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Abstract--This paper presents how the efficiency of solar cell

can be increased with the design of compound parabolic concentrator (CPC) and the implementation of sun tracking system. Sun tracking systems is an application of the Machine Vision (MV) and collaboration with Data Acquisition (DAQ) to systems by using a webcamera as a sensor and sound card as an output channel to drive a motor. The motors will react as the mechanism of the camera to make sure it always focuses on the target of sun. By using a MatLab software programming environment, closes loop control is implemented to provide interaction between camera and sound card as a device to control the motor to track the sun. Sun tracking system with webcamera will be an effective tool to increase the efficiency of the solar cells. Camera is the sensor of the system, be an eye of the human to take care and observe the sun. As soon the sun can be tracked with the CPC, the voltage, current and power received will always be at the maximum of the efficiency. This research could provide significant improvement in alternative energy.

Index Terms--Solar Cell, Efficiency, Compound Parabolic Concentrator, Sun Tracking System.

I. INTRODUCTION UNLIGHT is a source of energy regarded as an alternative source of energy along with other alternative source such

as hydrogen and natural gas. Solar energy is a vital that can make environment friendly energy more flexible, cost effective and commercially widespread. Photovoltaic source are widely used today in many applications such as battery charging, water heating system, satellite power system, and others. Although the installation cost is high but the advantage of photovoltaic source is free. The problem identification for the PV solar cell is that it has low efficiency if the position of the solar cell is in static location. It needs maximum heat sun light to produce the highest efficiency. Therefore, the compound parabolic concentrator is developed to solve this problem. When the sun tracking system is combined with the compound parabolic, it can produce the voltage in the maximum efficiency. Compound parabolic concentrator is a

E. Hossain is with the Department of Mechatronics Engineering, International Islamic University Malaysia, Gombak, Kuala Lumpur 53100, Malaysia (e-mail: G0724663@stud.iiu.edu.my).

R. Muhida is with the Department of Mechatronics Engineering, International Islamic University Malaysia, Gombak, Kuala Lumpur 53100, Malaysia (e-mail: muhida@iiu.edu.my).

A. Ali is with the Department of Mechanical Engineering, Lawrence Technological University, Southfield, MI 48075 USA (e-mail: aali@ltu.edu).

significant of photovoltaic source because it is the combination of parabolic concentrator and the solar panel. The purpose of using parabolic concentrator is to get the ray reflection of light at the highest efficiency and to get the source of energy at the maximum value. The development of this system is as an alternative of power source and also to increase the source of the electricity at the highest efficiency from morning until afternoon.

Solar radiation can be converted into useful energy directly, using various technologies. In order to get the maximum efficiency of solar cell, the sun has to be monitored from time to time when it appears and it is called sun tracking systems. Currently there are some projects related to the sun tracking systems, but almost all of them were using photosensitivity sensors as devices. The construction of a mechanism which follows the sun is not a new problem. The first attempt in Chile was completely mechanical, done by Finster in 1962 [1]. Later Saavedra [2] presented a mechanism with automatic electronic control. It was used to orient an Eppley pyrheliometer. A recent review of the existing systems has been published by Myers et al. [3]. Roth, Georgiev, and Boudinov [4] presented a design and construction of a system for sun-tracking in their paper. In this research, the webcamera and sound card are chosen as alternative devices to get the best performance of the tracking system with machine vision method and data acquisition (DAQ). By using the webcamera as a sensor, we have to implement the machine vision techniques in order to make the systems look perfect.

