Exergoeconomic and enviroeconomic analyses of hybrid double slope solar still loaded with nanofluids

Energy Conversion and Management 148 (2017) 413–430

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Exergoeconomic and enviroeconomic analyses of hybrid double slope solar still loaded with nanofluids Lovedeep Sahota a,⇑, G.N. Tiwari a,b a b

Centre for Energy Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India Bag Energy Research Society (BERS), Sodha Bers Complex, Plot No. 51, Mahamana Nagar, Karaudi, Varanasi, UP 221005, India

a r t i c l e

i n f o

Article history: Received 16 March 2017 Received in revised form 18 May 2017 Accepted 27 May 2017

Keywords: Exergoeconomic Enviroeconomic Energy matrices Solar still Heat exchanger Nanofluids

a b s t r a c t In recent times, incorporation of nanotechnology in solar distillation systems for potable water production is a new approach harvesting solar thermal energy. In present manuscript, concentration of assisting nanoparticles and basin fluid (basefluid/nanofluid) mass have been optimized for hybrid solar still operating (a) without heat exchanger (system A), and (b) with helically coiled heat exchanger (system B). Corresponding to the optimized parameters, overall thermal energy, exergy, productivity (yield), and cost analysis of the proposed hybrid systems loaded with water based nanofluids have been carried out; and found to be significantly improved by incorporating copper oxide-water based nanofluid. Moreover, on the basis of overall thermal energy and exergy, the amount of carbon dioxide mitigated per annum is found to be 14.95 tones and 3.17 tones respectively for the hybrid system (A); whereas, it is found to be 24.61 tones and 2.36 tones respectively for the hybrid system (B) incorporating copper oxide-water based nanofluid. Annual performance of the proposed hybrid systems has been compared with the conventional solar still (system C). Ó 2017 Elsevier Ltd. All rights reserved.

1. Introduction The solar photovoltaic (PV) technology is one of the most promising and fastest growing renewable energy technologies which will play a primary role in clean energy. Photovoltaic thermal systems or renewable energy (RE) systems on harvesting an ample source of (solar) energy are the viable option for various applications viz. solar water collector, solar air collector, space heating, greenhouse dryer, heat exchanger and building integrated photovoltaic thermal system, etc. Including clean food and air, potable water is a fundamental human need and it is essential to sustain life for all creatures on the Earth. Moreover, consumption of contaminated drinking water originates various diseases i.e. bacterial infections, viral infections, protozoal infections, etc. Worldwide, various nations are affected with water shortages. This problem basically originates due to change in climate conditions; rapid growth in population; floods, poor management of water resources and excess use of potable water. Therefore, the protection of safe drinking (potable) water requires proper ‘‘framework”; adequate, effective, and comprehensive policies for water distribution; and a system of independent surveillance.

⇑ Corresponding author. E-mail address: [email protected] (L. Sahota). http://dx.doi.org/10.1016/j.enconman.2017.05.068 0196-8904/Ó 2017 Elsevier Ltd. All rights reserved.

Today, with advancement in science and technology, high and medium techniques have been developed to produce drinking water from the contaminated water. But, these techniques depend on the conventional source of energy i.e. electricity. Solar distillation is the simplest, cost-effect and environment friendly method for the production of potable water. Solar distillation systems or simply solar stills are categorized into passive and active solar stills [1]. There are some advantages of solar distillation over the other techniques i.e. no need of high tech exchange parts like batteries, filers, or membranes; purify highly saline water, feasible for local manufacturing, no conventional source of energy is required, and low initial investment. The productivity of solar still mainly depends on the working temperature and internal heat transfer mechanism [2]. The heat transfer coefficients (HTCs) can be enhanced by improving the thermo-physical properties of water (basefluid). In recent times, nanotechnology has been implemented in the solar stills in order to improve further their performance. Nanofluids are simply the suspension of 1–100 nm nanoparticles (NPs) in the basefluid (water, thermal oil, ethylene glycol, etc.). These are the embryonic fluids with ultrafast heat transfer capabilities due to their better thermo-physical and optical properties. These properties can be improved by tailoring the size and shape of the NPs in a particular basefluid.

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Nomenclature Am Ac AgE AgW Ab Cp C nf C bf Di dp F0 h1g;E h1g;W h1f ;E h1f,W hEW hef ;E hef ;W hba hFPC hHE hb;f hpf hi ho ISE ISW ISW Kp kp knf kbf Kg L Lg Lb Lp Mf _f m _ bf M Pgi Pf PF 1 PF 2 PF 3 r 11 r 22

area of the PV module, (m2) area of the glazing, (m2) surface area of condensing cover of east side of solar still, (m2) surface area of condensing cover of west side of solar still, (m2) basin area of solar still, (m2) specific heat capacity of NP, ðJ=Kg-KÞ specific heat capacity of nanofluid, ðJ=Kg-KÞ specific heat capacity of basefluid, ðJ=Kg-KÞ diameter of the FPC tube (mm) diameter of nanoparticle (nm) collector efficiency factor total external heat transfer coefficient on east side, (W/m2 °C) total external heat transfer coefficient on west side, (W/m2 °C) total internal heat transfer coefficient on east side, (W/m2 °C) total internal heat transfer coefficient on west side, (W/m2 °C) internal radiative heat transfer coefficient between glass covers, (W/m2 °C) evaporative heat transfer coefficient on east side, (W/m2 °C) evaporative heat transfer coefficient on west side, (W/m2 °C) heat transfer coefficient between basin liner and ambient air, (W/m2 °C) convective heat transfer in the flat plate collector, (W/m2 °C) convective heat transfer in the heat exchanger, (W/m2 °C) heat transfer coefficient between basin liner and fluid, (W/m2 °C) heat transfer coefficient from blackened plate to ambient, (W/m2 °C) heat transfer coefficient for space between absorption plate and glazing, (W/m2 °C) heat transfer coefficient from top of PV water collector to ambient, (W/m2 °C) solar intensity on east side of the glass cover, (W/m2) solar intensity on west side of the glass cover, (W/m2) solar intensity on FPC, (W/m2) thermal conductivity of the absorption plate (W/m-K) thermal conductivity of nanoparticle, (W/m-K) thermal conductivity of nanofluid, (W/m-K) thermal conductivity of basefluid, (W/m-K) thermal conductivity of condensing cover, (W/m2 °C) length of the helical heat exchanger (mm) thickness of condensing cover, (m) thickness of basin, (m) thickness of the absorption plate (m) mass of fluid in the basin of solar still (kg) mass flow rate of the fluid (kg/s) yield obtained from the system (kg/h) partial saturated vapor pressure of the inner glass cover, (N/m2) partial saturated vapor pressure of the fluid, (N/m2) penalty factor due to glass covers of the module penalty factor due to absorption plate below the module penalty factor due to absorption plate for the portion covered by the glazing outer diameter of the heat exchanger tube (mm) inner diameter of the heat exchanger tube (mm)

T goE T goW T bf T nf T giE T nf Tv Ta T giW

DT DSSS DT FPC DT HE Dt Utp,a U L;m U L;c U tc;a U ga U ba U gaE U gaW U tc;p X

outer condensing cover temperature of east side solar still, (°C) outer condensing cover temperature of west side solar still, (°C) basefluid temperature, (°C) nanofluid temperature, (°C) inner condensing cover temperature of east side of solar still, (°C) fluid temperature, (°C) vapor temperature, (°C) ambient temperature, (°C) inner condensing cover temperature of west side solar still, (°C) temperature difference between NF and BF in DSSS, (°C) temperature difference between NF and BF at the outlet of PVT collectors, (°C) temperature difference between NF and BF in heat exchanger, (°C) time interval (s) overall heat transfer coefficient from absorption plate to ambient, (W/m2 °C) overall heat transfer coefficient from module to ambient, (W/m2 °C) overall heat transfer coefficient from glazing to ambient, (W/m2 °C) overall heat transfer coefficient from cell to ambient from the top surface, (W/m2 °C) overall heat transfer coefficient between condensing cover and ambient air, (W/m2 °C) overall heat transfer coefficient between basin liner and ambient air, (W/m2 °C) overall heat transfer coefficient between outer condensing cover of east side and ambient air, (W/m2 °C) overall heat transfer coefficient between outer condensing cover of west side and ambient air, (W/m2 °C) overall heat transfer coefficient from cell to the absorption plate, (W/m2 °C) characteristic length of solar still, (m)

