**Open Access**-
**Total Downloads**: 9 -
**Authors :**Lakshminarasimha N, Dr. M.S. Rajagopal, M. Vedavyasa -
**Paper ID :**IJERTCONV3IS17087 -
**Volume & Issue :**NCERAME – 2015 (Volume 3 – Issue 17) -
**Published (First Online):**24-04-2018 -
**ISSN (Online) :**2278-0181 -
**Publisher Name :**IJERT -
**License:**This work is licensed under a Creative Commons Attribution 4.0 International License

#### Thermal Management of Solar Power Pack using Computational Fluid Dynamics

Lakshminarasimha N 1

1PG Student, Thermal Engg. Department of Mechanical Engg.

Global Academy of Technology Bangalore, India

Dr. M.S. Rajagopal 2

2Professor & Head Department of Mechanical Engg. Global Academy of Technology

Bangalore, India

Vedavyasa 3

3Associate Professor Department of Mechanical Engg. Global Academy of Technology

Bangalore, India

Abstract Solar Power Pack (SPP) is an enclosure which houses heat generating electrical devices such as Battery Bank, Inverter and Controller. The present study involves cooling and ventilation analysis of the enclosure such that the electrical components operate at less than their limiting temperatures. Further, optimization studies are also carried out to determine fan location and locations of inlet and exit vents besides positioning of Baffles for uniform air motion. This study will also help in minimizing the pumping power cost by determining the pressure losses. Thermal Management of SPP has been carried out using CFD software ANSYS Workbench- FLUENT for both 2D and 3D geometry. Numerical results obtained from FLUENT agree well with analytical results.

Keywords– Thermal Management, Solar Power Pack, Enclosure, CFD, Optimization, FLUENT, Cooling, Ventilation

Terminology–

L = Length of SPP

W = Width of SPP

H = Height of SPP

Lb = Location of Battery Bank LC = Location of Controller

Li = Location of Inverter

Lf = Location of exhaust fan LV = Location of inlet vent 2D = Two-dimensional

3D = Three-dimensional TSA = Total surface area CFM = Cubic feet per minute

INTRODUCTION

In todays climate of growing energy needs and increasing environmental concern, alternatives to use of non-renewable and polluting fossil fuels have to be invested. One such alternative is solar energy. Solar power is the conversion of sunlight

into electricity directly using photovoltaics. The latest and the most cost effective method for integrating solar power to homes/offices/colleges/rural electrification etc. are through the use of Solar Power Pack. Present work is generic and can be used as preliminary literature for studying any different kinds of Solar Power Pack models.

Internal flow and thermal analysis in an enclosure containing heat generating equipments is always a challenge in the field of Heat transfer. Due to high expense of experimental study in recent years, Computational Fluid Dynamics (CFD) is gradually becoming the most efficient tool in thermal enclosure design. Study of Solar Power Pack comprises of; overall evaluation of design involving ventilation and cooling, study of velocity and temperature contours and optimization of design such as; fan size and location, location and size of inlet and exit vents and positioning of Baffles for uniform air motion. Also compute the many derived parameters along with the graphical representation of the interested regions. The main objective of the present work is to undertake a numerical investigation to evaluate the thermal design of SPP and further optimize the design to minimize the cost using simple 2D & 3D models.

LITERATURE SURVEY

In this section, literature survey has been conducted to understand the state of the art in thermal management of Solar Power Packs in particular and CFD in general to know the appropriate boundary conditions, modeling of heat sources and various CFD models. The summaries of most important papers are listed below.

Hoffman- A Pentair Company [1], [2003], released technical information data sheet on heat dissipation in an electrical enclosure. This technical data/cut sheet is majorly for electrical enclosures exposed to outdoor conditions. The technical information highlights majorly about, Enclosures temperature

rise/ Determination of temperature rise for an enclosure, Evaluation of solar heat gain and Selection of fans as per cooling requirement for an enclosure. Hence this manual is highly helpful in preliminary design stage, in predicting the cooling requirements for electronic and electrical enclosures.

