is included.
(23)
The outer boundaries of the PV panel are subjected to convective and radiation losses. These can be modelled using the convective heat transfer boundary conditions. The external convective and radiative heat transfer coefficients can be related to the PV surface as
Fig. 11. Ambient conditions obtained using the outdoor weather station and the inlet water conditions recorded using K-Type thermocouples. 626
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Fig. 12. Typical illumination distribution profiles on the PV panel corresponding to (a) 8 am (b) 1 pm and (c) 4 pm.
q = −hext (Tamb−TPV − Surface )
(24)
where hext is the external heat transfer coefficient, which is the sum of both the convective and radiative heat transfer coefficients and Tamb is the ambient temperature. Mcadams (1954) reported the convection coefficient as a function of the wind velocity whilst including the effects of radiation heat transfer as shown in Eq. (25)
hext = 5.7 + 3.8Vwind
(25)
An inlet velocity uin, and temperature Ti is specified as a boundary condition on the inlet pipe, which can be varied to study the impact of the water flow rate. Finally, a pressure outlet condition is to be applied to the water outlet for setting up the problem. One of the important steps is the grid generation while solving the problem using finite element methods. This process involves partitioning the physical geometry (the domain) into small size units known as cells/mesh elements. It is important that proper meshing is applied to obtain correct results.
Fig. 13. Intensity of the solar irradiation reaching the PV unit. 627
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collector/flux receiving surface. The input parameters like the ambient temperature, the wind speeds and the inlet water temperature are also utilised in the model as shown in Fig. 11. 4. Results Using the coupled optical-electrical and thermal model presented in Section 3 a numerical study was carried out to evaluate the impact of cooling the PV system under varying atmospheric conditions. The effect of varying atmospheric factors such as ambient temperature, wind velocity and solar irradiance were included in the model to estimate the electrical and thermal efficiency of the system. The results obtained are compared against experimental values under similar conditions. 4.1. Optical results Fig. 14. Streamlines showing the velocity profile of the fluid flow occurring inside the heat exchanger unit.
The optical analysis was carried out using ray tracing under varying zenith and azimuth angles to obtain the incoming flux of the PV panel. This method is effective as it can also be used to evaluate the variation of irradiance distribution on the PV panel when incorporating different inclinations during different periods of the year. Fig. 12 shows the typical flux profiles obtained during different times of the day. The relevant features of the flux profile are distinct with the incident flux increasing as a function of time. The incident radiation was measured on a bare panel along with the V- trough system. It may be seen clearly in Fig. 12, how the flux profiles change both in its intensity along the PV panel depending on the time of the day. The flux profiles obtained are averaged across the PV panel and represented in Fig. 13. The optical analysis is carried for every half hour intervals to estimate the incident radiation on the V-trough PV/T system. The solar radiation incident on the PV unit is also compared with the values obtained experimentally. It may be seen that the model prediction is slightly higher to the values obtained experimentally. A maximum difference of about 10% was seen in the values. This could possibly occur due to the difference in the reflectivity of the unit reflector at different angles which is assumed constant essentially during the optical analysis.
Increasing the number of mesh means an increment in the solution time and accuracy. In the present study, we have used 0.2 Million mesh elements of different shapes to solve the problem using HPC Beowulf cluster Carson based at the Environmental and Sustainability Institute, University of Exeter, UK. 3.4. Boundary conditions While preparing the computational model it is very important to identify and apply the correct boundary conditions for convergence of the numerical problem. In the current study, we have a multi-physics problem requiring the application of both thermal and fluid boundary conditions and establishing a relationship between them. We have summarised both the types of boundary conditions in Tables 2 and 3. We have assumed water as an incompressible fluid, and the climatic conditions to be stable and representative of actual environmental conditions. While modelling the problem in 3D, we assume the incoming solar radiation reaching the PV is converted into electricity and the rest is dissipated in the form of heat. Hence the PV is assumed as a source of heat and all other surfaces are subjected to convective heat transfer conditions. It is important to note that the convective heat transfer would be different on different sides of the concentrator/
4.2. Fluid flow The water flow occurring inside the heat exchanger is visualised in
Fig. 15. Variation in cell temperature with varying flow rates for V-Trough PV/T system. 628
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Fig. 16. Variation in outlet water temperature with varying mass flow rate for V-Trough PV/T system.
Fig. 17. Thermal images showing the temperatures of (a) bare PV panel and (b) V-Trough PV/T system with cooling.
298 K was observed at maximum flowrate condition at 1.2 LPM at solar noon. Towards the end of the day when the solar radiation decreases both the PV and the feed water temperature decreases. At no flowrate condition, the PV temperature was found to reach 310.4 K and the water temperature reached 308.8 K. At a flow rate of 1.2 LPM, the PV temperature was found to reach 298.64 K and the water temperature reached 294.5 K.
Fig. 14, the arrows show the direction of the flow as it circulates inside the heat exchanger before exiting the tube. The turbulent intensity is highest towards the inlet of the heat exchanger and can be seen to drop as the fluid goes through the heat exchanger tray. The velocity profile of water flow inside the heat exchanger is shown in Fig. 14. The velocity of the water ranges from 0.02 to 0.12 m/s inside the heat exchanger. While the water circulates through the heat exchanger it absorbs extra heat from the panel, while being in contact with the lowest layer of the PV panel and thus helps in reducing the temperature of the PV panel. A set of parametric analysis using meteorological data corresponding to 21st January was carried out to predict the effect of changes in the mass flow rate of water on the performance of the VTrough PV/T system. The case where there is no flowrate and the water is stagnant in the heat exchanger, the heat exchange from the PV to the water occurs slowly leading to minimum heat transfer and thereby leading to a higher PV temperature and a higher feed water temperature at the outlet. It is very critical to balance the electrical energy output and the thermal energy output in a hybrid system. A maximum PV temperature of 316.5 K and outlet water temperature of 314.8 K was observed at zero flowrate condition as shown in Figs. 15 and 16 respectively at solar noon. When the water is circulated the heat transfer rate increases with increasing flow rate which leads to decreasing the solar cell temperature and improving the electrical output. For the existing system, the water flow rate was varied from 0 to 1.2 LPM. A maximum PV temperature of 305 K and outlet water temperature of
4.3. Thermal The incident radiation raises the temperature of the PV panel, having a cooling system reduces the temperature of the PV panel surface and helps improve the PV efficiency. A thermal imaging camera was used to measure the surface panel temperature for both the bare PV unit and the V-Trough PV/T unit under cooling. The temperature is averaged using 24 points on the system. The temperature profile of bare PV Panel and CPV/T is shown in Fig. 17. Similarly, contours of temperature can be extracted for both the PV and V-Trough PV/T system at any given time of day. The bare panel was also modelled to obtain the surface temperature of the PV, using the environmental conditions as shown in the previous section. Fig. 18 shows the temperature contours of both the systems at 8 am, 10 am and 1 pm respectively. The temperature of the water starts to increase behind the PV panel as a function of time. The results obtained using the simulations are compared to those obtained experimentally. 629
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Fig. 18. Showing the Temperature contours of the V-Trough with cooling and bare PV panels at (a) 8 am (b) 10 am and (c) 1 pm respectively.