Greek letters ag fraction of solar energy absorbed by condensing cover ab fraction of solar energy absorbed by basin surface af fraction of solar energy absorbed by fluid ac fraction of solar energy absorbed by solar cell sg fraction of solar energy transmitted by top glass cover of the PVT-FPC up volume fraction of nanoparticles (%) gc efficiency of the PVT- FPC collector (%) b packing factor bp thermal expansion coefficient of nanoparticle, (K1) bnf thermal expansion coefficient of nanofluid, (K1) thermal expansion coefficient of basefluid, (K1) bbf lbf dynamic viscosity of basefluid, (Ns/m2) lnf dynamic viscosity of nanofluid, (Ns/m2) qp density of nanoparticle, (Kg/m3) qnf density of nanofluid, (Kg/m3) qbf density of basefluid, (Kg/m3) Subscripts a ambient b basin surface v vapor gi inner condensing cover go outer condensing cover

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f p FPC th sol E W ann ex en HE

fluid particle flat plate collector thermal solar east side west side annual exergy energy heat exchanger

Abbreviation HTC heat transfer coefficient

Lawrence and Tiwari [3] analytically analyzed the hybrid solar still system (with water as working fluid) under natural circulation mode by incorporating heat exchanger to develop the empirical relation for internal heat transfer coefficients. They found that collector significantly enhances the operating temperature of the system which intern improves the overall efficiency of the system; also, the efficiency decreases with increase in water depth. Kabeel et al. [4] have studied the performance of single slope solar still integrated with vacuum fan by incorporating aluminium oxide (Al2O3) - water based nanofluid. Elango et al. [5] experimentally analyzed the performance (thermal energy, exergy, productivity) of single basin single slope solar still using different nanofluids. Sahota and Tiwari [6,7] studied the effect of nanofluids on the performance of passive double slope solar still (DSSS). They found that Al2O3- water based nanofluid gives better productivity of the passive DSSS. Omara et al. [8] studied the effect of nanofluids and vacuum on the performance of convensional solar still and corrugated wick type solar still. Shashir et al. [9] experimentally studied the effect of graphite and copper oxide micro-flakes (nanoparticles) on the performance of solar still with different cooling flow rates over the toughen glass cover. They found that the use of copper oxide and graphite micro-flakes in combination with water flow gives 47.80% and 57.60% enhancement in the solar still productivity. Sahota et al. [10] analytically investigated the performance of N photovoltaic thermal flat plate collectors integrated with double slope solar still (N-PVT-FPC-DSSS) operating with/without helically coiled heat exchanger by incorporating different water based nanolduids. Performance of the hybrid system operating without heat exchanger is found to better with copper oxide (CuO) water based nanofluids. Saleha et al. [11] reported the influence of solvent in the synthesis of zinc oxide (ZnO); and found it effective while using in solar still as an application. Chen et al. [12] experimentally investigated the effect (stability, optical properties, and thermal conductivity) of saline water based silicon carbide (SiC) nanofluids in solar distillation systems. They found very good stability; low luminousness and effective thermal property of SiC nanofluids; and confirmed the feasibility of nanofluids application in solar distillation system. Mahian et al. [13] experimentally studied the effect of copper (Cu) and tin oxide (SiO2) water based nanofluids on the evaporative heat transfer mode in solar still integrated with two series connected flat plate collectors and heat exchanger; and also validated the results by developing thermal modeling. They fund that the use of heat exchanger is not significant at temperatures lower than 50 °C; and the corresponding yield is found to be around two times higher (than that of solar still without the heat exchanger) when the inlet temperature is 70 °C. Moreover, they found that Cu/water gives the significant enhancement in evaporation rate at low temperature; whereas, SiO2/water provides improved enhancement at high temperatures.

DSSS FPC NP EPBT EPF NPV HE NF BF LCCE UAC CRF SRF

415

double slope solar still flat plate collector nanoparticle energy payback time energy production factor net present value heat exchanger nanofluid basefluid life cycle conversion efficiency uniform annual cost capital recovery factor shrinking fund factor

Understanding of economic/cost analysis (life cycle cost, net present value, and payback period, uniform annual cost) of renewable energy systems is important to assess their economic feasibility (design, construction, and implementation). Tiwari et al. [14] experimentally studied the exergoeconomic and enviroeconomic analysis of active solar still using water as a basin fluid. Their purposed system, photovoltaic thermal –flat plate collector (PVT-FPC) meets the daily demand of potable water during the sunshine hours. The result obtained has been compared with the results obtained by other researchers. The environmental cost is found as 6.29 $ per year. Liu et al. [15] performed the thermal and economic analysis of evacuated tubular collector (ETC) integrated solar distillation system using water. Later, Sharon and Reddy [16] reported the enviroeconomic analysis of active vertical solar distillation system loaded with saline water. On the basis of annual performance, Singh et al. [17] studied the effect of energy matrices for comparative study of life cycle of conventional single slope and double slope solar still with water as a basin fluid. They have found 0.144 kW h/Rs. and 0.137 kW h/Rs. per unit cost for single and double slope passive solar stills respectively based on exergoeconomic parameter. Khullar and Tyagi [18] reported that carbon dioxide (CO2 ) emissions reduced by approximately 2:2  103 kg of CO2 /household/year for concentrating solar water heating system by incorporating nanofluids. Otanicar and Golden [19] investigated the environmental and economic aspects of solar collectors by incorporating nanofluids. On the basis of enviroeconomic analysis, they found that solar collectors with nanofluids neutralizes 74 kg of CO2 over its life span of 15 years. Faizal et al. [20] performed the cost analysis of flat plate collector (FPC) using copper oxide (CuO), tin oxide (SiO2), titanium oxide (TiO2), and aluminium oxide (Al2O3) water based nanofluids. They found that the solar collector gives better thermal performance with CuO nanofluid than others (SiO2, TiO2, and Al2O3). The better performance with CuO water based nanofluid is credited to its higher density, thermal conductivity and lower specific heat. They conclude that nanofluid based each solar collector saves an average of 220 MJ of embodied energy and causes 170 kg less CO2 emissions. Sahota et al. [21] studied the enviroeconomic and exergoeconomic analysis of passive DSSS loaded with copper oxide (CuO), titanium oxide (TiO2), and aluminium oxide (Al2O3)- water based nanofluids. On the basis of energy and exergy, they found that energy payback time (EPBT) of the system becomes lower; and the amount of CO2 mitigated and environmental cost per annum becomes higher on incorporating nanofluids. In literature, most of the studies (performance and cost analysis) have been found on the flat plate collectors and heat exchangers; and very few on the solar still using nanofluids. None of the study is focused on the exergoeconomic and enviroeconomic analysis of active solar stills loaded with nanofluids. The research

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Table 1 Previous research work on solar still with water based nanofluids. References

Modification in passive/active solar still

Results

Kabeel et al. [29]

Passive single slope solar still providing vacuum, CuO and Al2O3 NPs

Kabeel et al. [4] Elango et al. [5]

Passive single slope solar still with Al2O3 NPs and external condenser Single basin single slope solar still with Al2O3, ZnO, and Fe2O3 NPs

Sahota and Tiwari [7]

Passive double slope solar still with Al2O3, TiO2, and CuO NPs

Omara et al. [8] Shashir et al. [9]

Corrugated wick solar still providing vacuum, CuO and Al2O3 NPs Passive solar still with graphite and CuO NPs; and with different cooling flow rates over the glass cover Solar still Solar still Active solar still operating with heat exchanger; and CuO and SiO2 NPs System (A): N-PVT-FPC-DSSS without heat exchanger and CuO, Al2O3, and TiO2 NPs System (B): N-PVT-FPC-DSSS with heat helically coiled exchanger and CuO, Al2O3, and TiO2 NPs

125.5% with CuO 133.64% with Al2O3 and vacuum 116% with Al2O3 and vacuum 29.95% with Al2O3 18.63% with Fe2O3 12.67%, with ZnO 45.23% with Al2O3 42.72% with TiO2 39.74% with CuO 285.10% with CuO 254.88% with Al2O3 47.80% with CuO 57.60% with graphite Recommend ZnO Recommend SiC 9.86% with CuO Enhancement in annual yield, energy matrices and CO2 mitigation with CuO NPs than Al2O3, and TiO2 NPs for both the systems

Saleha et al. [11] Chen et al. [12] Mahian et al. [13] Present study

question is to know about the economic feasibility of the incorporation of nanofluids in solar stills. The previous research work carried by the researchers on the solar still using nanofluids is summarized in Table 1. In the present paper, efforts have been made to investigate the complete cost analysis (energy matrices, exergoeconomic and enviroeconomic analysis) of two different hybrid solar stills viz. (a) N-PVT-FPC-DSSS operating without helically coiled heat exchanger (System A) and (b) N-PVT-FPC-DSSS operating with helically coiled heat exchanger (System B). The results have been compared with the conventional DSSS (System C) [21]. The annual analysis of these proposed systems has been studied for the optimized concentration of assisting Al2O3, TiO2, and CuO metallic NPs; and basin fluid (BF/NF) mass. 2. System description Systematic diagram of partially covered N photovoltaic thermal flat plate collector integrated double slope solar still (N-PVT-FPC-

DSSS) without operating heat exchanger (System A), with operating helically coiled heat exchanger (System B), and passive DSSS (System C) loaded with nanofluid is presented in Figs. 1–3 respectively. The main components of the hybrid system (A and B) are DSSS ðarea 2  1 m2 Þ, N-PVT-FPC, helically coiled heat exchange (copped) and mechanical water pump. The DSSS is made of fibre reinforced plastic kept in east-west direction with top cover of transparent glass at an inclination of 30°. Whereas, the partially covered (semitransparent) PVT-FPC with south facing is placed at an inclination angle of 45° [22]. The latitude ðuÞ of the systems location (New Delhi) is 28:610 . Inner surface (bottom and sides) of the DSSS is painted mat black to absorb the maximum solar radiation. In system (B), the coupled heat exchanger is properly dipped inside the basin water in order to utilize its entire transferred heat. The PV modules generates the electrical energy and supply it to the DC motor water pump which further circulates the basin water under the forced mode of operation; and thus overcomes the pres-

Fig. 1. Schematic view of active DSSS without heat exchanger (System (A)).

