Energy Conversion and Management 51 (2010) 1610–1615

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Energy Conversion and Management

journal homepage: www.elsevier .com/locate /enconman

Optimization of solar adsorption refrigeration system using experimentaland statistical techniques

Nidal H. Abu Hamdeh *, Mu’taz A. Al-Muhtaseb *

Mechanical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 961060, Amman 11196, Jordan

a r t i c l e i n f o

Article history:Available online 8 February 2010

Keywords:SolarCoolingAdsorptionCOPRefrigerator

0196-8904/$ - see front matter � 2009 Elsevier Ltd. Adoi:10.1016/j.enconman.2009.11.048

Abbreviations: CFC(s), Chlorofluorocarbon (s); COPGWP, Global warming potential; HCFC(s), Hydrochlor

* Corresponding authors. Tel.: +962 795614261.E-mail addresses: nidal@just.edu.jo (N.H. Abu H

gmail.com (M.A. Al-Muhtaseb).

a b s t r a c t

This paper presents the design of new prototype of a solar adsorption refrigeration unit with certain spec-ifications and requirements to be used as an air conditioning and refrigeration unit suitable to be used inremote areas. The new device uses activated carbon (used as adsorbents) with methanol (as adsorbate)forming an adsorbent–adsorbate pairs.

Experimental data with statistical technique are used in this paper to get the optimum design param-eters of the solar adsorption refrigeration system with an acceptable result of COP (coefficient of perfor-mance) and cooling production.

The minimum temperature obtained for the refrigerator was 9 �C while the ambient temperature was26 �C. The effective refrigeration started at 21:10 and the temperature decreased gradually until itreached 9 �C at 01:30 next day then it increased above the minimum temperature. The gross cycle coef-ficient of performance, COPa = 0.688 from the thermodynamic calculations.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Solar adsorption refrigeration devices are of significance tomeet the needs for cooling requirements such as air-conditioning,ice-making and medical or food preservation in remote areas. Theyare also noiseless, non-corrosive and environmentally friendly. Theuse of solar energy for environmental control is receiving muchattention as a result of the projected world energy shortage. Refrig-eration is particularly attractive as a solar energy application be-cause of the near coincidence of peak cooling loads with theavailable solar power. Solar refrigeration has the potential to im-prove the quality of life of people who live in areas with electricityinsufficient. Solar cooling to produce ice accumulates latent heat,thus leading to smaller volume of ice-makers. The adsorption sys-tem is one of the promising solar thermal refrigeration methods,and it is environmentally friendly along with low cost and lowmaintenance requirements Al-Muhtaseb [1].

In Jordan, the refrigeration and air conditioning systems are oneof the major energy consumers [2]. These systems normally useCFCs as working fluid that induces ozone depletion and conse-

ll rights reserved.

, Coefficient of performance;ofluro carbon(s).

amdeh), almuhtaseb.mutaz@

quently greenhouse effect. Therefore, promotion of sustainable en-ergy utilization is an urgent issue.

The solid adsorption system is considerably an alternative wayto reduce CFC usage. The system could exploit low grade energysource (e.g. waste heat from industrial process, solar energy) andno compression work. On the other hand, the adsorption technol-ogy applicable to refrigerating systems differs significantly fromthat of absorption on account of its unsophisticated functioning.In adsorption, there occur the interaction between a solid and afluid, the transportation of the latter being thermal gradientdependable, i.e. It does not require the use of pumps, as in the caseof the absorption one. The climatic conditions are fixed in thisstudy; and the location of this unit was inside Jordan Universityof Science and Technology – north of Jordan where the solar irradi-ation and ambient temperature are known for the north of Jordanas shown in Table 1.

The objective of this paper is to design a complete new solaradsorption unit using optimum parameters, obtained from statisti-cal analysis, to be used as an air conditioning and refrigerationunit.

2. Principle of adsorption

Adsorption occurs at the surface interface of two phases, inwhich cohesive forces including electrostatic forces and hydrogenbonding, act between the molecules of all substances irrespective

Table 1General data used to calculate COP and g for the whole unit.