The main objective is to increase the efficiency of solar cells by using a compound parabolic concentrator with the implementation of the sun tracking systems. This objective is concerned with detecting an object exists in the field of view of the camera. The implemented algorithm will be able to track lies in the field of view of the camera. Then, the motion control will be executed to command the camera to move such that the object will lie at the center of the camera, i.e., center of the object. The success of the tracking activity depends on an efficient feature extraction algorithm. A step by step procedure is designed and developed. In this system, the camera is connected to the computer, and then computer will capture the image via MATLAB SIMULINK. The image will be processed to reduce any noise detected and clarify between the object and background. The image appears only represent in black and white colors and the image is analyzed to

Efficiency Improvement of Solar Cell Using Compound Parabolic Concentrator and Sun

Tracking System Eklas Hossain, Riza Muhida, and Ahad Ali, Member, IEEE

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2008 IEEE Electrical Power & Energy Conference

978-1-4244-2895-3/08/$25.00 ©2008 IEEE

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determine how many objects appear in the image. The object presence is determined its location in the image. Then all the data is sent to be processed with the DAQ method. The DAQ will identify the position of object and assign the motor to reacts according to the instruction given. The combination between the Machine Vision method and DAQ make the system perfect and powerful. The task is to compile both programs as one where the true value of centroid will be automatically displayed on the front panel once the object is detected in the field of view of the camera. The camera then will automatically moves to the centroid of the object. This will definitely reduce the processing time and finally the cost to run the system.

II. DESIGN CONFIGURATION AND SELECTION Figure 1 illustrates the design with the base design by using

Catia and Autocad. The design is used to measure and plot the dimension of the prototype. It can be used as a guideline before start doing assembly process of the prototype. Two types of DC motor are used; the 6W DC motor for pan rotation of the CPC, and 40W DC motor for tilt rotation of the base. The worm gear is combined with the 6W DC motor to make the CPC rotate and hold its position when the motor stop. The worm gear is combining with spur gear with ratio reduction 10:1. The DC motor also is combined with the gear head. The gear head is used to reduce the speed from high rotation to slow rotation with reduction ratio 50:1. Therefore, the combination of both reduction gears will produce 500:1 of the reduction speed. The slow rotation of the CPC is important because the movement of the sun is slow and it is easy to control the position of the CPC when doing the tracking process. The reduction gear for base rotation is also same as 6W DC motor.

Fig. 1. Base design and full design

Figure 2 illustrates the dimension of the CPC. The material that use in designing compound parabolic concentrator are aluminum beam for supporting base, stainless steel for reflection, and camera as a sensor. The most important part in designing CPC is the focus point location of the solar cell. The focus point is the place where the location of the sunray is reflected on that point. Figure 3 illustrates the curve and calculation of the CPC. From the calculation shows that the focus point of the reflection is 15cm. therefore, the solar cell should be located at this position.

Fig.2. The dimension of the compound parabolic concentrator

Fig.3. The curve of the parabola and focus point

Fig. 4. Flow diagram

III. VISUAL TRUCKING SYSTEM DESIGN Web camera is the main sensor. It plays the main role to

make sure the sun always in the ways in order to get higher efficiency of solar cells. It basically captures the image of the environment and detects the presence of the targeted object. Image processing is done to determine the offset of the object from the center position of the camera field of view, and thus directing the mechanism to align the center of the image to the centroid of the image. Figure 4 shows the flow diagram.

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Fig. 5. System flow functionality

Figure 5 shows that the system uses web camera as a sensor detector of the sun. Then it will connect with computer and process by using matlab programming. In this program the image will process by using simulink image processing tool. From the matlab programming, it will be used to determine the center position of the sun. The signal will be created from the matlab programming to create the PWM (Pulse Width Modulation) to control the speed of motor. This system uses two types of signal, sound card from motherboard and external sound card. The signal from the sound card produce negative and positive signal. The signal positive signal will generate the forward rotation and the negative signal will generate backward rotation. The output signal is applied at the H bridge circuit and amplified with Opamp. The opamp is used to amplify the signal to increase the value of the output voltage. This two sound card will control the motor at tilt rotation and pan rotation. The rotation of the motor is used to make the position of the camera center with the sun position.

The controlling system for the sun tracking system uses MATLAB simulink programming and M file to control the speed of motor rotation is shown in Figure 6. Basically, the MATLAB simulink is used to process the data and image processing of the sun. The process that includes in the image processing step is thresholding, median filter, image enhancement, centroid and quadrant of the image. All the steps are important because it is the way to determine the center position of the sun with camera. Part A is included the process of the image processing. It is also include the pixel adjustment of the camera. The adjustment of the pixel is very important because it can protect the camera from any damage. From the image processing, the position of the camera will be controlled by using M file coding to generate the PWM signal. The PWM signal is produced at the sound card. All the controlling motor rotation is at part B. The motor of tilt and pan rotation is controlled at this part and it will default condition when the position of the camera and sun is centered. The centroid position of the camera is displayed at the centroid display. The pulse generator is used to generate the controlling system according whatever time we want. In this system, the system is set to do the process for every 30 second. Therefore, the process of the controlling system will be generating in every 30 second.