L. Sahota, G.N. Tiwari / Energy Conversion and Management 148 (2017) 413–430

417

Fig. 2. Schematic view of active DSSS with heat exchanger (System (B)).

Fig. 3. Systematic view of passive DSSS loaded with nanoparticles (System (C)).

sure drop in collectors and flow channels. The fluid passing through the pipe in the collector pipes gets heated after receiving the thermal energy from (i) the blackened surface of the collector, (ii) the thermal energy convected from the back surface of the PV module and (iii) solar radiation being transmitted through non packing area of module. The outlet of the PVT-FPC is coupled to the basin of the solar still as shown in Figs. 1 and 2. Therefore, the thermal energy of the N-PVT-FPC can be transferred to the DSSS either directly (System A) or indirectly via heat exchanger (System B). Coiled tubes are effective heat exchangers as compared to straight tube heat exchangers because of their excellent heat

transfer performance, compact size and the enhanced turbulence. Helically coiled heat exchangers (large heat transfer area per unit volume) are frequently used and mostly preferred over the straight tubes due to their excellent heat transfer performance, compact size and enhanced turbulence which intern enhances the heat transfer coefficient of the tube’s internal surface. Maximum portion of the incident solar radiation is absorbed by the basin water and the remaining fraction is absorbed by the blackened surface. Assisting metallic NPs directly absorbs the incident solar energy (electromagnetic radiation) and later converted to heat. Thermal properties of assisting copper oxide (CuO),

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Table 2 Thermal properties of metallic NPs used in proposed systems. Metallic NPs

Al2 O3

Density (qp )

Specific heat (Cp)

(kg/m3)

(J/kg-K)

(W/m-K)

3:89  103

880

40

Thermal conductivity (kp)

TiO2

4:23  10

3

697

11.8

CuO

6:31  103

550

17.6

where, Q_ uN is the rate of useful thermal energy gain from the series connected N- identical PVT water collectors expressed as follows:

Q_ uN ¼ Ac F 0 ½ðasÞN;eff Ic  U LN ðT f  T a Þ

ð5Þ

On solving Eqs. (1)–(4), one can get

titanium oxide (TiO2), and aluminium oxide (Al2O3) metallic NPs are given in Table 2. As, the plasmon resonance of NPs has high absorption modes in the spectral regions of ultraviolet and infrared; consequently, the toning between the spectrum of optical absorption (nanofluids) and solar radiation causes the absorption of direct solar radiation by the nanofluids. Further, nanofluids transferred the absorbed energy or heat via different mechanisms viz. Brownian motion, NP clustering, nature of heat transport across NPs, and liquid layering at an interface of liquid and NP. Stability of nanofluids is a main concern which depends on the characteristics of assisting NPs as well as basefluid. Also, the NPs often have a tendency of agglomeration due to Van der Waals forces of attraction which further leads to sedimentation. Owing to small dimensions and higher concentration of the assisting NPs, they spread more in the chosen basefluid (water) gives higher surface to volume ratio and absorb more solar radiation; and hence, raise the nanofluid temperature. Thus, the mutual contribution of the basin liner, external thermal energy transfer, and assisting NPs increases the temperature of the basin fluid (BF/NF). Ultimately, it enhances the evaporative heat transfer from fluid (BF/NF) surface inside the solar still cavity. Condensation of evaporated water vapors takes place with release of latent heat at inner surface of the glass cover; eventually, the potable water droplets drip into the measuring jars at lower ends of the glass covers as shown in Figs. 1–3.

dT f 1 þ a1 T f 1 ¼ f 1 ðtÞ dt

ð6Þ

The soultion of above eqution can be expressed as

Tf 1 ¼

f 1 ðtÞ ð1  ea1 Dt Þ þ T f 0 ea1 Dt a1

where,

f 1 ðtÞ ¼

ð7Þ




 Ab f½ðK 1E þ afb ÞISE ðtÞ þ ðK 1W þ awb ÞISW ðtÞ 2H

þ Ac F 0 ðasÞN;eff Ic ðtÞ þ T a ðH1 þ H2 þ H3 þ H4 þ H5 Þg


 Ab ½h1bf ;E ðE1 þ E2 Þ þ h1bf ;W ðE01 þ E02 Þ þ ðU ba Ab þ Ac F 0 U L;N Þ 2H

a1 ¼

" # PF 2 ðasÞm;eff F Rm 1  ð1  K k;A ÞN Am F Rm U L;m ; K k;A ¼ ðasÞN;eff ¼ ; _ f Cf N K k;A m " # F Rm U L;m 1  ð1  K K;A ÞN U L;N ¼ N K k;A Unknown terms in above equations are given in appendix (A) of [10]. 3.2. System (B): Operating with helically coiled heat exchanger

3. Mathematical formulation

Energy balances of the heat exchanger immersed in the fluid (BF/NF) of the solar still [10]:

Following assumptions given by Sahota et al. [21], an expression for the basin fluid (BF/NF) temperature for system (A), (B), and (C) has been derived as follows:

_ f Cf m

3.1. System (A): Without operating helically coiled heat exchanger Energy balances of different components of the system (A) [10]:


 A ag ISE AgE þ h1f ;E ðT f  T giE Þ b  hEW ðT giE  T giW ÞAgE 2

(b) West side

ð1Þ

Rest of the energy balance equations of the system (B) are same as given in Eqs. (1)–(4). Boundary conditions: T f ðx ¼ 0Þ ¼ T FoN and T f ðx ¼ LÞ ¼ T fi Solving Eq. (8) subjecting to the above boundary conditions, one can get the temperature of heat exchanger

where, U ¼

h

1 hbf

þ


 Ab  hEW ðT giE  T giW ÞAgW 2

      i1 r11 1 log rK221 þ rr11 K1 h 22 bf

ð2Þ

T FoN ¼

! ! ðAF R ðasÞÞ1 1  K Nk ðAF R U L Þ1 1  K Nk Ic ðtÞ þ T a þ K Nk T fi _ f Cf _ f Cf 1  Kk 1  Kk m m

(c) Basin liner

ab ðISE þ ISW ÞAb ¼ 2hb;f ðT b  T f ÞAb þ 2hba ðT b  T a ÞAb

ð10Þ ð3Þ

(d) Bain fluid mass



 dT f Ab Ab Mf C f ¼ af ðISE þ ISW Þ þ 2hb;f ðT b  T f Þ dt 2 2
 Ab  h1f ;W ðT f  h1f ;E ðT f  T giE Þ 2
 Ab þ Q_ uN  T giW Þ 2

ð9Þ

Following Dubey and Tiwari [23], the outlet water temperature at the end of the Nth PVT water collector is given by

ag ISW AgW þ h1f ;W ðT f  T giW Þ ¼ h1gW ðT goW  T a ÞAgW

ð8Þ



 2pr 11 UL 2pr 11 UL þ T FoN exp  T fi ¼ T f 1  exp  _ f Cf _ f Cf m m

(a) East side

¼ h1gE ðT goE  T a ÞAgE

dT f dx ¼ ð2pr 11 UÞðT HE  T f Þdx dx

Using Eqs. (9) and (10) in Eq. (5), one can get

Q_ uN ¼ D1 T f þ D2 Ic ðtÞ þ D3 T a

ð11Þ


   N z _ f C f ðK Nk  1Þ 1eNzz ; D2 ¼ ðAF R ðasÞÞ1 1 þ ðK k 1Þe where, D1 ¼ m z 1K k e 1K N e k    N  1K k ðK N 1Þez 1K N k k ; and D3 ¼ ðAF R U L Þ1 1 þ 1K N ez 1K 1K k

ð4Þ

k

k

On solving Eqs. (1)–(4) using the value of Q_ uN from Eq. (11), one can obtain

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dT f 2 þ a2 T f 2 ¼ f 2 ðtÞ dt

ð12Þ

The soultion of above eqution can be expressed as

Tf 2

f ðtÞ ¼ 2 ð1  ea2 Dt Þ þ T f 0 ea2 Dt a2

where, a2 ¼

  Ab 2H

ðH011 þ H0033 Þ






1 Mf C f

Similarly, the solution of above equation can be expressed as

Tf 3 ¼ ð13Þ



f 3 ðtÞ ð1  ea3 Dt Þ þ T f 0 ea3 Dt a3

where, f 3 ðtÞ ¼ ½C 22 þTMa CC33 þC44  and a3 ¼ f

Unknown terms in above equations are given in Appendix (B) of [12].