Bud Industries, Inc., [2], [2007], released technical data hand book on Enclosure design tips. This guide helps in selecting cabinets, enclosures and other packaging system for electronic products. Also this booklet summarizes some of the more important issues of packaging for electronic systems and products, with the goal of helping us evaluate our options quickly, and then selecting the optimum solution for our application. As per project concerned the booklet majorly highlights about Materials and finishes for an enclosure and Basics of cooling for cooling requirement in an enclosure.

It is observed that very few literatures are available on thermal management of SPP using CFD though thermal analysis at PCB and chip level is available. However, industrial data sheets are available as ready reckoner to help designers to choose the right size of fan and number of fans. This study is aimed at optimizing the cooling and ventilation parameters to have better understanding of the system.

METHODOLOGY

The analysis of SPP is been carried out using Commercial CFD code ANSYS Workbench- FLUENT and Modeling and Meshing for 3D SPP enclosure were carried out in ANSYS ICEPAK.

ANSYS WORKBENCH

Combination of

Mahendra Wankhede, et al., [3], [2010], Paper comprises study on evaluation of cooling solutions for outdoor electronics. Both experimental and CFD simulation had been carried out for three different conFig.urations of enclosures including a

Geometry using design modeller

Meshing using ICEM

Boundary condition, solver & postprocesssing using FLUENT

solar radiation shield, double-wall enclosure and a air-to-air heat exchanger; using a typical Aluminium enclosure. Each enclosure was consisting 100W generating PCBs. The work showed that solar heat load can increase the internal air temperature by 20%, White coating of an enclosure reduces internal air temperature by around 25% and as the major part of the work highlighted that 50-55% can reduce T due to the internal fans compared to a sealed enclosure with no fans and having radiation shield and double- walled enclosure with air circulation provided modest improvements of around 25%, where as air- to-air heat exchanger showed improvement by 75%.

Tom Kowalski and Amir Radmehr, [4], This Paper highlights the significance of using coupled FNM and CFD based analysis in cooling of electronic enclosure. The study demonstrates the application of coupled Fluid Network Method (FNM) and CFD in the analysis of flow behavior and Thermal behavior in a telecommunication cabinet. The cabinet is forced- flow air cooled consisting a stack of PCBs. The work showed detailed measurement of airflow velocities in various parts of the cabinet, the predicted variation of the flow rates through card passages and total flow through system were found to be within 10% of their experimentally measured values.

Fig. 1: Combined module of CFD code

ANSYS Workbench delivers innovative, dramatic simulation technology advances in every major physics discipline, along with improvements in computing speed and enhancement to enabling technologies such as geometry handling, meshing and post-processing (Fig. 1). These advancements alone represent a major step ahead on the path forward in Simulation driven Product Development.

ANSYS ICEPAK provides highly simplified way of modeling and meshing for cubical electronic enclosure probems.

GEOMETRY

The Geometry of SPP consists of Battery Bank, Inverter, Controller, and Inlet vent and outlet/exhaust fan. The most important thing to be noted is that the geometry is planar symmetry. The dimensions specified for the models below in 3.1.1 and 3.1.2 are elaborated in the above terminology.

3.1.1 2D Geometry model

H

L

Fig. 2: 2D SPP Model

Fig. 2, shows the 2D cut plane (XY plane- right bottom corner of Fig. 2) taken from planar

MESHING

symmetry 3D model which has been considered for 2D analysis. A simplified 2D analysis is carried out at the mid-plane of SPP to get an insight of the physics of the problem though this model doesnt capture the overall objective of determination of accurate flow and temperature distributions. 2-D geometry does not accurately capture locations of inlet vent, fan location and heat generating devices.

3.1.2 3D Geometry model

The planar symmetry 3D SPP domain with dimensions as per above terminology is shown in Fig. 3. The 3D model captures the problem objective and fetches us real results and provides us the clear visualization of contours and vectors at our interested spots in the domain.

Fig. 3: 3D SPP Model

Meshing is the important criteria as part of analysis considered. Maximum time spent in meshing is the time well spent. Mesh independence studies have been carried out for both 2D and 3D domain meshes. The details of meshing for 2D and 3D domain are as described below.