Fig. 19. Comparison of PV surface temperature for the bare PV panel and the VTrough PV/T panel with cooling.
The average temperature of the PV module is shown in Fig. 19. The temperature of the bare PV panel ranges between 10 °C and 47 °C. The bare panel was found to reach a maximum of 47 °C under the environmental conditions illustrated in earlier sections. The V-Trough PV/ T, on the other hand, was found to have a maximum of 40 °C when subjected to cooling using the modelling. However experimental results show the maximum temperature of the PV to be 35 °C, this is essentially because of the slightly higher input flux used while modelling the VTrough PV/T unit as shown in Fig. 13 and due to the difference between the actual efficiency of the PV panel against that obtained experimentally. The error between the modelled and experimentally obtained temperature is found to be less than ± 5% in the case of the V-Trough PV/T unit. The temperature of the water exiting the V-Trough PV/T system acts as an input to the reverse osmosis plant.
Fig. 20. Comparison of outlet water temperature obtained from the V-Trough PV/T unit with cooling.
Fig. 20 shows the comparison of the temperature of the outlet water from the unit. The maximum temperature of the water reached by the system was found to be 32 °C. When compared to the water entering the PV/T unit a maximum of 5.2 °C increase was observed around solar noon time experimentally. An average temperature difference of 2.1 °C was observed over the whole day. In the desalination system, the power consumption depends on the incoming feed water temperature and pressure. Under constant pressure conditions, as feed water temperature increases, water flux 630
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35 °C. A parametric analysis of varying the flow rate of the working fluid on the performance of the V-Trough PV/T system significantly showed the advantage of implementing it over the conventional module and helped in determining the optimum flow rate for running the system. These results have been obtained for the system under stable environmental conditions. Further, the model can be utilised for the prediction of the device performance over any given location, day, and time of the year. Additional, features like the addition of fins or tubes will also be explored in the future studies. Acknowledgements Support from Indo-UK collaborative project (DST/INT/UK/P-83/ 2014), DST-SERI project (DST/TM/SERI/2k11/101(G) is acknowledged. The authors thank CSIR, India for infrastructure support to carry out the experiments and this is CSIR-CSMCRI – 124/2017. Appendix A. Supplementary material
Fig. 21. Power increment of the PV panel due to the addition of the V-troughs.
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.solener.2018.06.018.
increases almost linearly, primarily due to the higher diffusion rate of water through the membrane. One of the mechanisms of transport of water through an RO membrane is by diffusion from one bonding site to another within the membrane. The change in the permeate flux rate (Ammous and Chaabene, 2015) with temperature can be described by Eq. (26);
1 ⎞− 1 ⎞ Temperaturecorrectionfactor = exp ⎛K × ⎛ ⎝ 273 + T ⎠ 298 ⎠ ⎝ ⎜
References Ammous, M., Chaabene, M., 2015. Multi criteria sizing approach for photovoltaic thermal collectors supplying desalination plant. Energy Convers. Manage. 94, 365–376. Amrizal, N., Chemisana, D., Rosell, J.I., 2013. Hybrid photovoltaic–thermal solar collectors dynamic modeling. Appl. Energy 101, 797–807. Anderson, T.N., 2013. Natural convection heat transfer in V-trough solar concentrators. Sol. Energy 95, 224–228. Baig, H., Mallick, T., 2011. Challenges and opportunities in concentrating photovoltaic research. Mod. Energy Rev. 3, 20–26. Baig, H., Heasman, K.C., Mallick, T.K., 2012. Non-uniform illumination in concentrating solar cells. Renew. Sustain. Energy Rev. 16, 5890–5909. Baig, H., Sellami, N., Bahaidarah, H., Mallick, T., 2013. Optical Analysis of a CPC based CPV/T system for application in the Kingdom of Saudi Arabia. In: 28th European Photovoltaic Solar Energy Conference and Exhibition, pp. 653–657. Broman, L., 1984. Non-Imaging Solar Concentrators With Flat Mirrors, pp. 102-109. Chemisana, D., Rosell, J.I., 2013. Electrical performance increase of concentrator solar cells under Gaussian temperature profiles. Prog. Photovolt. Res. Appl. 21, 444–455. Green, M.A., Hishikawa, Y., Dunlop, E.D., Levi, D.H., Hohl-Ebinger, J., Ho-Baillie, A.W.Y., 2018. Solar cell efficiency tables (version 51). Prog. Photovolt. Res. Appl. 26, 3–12. Huang, B.J., Lin, T.H., Hung, W.C., Sun, F.S., 2001. Performance evaluation of solar photovoltaic/thermal systems. Sol. Energy 70, 443–448. Iyican, L., Witte, L.C., Bayazitoĝlu, Y., 1980. An Experimental Study of Natural Convection in Trapezoidal Enclosures. J. Heat Transfer 102, 648–653. Kandilli, C., 2013. Performance analysis of a novel concentrating photovoltaic combined system. Energy Convers. Manage. 67, 186–196. Kern, E.C.J., Russell, M.C., 1978. Combined Photovoltaic and Thermal Hybrid Collector Systems. Kumar, A., Baredar, P., Qureshi, U., 2015. Historical and recent development of photovoltaic thermal (PVT) technologies. Renew. Sustain. Energy Rev. 42, 1428–1436. Li, G., Pei, G., Ji, J., Su, Y., 2015. Outdoor overall performance of a novel air-gap-lenswalled compound parabolic concentrator (ALCPC) incorporated with photovoltaic/ thermal system. Appl. Energy 144, 214–223. Lo Brano, V., Orioli, A., Ciulla, G., Di Gangi, A., 2010. An improved five-parameter model for photovoltaic modules. Sol. Energy Mater. Sol. Cells 94, 1358–1370. Maiti, S., Sarmah, N., Bapat, P., Mallick, T.K., 2012. Optical analysis of a photovoltaic Vtrough system installed in western India. Appl. Opt. 51, 8606–8614. Mcadams, W.H., 1954. Heat Transmission, third ed. McGraw-Hill. Michael, J.J., Iniyan, S., Goic, R., 2015. Flat plate solar photovoltaic–thermal (PV/T) systems: a reference guide. Renew. Sustain. Energy Rev. 51, 62–88. MNRE Ministry of New and Renewable Energy, 2018. https://mnre.gov.in. Naewngerndee, R., Hattha, E., Chumpolrat, K., Sangkapes, T., Phongsitong, J., Jaikla, S., 2011. Finite element method for computational fluid dynamics to design photovoltaic thermal (PV/T) system configuration. Sol. Energy Mater. Sol. Cells 95, 390–393. Narasimha Rao, A.V., Chalam, R.V., Subramanyam, S., Sitharama Rao, T.L., 1993. Energy contribution by booster mirrors. Energy Convers. Manage. 34, 309–326. Pucar, M.D.J., Despic, A.R., 2002. The enhancement of energy gain of solar collectors and photovoltaic panels by the reflection of solar beams. Energy 27, 205–223. Qin, L., Wang, Y., Vivar, M., Huang, Q., Zhu, L., Fuentes, M., Wang, Z., 2015. Comparison of photovoltaic and photocatalytic performance of non-concentrating and V-trough SOLWAT (solar water purification and renewable electricity generation) systems for water purification. Energy 85, 251–260. Reis, F., Brito, M.C., Corregidor, V., Wemans, J., Sorasio, G., 2010. Modeling the performance of low concentration photovoltaic systems. Sol. Energy Mater. Sol. Cells 94, 1222–1226. Rommel, M., Zenhäusern, D., Baggenstos, A., Türk, O., Brunold, S., 2015. Development of
