Modeling and Simulation of Evaporative Cooling System in Controlled Environment Greenhouse

doi:10.4236/sgre.2012.31010

Paper Menu >>

Journal Menu >>

Smart Grid and Renewable Energy, 2012, 3, 67-71

http://dx.doi.org/10.4236/sgre.2012.31010 Published Online February 2012 (http://www.SciRP.org/journal/sgre)

Modeling and Simulation of Evaporative Cooling System i n

Controlled Environment Greenhouse

Faten Hosney Fahmy, Hanaa Mohamed Farghally, Ninet Mohamed Ahmed, A. A. Nafeh

Electronics Research Institute, Giza, Egypt.

Email: [email protected]

Received August 2nd, 2011; revised September 6th, 2011; accepted September 13th, 2011

ABSTRACT

Greenhouses are used for the main purpose of improving the environmental conditions in which plants are grown. There

are many parameters can affect the growing of plants inside greenhouse, such as air temperature and relative humidity.

The adjustment of these parameters is achieved by selecting appropriate control actions. This work proposes a control-

ling technique for greenhouse indoor temperature and relative humidity. The proposed greenhouse cooling system tem-

perature controller is designed to adjust the air volume flow rate in pad-fan cooling system to fix the greenhouse indoor

temperature at 20˚C and 70% relative humidity. The designed control technique is realized to ensure the required and

continuous operation of the greenhouse. Moreover, this work present, a complete mathematical modeling and simula-

tion of cooling system is introduced. In addition, a computer model based on MATLAB SIMULINK software has been

used to predict the temperature and relative humidity profiles inside the greenhouse. The results are realized the re-

quirements of the greenhouse cooling system environment.

Keywords: Pad-Fan; Evaporative Cooling System; PI Controller and Greenhouse

1. Introduction

One of the benefits of cultivating plants in a greenhouse

is the ability to control all aspects of the growing envi-

ronment. Two of the major factors influencing plant

growth are the temperature and relative humidity [1].

Different plant species have different optimum growing

temperatures and humidity. Medicinal herbs (e.g. Marjo-

ram) often need a temperature of 20˚C and about 70%

relative humidity to grow [2]. Low or high temperatures

may cause herb stress, inhibit growth, or promote the

dropping of herb leaves. Also, when the humidity is low,

this will impede the growth of the herb by stopping

photosynthesis and will eventually cause the herb to wilt.

On the other hand, high humidity will increase the poten-

tial for spreading diseases [2]. Therefore, a temperature

and humidity controllers should be used for avoiding the

previously harmful effects. The emphasis of this paper is

concerned with the control of the temperature and relative

humidity of a proposed greenhouse. Also, a complete

mathematical modeling and MATLAB SIMULINK mo-

del for the different components of the evaporative cool-

ing system in the proposed greenhouse is presented in

this paper.

2. The Proposed Greenhouse

The proposed greenhouse in this work consists mainly of

eight components as shown in Figure 1. These compo-

nents are polyethylene white coating, water impermeable

plastic material cover, woven water-porous shade curtain

material, aluminum pad, cool air fan, sumps, pump and

soil. In this work, the proposed cooling system consists

1. polyethylene white coating reflects 50% of radiation; 2. water im-

permeable plastic material cover; 3. greenhouse shading (woven wa-

ter-porous shade curtain material); 4. aluminum pad; 5. cool air fan; 6.

sumps; 7. pump; 8 soil.

Figure 1. The proposed greenhouse.

Modeling and Simulation of Evaporative Cooling System in Controlled Environment Greenhouse

mainly, of four components. These components are alu-

minum pad, cool air fan, pump and sump. This cooling

system can maintain a greenhouse interior temperature

and relative humidity to about 20˚C and 70% respect-

tively.

3. Cooling System Mathematical Modeling

3.1. Greenhouse Energy Balance

In order to study the variables, which determine the

greenhouse air temperature, a simplified version of the

greenhouse energy balance is formulated.