Global solar radiation, measured on calculatedGi

0.650 kW/m2

Average ambient temperature, Ta 25 �CAdsorbent/adsorbate pair Activated carbon/

methanolSpecific heat capacity of methanol, Cpr 22.545 kJ/kg �CEnthalpy of solid–gas phase of methanol, hsg 1400 kJ/kgEnthalpy of liquid–gas phase of methanol, hfg 1100 kJ/kg

N.H. Abu Hamdeh, M.A. Al-Muhtaseb / Energy Conversion and Management 51 (2010) 1610–1615 1611

of their state of aggregation. Unbalanced surface forces at thephase boundary cause changes in the concentration of moleculesat the solid/fluid interface [3]. The process of adsorption involvesseparation of a substance from one phase accompanied by its accu-mulation or concentration at the surface of another. The adsorbingphase is the adsorbent, and the material concentrated or adsorbedat the surface of that phase is the adsorbate. Physical adsorption isan exothermic process and heat is always released when adsorp-tion occurs.

3. The prototype description

The prototype consists of four beds; one bed for each adsorberof the four adsorbers used (Jojoba seeds, palm seed, coconut shells,and charcoal activated carbon), in this study the results of coconutshells are displayed in the results. Copper tubes pass through theadsorber to acquire the heat that will be released during theadsorption process.

The flat plate collector (1.78 � 0.78 � 0.2 m thick) is made ofsteel shells tilted 40� from ground. A faucet comes out from eachbed and opens into a common header, such that the operatingbed is the one with the opened faucet. A black sheet covers eachbed, it is placed directly over the activated carbon; the black colorincreases the absorption of the solar radiation. A space of about5 cm separates the sheet. The glass panel (5 mm thick) covers eachbed and prevents the long wave radiation from escape. It works ex-actly like a greenhouse (see Fig. 1).

Condenser is defined as a heat exchanger where the fluid flowsthrough a pipe or system of pipes. Heat is transferred from thefluid, and hence the fluid will be cooled and condensed from vaporto liquid. In this prototype the condenser is a simple pipe located atthe back of the refrigerator.

Another component of the prototype is the evaporator. It is aheat exchanger where the fluid flows throw system of pipes. Heatis transferred to the fluid, and hence the fluid will be evaporated. Inthis prototype the evaporator is used as an ice-maker operated atthe night cycle.

The Easy Data App was used for instrumentation. It is a graphingcalculator application. It can collect, view, and analyze real-world

Fig. 1. The prototype of solar adsorption system.

data on certain TI-graphing calculators using Vernier USB devices(EasyTemp and EasyLink) and other data collection devices, suchas Texas Instruments CBR 2™ motion detector, CBL 2™ System, orVernier Go!Motion™, and LabPro�.

The data acquisition system is used to measure the temperatureof the system instrumentation and store them electronically for la-ter analysis. The time base on the LabPro is controlled by a crystalwith 50 ppm accuracy. The measurement times are determined bythe LabPro, not the computer, as long as the data rate is faster than2 Hz. For 2 Hz and slower.

The existing instrumentation on the system consists of thermo-couples. The thermocouples used on this system are Type T (cop-per-constantan) normally used for reading temperatures from(�150 �C to +350 �C). These thermocouples, as well as all othertypes, consist of a bimetallic junction that produces a voltage out-put that is related to the temperature of the junction. Five thermo-couples were used in the experiments; four for the beds and arepass through the activated carbon and the fifth is located insidethe refrigerant.

4. Performance estimates

The limit of this performance is determined the absolute limitfor the COPref of a sorption refrigerator operating between theevaporating temperature Te and generating temperature Tg isequivalent to the overall COPref of combination of a reversible heatengine and a reversible reversed heat engine operating between Te

and Ta [1], The derivation leading to following equation:

COPref ¼TeðTg � TaÞTgðTa � TcÞ

ð1Þ

where Tg = generating temperature, Ta = ambient temperature,Te = evaporating temperature.