⎟
(26)
where K is a constant and characteristic for a given membrane material, and T is feed water temperature in °C. In the above equation, the temperature of 25 °C is used as a reference point, with temperature correction factor = 1. The enhanced feed water temperature also causes lower salt rejection or higher salt passage. This is due to a higher diffusion rate for salt through the membrane. The rate of change of the permeate flux is about 3% for every degree rise in temperature, which could equal about 6% increase in the permeate level due to the increase in the feed water temperature. The electrical output is also increased considerably due to the addition of the V-trough. Fig. 21 shows the ratio of the power obtained while using the PV panel with a V-trough and without a V-Trough. It can be clearly seen that the power ratio increases during the noon times; this is particularly because of the intensity and the orientation of the sun during these times. A maximum power ratio of 1.7 is observed around 1 pm. An average increment of about 35% is seen in the power output over the whole day. Using the above-showcased model long-term performance evaluation can be performed on these types of systems. The model offers the flexibility of changing the angular inclinations of the V-Trough, in addition to all the other parameters used for modelling. Using the model, further studies can be carried out to evaluate the impact of these individual parameters on the performance of the system. 5. Conclusions A detailed numerical and experimental analysis of a V-Trough PV/T system has been presented and validated in this study. Using a VTrough was found to improve the electrical output of the system. The rise in temperature due to increased flux was countered by use of heat exchanger improving the overall efficiency of the system. A coupled optical-electrical-thermal fluid model was developed capable for the prediction of the power output of the V-Trough PV/T module depending on the environmental conditions. It also allows for evaluation of factors and their relevant impact on the performance of the system. Experiments are carried out on a PV module placed under exactly same conditions to evaluate the overall benefit of using a V-Trough PV/T system. Experimentally the maximum temperature was found to be 631
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H. Baig et al. glazed and unglazed PVT collectors and first results of their application in different projects. Energy Procedia 70, 318–323. Seitel, S.C., 1975. Collector performance enhancement with flat reflectors. Sol. Energy 17, 291–295. Sharaf, O.Z., Orhan, M.F., 2015. Concentrated photovoltaic thermal (CPVT) solar collector systems: part I – fundamentals, design considerations and current technologies. Renew. Sustain. Energy Rev. 50, 1500–1565. Siddiqui, M.U., Arif, A.F.M., 2013. Electrical, thermal and structural performance of a cooled PV module: transient analysis using a multiphysics model. Appl. Energy 112, 300–312. Solanki, C.S., Sangani, C.S., Gunashekar, D., Antony, G., 2008. Enhanced heat dissipation of V-trough PV modules for better performance. Sol. Energy Mater. Sol. Cells 92, 1634–1638. Swanson, R.M., 2000. The promise of concentrators. Prog. Photovolt. Res. Appl. 8,
93–111. Tabor, H., 1966. Mirror boosters for solar collectors. Sol. Energy 10, 111–118. Tina, G.M., Ventura, C., 2015. Energy assessment of enhanced fixed low concentration photovoltaic systems. Sol. Energy 119, 68–82. Usama Siddiqui, M., Arif, A.F.M., Kelley, L., Dubowsky, S., 2012. Three-dimensional thermal modeling of a photovoltaic module under varying conditions. Sol. Energy 86, 2620–2631. Vyas, H., Suthar, K., Chauhan, M., Jani, R., Bapat, P., Patel, P., Markam, B., Maiti, S., 2015. Modus operandi for maximizing energy efficiency and increasing permeate flux of community scale solar powered reverse osmosis systems. Energy Convers. Manage. 103, 94–103. Zhou, J., Yi, Q., Wang, Y., Ye, Z., 2015. Temperature distribution of photovoltaic module based on finite element simulation. Sol. Energy 111, 97–103.
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Modelling and experimental analysis of a seasonally tracked V-trough PV/T system in India ⁎
Hasan Baiga, Ruchita Janib, Bhupendra K. Markamb, Subarna Maitib, , Tapas K. Mallicka, a b
T
⁎
Environmental and Sustainability Institute, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK PDEC, CSIR-Central Salt and Marine Chemicals Research Institute, G.B. Marg, Bhavnagar 364002, Gujarat, India
A R T I C LE I N FO
A B S T R A C T
Keywords: Desalination FEA PV/T Simulation V-Trough
Hybrid PV/Thermal (PV/T) systems can generate both electrical and thermal energy simultaneously. These systems are already finding interesting applications in the fields of desalination, sensible heating/cooling and other allied industrial processes. An effective way to further improve the overall system efficiency is by using VTrough’s to concentrate incoming sunlight and enhance the power output from these systems. In this work, we study the performance of a V-Trough PV/T system connected to a reverse osmosis plant in India. A coupled optical, electrical, and thermal model is presented and validated by experiments. The optical analysis was carried out while including the variations in suns altitude and zenith angle over the day. The impact of the variable inlet water temperature with time is included in the model. The performance of a V-Trough PV/T system is compared with a standard PV system. An average increase of 35% was observed in the electrical power output from the V-Trough PV/T system as compared to the conventional one, with the maximum being 63%. Using the water circulation, an average of 778 BTU/m2 of thermal energy was extracted from the V-Trough PV/T system. A maximum temperature difference of 5.2 °C was observed in the feed water at the system outlet, this accounted for a maximum 1/3rd of the total energy recovery when using the V-Trough PV/T system. Feeding heated water to the RO unit in the PV-RO system helped in significantly increasing the quantity and quality of the permeate obtained from the system. A parametric study of the effect of varying mass flow rate on the performance of the system is also discussed.