Usually, the greenhouse microclimate is represented

by the climate in the middle of the enclosure. The energy

balance in the middle area of the greenhouse can be

written as following [2-4]:



 

,1c

nii opi o

RKTTC



 

 

 

 



(1)

where Rn,i is the incoming net radiation (in W·m–2),



is the ratio of latent heat flux to net radiation. Conse-

quently, the term “







” is the part of the incom-

ing net radiation which is transformed to sensible heat

contributing to the greenhouse air temperature increase,

To and Ti are the outside and inside greenhouse air tem-

peratures respectively (in ˚C), K (in W·m–2·˚C–1) is the

heat exchange coefficient of the greenhouse cover (by

convection and conduction), which depends on the cover

type and the wind speed, Ac is the greenhouse cover sur-

face area (in m2), Ag is the greenhouse ground surface

area (in m2), Q is the ventilation air flow rate (in m3·s–1),



is the air density (in kg·m–3), and Cp is the specific

heat of air at constant pressure (J·kg–1·˚C–1). Replacing

the term Q/Ag by Va, which represents the greenhouse

ventilation rate in (m3·s–1·m–2) of floor area, assuming

that Rn,i is very close to the incoming solar radiation Rs,i,

and that K is a function of the wind speed (K = K1 + K2u).

Equation (1) becomes:

 

 

,12

niio paio

RK KuTTCVTT





 









(2)

where K1 and K2 are constants and u is the outside air

speed in m·s–1. Taking into account that Rs,i = τRs,o,

where Rs,o is the outside solar radiation (in W·m–2) and τ

is the greenhouse transmissivity to solar radiation. Thus,

using Equation (2), the greenhouse air temperature Ti can

be calculated by the following relation:



cg pa

AKKu CV







  (3)

Dividing both numerator and denominator of second

part of Equation (3) by the term “



1cg

AK” we take:









21 1

so c g

RAAK

KuCV KAA











 (4)

If we replace the term



1cg





 by 1



the term





K by 2



and the term









1pcg

CKAA









 by 3



, then we obtain:

TT uV







 (5)

Equation (5) is a simplified version of the greenhouse

energy balance must be applied for the determination of

the unknown parameters 1



, 2



and 3



. Accordingly,

measurements of Ti, To, Rs,o,



, u and Va are needed, in

order to calibrate Equation (5) and statistically determine

the values of 1



, 2



and 3



3.2. Pad-Fan Subsystem Mathematical Modeling

3.2.1. Fan Mathematical Modeli ng

Pad-fan systems are commonly used for cooling the en-

vironment inside greenhouses to be suitable for growing

plants (e.g., nurseries, residential and commercial vege-

tables or flower production, etc). Fans push outside air

toward a wet pad, bringing cooled and humidified air

into the greenhouse. Typically, the wet pads and fans are

located on opposite walls so that the evaporative cooled

air is pulled from one end of the structure to the other.

A linear model of a simple fan consists of a mechanic-

cal equation and electrical equation as determined in the

following [5,6].

aaaa

VEIRL

  (6)

eLmm

TTBJt



  (7)

fan

PNDv (8)

where N is fan speed, D is fan diameter, v is specific

weight of air (11.82 N/m2), Ra is armature resistance (Ω),

La is armature inductance (H), Va is terminal voltage (V),

J is moment of inertia (kg·m2), B is damping factor of

mechanical system (N·m·s). Ia is armature current (A),

TL is load torque (N·m), Te is developed torque, and ω

is speed of rotation (rpm).

3.2.2. Pad Mathematical Modeli ng

The cooling efficiency ηc of the evaporative pad cooling

system is defined by [7,8]:

db o

db owb o





 (9)

Modeling and Simulation of Evaporative Cooling System in Controlled Environment Greenhouse

where Tdb,o and Twb,o are the dry and wet bulb tempera-

tures of the air outside the greenhouse in ˚C, and T is the

dry bulb temperature of the cooled air passing over the

wet pad in ˚C. Equation (9) works well for evaporative

pad cooling systems because the cooling process (an

adiabatic process) occurs nearly at a constant wet bulb

temperature of the outside air. Equation (9) can be rear-

ranged as [7]:

control signal of the greenhouse fan and pad system vc.

The greenhouse inside temperature and humidity (Tin &

Hin) are the feedback signals to PI the controller.