2D Meshing

The 2D mapped fine mesh is shown in Fig. 4. Mesh independence study graphs for the 2D mesh are shown in Fig. 5 and Fig. 6. Based on this study, further analyses are carried out for Quad mesh with 46280 elements and 47204 nodes. The convergence criteria for the continuity, x-velocity, y-velocity, energy, k and epsilon are shown in Fig. 7.

Fig. 4: 2D Mesh

Max. velocity (m/s)

Max. velocity (m/s)

#### Mesh independence chart Max. Velocity vs. Mesh elements

6.465

6.46

is the optimum mesh which is shown in Fig. 8. The convergence criteria trends for the continuity, x- velocity, y-velocity, z-velocity energy, k and epsilon are shown in Fig. 11.

6.455

6.45

6.445

32144 46280 52560

Max. velocity (m/s)

Fig. 5: 2D Mesh independence plot for Maximum Velocity vs.

Mesh elements

Max. temperature (K)

Max. temperature (K)

#### Mesh independence chart Max. Temp vs. Mesh elements

329.5

329

328.5 328

327.5

max. temperature (k)

Max. Velocuty (m/s)

Max. Velocuty (m/s)

6.6

6.4

6.2

6

5.8

Fig. 8: 3D Mesh

Fig. 6: 2D Mesh independence plot for Maximum Temperature vs. Mesh elements

5.6

5.4

5.2

5

Max Velocity (V)

Number of mesh elements

Fig. 9: 3D Mesh independence plot for Maximum Velocity vs.

Mesh elements

Max Temp (deg. C)

Max Temp (deg. C)

47

46

45

44

43

42

41

40

Fig. 7: 2D Mesh Convergence criteria

Max temperature (T)

3D MESHING

Creating a 3D mapped hexahedral mesh is a big challenge; however Icepak provides an easy platform to create mapped hexahedral mesh for cubical geometries. Icepak also facilitates fluid and solid surface extractions which can be named appropriately. Icepak is used for modeling & meshing process & the mesh has been transferred to fluent for further analysis.

Mesh independence study graphs for the 3D mesh are shown in Fig. 9 & Fig. 10. The study shows that mesh with 272786 elements and 284868 nodes

39424

80249

157005

272786

416174

1059528

39424

80249

157005

272786

416174

1059528

Number of mesh elements

Fig. 10: 3D Mesh independence plot for Maximum Temperature vs. Mesh elements

Page 4 of 10

Fig. 11: 3D Mesh Convergence criteria

SOLUTION METHODOLOGY

In the present investigation, the enclosure exhaust fan of 285 CFM has been selected through analytical calculation [1]. Flow is considered to be incompressible and steady. The internal flow is governed by Reynolds Average Navier-Stokes equations (RANS). Standard K-epsilon model is used to solve the flow analysis. The heat generating sources wall are at heat flux and no slip condition. Standard K-epsilon model comes under two equation model of turbulence kinetic energy k and its dissipation rate & hence these two equations are solved for obtaining the result. The incoming air through inlet vent is due to negative pressure occurred & removing heat through exhaust fan. Transport equation for momentum and turbulence parameter is solved with SIMPLE discretization scheme.

MATHEMATICAL MODELS

Mass con

+ . (

Mass con

+ . (

FL

ser

um

FL

ser

um

UE

vatio

) =

con

UE

vatio

) =

con

NT a

n e

m

serva

NT a

n e

m

serva

Conservation equations of mass and momentum for all flows are solved in ANSYS FLUENT and an additional equation for energy is solved for flows involving heat transfer. Flow inside a Solar Power Pack involves both fluid flow and fluid flow with heat transfer, hence governing equations [8] that are solved in re as listed below:

Moment

Moment

(

Where,

(

Where,

) +

) +

ti

)

ti

)

o

=

o

=

ua

ua

)

)

+

+

quation:

eq

is

.

eq

is

.