1. Introduction India is geographically well placed on the earth's solar belt (40° S–40° N) having 250–300 sunny days in a year with most of the regions receiving an average annual global horizontal radiation amounting 1800–2000 kWh/m2. However, this huge solar potential remains untapped due to the associated deployment costs and alternative land usage. The power generation using solar energy has reached a cumulative of 13 GW till date and is planned to increase to 175 GW by 2021 (MNRE, 2018). The photovoltaic systems are essentially limited by their efficiency (currently reported maximum efficiency) up to 26% (Green et al., 2018) making it an expensive power generating source in developing countries like India. Applications are sought where we can employ the PV systems with other technologies making it cost-effective and environment-friendly at the same time. Solar concentration is an effective route towards increasing the output from typical Si solar panels, (Baig and Mallick, 2011; Swanson, 2000; Maiti, et al.,2012). Baig et al. highlights the effective routes that could help increase the power output of silicon cells using concentrators ⁎
and draws attention to how they can be used as an alternative to reduce consumption of expensive silicon-based materials and couple it with low cost concentrators. However, it tends to reduce the reliability of the system due to the hot spots formed by the non-uniform illumination on both single and multi-junction solar cells and the temperature rise caused by this ultimately reduces the efficiency of the system and increases the cost of electric power produced by such systems, these effects can be minimised by improving the design procedure adopted for making them (Baig et al., 2012). Employing suitable cooling mechanisms (Chemisana and Rosell, 2013) and utilising the excess heat generated from the system can prove to be a suitable method to increase the overall performance of the system and reduce the overall cost. A review of different mechanisms that can be employed has been showcased recently (Michael et al., 2015). The excess heat from the PV panels can be utilised as a source of low grade thermal energy and these hybrid systems can be utilised for generating the electrical power and hot water at the same time (Baig et al., 2013; Kumar et al., 2015, Kern and Russell, 1978; Kandilli, 2013). Adding solar concentration to such systems (CPV/T) will further increase the overall energy output because
Corresponding authors. E-mail addresses: [email protected] (H. Baig), [email protected] (B.K. Markam), [email protected] (S. Maiti), [email protected] (T.K. Mallick).
https://doi.org/10.1016/j.solener.2018.06.018 Received 13 December 2017; Received in revised form 5 April 2018; Accepted 4 June 2018 0038-092X/ © 2018 Elsevier Ltd. All rights reserved.
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Nomenclature a AreaPV Cw hext I IL IO L ṁ Qth RS Rsh S Tamb Tin Tout TPV U V Vwind Qs Cp F
Fx Fy Fz g k ksi
ideality factor area of the PV panel (m2) specific heat of water (J/kg K) external heat transfer coefficient (W/m2 K) current under load condition (A) light generated current (A) diode reverse saturation current (A) characteristic length scale (m) mass flow rate of incoming water (kg/s) amount of energy removed by the heat exchanger (J/kg K) series resistance (Ω) shunt resistance (Ω) absorbed solar radiation (W/m2) ambient temperature (K) inlet water temperature (K) outlet water temperature (K) temperature of the PV layer (K) characteristic velocity (m/s) voltage under load condition (V) wind velocity (m/s) amount of heat generated by volume of PV layer (W/m3) heat capacity (J/kg K) volume force (N /m3)
p T TPV-surface Td u, v, w
body force in x direction (N/m3) body force in y direction (N/m3) body force in z direction (N/m3) acceleration due to gravity (m/s2) turbulent kinetic energy (J/kg) thermal conductivity of the thin layer (silicon-Si) (W/ m2 K) pressure (Pa) feed water temperature (°C) temperature of the PV (°C) temperature at the surface having a thickness of d in mm (°C) components of the velocity (m/s)
Greek symbols γPV ε ηn ηel θ μ μT ρ
temperature coefficient (%/°C of temperature) turbulent dissipation rate (J kg s) nominal efficiency electrical efficiency of the panel tilt angle (°) dynamic viscosity (Pa s) turbulent viscosity (m2/s) density (kg/m3)
atmospheric conditions as inputs were presented recently. An energy assessment method incorporating the effects of shading on a low concentrating photovoltaic system with PV panels, with and without bypass diodes was recently presented by (Tina and Ventura, 2015). Finite element simulation was used to carry out simulation of PV (Usama Siddiqui et al., 2012) and PV/T (Siddiqui and Arif, 2013) systems in order to study the heat transfer phenomenon taking place in them, however very little has been published on the detailed modelling of VTrough based CPV/T systems. Zhou et al. recently presented the finite element analysis of a PV module where they evaluated the thermal and electrical performance of a PV system and its dependence on ambient temperature and wind velocities (Zhou et al., 2015). The impact of the flow and its configuration on a PV/T system was investigated by (Naewngerndee et al., 2011), they found that the number of strings used is inversely proportional to the quality of the flow distribution and the best performance can be obtained by using fewer strings in the horizontal direction. PV/T systems have found their applications in several process applications, they have been used for space heating and domestic hot water supply (Rommel et al., 2015). A V-Trough based water purification and power generation were presented recently (Qin et al., 2015). Results showed that the electrical output was more than double compared to a non-concentrating system. In remote locations, such small-scale solar photovoltaic powered Reverse Osmosis (RO) desalination systems can be utilised to provide potable water for its residents. The temperature of water supplied to an RO desalination unit influences the performance of the quality and quantity of permeate obtained. Employing CPV/T technologies for such systems can be used for increasing the temperature of the water supplied to such RO based system’s feed water (Vyas et al., 2015) while still increasing the electrical output. The objective of the current work was to develop a coupled multiphysics model using ray tracing and finite element methods capable of predicting the performance of the V-Trough based PV/T system. Results obtained using the optical analysis are utilised to evaluate the thermal and electrical performance of the system. Impact of adding the thermal heat exchange system to the existing plant is evaluated. The model is experimentally validated, and shortcomings identified. Atmospheric
it not only concentrates direct but also diffused radiations quite effectively (Baig et al., 2013). Several designs of such systems have been developed in the past few years based on the desired application (Sharaf and Orhan, 2015). Use of flat mirrors placed at an angle (V-Trough) to boost the performance of solar collectors is a well-established methodology (Tabor, 1966; Seitel, 1975; Pucar and Despic, 2002; Broman and Mirrors, 1984). These systems require occasional tracking and can work much effectively even if the position of the mirrors is changed once a month. The V-Trough walls can be used for light concentration as well as heat dissipation from the solar cells (Solanki et al., 2008) which is an effective way of improving the performance if we do not intend to utilise the excess heat generated. Results show that the temperature of the PV cell remains the same when placed under concentration whilst using this design. Andersen et al. characterized the natural convection heat transfer phenomena experimentally in a V-Trough system (Anderson, 2013). It was found that the parameters could be predicted extending a relationship described earlier (Iyican et al., 1980) for a Rayleigh number range of 2 × 103–5 × 107. Recently, Baig et al. performed the optical analysis of a reflective Compound Parabolic Concentrator (CPC) based PV/T system designed for similar application in Saudi Arabia (Baig et al., 2013). The system was later experimentally studied and evaluated (Li et al., 2015). It was found that the PV-CPC design helps reducing the solar cell temperature and produces hot water simultaneously. Li et al. developed and tested an air-gap-lens-walled compound parabolic concentrator incorporated with the photovoltaic/ thermal system (ALCPC-PV/T) with the geometrical concentration ratio of 2.4× designed for building integration (Li et al., 2015). The thermal efficiency of the ALCPC-PV/T system was found to be 52.0%, but the electrical efficiency was found very low having a value of 6.6%. Numerical methods have been employed for evaluating the performance of such systems (Huang et al., 2001; Amrizal et al., 2013) and have been validated using experiments. Rao et al. developed an algorithm to assess the contribution of solar energy on a horizontal receiver by plane booster mirrors (Narasimha Rao et al., 1993). Results showed that placing a south facing mirror is the best choice for boosting the energy outputs, especially at lower solar altitudes. A model (Reis et al., 2010) to describe the performance of V-Trough systems in terms of the module temperature, power output and energy yield using the 619
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heat exchanger connected to the PV panel. However, it was important to understand the physical phenomenon occurring due to the inclination angle and the flow rate of water a model to optimise the overall performance. A direct contact type heat exchanger system was arranged behind the panel where water can be circulated from one end and extracted from another. Previous research (Vyas et al., 2015) suggests that there is a notable increase in the output permeate from a reverse osmosis unit if there is a rise in feed water temperature (up to a certain limit i.e. 40 °C) which is given as inlet to the RO unit. Thus, the heated water received after cooling of PV panels can be supplied as feed water to the RO unit for desalination purposes. To analyse such a complex system where we have optical reflectors, electricity generating PV modules and water heating technologies coupled together we need to break down each analysis separately and couple them together to evaluate the overall performance of the system. In the present study, we have isolated a single unit of PV panel along with a V-Trough and cooling system and compared its performance against a similar PV panel placed next to it under similar environmental conditions to estimate the benefit obtained by using such a system. The experimental set up was constructed on the terrace of Solar Energy Lab of CSMCRI, Bhavnagar. Fig. 2 shows the experimental setup and the parameters being monitored in the system. The water was circulated in the heat exchanger behind the PV panel using a diaphragm pump and the flow rate was maintained at 1.5 LPM. The heat exchanger connected behind the PV panel simply consisted of a tray of a 2 mm GI sheet arranged along with each PV panel. Measurements were carried out in 30-minute intervals. The thermal images of the PV panel were taken using the Testo Thermal Imager 876.