Fig. 6. Main Program of the whole controlling system in SIMULINK

The main program of the systems consists of the video

input from the camera. Since the sun cannot be seen by the normal ways, the camera has to be filtered to reduce the ultraviolet radiation. To solve this problem, the camera lens is filtered with the thin film inside the floppy disk. The video input is then converted from RGB colors to grayscale in intensity color to start the image processing. There is two parts in the main program which are part A and part B. part A will concentrate to the image processing and part B is focused to the data acquisition systems and link to the coding in M File. Both parts will be described in details. In this figure, the video input will always enable because it is running in a real time. Thus, a special pulse generation block is added to generate square wave pulses at regular intervals. An enable block is added in the part A and a trigger is added in part B. The block's waveform parameters, Amplitude, Pulse Width, Period, and Phase Delay, determine the shape of the output waveform. Figure 7 shows how each parameter affects the waveform.

Fig. 7. Block waveform parameter

The block's Pulse type parameter allows user to specify whether the block's output is time-based or sample-based. This time, the time-based is selected where Simulink computes the block's outputs only at times when the output actually changes. This can result in fewer computations being required to compute the block's output over the simulation time period. The step size such that the period, phase delay, and pulse width (in seconds) are integer multiples of the step size is specified.

The camera is placed at the main program because it cannot be stop during the real time. It will always see the object and the filter has to be added at the lens of camera. Here the pixel of camera is set to 240 x 320 pixels; it means that the pixels have 240 rows and 320 columns. The details of the camera and the image view are shown in Figure 8.

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Fig. 8. (a) Description of camera (b) image seen from the camera

A. Part A In this part, the image is captured, processed and analyzed.

An enable block is added to enable a subsystem. Figure 9 shows the flowchart of part A. Part A includes major parts of image processing. The image data received from the main program will be processed in part C, D, and E. all the details of those parts are described in details later.

Fig. 9. Part A; Image Processing

In this part, the output port from part C is sent to insert label block and part D. Number of object block shows how many object appear in the image after the system count the presence of the object. The only one object is considered to make sure the system can perform the task smoothly. Otherwise, the object could be failed to be tracked. Insert label block is used to type any label to show the appearance of the object. Here, the label is represented by “Object detected:”. The detail is shown in the Figure 10.

Fig. 10. The image after the centroid is detected and label is inserted

B. Part C In this part, the enhancement processed is done. Figure 11

shows image is started with the gamma correction block. Gamma correction block is used to apply or remove gamma

correction from an image or video stream. Typical gamma values range from 1 to 3. Most monitor gamma values range from 1.8 to 2.2. Then, the median filter block is added. The median filter is used to replaces the central value of an M-by-N neighborhood with its median value. After these two processes like gamma correction and media filter is completed, the image is enhanced.

Fig. 11. Part C; Image Enhancement Process

C. Part D They are threshold process, morphology operation process

and blob analysis. Image data after enhancement is then converted to white and black color by suing the threshold block. The threshold block is used to convert an intensity image to a binary image using a threshold value computed using Otsu's method. The block computes this threshold value by splitting the histogram of the input image such that the variance of each pixel group is minimized.

After the threshold process, the entire image is converted to black and white color only. From here, the process of the morphology operation will become easier. The image of the threshold process is shown in Figure 12.

Fig. 12. Threshold image

The morphology operation includes erosion and dilation

process. The erosion is used to find local minima in binary or intensity images. The Erosion block slides the neighborhood or structuring element over an image, finds the local minima, and creates the output matrix from these minimum values. Meanwhile, the dilation is used to find local maxima in binary or intensity images. The Dilation block rotates the

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neighborhood or structuring element 180 degrees. Then it slides the neighborhood or structuring element over an image, finds the local maxima, and creates the output matrix from these maximum values.

