Experimental Analysis of Power Consumption in Ceiling Fan

Abstract

Ceiling fans are one of the main power consuming sources. Total power consumption is multiple of fan rotation frequency. As India is facing the power crisis it is important to reduce the power consumption in every power consuming device. Hence Power reduction in ceiling fan is perhaps one of the most important parameter. Every power reduction process starts with identification of power consumption sources. Ceiling fans are extensively used to create an indoor breeze, improve the space air distribution and hence enhance the feeling of comfort. The fan speed, diameter, number of blades, blade angle and vibrations all play an important role in deciding the power consumption. Few previous studies have investigated fan induced flow and its characteristics under different geometric and operating conditions .In this study ,response surface methodology is used to predict power consumption characteristics. The experiments were conducted based on the three different fans having three different blades, three room size, three different ceiling fan rod lengths three regulator knob positions and mathematical model was developed.

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IJRMET Vo l . 4, Is s u E 2, Ma y - oc T o b E R 2014
www.ijrmet.com InternatIonal Journal of research In MechanIcal engIneerIng & technology 43
ISSN : 2249-5762 (Online) | ISSN : 2249-5770 (Print)
Experimental Analysis of Power Consumption
in Ceiling Fan
1Rupesh V. Bhortake, 2Siddharth Gulavani, 3Darshan Satpute,
4Abhijit Landge, 5Vishwajeet Sankpal
1,2,3,4,5P.V.P.I.T., Pune, Maharashtra, India
Abstract
Ceiling fans are one of the main power consuming sources. Total
power consumption is multiple of fan rotation frequency. As India
is facing the power crisis it is important to reduce the power
consumption in every power consuming device. Hence Power
reduction in ceiling fan is perhaps one of the most important
parameter. Every power reduction process starts with identication
of power consumption sources. Ceiling fans are extensively used
to create an indoor breeze, improve the space air distribution and
hence enhance the feeling of comfort. The fan speed, diameter,
number of blades, blade angle and vibrations all play an important
role in deciding the power consumption. Few previous studies have
investigated fan induced ow and its characteristics under different
geometric and operating conditions .In this study ,response surface
methodology is used to predict power consumption characteristics.
The experiments were conducted based on the three different fans
having three different blades, three room size, three different ceiling
fan rod lengths three regulator knob positions and mathematical
model was developed.
Keywords
Response Surface Method, Ceiling Fan Power Consumption,
Optimization, MINTAB 16, L81 Array
I. Introduction
People feel discomfort when they get sweat in a space with a
stagnant air. Therefore people try to Create air breeze around
their bodies either naturally or mechanically to enhance body
Convective heat transfer .Air motion helps sweat evaporation
and accordingly brings body comfort feeling. Ceiling fans
are used in ofces; residences as an alternative in summer for
comfort. The ow pattern features induced by ceiling fans are
very helpful for people having interest working in this eld. So
knowing ow characteristics, as a result of ceiling fan rotation
would help improving the fan design in addition to selecting its
optimum placement to save energy. Therefore it is very important
to select and control the input parameters for power saving. Various
prediction methods can be applied to dene the desired output
variables through developing mathematical models to specify the
relationship between the input parameters and output variables.
The response surface methodology (RSM) is helpful in developing
a suitable approximation for the true function relationship between
the independent variables and the response variable that may
characterize the power level for ceiling fan.[1] It has been proved
by several researchers that efcient use of statistical design of
experimental techniques, allow development of an empirical
methodology, to incorporate a scientic approach in analysis of
ceiling fan power consumption .Even though sufcient literature
is available on analysis of ceiling fan power consumption, no
systematic study has been reported so far to correlate the process
parameters and power consumption. Hence, in this investigation,
the design was used to conduct experiments for exploring the
interdependence of the process parameters and second order
mathematical model for power consumption was developed from
the data obtained by conducting the experiments.
II. Experimental Identification of Important Parameters
From the literature and previous work done among many
independently controllable parameters affecting power
consumption, the parameters viz. Fan Blades (A), Room volume
(B), Downrod length (C) Fan speed (D)were selected as primary
parameters for the study. These parameters are contributing to the
power consumption in the ceiling fan. Different combinations of
parameters were used to carry out the trial runs. This was carried
out by varying one of the factors while keeping the rest of them
at constant values.