In this case, Q_ uN ¼ 0; therefore, by solving Eqs. (1)–(4), one can get

ð14Þ

Table 3 Numerical constants used in computation. Parameter

Numerical value

Parameter

Numerical value

ag ab abf ac ap

0.05 0.8 0.6 0.9 0.80 0.89 0.95 0.95

Am Ac Lp Kp Ki Li hi h0 Utc,p

0.605 m2 1.395 m2 0.002 m 64 (W/m-K) 0.166 (W/m-K) 0.1 m 5.7 (W/m2-K) 9.5 (W/m2-K) 5.58 (W/m2-K)

Utc,a Utp,a UL,m UL,c PF1 PF2 PFc

9.20 (W/m2-K) 4.74 (W/m2-K) 7.58 (W/m2-K) 4.52 (W/m2-K) 0.378 0.934 0.955 0.15

ebf r Kg KB Lg Lb b0 X

sg F’

5:67  108 ðW=m2 K4 Þ 0:780 ðW=mÞ °C 0:035 ðW=mÞ °C 0.004 0.005 m 0.0045/K 0.33 m 0.95 0.968

g0

C 11 þC 33 Mf C f

i


 Ab Ehourly;en ¼ ½hef ;E ðT f  T giE Þ þ hef ;W ðT f  T giW Þ 2

Ehourly;ex ¼

3.3. System (C): Convensional double slope solar still [21]

b 2g

h

f

Unknown terms in above equations are given in appendix of [21]. Hourly thermal energy ðEhourly;en Þ and exergy ðEhourly;ex Þ of the proposed systems can be obtained from the following equations:

 Ab f 2 ðtÞ ¼ ff½ðaf þ 2ab h1 ÞH þ K 01E ISE ðtÞ þ ½ðaf þ 2ab h1 ÞH 2H
 1 þ K 01W ISW ðtÞ þ D2 Ic ðtÞg þ þT a ðH011 þ H0044 Þg Mf C f

dT f 3 þ a3 T f 3 ¼ f 3 ðtÞ dt

ð15Þ

ð16Þ

 
 T f þ 273 hef ;E ðT f  T giE Þ  ðT a þ 273Þln T giE þ 273 

 T f þ 273 Ab þ hef ;W ðT f  T giW Þ  ðT a þ 273Þln 2 T giW þ 273 ð17Þ

Hourly productivity (yield) from the proposed systems can be obtained as

_ _ w ¼ q1g  3600 ¼ h1g ðT f  T g Þ  3600 M Lv Lv

ð18Þ

where, the latent heat of vaporization ðLv Þ can be expressed as [22],

Lv ¼ 3:1625  106 þ ½1  ð7:616  104  ðT v ÞÞ for T v > 70  C Lv ¼ 2:4935  106 ½1  ð9:4779  104  ðT v Þ þ 1:3132  107  ðT 2v Þ  4:7974  103  ðT 3v ÞÞ for T v < 70  C The hourly variation of basin fluid (BF/NF) temperature (Eqs. (7), (13), and (15)), thermal energy (Eq. (16)) and exergy (Eq. (17)); and productivity (Eq. (18)) of the proposed systems loaded with basefluid (water) and different nanofluids have been obtained using the heat transfer relations [10,21], correlations of thermophysical properties of vapors [22], basefluid [24] and nanofluid (Table 5).

Table 4 Numerical values of (a) double slope solar still, (b) flat plate collector, (c) PV module, and (d) helically coiled heat exchanger. (a) Double slope solar still Parameter

Numerical value

Area of the glass cover ðAgE andAgE Þ Basin area ðAb Þ Inclination of the glass cover ðhÞ

1:025 m  1:025 m 2 m1 m 30°

(b) Flat Plate Collectors (tube in plate type) Parameter Area of each collector Tube material Tube diameter Plate thickness Riser- outer diameter Riser thickness

Numerical value 2.00 m2 Copper tubes 0.0125 m 0.002 m 0.0127 m

Spacing between two risers Effective area of collector under PV module (c) PV Module (under standard test conditions) Area of single solar cell Size of PV module Number of solar cells (d) Helical heat exchanger (copper) Length of the heat exchanger Diameter of the coil tube

Parameter Thickness of insulation Weight of the collector Collector efficiency factor Angle of Collectors Thickness of top glass Motor used for water pumping

Numerical value 0.1 m 48 kg 0.968 450 0.004 m (Toughened) Dc shunt motor (18 V, 40 W and 2800 rpm)

Effective area of collector under glass

1.34 m2

0.007 m2 1:25 m  0:55 m 36

Fill factor Efficiency of module Max power rating Pmax

0.8 12% 40 W

0.937 m 0.0125 m

Diameter of the coil Number of turns

0.045 m 12

0:56  103 0.112 m 0.66 m2

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Table 5 Thermo-physical properties of Al2O3, TiO2, CuO-water based nanofluids. Quantity

Expression

Specific heat

   0:4167 up 2:272 T nf 0:3037 d C nf ¼ 0:8429 1 þ 50 1 þ 50p ð1 þ 100 Þ 15 < dp < 50nm; 0 < up < 4%; 20 < T nf < 50 °C (Al2O3, and CuO- water) [30]   D  Cp C nf ¼ Aðup ÞB ðT nf ÞC C p;bf C p;bf A ¼ 1:387; B ¼ 0:00425; C ¼ 0:001124; D ¼ 0:21159 dp ¼ 21nm; 0 < up < 8%; 15 < T nf < 65 °C (TiO2- water) [31]

Density Thermal conductivity

qnf ¼ up qp þ ð1  up Þqbf [32]

h    i kp knf ¼ kbf 1 þ ð1:0112Þup þ ð2:4375Þup dp 47  ð0:0248Þup 0:613 ðnmÞ

0 < up < 10%; 20 < T nf < 70 °C; 11 < dp < 150nm (Al2O3 -water) [33]   0:273  0:547  0:234  k T nf 100 knf ¼ kbf 1 þ ð0:135Þ kbfp ðup Þ0:467 20 dp ðnmÞ 0 < up < 10%; 20 < T nf < 70 °C; 11 < dp < 150nm (TiO2 -water) [34] 

 l 0:0235  0:2246   u2 u u 1 knf ¼ kbf 0:9843 þ ð0:398Þðup Þ0:467 lnf  ð3:951Þ T nfp þ ð34:034Þ T 3p þ 32:51 T 2p dp ðnmÞ bf

Viscosity

nf

nf

0 < up < 10%; 20 < T nf < 70 °C; 11 < dp < 150 nm (CuO -water) [33]

    2  2 u3 u u u lnf ¼ 0:4491 þ 28:837 þ 0:547up  0:163u2p þ ð23:653Þ T nfp þ ð0:0132Þu3p  ð2354:7Þ T 3p þ ð23:498Þ dpp  ð3:018Þ 2p T nf dp

nf

11 6 up 6 9; 13 6 dp 6 130 nm;20 6 T nf 6 90 °C (Al2O3 -water) [33]    0:038   dp 0:061 lnf ¼ lbf ð1 þ up Þ11:3 1 þ T70nf 1 þ 170 10 6 up 6 4; 20 6 dp 6 170nm;0 6 T 6 70 °C (TiO2 -water) [35]   247:8

Thermal expansion coefficient

lnf ¼ ð2:414  105 Þ  10 Tnf 140 10 6 up 6 10%; 11 6 dp 6 150 nm;20 6 T 6 70 °C (CuO -water) [33] bnf ¼ ð1  up Þbbf þ up bp [36,37]

Table 6 Embodied energy of different components of the hybrid solar still.