The blob analysis starts after the morphology operation finished. The blob analysis block is used to calculate statistics for labeled regions in a binary image. The block returns some quantities, such as the Centroid, as values that represent spatial coordinate locations. Locations can be specified in images using various coordinate systems. This topic discusses pixel coordinates and spatial coordinates, which are the two main coordinate systems used in the Video and Image Processing Blockset. Since the process is performed in pixels, the pixel coordinate is chosen.

For pixel coordinates, the first component r (the row) increases downward, while the second component c (the column) increases to the right. Pixel coordinates are integer values and range between 0 and the length of the row or column. Note that the pixel coordinates used in the Video and Image Processing Blockset are zero based, while the pixel coordinates used by the Image Processing Toolbox and MATLAB are one based. Thus, the pixel coordinates used here are zero based. According to the main program, there is a display block for centroid. The upper box displays the rows pixel; the lower box displays the columns pixel. The details of the image and its centroid are shown in Figure 13.

Fig. 13. Image centroid with the Centroid display block

D. Part E This part is used to mark the centroid of the object. How

many object appears in the image, this part will create the circle to mark each of the object presence. Therefore, in the process before, the only one object is allowed to appear to make sure the process of data acquisition can be performed well to tracking system. Part E is shown in Figure 14.

E. Part B After all the steps in the image processing done, the centroid of image is identified, and the coordinate is determined, then the data is transferred to the data acquisition in the M-Files editor. In part B, the MATLAB function block is used to hyperlink between the SIMULINK and the M-Files editor. Figure 15 shows the how coding in the M-Files editor is connected to the SIMULINK. From the main program Part B received the data from two sources; the pulse generator block and the part A. the part B will only enable when the pulse generator is enable. Then, the triggered subsystem will allow the part B to receive the data from part A and process the data.

Fig. 14. Part E; Mark circle in centroid of object

Fig. 15. Data Acquisition

The MATLAB function in Figure 15 will call the coding in

the M-Files editor through the ‘move (u)’ instruction. Then in the M-Files editor, the function a = move ( ) is used the received the command from SIMULINK. The alphabet ‘a’ in the function is used to specify the next instruction with other coding in order to run the entire motor and rotation needed.

IV. DEVELOPMENT OF DATA ACQUISITION We have used a new theory and concept of communication

with external device. The external device contains of three ports which are parallel port, serial port and sound card. Since the only sound card is used, thus the only development of DAQ by using sound card is focused. Sound card is commonly used in the PC. This port is used to give the sound output from the computer. It is easier to be used and control in any time. The advantage of using sound card cheaper, easy to install, and can be installed in a PC more than one, can configure property values, acquire data and can close the device.

Before proceed to the details of how the data acquisition can produce a signal PWM through sound card, its better to understand the way how the sound card will work efficiently. This command is used to determine analog input or output will be used. The other device like nidaq, shows the NI Data Acquisition Card is used instead. The number ‘0’ represent the port sound card is being used. Here, the built-in sound card is used. To add more sound cards to be used, the ‘0’ will be replaced with number 1, 2, and so on. We can specify any waveforms like sinusoidal, square, triangle, sawtooth, chirp and sinc waveform as needed. Since we want the output is produced like PWM waveform, the square wave is chosen. Linspace in the command is used to generate linearly spaced vector. The best thing here, since the waveform is set in square, the duty cycle can be controlled like in the PWM circuits and its range from 1 to 100%. The output PWM and

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how the duty cycle is controlled shown in Figure 16.

Fig. 16. PWM signals with duty cycles

Since we want to control the left and right channel of the sound, one of the data must be equal to zero. The above command shows the left data (zerobuffer) is set zero to allow the right channel from the sound card to perform only. If this is applied to the dc motor, the dc motor will rotate to the right. Otherwise, the left data will perform and the dc motor will rotate to the left. This time, the dc motor will set to always rotate to the right. Before the output can be applied to the dc motor to run it, a simple circuit must be added which is shown in Figure 17.