Table 1: Parameters Level selected for the Experimentation
Parameters
Levels
Low (1) Medium (2) High (3)
Fan(A) 2 3 4
Room Size ( m3) (B) 66.56 167.19 355.84
Rod Length (Inch)(C) 6.5 10.25 12
Speed Knob Position(D) 2 3 4
A. Conducting Experiments
For conducting experiments three different fans of various blades
mainly (2, 3, 4), three different room size, three different rod
length, and three different fan speed position were selected. Using
clamp meter power consumption level in (kW) was recorded. Rod
length for fan was measured. Reading in different room, using
different rod at different regulator knob position were recorded
as in observation table, (Table 1).
III. Development of Mathematical Model
A. Response Surface Methodology
Response Surface Methodology (RSM) is a collection of
mathematical and statistical technique useful for analyzing
problems in which several independent variables or responses are
considered to optimize the desired output. In many experimental
conditions, it is possible to represent independent factors in
quantitative form as given in Eq. (1).Then these factors can be
thought of as having a functional relationship or response as
follows:
Y=Φ(x1, x2…xk) Eq.(1).
Between the response Y and x1, x2… xk of k quantitative factors,
the function Φ is called response surface or response function.
For a given set of independent variables, a characteristic surface is
responded. In the present investigation, RSM has been applied for
developing the mathematical model for characteristics of power.
[7] In applying the response surface methodology, the independent
variable was viewed as surface to which a mathematical model
is tted.

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Table 2: Observation Table
Run
Order
Fan
blades
Room
Volume
Down
rod
Length
Fan
speed
Energy
Consumption
1 1 1 1 1 0.386604
2 1 1 1 2 0.447822
3 1 1 1 3 0.522816
4 1 1 2 1 0.379848
5 1 1 2 2 0.44478
6 1 1 2 3 0.513646
7 1 1 3 1 0.38173
8 1 1 3 2 0.443813
9 1 1 3 3 0.518221
10 1 2 1 1 0.366597
11 1 2 1 2 0.426765
12 1 2 1 3 0.481712
13 1 2 2 1 0.377185
14 1 2 2 2 0.439589
15 1 2 2 3 0.508561
16 1 2 3 1 0.374164
17 1 2 3 2 0.428505
18 1 2 3 3 0.494278
19 1 3 1 1 0.379691
20 1 3 1 2 0.442081
21 1 3 1 3 0.514178
22 1 3 2 1 0.375094
23 1 3 2 2 0.434157
24 1 3 2 3 0.497448
25 1 3 3 1 0.355169
26 1 3 3 2 0.416342
27 1 3 3 3 0.483553
28 2 1 1 1 0.332564
29 2 1 1 2 0.393652
30 2 1 1 3 0.486167
31 2 1 2 1 0.34351
32 2 1 2 2 0.412415
33 2 1 2 3 0.521486
34 2 1 3 1 0.347231
35 2 1 3 2 0.423069
36 2 1 3 3 0.539721
37 2 2 1 1 0.331019
38 2 2 1 2 0.404062
39 2 2 1 3 0.509884
40 2 2 2 1 0.316716
41 2 2 2 2 0.376953
42 2 2 2 3 0.454104
43 2 2 3 1 0.341376
44 2 2 3 2 0.406711
45 2 2 3 3 0.513912
46 2 3 1 1 0.341376
47 2 3 1 2 0.405748
48 2 3 1 3 0.510413
49 2 3 2 1 0.31456
50 2 3 2 2 0.374396
51 2 3 2 3 0.461948
52 2 3 3 1 0.334897
53 2 3 3 2 0.400037
54 2 3 3 3 0.505121
55 3 1 1 1 0.33479
56 3 1 1 2 0.403581
57 3 1 1 3 0.478373
58 3 1 2 1 0.335458
59 3 1 2 2 0.40045
60 3 1 2 3 0.467309
61 3 1 3 1 0.340704
62 3 1 3 2 0.410222
63 3 1 3 3 0.47915
64 3 2 1 1 0.334233
65 3 2 1 2 0.398412
66 3 2 1 3 0.471664
67 3 2 2 1 0.328381
68 3 2 2 2 0.394842
69 3 2 2 3 0.454356
70 3 2 3 1 0.328601
71 3 2 3 2 0.395556
72 3 2 3 3 0.447321
73 3 3 1 1 0.332906