For ideal adsorption refrigerators, Critoph obtained a differentexpression for the COPref(ad) [1]

COPref ðadÞ ¼Te

Tad¼ Te

Tgð2Þ

The total incident global solar energy, Qit, is determined fromthe product of the incident global solar flux over the whole day,Gi, and the collector exposed surface area (Ae) as:

Qit ¼ GiAe ð3Þ

The useful heat energy delivered to the rich concentrationadsorbent to expel the methanol is determined by the sum of thesensible heat absorbed by the adsorbent and methanol and the la-tent heat of generation of methanol as:

Qic ¼ ðmacCpac þmrCprÞDTg þmrhsg ð4Þ

The available or gross heat extraction as:

Qa ¼ mrhfg ð5Þ

This is also the condensate cooling capacity. From the aboveconsiderations, the performance indices of the solar refrigeratorare evaluated as follows:

The available or gross cycle coefficient of performance, COPa:

COPa=Qa=Q ic ð6Þ

The solar collector/generator/adsorber efficiency, g:

g ¼ Q ic=QicQit ð7Þ

From the above equations, the gross cycle coefficient of perfor-mance was calculated to be COPa = 0.688.

Multiple regression was used to obtain the optimum region ofthe parameters of the solar adsorption system, this was done using

Table 2Data for coconut shell.

Maximum generation temperature, Tg 110 �CCondensing temperature, Tc 25 �CEvaporating temperature, Te 8 �C

1612 N.H. Abu Hamdeh, M.A. Al-Muhtaseb / Energy Conversion and Management 51 (2010) 1610–1615

statistical software called Minitab, where the option of the multi-ple regression technique is available inside it.

The uncertainty and the accuracy were put in the work consid-erations, where the Easy Data App was used for instrumentation, ituses a graphing calculator application. It can collect, view, and ana-lyze real-world data on certain TI-graphing calculators using Ver-nier USB devices, The data acquisition system is used to measurethe temperature of the system instrumentation and store themelectronically for later analysis, The time base on the LabPro is con-trolled by a crystal with 50 ppm (ppm) accuracy. The measurementtimes are determined by the LabPro, not the computer, as long asthe data rate is faster than 2 Hz. For 2 Hz and slower, you are atthe mercy of the computer clock.

5. Results and discussion

Table 1 shows the data that were used to calculate the COP andg for the whole unit. Table 2 shows the data obtained from coconutshell.

Table 3 shows the data harvest output for the coconut shell ad-sorber. The first column represents the time interval in secondsthat was set to be automatically acquired every hour. The second,third and forth columns represent the bed temperature for coconutshell. As shown in the table. The maximum temperatures for coco-nut shell, was 103 �C. Also, the minimum temperature for therefrigerator was 9 �C while the ambient temperature was 29 �C.

The effective refrigeration started at 21:22 and the temperaturedecreased gradually until it reached 8 �C at 01:22 next day then itincreased from the minimum temperature, the standard minimumtemperature should be less than the obtained one. The standardamount of the adsorbate was used is (900 ml). The limitation forthe amount of the adsorbate that used is due to the limited sizeof the refrigerator reservoir. The temperature increases rapidlyafter 02:22 because the refrigerator is not perfect insulated.

Fig. 2 shows the response surface of COP as a function of tankvolume and collector area using statistical software (Minitab),multiple regression method is used in this software. As shown inthe figure, the optimum value of the COP lies in the region where

Table 3Data harvest output for the coconut shell adsorber.

Actualtime

Adsorbertemperature (�C)

Refrigeratortemperature (�C)

Bedtemperature(�C)

10:29:19 92 27 9712:26:10 94 27 10314:31:18 99 29 9215:29:21 91 26 7016:49:16 86 26 6218:32:19 56 24 3020:24:23 26 25 3022:32:33 24 16 3123:20:11 25 13 2900:25:18 24 9 2902:25:31 26 9 2903:32:44 27 10 3204:20:52 25 14 2906:23:22 27 17 5107:20:12 36 19 67

the collector area is from 3 to 4.5 m2, and tank volume from 0.2to 0.23 m3. The literature shows that the increase of volume morethan 0.3 m3 will decrease the COP. It is obvious that for low tankvolumes (representing less volume of water), the water could at-tain the required desorption temperature much earlier, which af-fects the system performance. Hence, it is recommended to usethe lowest tank volume without affecting the COP of the system.The COP decreases beyond a collector area of 5 m2. This is due tothe fact that the cooling production does not increase much oncethe water temperature reaches above 100 �C which is attained ifthe collector area is beyond 5 m2. Hence, with further increase inthe water temperature as a result of increasing collector area, thecooling production remains stable, but the COP decreases.