Fig. 17. Flow of the M-files editor to run the dc motor

Previous section is only to make the rotation of the motor

forward and backward. It is only sub program from the main program. The main program is very important because it is used to make the rotation for the both DC motor. To control the direction of the motors for the pan-tilt mechanism system, the quadrant approach is used.

The quadrant approach is implemented. The center of the image is set at the coordinate (160, 120). Since the motor cannot be controlled in terms of the distance, the tolerance is created to allow the motor to rest if the object is detected in the boundary of the tolerance. The frame is set to move left and up if the object appears in the Q1. It is set to move right and down if the object appears in the Q4 and so forth. The symbol X and Y are referred to the pan and tilt motor respectively.

V. INTERFACE HARDWARE AND SOFTWARE Interface hardware and software are a crucial task by itself

as it links all components together for complete operation of the Sun Tracking System. Prior interfacing them together, all the required hardware and software are first identified. The choice of hardware and software and how all the components involved are interfaced together.

A. MOSFET IRF 530

Metal Oxide Semiconductor Field-Effect Transistors (MOSFET) is used as an ON/OFF switch to run the motor. Figure 18 shows the switching operation of a MOSFET. For the N-channel device the drain is always biased positive relative to the source. The gate-to-source voltage VGS is the input voltage, which is used to control the resistance between drain and source and therefore determines whether devices is on or off. When VGS = 0, there is no conductive channel between source and drain, and the devices is off. The MOSFET will remain off as long as VGS is zero or negative. Typically when threshold is reached or VT = +1.5V for N-MOSFET, will cause the MOSFET to conduct. Generally, a value of VGS much larger than VT is used to turn on the MOSFET more completely.

Fig. 18. Switching operation of a MOSFET

B. Half-Bridge Circuit (H-Bridge) To control the direction of the motor to run in clockwise or

counterclockwise, the H-Bridge circuit of four MOSFETs is needed. H-Bridge is very useful to control the direction of the dc motor. Figure 19 shows the H-Bridge circuit by using the MOSFET as a switch. The input gate (G) G1 is connected parallel with the G4, similarly the gate G2 is connected parallel with the G3. These both parallel inputs are connected from the output gain amplifier. If the output gain amplifier one is set ON, the gate G1 and G4 will be enable. Otherwise, if the output gain amplifier two is set ON, the gate G2 and G3 will enable. The two operations are shown in Figure 20.

To operate the systems, the user has to click the play button in the SIMULINK browser. Before that, the time is set to infinite to make sure the systems will always running al the times. First, the image will be captured. Then, image will be processed in the MATLAB SIMULINK until the real image appears in black and white colors only. The image of camera is represented by frame and the frame can be split into four regions. The object is determined by region it detected and MATLAB sends the data from the analog output from sound card to the motor to move the parabola. The output from sound card will pass through the op-amp to increase the voltage with the gain set and enter the H-Bridge circuit. The motor will rotate according to the output from the entire sound card and the H-bridge circuit used. One H-bridge circuit is used for one output channel from sound card. The image will be scanned again and the motor will run until the image appears at the center of the frame. The camera will always capture the image and send data to the motor if the object is not at the center of the image. The system is complete when

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the camera can act as an eye and the motors can run as an actuator of the system.

Fig. 19. H-Bridge Circuit

Fig. 20. Operation of H-Bridge Circuit

VI. RESULTS AND DISCUSSION There are two test of the experiment that has done to test

the efficiency of solar cell. The test is making the comparison between the efficiency of solar cell at the CPC and horizontal position. Thus, the measurement of the voltage, and temperature of the solar cell surface for both solar cell are recorded. Then, the results are recorded for every 10minute when the sun ray is at the highest temperature. The result of the experiment has been done from 11.30 am until at 1p.m. The results are including the measurement of voltage, current and temperature of solar surface area.