parameters like ambient temperature and wind speed affecting the system performance are analysed for their impact on the PV module temperature and the water outlet temperature. The model can be extended to evaluate the impact of different boundary conditions including both the environmental, geometrical design and incoming flow rates of the water used for cooling the system.
2. System description In the present study, we consider a community scale Solar powered Reverse Osmosis desalination plant located at the rooftop of Solar Energy Lab, CSMCRI Bhavnagar, Gujarat (Latitude and Longitude of 21.45° N and 72.08° E respectively) is shown in Fig. 1. The plant consists of two different V-trough PV arrays (one PV and the other PV/T) connected in the opposite directions that provide electrical energy and low-grade thermal energy for carrying out the desalination using the Reverse osmosis plant. Both were used to run the RO system, the heated water from the PV/T system was used at the inlet of the RO plant. The PV/T array having 8 modules sloped at an angle of 20° facing south. The V-Trough mirrors are placed at inclinations which can be changed depending on the time of the year. The system also consists of 8 PV panels with V-Trough without any energy recovery system. The main objective of this system was to increase the power output obtained through each panel using V-Trough whilst reducing the number of panels required for operating the setup. This was done by placing Aluminium reflectors in V- Trough alignment in a North-South direction to increase the amount of solar intensity falling on the PV panel. The increased intensity of solar radiation helped in improving the electrical output and increased the temperature of the water leaving the
Fig. 1. Schematic of the V-trough PV/T system connected to an RO desalination unit. 620
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Fig. 2. Experimental setup showing different parameters being measured.
3.1. Optical analysis
The solar radiation incident on the PV panel was measured using a Kipp and Zonen CM4 High-Temperature pyranometer. The sensitivity of the instrument was 4–10 μV W−1 m−2 and response time was < 8 s. The IV curve of the solar panel was measured with the help of Autosys PV Array tester-SAT10030ACH2. The atmospheric conditions during all experiments were recorded using AWS 3001K-13-2 Virtual Electronics Weather station which has an inbuilt anemometer and capable of recording ambient temperature, relative humidity, wind speed and wind direction. The temperature of the water at the inlet and exit of the heat exchanger are measured using K-type thermocouples.
An optical analysis was performed to evaluate the incoming solar radiation on the PV panels using ray tracing methods. The PV panels are fixed at a slope of 20° facing south and the reflectors are tilted at −9° and 63° from the vertical plane as shown in Fig. 4. The position of the reflectors can be varied to suit the experimental setup which could be changing over the period of the year. To understand the effects of both the azimuth and zenith angle a model as shown in Fig. 5 was developed. A V-trough PV/T system was modelled along with the north and south side reflectors. It is important to note that the reflectors are modelled extending on both the sides of the PV panel to include the lateral concentration effects caused by adjacent systems in both the directions. In the present analysis, the trajectory of the sun for a given day can be determined in terms of its zenith and azimuth angle with the use of MIDC SOLPOS calculator (Mcadams, 1954). At a given time instance, total reflected power, received by the PV panel array was determined using the ray tracing method. The integration of these values was then performed over the time interval from sunrise to sunset to get the total solar energy received by the PV panel array. The optical properties of the reflector play an important role in the determination of the solar radiation incident on the PV panel. Anodized aluminium sheets were used in the experimental setup, whose reflectivity was determined using PerkinElmer UV–Vis-NIR spectrophotometer based at the Environment & Sustainability Institute, Penryn, the UK as shown in Fig. 6. Additionally, the standard AM1.5G solar spectrum used in the optical model and the silicon solar cell quantum efficiency are also represented. The incident angles of solar radiation on the aperture were calculated for a specified day using the MIDC SOLPOS calculator. The
3. Computational model To perform the numerical analysis of this system we have adopted a detailed procedure as highlighted in Fig. 3. Input parameters like the solar radiation based on the time of the day, the reflectivity of the mirrors, and absorption of PV are utilised. Based on this, ray tracing is carried out to estimate the amount of solar radiation incident on the PV panels as a function of time. Once this is estimated the energy conversion to electrical power is modelled and the dissipated heat from the PV module to thermal energy is estimated simultaneously. This is then introduced in the thermo-fluid model of the PV/T device to estimate the solar cell temperature under steady state conditions. Initially, a steady state analysis is carried out to obtain an initial solution for the system. On convergence, this becomes the initial solution for the transient thermo-fluid model. The temperature of the PV in the heat transfer model is interlinked with the thermo-fluid model of the heat exchanger. This is then finally utilised to estimate the electrical and thermal performance of the PV/T system. The outlet temperature of the water is then evaluated using which the thermal efficiency of the system can be estimated. 621
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Fig. 3. Detailed procedure used for the analysis of the V- trough system.
function of the zenith and azimuth angle. Based on the day and time of the year the position of the source could be modelled. Rays emanating from the source are incident on the reflectors and the PV panel. Some rays directly reach the PV panel and the rest arrive via reflection from the adjoining mirror surfaces. The angular variation of the reflectors can also be changed in the model if needed for evaluation during a different period of the year.