Figure shows also the contour plot of the COP of the system as afunction of tank volume and collector area, the figure shows againthat the optimum value of COP lies in the region when the collectorarea is from 3 to 4.5 m2, and tank volume from 0.2 to 0.23 m3.

Fig. 3 discusses the adequacy of the response surface of the COPas a function of tank volume and collector area. The residuals arenormally and independently distributed with no crystals or cretindistributed shape. The R2 and adjusted R2 were calculated andthey were, R2 = 99.6% and adjusted R2 = 99.3%.

Fig. 4 shows the response surface of the COP of refrigerator asa function of mass and collector area. As shown in the figure, theoptimum value of the COP lies in the region where the collectorarea is from 3 to 4.5 m2, and mass from 40 to 50 kg. The COP de-creases beyond 5 m2. This is due to the fact that the cooling pro-duction does not increase much once the water temperaturereaches above 100 �C which is attained if the collector area is be-yond 5 m2. Hence, with further increase in the water temperatureas a result of increasing collector area, the cooling production re-mains stable, but the COP decreases. The figure shows also thatthe COP and cooling production increases as long as the adsorbentmass is less than 60 kg. The increase in adsorbent mass indicatesmore methanol being adsorbed initially. Hence, during thedesorption phase, more methanol vapor can be desorbed, whichproduces more cooling and thereby results in high COP. On theother hand, if the mass of adsorbent is increased to more than60 kg, the COP as well as the cooling production decreases. Thisis because with the given heat input, only the bed could beheated, and this is not sufficient to desorb the required amountof methanol.

Fig. 4 shows the contour plot of the COP of the system as a func-tion of mass and collector area, the figure shows that the optimumvalue of COP lies in the region when the collector area is from 3 to4.5 m2, and adsorbent mass from 40 to 50 kg.

Fig. 5 discusses the adequacy of the response surface of the COPas a function of adsorbent mass and collector area. The residualsare normally and independently distributed with no crystals orcretin distributed shape. The R2 and Adjusted R2 values were cal-culated and they were R2 = 99.7% and Adjusted R2 = 99.3.

Fig. 6 shows response surface of the COP of the system as a func-tion of tank volume and mass. As shown in the figure, the optimumvalue of the COP lies in the region where the adsorbent mass isfrom 50 to 60 kg, and tank volume from 0.2 to 0.23 m3. The figurealso shows the effect of adsorbent mass on the system perfor-mance. The figure shows that the COP and cooling production in-creases as long as the adsorbent mass is less than 60 kg. Theincrease in adsorbent mass indicates more methanol being ad-sorbed initially. Hence, during the desorption phase, more metha-nol vapor can be desorbed, which produces more cooling andthereby results in high COP. On the other hand, if the mass ofadsorbent is increased to more than 60 kg, the COP as well as thecooling production decreases. This is because, with the given heatinput, only the bed could be heated, and this is not sufficient todesorb the required amount of methanol.

0.02

0.07

0.12COP

2 3 4

0.17

0.085

0.180.13

0.23

Surface Plot of COP

Collector Area (m )2

Tank Volume (m )3

0.09 0.13 0.17

5432

0.23

0.18

0.13

0.08

Tank

Vol

ume

(m )

Contour Plot of COP

3

Collector Area (m )2

Fig. 2. Response surface of the COP of the system as a function of tank volume and collector area (left). Contour plot of the COP of the system as a function of tank volume andcollector area (right).

1412108642

0.0020.0010.000

-0.001-0.002-0.003-0.004

Observation Order

Res

idua

l

Residuals Versus the Order of the Data(response is COP)

0.0020.0010.000-0.001-0.002

2

1

0

-1

-2

Nor

mal

Sco

re

Residual

Normal Probability Plot of the Residuals(response is COP)

Fig. 3. Residuals vs. the order of the data of the response of COP (left), normal probability plot of the residuals of the response of COP as a function tank volume and collectorarea (right).