74 3 3 1 2 0.400756
75 3 3 1 3 0.468077
76 3 3 2 1 0.328381
77 3 3 2 2 0.39181
78 3 3 2 3 0.45764
79 3 3 3 1 0.341152
80 3 3 3 2 0.40623
81 3 3 3 3 0.470896
The mathematical equations for energy consumption by using
Response Surface Method (RSM) is,
Energy Consumption= 0.41653-0.01913*A-0.0063
9*+0.00040*C+0.07126*D+0.00248*AB+0.00193*
AC+0.00088*AD-0.00499*BC-0.00218*BD+0.0001
0*CD+0.00294*ABC-0.00007*ABD-0.00119*ACD-
0.00185*BCD+0.00038*ABCD
Where,
A=Fan blades level
B=Room Volume
C=Down rod length
D=Fan speed
B. Optimizing Parameters
Contour plots show distinctive circular shape indicative of possible
independence of factors with response [7]. Contour plots play
a very important role in the study of the response surface. By

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generating contour plots using software for response surface
analysis, the optimum is located with reasonable accuracy by
characterizing the shape of the surface. If a contour patterning of
circular shaped contours occurs, it tends to suggest independence
of factor effects while elliptical contours as may indicate factor
interactions Response surfaces have been developed for both
the models, taking two parameters in the middle level and two
parameters in the X and Y axis and response in Z axis. The response
surfaces clearly reveal the optimal response point. RSM is used to
nd the optimal set of process parameters that produce a maximum
or minimum value of the response. In the present investigation
the process parameters corresponding to the power consumption
are considered as optimum. Hence, when these optimized process
parameters are used, then it will be possible to attain the minimum
power consumption. Figure1 presents three dimensional response
surface plots for the power consumption. The surface plots
generated are almost circular which reveals that there is lest
dependency of the parameters on the power consumption.
C. Surface Plots
3
0.40
2
0.45
0.50
1
0.55
21
3
Ener gy C onsumpt ion
Fan speed
Downr od Le ngth
Fan 1
Room Volume 1
Hold Values
Surface Plot of Energy Consumption vs Fan speed, Downrod Length
3
0.35
2
0.40
0.45
1
0.50
2 1
3
Ener gy C onsumpt ion
Fan speed
Fan
Room Volume 1
Downr od Length 1
Hold Values
Surface Plot of Energy Consumption vs Fan speed, Fan
3
0.32 2
0.34
0.36
1
0.38
21
3
Ener gy C onsumpt ion
Downr od Le ngth
Fan
Room Volume 1
Fan speed 1
Hold Values
Surface Plot of Energy Consumption vs Downrod Length, Fan
3
0.40
2
0.45
0.50
1
0.55
21
3
Ener gy C onsump tion
Fan speed
Downr od Le ngth
Fan 1
Room Volume 1
Hold Values
Surface Plot of Energy Consumption vs Fan speed, Downrod Length
3
0.32 2
0.34
0.36
1
2 1
3
Ener gy C onsump tion
Room Volum e
Fan
Down rod Length 1
Fan speed 1
Hold Values
Surface Plot of Energy Consumption vs Room Volume, Fan
3
0.35
2
0.40
0.45
1
0.50
2 1
3
Ener gy C onsump tion
Fan speed
Fan
Room Volume 1
Down rod Length 1
Hold Values
Surface Plot of Energy Consumption vs Fan speed, Fan
Fig. 1: Surface Plots for Power Consumption
D. Contour Plots
Fan
Room Volume
3.02.52.01.51.0
3.0
2.5
2.0
1.5
1.0
Down rod Length 1
Fan speed 1
Hold Values
>
–
–
–
< 0.33
0.33 0.34
0.34 0.35
0.35 0.36
0.36
Con sumption
Energy
Contour Plot of Energy Consumption vs Room Volume, Fan

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Room Volume