4. Energy matrices For any renewable technology, the evaluation of energy matrices is very important. The basic energy matrices of any renewable system are viz. energy payback time (EPBT), energy production factor (EPF), and life cycle conversion efficiency (LCCE). These energy matrices for the proposed systems have been discussed in detail as follows: (a) Energy payback time (EPBT): It is always be one of the criteria used for comparing the viability of renewable energy (RE) systems. It depends on the embodied energy and the annual energy output (productivity) obtained from the system. Consequently, an implementation of some considerations viz. (i) improvement in overall efficiency (ii) use of cost effective materials with low energy densities with longer life (iii) minimum annual maintenance can reduce the EPBT of theses RE systems. Mathematical expression of energy payback time can be expressed as follows:

Energy payback time ðEPBTÞen=ex ¼

Embodied energy=exergyðEin Þ years Annual energy=exergy outðEout;ann Þ

ð19Þ

(b) Energy production factor (EPF): It determines the overall performance of the RE system on the basis of first law of thermodynamics. Mathematical expression of energy production factor can be expressed as follows:

Energy production factor ðEPFÞen=ex  1 Embodied energy=exergy inðEin Þ ¼ Annual energy=exergy outðEout;ann Þ

ð20Þ

Name of component FRP body of DSSS GI angle iron Glass cover FPC ðN ¼ 4Þ PV (glass –glass) Copper heat exchanger NPs (Average EE) ? On incorporating in system (A) On incorporating in system (B) Total EE of system (A) with NPs Total EE of system (B) with NPs Total EE of system (A) without NPs Total EE of system (B) without NPs

Embodied energy, EE (kW h)

Al2O3 11.84 8.507 4553.55 4575.84 4541.51 4567.34

755.61 416.40 180.50 2209.92 980 25.83 TiO2 10.01 7.56 4551.52 4574.9

CuO 25.58 17.82 4567.09 4585.16

(c) Life cycle conversion efficiency (LCCE): The LCCE is the net energy productivity of the RE system with respect to the input (solar energy) over the whole life span of the system (T years). The numerical value of LCCE is always less than unity; however, from energy point of view, the RE technology is the best technology if the value of LCCE approaches unity. Mathematical expression of life cycle conversion efficiency can be expressed as follows:

Life cycle conversion efficiency ðLCCEÞen=ex ¼

ðEen=ex;ann  nÞ  Ein Esol;ann  n

ð21Þ

where, Een=ex;ann is the annual solar energy/exergy output, Esol;ann is the annual solar energy retrieved by the system, and n is life span of the system. On the basis of energy and exergy, these energy matrices for the proposed systems (A, B and C) loaded with basefluid and water based nanofluids have been estimated.

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Cost

FRP body @ 340/kg Glass cover (1.15 m2) Iron stand Inlet/outlet nozzle Iron clamp Gaskets Silicon gel PVT-FPC @ 8500 each Motor and pump Helically coiled heat exchanger (HE) Fabrication cost and other changes 100 gms Al2O3 nanoparticles ð< 50 nmÞ 100 gms TiO2 nanoparticles ð10  25 nmÞ 100 gms CuO nanoparticles ð< 20  55 nmÞ Total cost of System A excluding NPs Total cost of System B excluding NPs Average salvage value of the system (A) after 30 years without NPs, if inflation remains @ 4% Average salvage value of the system (A) after 50 years without NPs, if inflation remains @ 4% Average salvage value of the system (A) after 30 years with NPs, if inflation remains @ 4%

Average salvage value of the system (A) after 50 years with NPs, if inflation remains @ 4%

Average salvage value of the system (B) after 30 years without NPs, if inflation remains @ 4% Average salvage value of the system (B) after 50 years without NPs, if inflation remains @ 4% Average salvage value of the system (B) after 30 years with NPs, if inflation remains @ 4%

Average salvage value of the system (B) after 50 years with NPs, if inflation remains @ 4%

*

(Rs.)

($)*

10,200 800 1000 200 250 200 200 34,000 1200 466.25 6000 4500 7200 7425 54,050 54,516.25 17,206 37,701 Al2O3 TiO2 CuO Al2O3 TiO2 CuO 17,357 38,032 Al2O3 TiO2 CuO Al2O3 TiO2 CuO

150.37 11.79 14.74 2.94 3.68 2.94 2.94 501.25 17.69 6.87 88.45 66.34 106.92 109.46 796.84 803.72 253.66 555.81 290.66 303.68 385.46 636.87 665.39 844.58 255.88 560.69 280.22 291.43 345.51 614.02 638.72 757.03

19,716 20,599 26,146 43,199 45,134 57,288

19,008 19,768 23,436 41,649 43,325 51,350

1 US $ = 67.83 Rs. on 25/12/2016.

Embodied energy of different components of any RE system plays a vital role to make the system cost-effective. For the estimation of embodied energy of different components, the information about their energy densities is required. The embodied energy of different components (heat exchanger, NPs, photovoltaic module, flat plate collector, glass cover, galvanized iron angles, and fiber reinforced plastic body) of the hybrid system is presented in Table 6. 5. Enviroeconomic (environmental cost) and exergoeconomic analysis Enviroeconomic analysis is based on the amount of carbon dioxide ðCO2 Þ mitigation by the RE system and encourage to use the RE technology as much as possible. Considering transmission (20%) and distribution losses (40%), the amount of CO2 emitted per kW h comes out to be 2.0 kg [25]. Mathematical expression of the environmental cost (carbon credits) and the amount of CO2 mitigated per annum is given as follows [26]:

Carbon credits earned ðZ CO2 Þ ¼ uCO2  zCO2 $

ð22Þ

Amount of CO2 mitigated per annum ðuCO2 Þ on the basis of energy ¼

ðwCO2 =0:38Þ  Een;ann 3

10

wCO2  Eex;ann 103

Uniform annual cost ðUACÞ ¼ ðNPV  CRFÞ þ ðMS  CRFÞ  S  SFF ð25Þ

ð23Þ n

Amount of CO2 mitigated per annum ðuCO2 Þ on the basis of exergy ¼

where, wCO2 is the average CO2 equivalent intensity for electricity generation from coal (2.04 kg CO2 /kW h); and the price of one tone of CO2 ðzCO2 Þ is equal to $14:5 [27,28]. Moreover, the factor 0.38 is used to covert the generated electrical energy of the photovoltaic thermal flat plate collector into equivalent thermal energy; hence, this factor is involved only for the system (A) and (B). On the basis of energy and exergy, environmental cost and the amount of CO2 mitigated per annum for the proposed systems by incorporating nanofluids have been evaluated and presented in Table 9. On the other hand, exergoeconomic analysis is an exergy based cost analysis method of the RE system; and it provide option for the designers to find an alternative techniques for the improvement of the system performance. In the present cost analysis, the replacement period of helically coiled heat exchanger, NPs, and PV module has been chosen as 10, 20, and 25 years respectively. The cost and salvage value of different components of proposed systems are given in Table 7. Mathematical expressions of exergoeconomic parameter ðRex Þ, uniform annual cost (UAC), net present value (NPV), shrinking fund factor (SFF), and capital recovery factor (CRF) is expressed as follows:

ð24Þ

Capital recovery factor ðCRFÞ ¼

Shrinking fund factor ðSFFÞ ¼

iði þ 1Þ n ði þ 1Þ  1

i n ði þ 1Þ  1

ð26Þ

ð27Þ

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Table 8 Annual yield, overall thermal energy and thermal exergy obtained from the system (A), (B), and (C) with basefluid and nanofluids. Outputs System (A) Total annual yield (kg) Overall thermal energy (kW h) Overall thermal exergy (kW h) System (B) Total annual yield (kg) Total thermal energy (kW h) Total thermal exergy (kW h) System (C) Total annual yield (kg) Total thermal energy (kW h) Total thermal exergy (kW h)

Water

Al2O3-water

TiO2-water

CuO-water

3663.23 2391.22 412.77

3825.31 2673.7 537.14

3743.93 2526.99 506.13

3961.24 2785.78 592.07

2735.01 1711.11 287.65

3084.26 2058.08 388.93

2863.33 1866.45 355.06

3250.99 2291.79 439.79

1241.89 1101.64 82.29

1483.65 1396.51 113.25

1370.86 1314.93 103.32

1307.21 1244.43 92.164

Table 9 Enviroeconomic analysis of the system (A) and (B) on the basis of thermal energy and exergy. Basefluid/nanofluid

System (A) Thermal energy

Thermal exergy

Energy production cost (Rs.)

($)*

Baefluid Water-Al2O3 Water-TiO2 Water-CuO

11956.1 13368.5 12634.9 13928.9

176.26 197.08 186.27 205.35

System (B) Baefluid Water-Al2O3 Water-TiO2 Water-CuO

8555.55 10290.4 9332.25 22925.8

126.13 151.70 137.58 337.98

CO2 mitigated (tones)

Environmental cost (carbon credits)

Exergy production cost

(Rs.)

($)*

(Rs.)