=

Ene

=

Ene

t

[gy c

t

[gy c

. (

stres

+

serva

. (

stres

+

serva

tenso

T)

ion eq

tenso

T)

ion eq

+

give

]

n:

+

give

]

n:

.

n by

.

n by

n tion:

,

,

( +

uati

uati

(

on

+

ove

(

on

+

ove

t

(

equatio

t

(

equatio

o

+ )

ns are

o

+ )

ns are

=

a ge

=

a ge

) +

orm

) +

orm

he s r

compressible and incompressible flows. The governing equations with no time derivative term states steady flow.

be Th Sta

be Th Sta

rbule

rd k-

) +

rbule

rd k-

) +

to nce

to nce

model

rbulen

)

model

rbulen

)

Also additional transport equations as shown low, need be solved since flow is turbulent.

e tu

nda

(

e tu

nda

(

Tu

(

Tu

(

used for this analysis is

+

+

el.

el.

+

+

ce mod

+

+

An

An

d

(

d

(

) +

) +

(

(

+

)

+

)

+

+

=

(

(

+

+

)

)

+

+

=

y vis

y vis

nera

nera

ion

ion

of

of

+

=

=

Where, turbulent or edd cosity,

he o

,

ues

he o

,

ues

vera

,

s be

vera

,

s be

issip

, a

:

issip

, a

:

p/>

and Gk & Gb represents the ge t turbulence kinetic energy due to mean velocity gradients and buoyancy. YM represents the contribution of the fluctuating dilation in compressible turbulence to t ll d ation rate.

ere ave

ere ave

el c ing

el c ing

=

=

H , the mod onstants C C C, nd

h the follow default val a low

C = 1.44 , C = 1.92 , C = 0.09, 1.0 ,

= 1.3

All the above mathematical models cannot be

solved by analytical method for complex flows. Hence all these equations are solved using FLUENT. Further in-depth details regarding mathematical models can be referred in FLUENT- Theory guide [8].

RESULTS AND DISCUSSION

2D RESULTS

It is stated in section 3.1.1, that the 2D analysis does not capture the overall problem objective but the main purpose of 2D analysis is to study different solver options, different Boundary conditions and effect of critical geometric parameters and understanding the velocity, pressure and temperature contours.

Figures shown below are the velocity (Fig. 12) and temperature contours (Fig. 13) for the SPP enclosure.

r

( )

The ab

r

( )

The ab

. . ( Sh

neral f of governing equations [8] and are valid for both

Fig. 12: Velocity contour for 2D domain

Fig. 13: Temperature contour for 2D domain

Maximum Velocity (m/s)

6.46

Maximum Temperature ()

57

Enclosure fluid Temperature rise (T) in ()

0.809

Table 1: 2D analysis results

Table-1 shows the results obtained from 2D analysis. Maximum temperature is found at the top surface of the Battery Bank and maximum velocity obviously near inlet and outlet. The locations of Battery Bank, Inverter and Controller are actual in 3D, where as in 2D their locations cannot be captured accurately, since 2D mid x-y plane is

considered. Further, locations of fan inlet and outlet vents are also approximate. Thus the results are expectedly not accurate, but certainly provide an insight of complex coupled flow and heat transfer problem.

3D RESULTS

3.5.2a. Velocity contours and Temperature contours

Fig. 14: Velocity contour for 3D domain

Fig. 15: Temperature contour for 3D domain

Maximum Velocity (m/s)

6.0

Maximum Temperature ()

42.5

Enclosure fluid Temperature rise (T) in ()

4

Table 2: 3D analysis results

Figures 14 & 15 show the velocity and temperature contours in 3D domain. The temperature contours near the Battery is shown in Fig. 16 and near the Inverter and Controller in Fig. 17. The maximum temperatures at the Inverter, Battery and Controller are shown in table-3. Though the overall velocity distribution is relatively uniform, the flows are relatively lesser at the Inverter resulting in higher temperature. Hence flows need to be optimized such that the temperatures of the devices are uniform.

Fig. 16: Temperature in Battery

Fig. 17: Temperature in Inverter and Controller

Table-2 shows the maximum velocity and temperatures in 3D analysis. Comparison of Table-

1 and Table-2, show that there is considerable difference in the values of maximum temperature, maximum velocity and temperature difference of fluid temperature. This is expected since 2-D and 3-D geometries are different.