Fan speed
3.02.52.01.51.0
3.0
2.5
2.0
1.5
1.0
Fan 1
Down rod Length 1
Hold Values
>
–
–
–
–
–
–
< 0.38
0.38 0.40
0.40 0.42
0.42 0.44
0.44 0.46
0.46 0.48
0.48 0.50
0.50
Con sumption
Energy
Contour Plot of Energy Consumption vs Fan speed, Room Volume
Fan
Downrod Length
3.02.52.01.51.0
3.0
2.5
2.0
1.5
1.0
Room Volume 1
Fan speed 1
Hold Values
>
–
–
–
–
< 0.33
0.33 0.34
0.34 0.35
0.35 0.36
0.36 0.37
0.37
Con sumption
Energy
Contour Plot of Energy Consumption vs Downrod Length, Fan
Fan
Fan speed
3.02.52.01.51.0
3.0
2.5
2.0
1.5
1.0
Room Volume 1
Down rod Length 1
Hold Values
>
–
–
–
< 0.35
0.35 0.40
0.40 0.45
0.45 0.50
0.50
Con sumption
Energy
Contour Plot of Energy Consumption vs Fan speed, Fan
Fig. 2: Contour Plots for Power Consumption
E. Response Optimization
Table 3: Parameters for Optimization
parameter
goal
Lower
Target
Upper
Weight
Import
Energy
Consumption Minimum 0.315 0.315 0.53 11 1
Cur
High
Low
0.86645
D
Optimal
d = 0.94791
Minimum
Energy C
y = 0.3263
d = 0.79200
Minimum
Vibratio
y = 2.5711
0.86645
Desirability
Composite
1.0
3.0
1.0
3.0
1.0
3.0
1.0
3.0
Room Vol Dow nrod Fan speeFan
[3.0] [3.0] [3.0] [1.0]
Fig. 3: Optimization Plot
F. Global Solution
Fan blades level = 3
Room Volume = 3
Down rod Length = 1
Fan speed = 1
Energy Consumption = 0.320608,
Desirability = 0.974156
Composite Desirability = 0.974156
IV. Conclusion
From the experimentation we got the global value of power
consumption 0.315 kW with the set up of Fan having four blades,
355.84 m3 Room Volume, 12 inch Downrod length and Desirability
function of 0.947912 which is the Probability of achieving power
consumption.
References
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Paramerter of a Backward-Inclined Centrifugal Fan Using DOE
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[2] DUAN Fajie,“Research on Detecting Technology of
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Mr. Rupesh V. Bhortake received the
Master of from University of Pune,
Maharashtra, India, and he is doing
his Ph.D. in Mechanical Engineering
at North Maharashtra University,
Maharashtra, India. At present he is
working as an Associate Professor in
TSSM’s, Padmabhooshan Vasantdata
Patil Institute of Technology, Bavdhan,
Pune -411021, Maharashtra. Mr.
Rupesh Bhortake is a also lifetime
member of Indian Society for
Technical Education. (ISTE), Institute of Engineers and ASME.
His interesting area of research is Noise and Vibration.
Mr. Siddharth.Gulavani is a student
of nal year mechanical Engineering
studying at department of Mechanical
Engineering TSSM’s, Padmabhooshan
Vasantdata Patil Institute of Technology,
Bavdhan, Pune, MS, India.
Mr. Darshan Satpute is a student of
final year mechanical Engineering
studying at department of Mechanical
Engineering TSSM’s, Padmabhooshan
Vasantdata Patil Institute of Technology,
Bavdhan, Pune, MS, India.
Mr. Vishwajeet Sankpal is a student
of nal year mechanical Engineering
studying at department of Mechanical
Engineering TSSM’s, Padmabhooshan
Vasantdata Patil Institute of Technology,
Bavdhan, Pune, MS, India.
Mr. Abhijit Landge is a student of nal
year mechanical Engineering studying at
department of Mechanical Engineering
TSSM’s, Padmabhooshan Vasantdata
Patil Institute of Technology, Bavdhan,
Pune, MS, India.