($)*

12.83 14.35 13.56 14.95

12625.7 14117.2 13342.6 14709

186.13 208.12 196.71 216.85

2063.85 2685.7 2530.7 2960.35

33.37 39.59 37.30 43.64

9.19 11.05 10.02 24.61

9034.71 10866.7 9854.91 24209.8

133.19 160.20 145.28 356.91

1438.15 1944.65 1775.3 2198.95

21.20 28.66 26.17 32.41

CO2 mitigated (tones)

Environmental cost (carbon credits) (Rs.)

($)*

2.21 2.88 2.71 3.17

2179.44 2836.12 2672.43 3126.15

32.13 41.81 39.39 46.08

1.54 2.08 1.91 2.36

1518.7 2053.66 1874.73 2322.1

22.38 30.27 27.63 34.23

Average unit electricity cost is taken Rs. 5/ kW h (7–8 US cents per kW h). * 1 US $ = 67.83 Rs. on 25/12/2016.

Net present value ðNPVÞ ¼ P þ R1  ðCRFÞn þ ½Rn1  ðSFFÞn1 þ Rn2  ðSFFÞn2 þ ... Rnk  ðSFFÞnk   S  ðSFFÞn

ð28Þ

Eex;ann UAC

ð29Þ

Exergoeconomic parameterðRex Þ ¼

where, P -present cost, S - salvage value, MS - maintenance cost, n - life span of the system, and Rnk - replacement factor. The estimated values of these expressions are presented in Table 10. The cash flow diagram of the system is shown below:

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Table 10 Net present value, capital recovery factor, shrinking fund factor, uniform annual cost, and unit cost obtained for the system (A) and system (B) with basefluid and water-based nanofluids. System (A)

Basefluid (water)

Years (n)

Interest rate, i (%)

NPV (Rs.)

CRF

SFF

UnaCost (Rs.)

Rex (kW h/Rs.)

30

4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10

58,494 56,101 55,525 59,080 56,150 55,542 1,77,160 1,16,100 1,01,750 1,92,140 1,17,230 1,02,090 1,82,030 1,18,390 1,03,440 1,97,650 1,19,580 1,03,800 2,12,620 1,32,830 1,14,070 2,32,210 1,34,310 1,14,510

0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009

0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086

3365.1 4956.2 5857.7 2736.1 4564.9 5571 10251 10321 10804 8949 9590.9 10307 10532 10526 10984 92052 97826 10479 12302 11807 12111 10814 10987 11559

0.123 0.083 0.070 0.151 0.090 0.074 0.0524 0.0520 0.0497 0.0600 0.0560 0.0521 0.0481 0.0480 0.0461 0.0550 0.0517 0.0483 0.0481 0.0501 0.0489 0.0547 0.0539 0.0512

4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10 4 8 10

59,195 56,661 56,065 59,768 56,702 56,077 1,72,580 1,12,990 99,002 1,87,160 1,14,090 99,330 1,76,780 1,14,970 1,00,460 1,91,900 1,16,110 1,00,800 1,97,000 1,24,510 1,07,480 2,14,750 1,25,850 1,07,880

0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009 0.0578 0.0888 0.1061 0.0466 0.0817 0.1009

0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086 0.0178 0.0088 0.0061 0.0066 0.0017 0.00086

3431.8 5046.2 5963.1 2789.1 4647.1 5670.9 9986.2 10045 10513 8717.2 9334.1 10028 10229 10221 10667 8937.7 9499.1 10177 11399 11069 11412 10001 10295 10891

0.0838 0.0576 0.0482 0.1031 0.0619 0.0507 0.0389 0.0387 0.0370 0.0446 0.0417 0.0388 0.0347 0.0347 0.0333 0.0397 0.0374 0.0349 0.0386 0.0397 0.0385 0.0440 0.0427 0.0404

50

Al2O3-water

30

50

TiO2-water

30

50

CuO-water

30

50

System (B) Basefluid (water)

30

50

Al2O3-water

30

50

TiO2-water

30

50

CuO-water

30

50

6. Methods The analysis has been carried out for the climatic conditions of New Delhi (India) and the data of different weather conditions (a, b, c, and d-type) [10] of all the months has been obtained from IMD, Pune, India. The hourly solar intensity for 300 inclination (northern hemisphere) of the east and west side of the glass cover; and 450 inclination of the flat plate collector has been evaluated using Liu and Jordan formulae. Numerical constants and specification of different components of the proposed systems are given in Tables 2–4. Following methodology has been executed in the MATLAB 2013a for the cost analysis of the proposed hybrid systems by incorporating Al2O3, TiO2, and CuO- water based nanofluids for N ¼ 4 number of collectors, 0.03 kg/s mass flow rate, optimized concentration of metallic NPs ðdp ¼ 20 nmÞ and basin fluid (BF/NF) mass:

i) The initial input and output values have been evaluated using the thermo-physical properties of vapors [22], basefluid [24] and nanofluids (Table 5) on considering different initial temperatures of different portions of the proposed hybrid system equivalent to the ambient temperature. ii) For the subsequent computation, these estimated initial values are used to evaluate the basin fluid (BF/NF) temperature (Eqs. (1) and (2), and Eq. (5)) of DSSS, fluid (BF/NF) temperature in heat exchanger (HE) (Eq. (3)) and collector’s outlet fluid (BF/NF) temperature (Eq. (4)). Also, the heat transfer coefficients (HTC) in different sections of the proposed systems have been evaluated using heat transfer correlations [10,21]. iii) Concentration of the assisting NPs and basis fluid (BF/NF) mass has been optimized for each month. iv) Monthly thermal energy ðEth;en Þ (Eq. (6)), exergy ðEth;ex Þ (Eq. _ w Þ (Eq. (8)) of the proposed systems (7)), and productivity ðM

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have been estimated corresponding to the optimized parameters. After estimating annual thermal energy, exergy and productivity (yield), the energy matrices (EPBT, EPF and LCCE) and exergoeconomic parameter have been evaluated. 6.1. Optimization of concentration of metallic nanoparticles and basin fluid mass

process slowed down hence peak value is shifted to lower basin fluid (BF/NF) mass for reduced input radiation. Hence, these optimized parameters depend on the climatic conditions or ultimately on the temperature of the basin fluid (BF/NF); consequently, these are different for all the proposed systems for each month. 7. Results and discussion

Concentration of assisting metallic NPs and basin fluid (BF/NF) mass has been optimized for a typical day of each month for the annual analysis. In order to perform the optimization of theses parameters, the temperature of basin nanofluid of the proposed systems is evaluated at particular concentration of NPs for different basin nanofluid mass for 24 h. The same has been repeated for the proposed systems without assisting NPs. The maximum temperature difference (occurs during noon hours) between basin nanofluid and basefluid has been plotted with the basin fluid (BF/ NF) mass. The peak value of this maximum temperature difference ðDTÞmax occurs at a typical basin fluid (BF/NF) mass. Moreover, the value of this maximum temperature difference ðDTÞmax increases with increase in concentration of assisting metallic NPs up to a typical value and beyond this value it again start decreasing with further increase in concentration of metallic NPs. Decrease in the value of ðDTÞmax beyond a typical value of the concentration of metallic NPs is due to the fact that, as the concentration increases the mass of nanofluid also increases and more thermal energy is utilized in raising the temperature of metallic NPs (sensible energy of nanoparticles), therefore amount of thermal energy transferred from these metallic NPs to the fluid decreases. This optimal value of the concentration of assisting metallic NPs which gives higher value of the maximum temperature difference ðDTÞmax corresponding to a particular basin fluid (BF/NF) depth gives the optimized values. Sahota and Tiwari [7] performed the optimization of concentration of assisting metallic NPs and basin fluid (BF/NF) for a typical day of the month March for New Delhi climatic conditions. Climatic conditions i.e. solar intensity and ambient temperature plays important role for the optimization of these parameters. The optimum value or peak value of the maximum temperature difference ðDTÞmax shifts towards the lower end of the basin fluid (BF/NF) depth for the month having lower solar intensity and ambient temperature. This happens due to the fact that some part of the input solar radiation absorbed by the basin liner raises the fluid (BF/NF) temperature in DSSS utilizing sensible heat and rest is responsible for the evaporation process. For higher basin fluid (BF/NF) mass more heat is utilized in sensible heat and evaporation