,,,,

dboc dbowboc dbocwbo

TTT TTT



 ,



(10)

The actual greenhouse inside temperature (Tin) is com-

pared with the reference temperature value (Tref = 20˚C)

through a comparator to give an error signal, which is

introduced to the system controller. In this case, the con-

troller uses the input error signal e to improve the system

response by producing the suitable control signal of the

greenhouse fan and pad system vc. Also, second com-

parator is used to compare the actual relative humidity to

the reference relative humidity (RH = 0.7) to obtain the

error signal for the PI controller. The humidity controller

operates between dehumidify and humidify modes for

removing unwanted atmospheric moisture accumulating

within the greenhouse or to add the needed moisture to

the air by means of humidification. In the dehumidifying

mode, high humidity conditions will activate moisture

fan until level drops approximately to 70% in relative

humidity. In the humidifying mode this control operates

pad-fan humidifying system by activating switches and

motors until the relative humidity increased to 70%.





,,db ocdbowb o

TT TTT



 ,



(11)

where ∆T is the temperature drop of the air through

evaporative pad cooling systems in ˚C. Equations (10)

and (11) indicate that both T and ∆T depend only on the

dry and wet bulb temperatures of the outside air at a con-

stant cooling efficiency. By assuming a value of 80% for

the efficiency of evaporative pad cooling systems Equa-

tions (10) and (11) can be written as:

0.2 0.8

db owb o

TT T (12)



0.8 db owb o

TTT (13)

During this operation of the greenhouse cooling sys-

tem, different situations may appear.

4. Control Strategy and Simulation of the

Greenhouse 4.1. First Situation: Humidity (RH < 0.7)

The evaporative pad-fan cooling system must have ade-

quate controller for the operator to be able to adjust the

greenhouse environment to provide the best growing

conditions for the selected herb and a comfortable envi-

ronment for worker. Two conventional controllers (PI

controllers) [9-11] are employed to maintain, optimal

temperature and relative humidity (Tref = 20˚C & Href =

0.7) inside the greenhouse at any time and to overcome

the load effect of the outdoor undesirable climatic condi-

tions. The block diagram that describes the control strat-

egy is illustrated in Figure 2. Also, the MATLAB SI-

MULINK block diagram of the greenhouse cooling sys-

tem is shown in Figure 3.

The pad-fan system switches on to increase the required

relative humidity.

4.2. Second Situation: Dehumidify (RH > 0.7)

The pad-fan system switches off while roof and side

greenhouse vents are opened for ventilation. In addition,

a roof fan is used to replace the air inside the greenhouse

(loaded with humidity) with the dry air outside the green-

house.

5. Results and Discussions

The cooling system has two controllers which control the

greenhouse inside temperature and relative humidity. PI

The input signal to the suggested controllers is the

system error e, while, the output action is the required

Figure 2. Block diagram of the greenhouse controlled system using PI controller.

Modeling and Simulation of Evaporative Cooling System in Controlled Environment Greenhouse

Tin

NPfan volume flow rate

pad syst em

In1 Out1

Tref 2

1000

Tref 1

To Work space2

Relay

Rela t ive Hum i di t y

In1 Out1

RHref

0.70

RH cont rol l er

PID

Product

Mositure Fan

Logical

Operator

NOT

Gain 2

-K-

Gain 1

-K-

Fcn5

f(u )

Fcn3

f(u )

Fcn2

f(u)

Fcn1

f(u)

.05*u^ 2

Fan Dc Motor

Clock2

Clock1

Clock

power cur ve1

power curve

PID

Figure 3. MATLAB SIMULINK bloc k diagram of the greenhouse cooling system.

control technique is proposed to fix the greenhouse in-

door temperature and relative humidity at the optimal

value for growing the marjoram herb. The proposed con-

troller is fine tuned and used to achieve a good regulatory

response. The fine-tuned parameters of the temperature

and relative humidity controllers are Kp = 10, KI = 0.0001,

and Kp = 0.1, KI = 0.2 respectively.

The greenhouse outside air temperature during 24

hours is shown in Figure 4. While, Figure 5 indicates

the response of greenhouse inside temperature. It is no-

Figure 4. Ambient temperature.