The velocity stream line plot is as shown in Fig. 18.

Fig. 18: Velocity stream line plot

From the stream line plot it is quite clear that the flow is channeled in all four directions (Top, right, left & bottom) and the most predominant flow being in the top direction. Considering this there is scope to optimize the flow and a suitable Baffle at the right position can be provided to direct more air towards the Inverter. These are discussed in section 3.5.2c. Further the locations of inlet and outlet also are studied in section 3.5.2b to understand its effect on temperature distribution.

3.5.2b. Optimization of the location of inlet-vent and exhaust fan

Two different locations for the inlet vent have been studied (Fig. 19) and the results are shown in Table-4

Heat generating devices

Temperature obtained in

Battery

39

Inverter

42.5

Controller

34.61

Volume 3, IssuTeab1l7e 3: Temperature of Heat generating devicePsublished by, www.ijert.org 7

Fig. 19: Inlet-vent optimization

Devices

Temperature in

for inlet location-1

Temperature in

for inlet location-2

Battery

39

37.64

Inverter

42.5

47

Controller

34.61

38.2

Table 4: Results obtained by optimizing the location of inlet vent

Changing the location of inlet vent from location-1 to location-2, the Battery temperature is reduced

3.5.2c. Positioning of Baffle

As stated in section 3.5.2a, the flow is predominant in top direction, hence decided to provide Baffle at position-1 and position-2.

In the first analysis, Baffles without perforation are provided near the inlet to direct more air towards the Inverter (Fig. 21). Fig.22 gives the comparison of temperatures of heat devices. It is observed that position-2 is better since the maximum temperature in all devices is limited to 38.

but the temperatures of Inverter and Controller

have increased. Hence location-1 is optimum. Similarly, effect of two different outlet locations on temperatures has also been carried out (Fig. 20). It is found that there was no considerable change in

Fig. 21: Positioning of Baffle with no perforated vents

Devices temperature at different baffle

the temperatures of heat devices. For location-2,

position for baffle with no perforated vents

the distance between inlet to exhaust fan is lesser compared to location-1 and considerable amount of air escapes without cooling the heating devices. And hence is not preferred.

39.5

Temperature in deg.C

Temperature in deg.C

39

38.5

38

37.5

37

36.5

36

35.5

35

34.5

Devices

Temperature for Baffle position-1

Temperature for Baffle position-2

Fig. 20: Optimization of exhaust fan

Fig. 22: Devices temperature at different Baffle position for Baffle with no perforated vents

In the next analysis, perforated Baffles with rectangular holes are provided at position 2 as shown in Fig. 23. The openings provided on the Baffle are 50% of the total area of the Baffle.

Enclosure Pressure drop & Devices temperature for different SPP analysis type

45

40

35

30

25

20

15

10

5

0

With no Baffle Baffle with no Baffle with

perforated vents at rectangular position-2 perforated vents at

position-2

Enclosure Pressure drop & Devices temperature for different SPP analysis type

45

40

35

30

25

20

15

10

5

0

With no Baffle Baffle with no Baffle with

perforated vents at rectangular position-2 perforated vents at

position-2

Fig. 23: SPP with Baffle with perforated rectangular vents

Fig. 24 shows the comparison results for three different cases viz. i. With no Baffle ii. Baffle with no vents iii. Baffle with rectangular vents. It is evident that results are better with Baffe compared

Fig. 24: Comparison graph for Temperature and Pressure drop for SPP with Baffle & with no Baffle

n

n

Battery

Inverter

Battery

Inverter

Controller

Controller

Pressure drop

Battery

Pressure drop

Battery

Inverter

Inverter

Controller

Pressure drop

Controller

Pressure drop

Battery

Battery

Inverter

Controller

Inverter

Controller

Pressure drop

Pressure drop

COMPARISON OF RESULTS WITH ANALYTICAL RESULTS

Considering flow to be incompressible and steady, Applying simple mass balance i.e. flow at inlet = flow at outlet. Since same areas provided at both

to the case without Baffles. In the cases with Baffles, Baffle without vents gives reduced temperatures but with increased pressure drops.