The results obtained during the exergoeconomic and enviroeconomic analysis of the proposed systems loaded with water based nanofluids have been discussed in detail as follows: 7.1. Results and explanations In the present study, optimization of concentration of assisting metallic NPs and basin fluid (BF/NF) mass was essential to perform the annual cost analysis; hence, these parameters have been optimized for each month as discussed in Section 6.1. For the hybrid system (A) and (B), the variation of optimized concentration of NPs and basin fluid (BF/NF) mass with number of months is presented in Fig. 4. The optimized concentration of NPs (up) is found to be in the range of 0.082% < CuO < 0.161%; 0.063% < Al2O3 < 0.124%; and 0.041% < TiO2 < 0.108% for the hybrid system (A). Whereas, it is found to be in the range of 0.059% < CuO < 0.131%; 0.043% < Al2O3 < 0.102%; and 0.037% < TiO2 < 0.093% for the hybrid system (B). On the other hand, the optimized basin fluid (BF/NF) mass is obtained in the range of 35 kg < Mw < 60 kg and 30 kg < Mw < 50 kg for the System (A) and system (B) respectively. These optimized parameters has been found to be higher for the hybrid system (B) than (A); and also found to be higher for the month of May due to availability of maximum solar radiation in this month. For other months having lower solar intensity, these optimized parameters found to be lower for both the hybrid systems. It is credited to the fact that some part of the input solar radiation absorbed by the basin liner raises the basin fluid (BF/NF) temperature utilizing sensible heat and rest is responsible for the evaporation process. For higher mass more heat is utilized in sensible heat and evaporation process slowed down; hence peak value is shifted to lower values of the optimized parameters for reduced input radiation [8]. Moreover, for both the systems, the optimized concentration is higher for copper oxide (CuO) metallic NPs as compared to the aluminium oxide (Al2O3) and titanium oxide (TiO2) metallic NPs. This trend is due to higher values of natural

Fig. 4. Variation of optimized concentration of nanoparticles and basin fluid (BF/NF) mass with number of months.

L. Sahota, G.N. Tiwari / Energy Conversion and Management 148 (2017) 413–430

425

Fig. 5. Monthly variation of overall thermal energy of (i) system (A) and (ii) system (B) using basefluid and nanofluids.

Fig. 6. Monthly variation of overall thermal exergy of (i) system (A) and (ii) system (B) using basefluid and nanofluids.

convective HTCs found in flat plate collector (FPC) and helically coiled heat exchanger section (lower than FPC) for CuO- water based nanofluid [10]. Monthly variation of overall thermal energy and exergy for both the hybrid systems is presented in Fig. 5 and Fig. 6 respectively; and the variation is found to be higher for the month of May for both the hybrid systems. Moreover, system (A) gives higher values overall thermal energy and exergy than system (B) using CuO- water based nanofluid; and found higher for the CuO-water based nanofluid. The better performance (overall thermal energy/exergy) of system (A) than (B) with CuO-water based nanofluids over the others is credited to the fact that higher volume fraction of NPs and mass flow rate reduces the entropy generation which intern improves the natural convective HTC (Reynolds number) in FPC section; hence raises the fluid (BF/NF) temperature. On the other hand, better performance of the hybrid system (A) is due to direct feeding of external thermal energy from the PVT-FPC (mutually receives the thermal energy from the blackened plate and assisting NPs). Also, NPs have been openly exposed to the solar radiation; therefore, they directly absorbs more solar radia-

tion in sunshine hours; resulting higher fluid (BF/NF) temperature in comparison to system (B). In case of hybrid system (B), external thermal energy from PVT-FPC is transferred via HE; hence, found low basin fluid (BF/NF) temperature than system (A). Apart from this, the rise in temperature of nanofluid is due to its better thermo-physical and optical properties. Higher concentration of suspended NPs in the basefluid provides the higher surface to volume ratio which intern absorbs the maximum solar radiation (enhances thermal conductivity) and eventually improves the heat transfer efficiency. Brownian motion of metallic NPs, liquid layering at liquid-particle interface and effect of NPs clustering contributes to enhance the thermal conductivity. Overall thermal energy and exergy of the hybrid system (A) and (B) is found to be (CuO 2785.78 kW h; Al2O3 2673.7 kW h; TiO2 2526.99) and (CuO 592.07 kW h; Al2O3 537.14 kW h; TiO2 506.13) respectively which are found to be significantly higher as compared to both the systems loaded with water (system (A) 2391.22 kW h; and system (B) 412.77 kW h) (Table 8). On comparing with system (C), the estimated value of overall thermal energy

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Fig. 7. Productivity (yield) of the system (A) obtained in (i) different months and (ii) different weather conditions (New Delhi climate) using basefluid and nanofluids.

Fig. 8. Productivity (yield) of the system (B) obtained in (i) different months and (ii) different weather conditions (New Delhi climate) using basefluid and nanofluids.

and exergy is found to be higher for the system (A) and lower for system (B). From Table 8, it is clear that the overall annual thermal energy of the hybrid systems is higher for the CuO- water based nanofluid. Whereas, these are found to be higher for Al2O3- water based nanofluid for the system (C). It happens due to better thermo-physical characteristics of CuO- NPs in PVT-FPC section in hybrid systems as explained earlier. Fig. 7(i) and (ii) respectively depicts the monthly variation of productivity (yield) and variation with different weather conditions (a, b, c, and d-type) for the hybrid system (A). Same variations have been also presented for the hybrid system (B) in Fig. 8. It has been observed that the hybrid system (A) gives better productivity than hybrid system (B) for the month of May and c-type weather conditions for CuO-water based nanofluid. Higher productivity for c-type weather conditions is due to higher number of sunshine days occurring in a year for this weather condition. Better productivity for the month of May is due to availability of higher solar radiation which contributed to higher basin fluid (BF/NF) temperature as explained earlier. Productivity obtained from the hybrid system (A) and (B) is found to be (CuO 3961.24 kg; Al2O3

3825.31 kg; TiO2 3743.93 kg) and (CuO 3250.99 kg; Al2O3 3084.26 kg; TiO2 2863.33 kg) respectively; it is significantly higher as compared to the systems loaded with water (system (A) 3663.33 kg; and system (B) 2735.01 kg) (Table 8). The higher productivity of the system (A) than (B) is due to direct transfer of external thermal energy from the PVT-FPC to the DSSS basin. Moreover, CuO- water based nanofluid provides higher productivity for the hybrid systems; whereas Al2O3 water based nanofluid gives higher productivity for system (C). The comparison of the obtained results with previous studies by incorporating nanofluids is given in Table 1. From literature, the PVT-FPC-DSSS loaded with basefluid (water) gives 5959.83 kg yield; 5386.88 kW h overall energy; and 1005.43 overall exergy annually for 0.14 m basin water depth, 11 number of collectors, and 0.03 kg/s mass flow rate. On the other hand, for conventional DSSS, it is found to be 1555.79 kg yield; 1037.19 kW h overall energy; and 89.24 kW h overall energy [17,38]. Further, the variation of energy payback time (EPBT) of the proposed systems with the basin fluids (basefluid and different water based nanofluids) is shown in Fig. 9. The EPBT for the system (B) is

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Fig. 9. Variation of EPBT with basefluid and (Al2O3, TiO2, and CuO- water based) nanofluids for the system (A), (B), and (C) on the basis of (i) overall thermal energy and (ii) overall thermal exergy.

Fig. 10. Variation of EPF with life span of the systems (A), (B), and (C) on the basis of (i) overall thermal energy and (ii) overall thermal exergy.

found to be higher than system (A) on the basis of both thermal energy and exergy. Also, it has been observed that system (A) and (B) loaded with CuO-water based nanofluid gives lower value of EPBT. On the other hand, EPBT is found to be higher for system (C) loaded with water (energy basis 1.24 year; and exergy basis 16.67 year) and lower for Al2O3- water based nanofluid (energy basis 0.98 year; and exergy basis 12.11 year). The lowest values of EPBT are found to be 2.01 year for system (B) and 1.64 year for system (A) loaded with CuO-water based nanofluid on the basis of energy (Fig. 9(i)). Whereas, on the basis of exergy, these are found to be 10.42 year and 7.71 year respectively, for system (B) and system (A) loaded with CuO-water based nanofluid (Fig. 9(ii)). Variation of energy production factor (EPF) with system’s life time (maximum 50 years) on the basis of thermal energy and exergy is shown in Fig. 10(i) and (ii) respectively. It has been observed that EPF increases with increase in life span of the system for both basefluid and nanofluid. It is found to be higher for the system (C) and lower for system (B) on the basis of thermal energy. For the hybrid system (A) and (B), EPF is found to be higher using CuO-water based nanofluid on the basis of thermal energy; and found higher with CuO metallic NPs. Whereas, for system (C), EPF is found to be higher with Al2O3 -water based nanofluid and lower with the system loaded with basefluid (water) on the basis

of thermal energy. The estimated maximum values (at 50 years life span) of EPF for the system (A), (B), and (C) has been obtained as (CuO 30.5 year; Al2O3 29.3 year; TiO2 27.5 year; and water 26.3), (CuO 24.9 year; Al2O3 22.5 year; TiO2 20.4 year; and water 18.7 year), and (CuO 45.3 year; Al2O3 50.8 kg; TiO2 47.9 year; and water 40.1 year) respectively on the basis of energy. Whereas, these are found to be (CuO 6.5 year; Al2O3 5.9 year; TiO2 6.5 year; and water 4.5), (CuO 4.8 year; Al2O3 4.2 year; TiO2 3.8 year; and water 3.2 year), and (CuO 3.3 year; Al2O3 4.1 year; TiO2 3.7 year; and water 2.9 year) respectively on the basis of thermal exergy. Variations of life cycle conversion efficiency (LCCE) of the proposed systems with life span of the systems (maximum 50 years) on the basis of thermal energy and exergy is presented in Figs. 11 and 12 respectively. From Fig. 11 (i-iv), it has been observed that LCCE for system (A) is found to be higher than system (B) and (C) loaded with basefluid and nanofluid; moreover, it is clear that LCCE improved significantly by incorporating nanofluids. Similar variation in LCCE has been observed for all the proposed systems by incorporating basefluid and nanofluids on the basis of thermal exergy as shown in Fig. 12(i-iv). On the basis of thermal exergy, the maximum LCCE (at 50 years life span) for system (A) and (B) is obtained as 14.8% and 10.8% respectively for CuO- water based nanofluid (highest with CuO NPs); whereas, it is found to be 2.5%