variation of the azimuth and altitude corresponding to 22 January 2016 is shown in Fig. 7. The sun’s azimuth position changes between 155° and 250°, the altitude/elevation angle varies between 6° and 50°. It is important to establish the variation of both these angles as it enables an approximate location of the sun when performing the optical analysis of the system. An accurate estimation of the solar position minimises the error between the model and the experiments. The optical analysis of the V-trough CPV unit was performed using ray tracing method. The geometry was modelled in Solid works and subsequently evaluated using the commercial ray tracing software. This gives much flexibility in analysing the optical performance as we can input the optical properties as a function of the wavelengths. In the present study, we have used the standard AM1.5 G spectrum for the source and the reflectivity as a function of the wavelength as shown in Fig. 6. The setup for the ray tracing is shown in Fig. 8. A circular light source representing the sun is chosen to produce one million collimated rays with a flux of 1000 W/m2. The position of the source is made a
3.2. Electrical model Typically, a five-parameter model (Lo Brano et al., 2010) is used to estimate the parameters and the I-V curve determining the electrical performance of the PV panel. It is important to note that the electrical performance is dependent on the operating PV temperature which is coupled with the thermal analysis of the system. Eq. (1) can be utilised to predict the I-V characteristic of this system at a fixed temperature and solar radiation. 622
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incident on the PV panel is converted into the electrical energy and the rest of energy is dissipated in the form of heat to the surroundings and to the water flowing behind the PV panel. The heat is dissipated to the surroundings in the form of radiation and convection losses from the front and side surfaces. Convection losses occur on the back side of the heat exchanger which have been modelled assuming a constant heat transfer coefficient. When solar energy is incident on a PV panel then only a portion of it is converted into electricity, part of it is lost to the surroundings and the remaining goes into heating the water in the heat exchanger behind the PV panel, so the energy balance can be expressed using Eq. (2).
⎡ RateofHeatloss ⎤ ⎡ RateofSolarEnergy ⎤ = ⎢ fromallthesurfaces ⎥ ⎣ AvailableonSolarPanel ⎦ ⎢ oftheSolarPanel ⎥ ⎣ ⎦ RateofHeatTransferfrom ⎤ +⎡ PVtothewater ⎣ ⎦ RateofElectrical ⎤ +⎡ ⎢ ⎥ EnergyProduced ⎣ ⎦
Fig. 4. Angular position of the mirrors during the study.
I = IL−Io ⎡exp ⎛ ⎝ ⎣
V + IRs V + IRs ⎞−1⎤− a Rsh ⎠ ⎦
(2)
To formulate the problem using finite element method, the geometry of the given dimensions was created as per the system specifications as shown in Fig. 10. The PV panel is modelled with all the different layers whose thermophysical properties used (Siddiqui and Arif, 2013) are shown in Table 1. The basic PV module consists of five layers of materials namely: glass, ethyl vinyl acetate as an encapsulant, silicon, second layer of encapsulant and Tedlar. While the PV/T module consists of an added heat exchanger made of GI metal sheet attached along with the panel that could store water in it for circulation purpose. There are two PVC pipes also attached to the PV/T system that acts as inlet and outlet points for water circulation. The heat exchanger placed behind the PV panel is constructed in the form of a simple rectangular tray made using galvanized iron whose thickness is 2 mm and bonded directly behind the PV panel with an inlet and exit pipe. Depending on the flow rate of the incoming water we can have laminar or turbulent fluid flow occurring inside the heat exchanger. Turbulence accounts for the additional localised random effects such as eddies and vortices at small length and timescales. This behaviour is characterised by a dimensionless number called the Reynolds Number.
(1)
where I and V represent the current and voltage respectively under load condition. The electrical circuit requires that five parameters be known, and they are light generated current (IL), diode reverse saturation current (I0), series resistance (Rs), shunt resistance (Rsh), ideality factor (a). The five parameters in the model are obtained using I-V characteristics of a module at reference condition supplied by the manufacturer and other known PV characteristics. Here values for Rs and Rsh are considered at the module level. 3.3. Thermo-fluid model A thermo-fluid model was developed to examine the heat transfer processes occurring in the system. The incoming solar radiation on the panel is converted to electricity and rejected to its surroundings via different heat transfer mechanisms as shown in Fig. 9. The incident solar radiation gets concentrated from the V-trough where it experiences reflection losses. A part of the concentrated solar radiation
Fig. 5. Schematic of the optical analysis method used to estimate the solar radiation received by the PV panel. 623
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Fig. 6. Reflectance of the anodized aluminium sheet used as a reflector, the silicon quantum efficiency and the standard AM1.5G solar spectrum used in the optical model.
Fig. 7. Variation of the solar azimuth and altitude on the test date, equinox, and solstice.
ρ∇∙ (u) = 0
The Reynolds number is a ratio of the inertial and viscous forces acting on the fluid and is determined using the Eq. (3).
ρUL Re = μ
(5)
The transport equation for the turbulent kinetic energy k and the dissipation rate of turbulence energy, ε are shown in Eqs. (6), (7).
(3)
μ ρ (u∙∇) k = ∇∙ ⎡ ⎛μ + T ⎞ ∇k ⎤ + Pk−ρ ∊ ⎢⎝ σk ⎠ ⎥ ⎣ ⎦
(6)
μ ε ε2 ρ (u∙∇) ε = ∇∙ ⎡ ⎛μ + T ⎞ ∇∊⎤ + Cε1 ρk −Cε 2 ρ , ε = e p ⎢⎝ ⎥ σ k k c ⎠ ⎦ ⎣
(7)
⎜
where ρ is the density, µ is the dynamic viscosity, U is the characteristic velocity, and L is the characteristic length scale. The Reynolds Averaged Navier Stokes (RANS) equations were solved using the k-ε model to compute the turbulent fluid flow occurring in the water in the heat exchanger. The momentum and continuity Eqs. (4), (5) used are shown below for steady state conditions.
ρ (u∙∇) u = ∇∙ [−pI + (μ + μT )(∇u + (∇u)T )] + F
⎜
⎟
⎟
Where the production term (Pk) is expressed as Eq. (8).
2 2 Pk = μT (∇u: (∇u + (∇u)T )− (∇∙u)2)− ρk∇∙u 3 3
(4) 624
(8)
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Fig. 8. Ray tracing of the system.
μT = ρCμ
k2 ε
(9)
The parameters Cε1 = 1.44, Cε2 = 1.92, Cµ = 0.09, σk = 1.0, σε = 1.3 are model constants. To incorporate the effects of gravity, a volume force (F) must be added to the Turbulent Flow, k-epsilon Interface as shown in the Eqs. (10)–(14). In the case where the module is flat (tilt angle 0°), the Volume Force of gravity is defined using the expression,
Fx = Fy = 0
(10)
Fz = −ρn g
(11)
Fig. 10. Schematic of the cross-section of the model used for thermo-fluid analysis of the PV/T system.
However, this changes with the change of the inclination of the system to
Fig. 9. Different thermal interactions occurring on the PV/T system. 625
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The energy transport equation used to model the heat transfer is expressed in Eqs. (15), (16)
Table 1 Thermo-physical properties of the different layers of the PV/T system. Layer
Thermal conductivity (W/m K)
Density (Kg/ m3)
Specific heat (J/Kg K)
Thickness (m)
Glass EVA 1 PV Cell EVA 2 Tedlar Water
1.8 0.35 148 0.35 0.2 0.667
3000 960 2330 960 1200 992.22
500 2090 677 2090 1250 4179
0.003 0.0005 0.000225 0.0005 0.0001 0.045
ρCp u∙∇T + ∇∙q = Q + Qp + Q vd
(15)
q = −k∇T
(16)
where Qvd accounts for the viscous dissipation effects and Qp is the pressure work term which is both negligible in the present study. The PV panel has several layers as shown in Table 1. For modelling thin layers, the following Eqs. (17)–(20) are applied, where ks is the layer thermal conductivity, Qs is layer internal heat source, i is the layer number and ds is the layer thickness
Table 2 Fluid flow boundary conditions.