Figure 5. Greenhouse indoor temperature with control tech-

nique.

ticed that, the greenhouse inside temperature tracks the

reference temperature very well. On the other hand, air

flow rate of the fan is indicated in Figure 6. It also ob-

served from this figure that the maximum air flow rate of

the fan occurs around noon at the corresponding maxi-

mum ambient temperature, while the minimum flow rate

occurs at the mid night at the corresponding minimum

ambient temperature. Also, the controlled relative hu-

midity is shown in Figure 7, which indicates a very good

performance, since there is a small overshoot, fast

Modeling and Simulation of Evaporative Cooling System in Controlled Environment Greenhouse 71

Figure 6. Air flow rate of the fan.

Figure 7. Greenhouse relative humidity with PI controller.

settling time and good tracking performance.

6. Conclusions

An evaporative cooling system is presented, in this work,

to reduce the air temperature inside the greenhouse that

affects the greenhouse environment and consequently the

growing of cultivated plants. A control technique (PI

controller) is proposed to fix the greenhouse inside tem-

perature and relative humidity at the optimal values (i.e. ,

20˚C and 70% respectively) that are suitable for growing

of marjoram herb. The fine-tuned parameters of PI con-

troller are, Kp =10, KI = 0.0001, and Kp = 0.1, KI = 0.2

respectively.

The proposed cooling system temperature controller is

designed to adjust the air volume flow rate of the fan by

adjusting the speed of the fan motor in pad-fan system; to

fix the greenhouse inside temperature at 20˚C. On the

other hand, the humidity controller operates between

dehumidify and humidify modes for removing unwanted

atmospheric moisture accumulating within the green-

house or to add the needed moisture to the air by means

of humidification, to fix the greenhouse inside relative

humidity at 70%. Also, a mathematical modeling and

MATLAB SIMULINK model for the different compo-

nents of the evaporative cooling system is presented in

this paper.

REFERENCES

[1] K. S. Kumar, K. N. Tiwari and M. K. Jha, “Design and

Technology for Greenhouse Cooling in tropical and Sub-

tropical Regions: A Review,” Energy and Buildings, Vol.

41, 2009, pp. 1269-1275.

doi:10.1016/j.enbuild.2009.08.003

[2] C. Kittas, M. Karamanis and N. Katsoulas, “Air Tem-

perature Regime in a Forced Ventilated Greenhouse with

Rose Crop,” Energy and Buildings, Vol. 37, 2005, pp.

807-812. doi:10.1016/j.enbuild.2004.10.009

[3] R. A. Bucklin, J. D. Leary, D. B. McConnell and E. G.

Wilkerson, “Fan and Pad Greenhouse Evaporative Cool-

ing Systems,” University of Florida, Florida, 2010.

[4] Abdel-Ghany and A. M. Kozai, “Dynamic Modeling of

the Environment in a Naturally Ventilated, Fog-Cooled

Greenhouse,” Renewable Energy, Vol. 31, No. 10, 2006,

pp. 1521-1539. doi:10.1016/j.renene.2005.07.013

[5] A. Hughes, “Electric Motors and Drives Fundamentals,”

Types and Applications, Newnes, 2006.

[6] I. M. Al-Helal, “A Computational Fluid Dynamics Study

of Natural Ventilation in Arid Region Greenhouses,”

Ph.D. Thesis, The Ohio State University, Columbus, 1998.

[7] E. M. Ahmed, O. Abaas, M. Ahmed and M. R. Ismail,

“Performance Evaluation of Three Different Types of

Local Evaporative Cooling Pads in Greenhouses in Su-

dan,” Saudi Journal of Biological Sciences, Vol. 18, No.

1, 2011, pp. 45-51.

[8] A. Ganguly and S. Ghosh, “Modeling and Analysis of a

Fan-Pad Ventilated Floricultural Greenhouse,” Energy

and Buildings, Vol. 39, No.10, 2007, pp. 1092-1097.

doi:10.1016/j.enbuild.2006.12.003

[9] W. Bolton, “Control Engineering,” Longman Group, Har-

low, 1992.

[10] K. Ogata, “Modern Control Engineering,” Prentice-Hall

Inc., Englewood Cliffs, 1990.

[11] J. L. Guzmán, F. Rodríguez, M. Berenguel and S. Dor-

mido, “Virtual Lab for Teaching Greenhouse Climate

Control,” Proceedings of the 16th IFAC World Congress,

IFAC, Prague, 2005, pp. 2158-2163.