0.04

0.09COP

2 3 4

0.14

1005

504030 Mass (kg)20

60

Surface Plot of COP

Collector Area (m )2

0.05 0.07 0.09 0.11 0.13

5432

60

50

40

30

20

10

0

Mas

s (k

g)

Contour Plot of COP

Collector Area (m )2

Fig. 4. Response surface of the COP of the system as a function of mass and collector area (left). Contour plot of the COP of the system as a function of mass and collector area(right).

N.H. Abu Hamdeh, M.A. Al-Muhtaseb / Energy Conversion and Management 51 (2010) 1610–1615 1613

Moreover Fig. 6 shows also the contour plot of the COP of thesystem as a as a function of tank volume and mass, the figureshows that the optimum region of COP lies in the region whenthe tank volume is from 0.2 to 0.23 m3, and adsorbent mass from40 to 50 kg.

Fig. 7 discusses the adequacy of the response surface of the COPas a function of adsorbent mass and tank volume. The residuals arenormally and independently distributed with no crystals or cretindistributed shape. The R2 and adjusted R2 values were calculatedand they were R2 = 99.8% and adjusted R2 = 99.6%.

Fig. 8 shows response surface of the cooling production of thesystem as a function of tank volume and mass. As shown in the

figure, the optimum value of the cooling production lies in the re-gion where the adsorbent mass is from 40 to 50 kg and tank vol-ume from 0.2 to 0.23 m3. This figure shows the effect ofadsorbent mass on the system performance. It can be seen thecooling production increases as long as the adsorbent mass is lessthan 60 kg. The increase in adsorbent mass indicates more metha-nol being adsorbed initially. Hence, during the desorption phase,more methanol vapor can be desorbed, which produces more cool-ing. On the other hand, if the mass of adsorbent is increased tomore than 60 kg, the cooling production decreases. This is becausewith the given heat input, only the bed could be heated, and this isnot sufficient to desorb the required amount of methanol.

1412108642

0.002

0.001

0.000

-0.001

-0.002

Observation Order

Res

idua

l

Residuals Versus the Order of the Data(response is COP)

0.0020.0010.000-0.001-0.002-0.003-0.004

2

1

0

-1

-2

Nor

mal

Sco

re

Residual

Normal Probability Plot of the Residuals(response is COP)

Fig. 5. Normal probability plot of the residuals of the response of COP as a function mass and collector area (left). Residuals vs. the order of the data of the response of COP(right).

0.0

0.1

0.2COP

10 20 30 40 50Mass (kg)

0 10 20

0.3

0.4

0.0860

0.180.13

0.23

Surface Plot of COP

Tank Volume (m )3

0.15 0.25 0.35

6050403020100

0.23

0.18

0.13

0.08

Mass (kg)

Tank

Vol

ume

(m )

Contour Plot of COP

3

Fig. 6. Response surface of the COP of the system as a function of tank volume and mass (left). Contour plot of the COP of the system as a function of tank volume and mass(right).

1412108642

0.0020.0010.000

-0.001-0.002-0.003-0.004

Observation Order

Res

idua

l

Residuals Versus the Order of the Data(response is COP)

0.0010.000-0.001

2

1

0

-1

-2

Nor

mal

Sco

re

Residual

Normal Probability Plot of the Residuals(response is COP)

Fig. 7. Residuals vs. the order of the data of the response of COP (left), normal probability plot of the residuals of the response of COP as a function of tank volume and mass(right).

0

10Cooling Production (kg)

30 40Mass (kg)

10 20

20

500.05

0.150.25

Surface Plot of Cooling Production

Volume (m )3

10 15 20

20 30 40 500.060.080.100.120.140.160.180.200.220.24

Mass (kg)

Contour Plot of Cooling Production

Volu

me

(m )3

Fig. 8. Response surface of the cooling production of the system as a function of tank volume and mass (left). Contour plot of the cooling production of the system as afunction of tank volume and mass (right).