∇∙ t qs = Qsi
(17)
No
Region
Boundary condition
qs = −ksi ∇t Ts
(18)
1
Wall condition, u·n = 0
Tu = (Ts )L = 0
(19)
2
External surface the heat exchanger Water inlet velocity
Td = (Ts )L = ds
(20)
3 4
Outlet Volumetric force
Velocity derived from the flowrate, u = uin Zero pressure, p0 = 0 Derived from bousinessq approximation
The solar radiation incident on the PV panel is converted to electrical and thermal power. Both these quantities are a function of the solar cell temperature (Tpv).
Table 3 Thermal boundary conditions.
Qs =
No
Region
Boundary condition
1
The external surface of the PV
2
The external surface of the heat exchanger Water outflow Water inlet temperature PV surface
Temperature Tamb, Convective heat transfer coefficient, ho Temperature Tamb, Convective heat transfer coefficient, hb −n·q = 0 Temperature, Ti Heat generation, Q
3 4 5
(1−ηel ) × S × Areapv Volumepv
(21)
where ηel is the electrical efficiency of the PV that can be defined as a function of the average PV temperature, nominal efficiency ηn and the temperature coefficient γpv as
ηel = ηn (1−γPV (TPV −25))
(22)
Fx = −ρn g cosθ
(12)
Fy = 0
(13)
Further effects of optical reflection which is the ratio of the solar transmittance at different angles to the normal incidence have been ignored in this study due to its minimal impact. The Tpv is the temperature of the PV layer, which is a function of the cooling rate and is coupled to the fluid flow heat transfer interface. The amount of energy removed by the heat exchanger Qth can be estimated using the equation
Fz = −ρn g cosθsinθ
(14)
̇ w (Tout −Tin ) Qth = mc
To model the temperature of the water and the solid domains the energy model is coupled to the fluid flow. To model the added dispersion of heat, transfer due to turbulence the Kays-Crawford turbulence heat transfer model is included.
(23)
The outer boundaries of the PV panel are subjected to convective and radiation losses. These can be modelled using the convective heat transfer boundary conditions. The external convective and radiative heat transfer coefficients can be related to the PV surface as
Fig. 11. Ambient conditions obtained using the outdoor weather station and the inlet water conditions recorded using K-Type thermocouples. 626
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Fig. 12. Typical illumination distribution profiles on the PV panel corresponding to (a) 8 am (b) 1 pm and (c) 4 pm.
q = −hext (Tamb−TPV − Surface )
(24)
where hext is the external heat transfer coefficient, which is the sum of both the convective and radiative heat transfer coefficients and Tamb is the ambient temperature. Mcadams (1954) reported the convection coefficient as a function of the wind velocity whilst including the effects of radiation heat transfer as shown in Eq. (25)
hext = 5.7 + 3.8Vwind
(25)
An inlet velocity uin, and temperature Ti is specified as a boundary condition on the inlet pipe, which can be varied to study the impact of the water flow rate. Finally, a pressure outlet condition is to be applied to the water outlet for setting up the problem. One of the important steps is the grid generation while solving the problem using finite element methods. This process involves partitioning the physical geometry (the domain) into small size units known as cells/mesh elements. It is important that proper meshing is applied to obtain correct results.
Fig. 13. Intensity of the solar irradiation reaching the PV unit. 627
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collector/flux receiving surface. The input parameters like the ambient temperature, the wind speeds and the inlet water temperature are also utilised in the model as shown in Fig. 11. 4. Results Using the coupled optical-electrical and thermal model presented in Section 3 a numerical study was carried out to evaluate the impact of cooling the PV system under varying atmospheric conditions. The effect of varying atmospheric factors such as ambient temperature, wind velocity and solar irradiance were included in the model to estimate the electrical and thermal efficiency of the system. The results obtained are compared against experimental values under similar conditions. 4.1. Optical results Fig. 14. Streamlines showing the velocity profile of the fluid flow occurring inside the heat exchanger unit.
The optical analysis was carried out using ray tracing under varying zenith and azimuth angles to obtain the incoming flux of the PV panel. This method is effective as it can also be used to evaluate the variation of irradiance distribution on the PV panel when incorporating different inclinations during different periods of the year. Fig. 12 shows the typical flux profiles obtained during different times of the day. The relevant features of the flux profile are distinct with the incident flux increasing as a function of time. The incident radiation was measured on a bare panel along with the V- trough system. It may be seen clearly in Fig. 12, how the flux profiles change both in its intensity along the PV panel depending on the time of the day. The flux profiles obtained are averaged across the PV panel and represented in Fig. 13. The optical analysis is carried for every half hour intervals to estimate the incident radiation on the V-trough PV/T system. The solar radiation incident on the PV unit is also compared with the values obtained experimentally. It may be seen that the model prediction is slightly higher to the values obtained experimentally. A maximum difference of about 10% was seen in the values. This could possibly occur due to the difference in the reflectivity of the unit reflector at different angles which is assumed constant essentially during the optical analysis.
Increasing the number of mesh means an increment in the solution time and accuracy. In the present study, we have used 0.2 Million mesh elements of different shapes to solve the problem using HPC Beowulf cluster Carson based at the Environmental and Sustainability Institute, University of Exeter, UK. 3.4. Boundary conditions While preparing the computational model it is very important to identify and apply the correct boundary conditions for convergence of the numerical problem. In the current study, we have a multi-physics problem requiring the application of both thermal and fluid boundary conditions and establishing a relationship between them. We have summarised both the types of boundary conditions in Tables 2 and 3. We have assumed water as an incompressible fluid, and the climatic conditions to be stable and representative of actual environmental conditions. While modelling the problem in 3D, we assume the incoming solar radiation reaching the PV is converted into electricity and the rest is dissipated in the form of heat. Hence the PV is assumed as a source of heat and all other surfaces are subjected to convective heat transfer conditions. It is important to note that the convective heat transfer would be different on different sides of the concentrator/
4.2. Fluid flow The water flow occurring inside the heat exchanger is visualised in
Fig. 15. Variation in cell temperature with varying flow rates for V-Trough PV/T system. 628
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Fig. 16. Variation in outlet water temperature with varying mass flow rate for V-Trough PV/T system.
Fig. 17. Thermal images showing the temperatures of (a) bare PV panel and (b) V-Trough PV/T system with cooling.
298 K was observed at maximum flowrate condition at 1.2 LPM at solar noon. Towards the end of the day when the solar radiation decreases both the PV and the feed water temperature decreases. At no flowrate condition, the PV temperature was found to reach 310.4 K and the water temperature reached 308.8 K. At a flow rate of 1.2 LPM, the PV temperature was found to reach 298.64 K and the water temperature reached 294.5 K.