3.5.2d. Pressure losses and Pumping power cost

Pressure drop is directly proportional to the Pumping power. Among the various cases studied, pressure losses are minimum for the case without Baffle and case with Baffle having rectangular

inlet and outlet, the velocity at both inlet and outlet

should be 6.0 m/s as per manual calculations. It is observed to be same from CFD as well. This is applicable for both 2-D & 3-D cases.

Similarly, considering heat balance, the heat dissipated by the heat devices should be equal to heat carried away by the fluid. This is verified in both 2-D & 3-D cases.

2-D case:

Fluid temperature rise by analytical method: 0.88

vents though the later is having

slightly lesser

Fluid temperature rise by CFD: 0.809

pressure drop (Fig. 24). It is obvious that Baffles result is higher drops at the entry, but pressure losses further downstream are also important. In general when the ventilation design is void of constrictions, pressure losses can be reduced which is also evident from CFD results. However, CFD plays a major role in determining the exact pressure drops which will be very useful to the designer.

3-D case:

Fluid temperature rise by analytical method: 4.0 Fluid temperature rise by CFD: 4.0

Thus it is evident that the CFD results are justified as both mass and heat balances are maintained.

3.7 CONCLUSIONS

The following conclusions can be drawn based on

CFD analysis carried out on Solar Power Pack

(SPP) enclosure consisting Battery Bank, Inverter and Controller.

1, CFD is very powerful tool to determine the exact pressure drops, maximum velocities and temperatures.

CFD also provides insight of the cooling and ventilation problem, by determining velocity and

temperature distributions. designer.

This will help the

Parametric studies have been carried out to understand the effect of following parameters:

Location of Inlet vent

Location of exhaust fan (outlet vent)

Provision of Baffles

Effect of Baffles with and without vents

It can be concluded that for minimizing temperatures, Baffles without vents are recommended though there is a higher pressure drop.

Considering both temperature and pressure drop, Baffle with rectangular holes is recommended.

It must be concluded that the present study is by no means exhaustive and there is further scope for optimization. However, the CFD results are very useful to the designer and these results will help him to make decisions faster. Further, they will aid in preparing a ready reckoner for cooling and ventilation design.

ACKNOWLEDGMENT

We would like to thank the Global Academy of Technology college management and Department of Mechanical Engineering, (VTU Research Centre) for providing us the facility to successfully complete this project and encouraging us in publishing paper. We also thank M/s. SunEdison for providing data at critical junctures and their overall support.

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Hoffman- A Pentair Company, Heat dissipation in Electrical enclosure, Technical information on Thermal Management of Electrical enclosures, Â©2003 Hoffman Enclosures Inc.

Bud Industries, Inc., Enclosure Design Tips Handbook, July 2007,

Â© Bud Industries Inc.

Mahendra Wankhede, Vivek Khaire, Dr. Avijit Goswami and Prof. S. D. Mahajan, Evaluation of cooling solutions for outdoor electronics, Journal on electronics cooling from electronics-cooling.com, Volume 16, No. 3, Fall 2010

Tom Kowalski and Amir Radmehr, Thermal Analysis of an Electronics Enclosure: Coupling Flow Network Modeling (FNM) and Computational Fluid Dynamics (CFD), no details

SÃ¼ddeutscher Verlag onpact (Rittal GmbH & Co. KG), Project Planning Manual: Enclosure Heat Dissipation, Â© 2009 by SÃ¼ddeutscher Verlag onpact

Anetis Stylianos, The process of heat transfer and fluid flow in CFD problems, American Journal of Science and Technology, 2014, 1(1): 36-49

A practical formula for air-cooled boards in ventilated enclosures, from link: http://www.electronics- cooling.com/1997/09/a-practical-formula-for-air-cooled- boards- in-ventilated-enclosures/

ANSYS Fluent User Guide, Release 15.0, Nov. 2013 and ANSYS Fluent 12.0, Theory guide, April 2009

H K Versteeg and W Malalasekara, Computational Fluid Dynamics- Finite Volume Method, Text book of CFD, edition 1995

Younus. A. Cengel, Text book of Heat transfer- chapter 15- cooling of electronic equipments