1614 N.H. Abu Hamdeh, M.A. Al-Muhtaseb / Energy Conversion and Management 51 (2010) 1610–1615

-0.2-2

-1

0

1

2

Nor

mal

Sco

re

Residual

Normal Probability Plot of the Residuals(response is Cooling)

2-0.2

-0.1

0.0

0.1

0.2

Observation Order

Res

idua

l

Residuals Versus the Order of the Data(response is Cooling)

0.20.10.0-0.1 16141210864

Fig. 9. Normal probability plot of the residuals of the response of cooling production as a function of tank volume and mass (left). Residuals vs. the order of the data of theresponse of cooling production (right).

N.H. Abu Hamdeh, M.A. Al-Muhtaseb / Energy Conversion and Management 51 (2010) 1610–1615 1615

Fig. 8 shows also the contour plot of the cooling production ofthe system as a function of tank volume and mass, the figure showsagain that the optimum value of cooling production lies in the re-gion when the tank volume is from 0.2 to 0.23 m3, and adsorbentmass from 40 to 50 kg.

Fig. 9 discusses the adequacy of the response surface of coolingproduction as a function of adsorbent mass and tank volume, Theresiduals are normally and independently distributed with no crys-tals or cretin distributed shape, The R2 and adjusted R2 valueswere calculated and they were R2 = 99.7% and adjusted R2 = 99.6%.

6. Conclusions

Solar air conditioning has a strong potential for significant pri-mary energy savings. In particular, for Mediterranean areas, solarassisted cooling systems can lead to primary energy savings inthe range of 40–50%.

The results of this study show that one can conclude that thepossibilities of using nonpolluting materials and to save more thanhalf of the primary energy involved in this sector are obviously themost important characteristics. The simplicity of the system, lowmaintenance costs and the absence of noisy components are alsovery important features that make this type of systems suitablefor numerous other applications such as air-conditioning, food pro-tection and solar cooling.

This model giving the thermodynamic performances of adsorp-tion refrigerator using activated carbon–methanol pair. The modelhas been validated by using experimental results and statisticaltechnique. These results demonstrate that for an optimized solaradsorption refrigeration system, the following parameters mustbe included:

Increasing of the adsorbent mass will increase the coefficient ofperformance. The statistical optimization results show that theoptimum adsorbent mass varies between 50 and 60 kg which givesa high solar coefficient of performance of the system up to 0.19.

Increasing of the tank volume will increase the coefficient ofperformance. The statistical optimization results show that the

optimum tank volume varies between 0.2 and 0.23 m3 whichgives a high solar coefficient of performance of the system upto 0.2.

Increasing of the collector area will increase the coefficient ofperformance. The statistical optimization results show that theoptimum collector area varies between 3.5 and 4.5 m2 which givesa high solar coefficient of performance of the system up to 0.18.Noting that the statistical value of solar coefficient of performanceof the system varied from 0.18 to 0.2 according to the way of multi-ple regression technique response as a function of the inputs.

The tilt angle of the collector was set to be optimum for our re-gion which 45� to ward the south [96].

The statistical optimization results show that the optimumcoefficient of performance of the solar adoration refrigerationsystem was 0.2, and the optimum cooling production was 10 kg/day.

References

[1] Al-Muhtaseb M. Design of solar adsorption refrigeration unit. Master Thesis inMechanical Engineering Department. Jordan University of Science andTechnology (JUST); 2008.

[2] Meunier F. Solid sorption: an alternative to CFCs. Heat Recov Syst CHP1993;13(4):289–95.

[3] Jaradat M. Experimental study of a solar adsorption refrigeration unit. ThesisJordan University of Science and Technology; 2004.

Glossary

Adsorption: The bonding of a solid with gas or vapor that touches its surfaceAdsorbate: A solid, liquid, or gas that is adsorbed as molecules, atoms, or ions onto

the surface of the adsorbentAdsorbent: A solid or liquid that adsorbs other substancesDesorption: The process of removing adsorbed substance by the reverse of

adsorption or absorptionAbsorption: A process in which material transferred from one phase to another

interpenetrates the second phase to form a solutionAbsorbent: A material that in contact with a liquid or gas, extracts one (or more)

substances for which it has an affinity, and is altered physically or chemicallyduring the process by the substance penetrating into the bulk of the material