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Fig. 11. Variation of life cycle conversion efficiency with life span of the proposed systems (A, B, and C) for (i) basefluid (water), (ii) Al2O3-water based nanofluid, (iii) TiO2water based nanofluid, and (iv) CuO-water based nanofluid on the basis of overall thermal energy.

for system (C) by incorporating Al2O3-water based nanofluid (highest with Al2O3 NPs). It is found that all the energy matrices has been improved significantly by replacing conventional basefluid (water) with the nanofluids. Also, the better effect is shown by the CuO- water based nanofluid for the hybrid systems 9A and B); whereas, Al2O3 is found to be more effective in conventional DSSS as discussed earlier. From literature, for 0.14 m basin water depth, 11 number of collectors, and 0.03 kg/s mass flow rate, the energy matrices (EPBT 1.91; EPF 0.52, and LCCE 0.211) have been estimated for PVT-FPC-DSSS; and for conventional DSSS these are found to be 1.43 (EPBT), 0.70 (EPF), and 0.28 (LCCE) respectively. Whereas, on the basis of exergy, these energy matrices are (EPBT 10.22; EPF 0.097, and LCCE 0.035) for PVT-FPC-DSSS; and for conventional DSSS these are found to be 17.85 (EPBT), 0.06 (EPF), and 0.018 (LCCE) respectively. From the present study, it is very obvious that for the same set of configuration and numerical parameters of these systems loaded with water; the studied systems (A and B) with nanofluids will give higher values of productivity and energy matrices [17,38]. The performance and exergetic analysis DSSS coupled with two number of PVT collectors is carried by the Tiwari et al. [14]. In the further analysis, the amount of CO2 mitigated per annum, energy production cost and the environmental cost has been estimated for the hybrid system (A) and (B) on the basis of thermal energy and exergy (Table 9). Amount of CO2 mitigated per annum and carbon credits earned is found to be higher for the hybrid sys-

tem (B) than system (A). Moreover, it has been observed that these estimated parameters gives higher values for the proposed systems loaded with CuO-water based nanofluid as compared to other studied nanofluids. On the basis of thermal energy and exergy, the amount of CO2 mitigated per annum is found to be 14.95 tones and 3.17 tones respectively for the hybrid system (A); whereas, it is found to be 24.61 tones and 2.36 tones respectively for the hybrid system (B) loaded with CuO-water based nanofluid. Also, the environmental cost (carbon credits) for the hybrid system (A) loaded with CuO-water based nanofluid is obtained as 216.85 $ and 46.08 $ respectively on the basis of thermal energy and exergy; whereas, it is found to be 356.91 $ and 34.23 $ for the hybrid system (B) (Table 9). The amount of CO2 mitigated per annum and carbon credits earned are estimated significantly higher for the hybrid system (A) and (B) than the conventional system (C). In conventional system (C), these estimated parameters were found to be higher for Al2O3- water based nanofluid on the basis of thermal energy and exergy [6]. In the exeroeconomic analysis, the net present value (NPV), uniform annual cost (UAC), shrinking fund factor (SFF), capital recovery factor (CRF), and exergoeconomic parameter (Rex) has been evaluated at different interest rates (4%, 8%, and 10%) for the 30 year and 50 year life span of the proposed hybrid systems loaded with basefluid and nanofluids (Table 10). For both the hybrid systems, NPV increases with increase in interest rate for fixed life span of the system; also, it increases with increase in life

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Fig. 12. Variation of life cycle conversion efficiency with life span of the proposed systems (A, B, and C) for (i) basefluid (water), (ii) Al2O3-water based nanofluid, (iii) TiO2water based nanofluid, and (iv) CuO-water based nanofluid on the basis of overall thermal exergy.

span of the system at any fixed interest rate. Both the hybrid systems loaded with CuO-water based nanofluid gives higher value of NPV (Table 10). The UAC decreases with increase in life span of the system at fixed interest rate but increases with increase in interest rate at fixed life span of the system. The UAC is found to be higher for the hybrid system (A) than the system (B); moreover, it is higher for both the hybrid systems loaded with CuO-water based nanofluid than the other studied nanofluids. Significant enhancement in the NPV and UAC has been obtained for both the systems loaded with nanofuids as compared to the basefluid (water) loaded systems. Thee exergoeconomic parameter (Rex) for the proposed systems has been evaluated for 30 year and 50 year life span of the system and different interest rates. It has been observed that Rex decreases with increase in interest rate for given life span of the system; and it also decreases with increase in life span of the system. It happens due to higher value of UAC with increase in in interest rate and life span of the system. The Rex is found to be higher for the hybrid system (B) than the system (A); and the significant drop in exergoeconomic parameter has been observed by incorporating nanofluids in the hybrid system. It is credited to the higher values of UAC of the system loaded with water based nanofluids. For 50 years life span and 4% interest rate, the estimated value of Rex of the hybrid system (A) and (B) loaded with basefluid (water) is 0.151 kW h/Rs. and 0.103 kW h/Rs. respectively. On the other hand, for the system (A) and (B) loaded with nanofluids, this parameter is found to be (CuO 0.0547 kW h/Rs.;

Al2O3 0.060 kW h/Rs.; TiO2 0.055 kW h/Rs.) and (CuO 0.041 kW h/ Rs.; Al2O3 0.045 kW h/Rs.; TiO2 0.039 kW h/Rs.) respectively. Tiwari et al. [14] reported the environmental cost as 6.29 $ per annum for PVT-FPC-DSSS loaded with basefluid (water) for two number of collectors. Moreover, they estimated exergoeconomic parameter as 0.0031 kW h/Rs. for 30 year life time of the system and 2% interest rate. 7.2. Discussion Although, the hybrid system (A) gives better performance on the basis of exergoeconomic and enviroeconomic analysis but it is not feasible for the case of nanofluids for the use of real application due to the problem of sedimentation, dispersion, clustering, improper circulation, re-collection of metallic NPs (i.e. complex maintenance). Consequently, the hybrid system (B) will be preferred for the implementation of nanofluids for their proper implication and circulation via the helically coiled heat exchanger. Moreover, CuO-water based nanofluid would be recommended in hybrid systems whereas Al2O3-water based nanofluid is recommended for the conventional system (C). The cost effectiveness of these systems can be achieved by lowering the price of assisting metallic NPs which is possible with advances in nano-technology in future. There is a further scope of improvement in the performance of these recommended systems by incorporating hybrid nanofluids and by testing other fluids (higher boiling temperature).

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Also, the effect of metallic NP’s shape and size can be investigated because it effectively alters the thermo-physical and optical properties. 8. Conclusions Following conclusions have been withdrawn from the annual analysis of the proposed systems loaded with water based nanofluids corresponding to the optimized parameters: i) Hybrid system (A) gives better annual performance (overall thermal energy and exergy; and productivity) than the system (B) and system (C) loaded with studied water based nanofluids. ii) CuO-water based gives better results (annual performance; and exergoeconomic and enviroeconomic) for the system (A) and system (B); whereas, Al2O3- water based nanofluid gives better results for the system (C). iii) Energy matrices (EPBT, EPF, and LCCE) has been improved significantly by incorporating water based nanofluids in the proposed systems. The same trend and variation has been observed as discussed in point (i) and (ii). iv) On the basis of overall thermal energy and exergy, both the hybrid systems give higher value of the amount of carbon dioxide (CO2) mitigation and environmental cost per annum by incorporating water based nanofluids (higher with copper oxide metallic NPs). System (C) gives higher values of these parameters for aluminium oxide (Al2O3)-water based nanofluid as mentioned above. v) The exergoeconomic parameter has been dropped significantly for the proposed systems loaded with water based nanofluids.

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