Fig. 14, the arrows show the direction of the flow as it circulates inside the heat exchanger before exiting the tube. The turbulent intensity is highest towards the inlet of the heat exchanger and can be seen to drop as the fluid goes through the heat exchanger tray. The velocity profile of water flow inside the heat exchanger is shown in Fig. 14. The velocity of the water ranges from 0.02 to 0.12 m/s inside the heat exchanger. While the water circulates through the heat exchanger it absorbs extra heat from the panel, while being in contact with the lowest layer of the PV panel and thus helps in reducing the temperature of the PV panel. A set of parametric analysis using meteorological data corresponding to 21st January was carried out to predict the effect of changes in the mass flow rate of water on the performance of the VTrough PV/T system. The case where there is no flowrate and the water is stagnant in the heat exchanger, the heat exchange from the PV to the water occurs slowly leading to minimum heat transfer and thereby leading to a higher PV temperature and a higher feed water temperature at the outlet. It is very critical to balance the electrical energy output and the thermal energy output in a hybrid system. A maximum PV temperature of 316.5 K and outlet water temperature of 314.8 K was observed at zero flowrate condition as shown in Figs. 15 and 16 respectively at solar noon. When the water is circulated the heat transfer rate increases with increasing flow rate which leads to decreasing the solar cell temperature and improving the electrical output. For the existing system, the water flow rate was varied from 0 to 1.2 LPM. A maximum PV temperature of 305 K and outlet water temperature of
4.3. Thermal The incident radiation raises the temperature of the PV panel, having a cooling system reduces the temperature of the PV panel surface and helps improve the PV efficiency. A thermal imaging camera was used to measure the surface panel temperature for both the bare PV unit and the V-Trough PV/T unit under cooling. The temperature is averaged using 24 points on the system. The temperature profile of bare PV Panel and CPV/T is shown in Fig. 17. Similarly, contours of temperature can be extracted for both the PV and V-Trough PV/T system at any given time of day. The bare panel was also modelled to obtain the surface temperature of the PV, using the environmental conditions as shown in the previous section. Fig. 18 shows the temperature contours of both the systems at 8 am, 10 am and 1 pm respectively. The temperature of the water starts to increase behind the PV panel as a function of time. The results obtained using the simulations are compared to those obtained experimentally. 629
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Fig. 18. Showing the Temperature contours of the V-Trough with cooling and bare PV panels at (a) 8 am (b) 10 am and (c) 1 pm respectively.
Fig. 19. Comparison of PV surface temperature for the bare PV panel and the VTrough PV/T panel with cooling.
The average temperature of the PV module is shown in Fig. 19. The temperature of the bare PV panel ranges between 10 °C and 47 °C. The bare panel was found to reach a maximum of 47 °C under the environmental conditions illustrated in earlier sections. The V-Trough PV/ T, on the other hand, was found to have a maximum of 40 °C when subjected to cooling using the modelling. However experimental results show the maximum temperature of the PV to be 35 °C, this is essentially because of the slightly higher input flux used while modelling the VTrough PV/T unit as shown in Fig. 13 and due to the difference between the actual efficiency of the PV panel against that obtained experimentally. The error between the modelled and experimentally obtained temperature is found to be less than ± 5% in the case of the V-Trough PV/T unit. The temperature of the water exiting the V-Trough PV/T system acts as an input to the reverse osmosis plant.
Fig. 20. Comparison of outlet water temperature obtained from the V-Trough PV/T unit with cooling.
Fig. 20 shows the comparison of the temperature of the outlet water from the unit. The maximum temperature of the water reached by the system was found to be 32 °C. When compared to the water entering the PV/T unit a maximum of 5.2 °C increase was observed around solar noon time experimentally. An average temperature difference of 2.1 °C was observed over the whole day. In the desalination system, the power consumption depends on the incoming feed water temperature and pressure. Under constant pressure conditions, as feed water temperature increases, water flux 630
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35 °C. A parametric analysis of varying the flow rate of the working fluid on the performance of the V-Trough PV/T system significantly showed the advantage of implementing it over the conventional module and helped in determining the optimum flow rate for running the system. These results have been obtained for the system under stable environmental conditions. Further, the model can be utilised for the prediction of the device performance over any given location, day, and time of the year. Additional, features like the addition of fins or tubes will also be explored in the future studies. Acknowledgements Support from Indo-UK collaborative project (DST/INT/UK/P-83/ 2014), DST-SERI project (DST/TM/SERI/2k11/101(G) is acknowledged. The authors thank CSIR, India for infrastructure support to carry out the experiments and this is CSIR-CSMCRI – 124/2017. Appendix A. Supplementary material
Fig. 21. Power increment of the PV panel due to the addition of the V-troughs.
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.solener.2018.06.018.
increases almost linearly, primarily due to the higher diffusion rate of water through the membrane. One of the mechanisms of transport of water through an RO membrane is by diffusion from one bonding site to another within the membrane. The change in the permeate flux rate (Ammous and Chaabene, 2015) with temperature can be described by Eq. (26);
1 ⎞− 1 ⎞ Temperaturecorrectionfactor = exp ⎛K × ⎛ ⎝ 273 + T ⎠ 298 ⎠ ⎝ ⎜
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⎟
(26)
where K is a constant and characteristic for a given membrane material, and T is feed water temperature in °C. In the above equation, the temperature of 25 °C is used as a reference point, with temperature correction factor = 1. The enhanced feed water temperature also causes lower salt rejection or higher salt passage. This is due to a higher diffusion rate for salt through the membrane. The rate of change of the permeate flux is about 3% for every degree rise in temperature, which could equal about 6% increase in the permeate level due to the increase in the feed water temperature. The electrical output is also increased considerably due to the addition of the V-trough. Fig. 21 shows the ratio of the power obtained while using the PV panel with a V-trough and without a V-Trough. It can be clearly seen that the power ratio increases during the noon times; this is particularly because of the intensity and the orientation of the sun during these times. A maximum power ratio of 1.7 is observed around 1 pm. An average increment of about 35% is seen in the power output over the whole day. Using the above-showcased model long-term performance evaluation can be performed on these types of systems. The model offers the flexibility of changing the angular inclinations of the V-Trough, in addition to all the other parameters used for modelling. Using the model, further studies can be carried out to evaluate the impact of these individual parameters on the performance of the system. 5. Conclusions A detailed numerical and experimental analysis of a V-Trough PV/T system has been presented and validated in this study. Using a VTrough was found to improve the electrical output of the system. The rise in temperature due to increased flux was countered by use of heat exchanger improving the overall efficiency of the system. A coupled optical-electrical-thermal fluid model was developed capable for the prediction of the power output of the V-Trough PV/T module depending on the environmental conditions. It also allows for evaluation of factors and their relevant impact on the performance of the system. Experiments are carried out on a PV module placed under exactly same conditions to evaluate the overall benefit of using a V-Trough PV/T system. Experimentally the maximum temperature was found to be 631
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