TABLE I RESULTS FOR CPC

Time Voltage Current Temperature 11.30 4.27 0.211 33.9 11.40 4.50 0.223 37.2 11.50 4.26 0.211 60.0 12.00 4.42 0.219 101.0 12.10 4.56 0.226 119.7 12.20 4.66 0.231 124.0 12.30 4.76 0.236 106.2 12.40 4.63 0.229 122.7 12.50 4.70 0.233 130.0 1.00 4.65 0.230 130.8

From the result shows in Table 1 that the temperatures of

the solar cell surface are increased because of the reflection of the sun ray at one focus point. The solar cell is located at the focus point of the parabola. Therefore, all the reflection is focus on the solar cell. The maximum of solar cell requirement for this solar cell is 4.23V. From this experiment, the voltage

of the solar cell can be increased when the temperature is high. Therefore, the voltage of the solar cell can be increased to the highest level of voltage requirement when the temperature is high. From the result shown in Table.2, the current and voltage for the 0 degree of solar cell are different with the value of the solar cell at the CPC. The temperatures of the solar cell also are less than the temperature of the CPC. This is because of the position of the solar cell at the horizontal position ant the sun ray doesn’t focus at the surface of the solar cell. Then, the solar cell can only generate the voltage at the maximum requirement of the solar cell.

TABLE II RESULTS FOR 0 DEGREE OF SOLAR CELL

Time Voltage Current Temperature 11.30 3.99 0.198 33.2 11.40 4.02 0.199 36.2 11.50 3.92 0.194 50.0 12.00 3.92 0.194 51 12.10 3.81 0.189 52 12.20 3.95 0.196 51.8 12.30 3.95 0.196 49.8 12.40 3.93 0.195 47.6 12.50 3.95 0.196 51.4 1.00 3.92 0.194 50.9

The second experiment test result started from 10 am until

2pm which is shown in Table 3. The voltage that produces from the solar cell should be recorded for every 10 minute. There are some problems happened during the second test. The main problem is the weather on that day is too hot and we have facing the problem on the image processing. Therefore, some adjustment of the image processing has been modified to filter the noise and also to get the centroid of the sun. The result of voltage and temperature is recorded. The solar cell is joining with resistance value 20.2 ohm for CPC and 19.2 ohm for non-CPC is combine series with the solar cell. The purpose of connect the resistance is to calculate the current that produce from the solar cell. From the result, we can make the calculation of the power, and current for both solar cells. The result from the experiment is compared between both solar cells to look the different efficiency for the solar cell. The result in this experiment is shown in Table 3.

According to the experiment that we have done, the result shows the efficiency of solar cell by using Compound Parabolic Concentrator (CPC) and the implementation of sun tracking system is highly better than the normal solar cell. The maximum voltage that we can get under load 20 Ω resistor is 4.85V meanwhile the normal solar cell only can get the maximum 4.02V. If we divided both voltages with the load, we get the maximum current 0.235 Ampere compared to 0.196 Ampere by using the normal solar cell. The temperature also give an outstanding value which is achieved the maximum 156.20°C by using CPC hotter than 60.80°C in the normal ways. The power also shows the 1.1419 Watt compared to 0.7563 Watt. Thus, with all this result that we get, it shows that the efficiency of solar cells can be increased by using

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CPC and the implementation of the sun tracking system.

TABLE III RESULTS FOR THE SECOND EXPERIMENT

Time Voltage, V Temperature, T Power, P

CPCNon CPC CPC Non CPC CPC Non CPC10.00 4.53 3.99 41.90 42.00 0.996 0.812 10.10 4.52 4.02 121.70 41.90 0.991 0.824 10.20 4.20 4.02 121.70 47.50 0.856 0.824 10.30 4.80 3.93 122.20 46.10 1.118 0.788 10.40 4.70 3.90 120.90 51.50 1.072 0.776 10.50 4.77 3.86 117.70 51.60 1.104 0.760 11.00 4.76 3.87 119.00 50.00 1.099 0.764 11.10 4.74 3.96 98.00 47.50 1.090 0.800 11.20 4.84 3.91 127.50 50.60 1.137 0.780 11.30 4.62 3.85 128.70 52.30 1.036 0.756 11.40 4.76 3.85 135.30 52.60 1.099 0.756 11.50 4.75 3.81 126.10 57.40 1.095 0.740 12.00 4.85 3.85 122.30 55.50 1.141 0.756 12.10 4.74 3.81 123.40 56.60 1.090 0.740 12.20 4.79 3.96 129.50 52.30 1.113 0.800 12.30 4.82 3.91 146.10 55.70 1.127 0.780 12.40 4.72 3.95 129.10 55.40 1.081 0.796 12.50 4.74 3.94 130.40 55.60 1.090 0.792 13.00 4.50 3.90 121.20 49.20 0.983 0.776 13.10 4.72 3.98 129.00 50.10 1.081 0.808 13.20 4.75 4.09 128.40 59.70 1.095 0.853 13.30 4.80 3.87 138.10 53.40 1.118 0.764 13.40 4.61 3.89 127.60 51.50 1.031 0.772 13.50 4.75 3.88 128.70 57.40 1.095 0.768 14.00 4.83 3.88 156.20 60.80 1.132 0.768

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VII. CONCLUSIONS Sun tracking system with the webcamera might provide

significant impact in solar energy efficiency. It is not only can cut the cost of the hardware setup, but also can increase the efficiency of the solar cells. Although this work is in photovoltaic, this research can go beyond the expectation for the future. The sun can be tracked with the CPC, the voltage, current and power received will always be at the maximum of the efficiency. If the efficiency becomes the matter of the

improvement of the solar cells, with this study we can improve the problems. This research can be continued and upgraded to get the higher efficiency to the maximum level.

VIII. REFERENCES [1] C. Finster, El heliostato de la Universidad Santa Maria. Scientia, 119,

pp. 5–20, 1962. [2] A. S.Saavedra, Diseño de un servomecanismo seguidor solar para un

instrumento registrador de la irradiación solar directa. Memoria, Universidad Técnica Federico Santa Maria, Valparaiso, Chile, 1963.

[3] D.R. Myers, T.L. Stoffel, I. Reda, S.M. Wilcox and A.M. Andreas, Recent progress in reducing the uncertainty in and improving pyranometer calibrations. J Sol Energy Eng 124, pp. 44–50, 2002.

[4] P. Roth, A. Georgiev, and H. Boudinov, Design and construction of a system for sun-tracking, Renewable Energy, Volume 29, Issue 3, Pages 393-402, March 2004.

[5] T. Pavlidis, Computers versus Humans, November 2002, http://www.theopavlidis.com/comphumans/comphuman.htm.

[6] M. H. Rashid, Power Electronics Circuits, Devices, and Applications, Prentice Hall; 2003.

[7] K. Sandberg, Introduction to image processing in Matlab 1, Department of Applied Mathematics, University of Colorado at Boulder, 2007.

[8] Machine Vision, 2008, http://en.wikipedia.org/wiki/Machine_vision. [9] A. Basid, and N. Azah, Design and Development of Automated Visual

Servoing System (AVSS), IIUM, Malaysia, November 2004. [10] W. R. Norshuhada, Design and Development of CameraControlled by

Using X-Y Cartesian Robot, December 2003. [11] R. Jain, R. Kasturi, and B. G. Schunk, Machine Vision, McGraw-Hill

International Editions, 1995.

IX. BIOGRAPHIES Eklas Hossain is a Masters Student in the Department of Mechatronics Engineering at the International Islamic University of Malaysia. He earned his BS in Electrical Engineering from Khulna University of Engineering and Technology, Bangladesh. He worked as Assistant Electrical Engineer at Kader Synthetic Fabrics, Gazipur, Bangladesh.

Riza Muhida was born in Jakarta, Indonesia. Dr. Muhida is an Assistant Professor in the Department of Mchatronics Engineering at the International Islamic University Malaysia. He got his Bachelor in Engineering Physics from Institute of Technology Bandung, Indonesia. He earned diploma in Japanese from Kokusai Kotoba Gakuin, Japanese School, Japan. He received MS in Electrical Engineering from Osaka University, Japan. He earned his Dr. Eng in Semiconductor and Optical Electronics from Osaka University, Japan. His research areas are Thin Film of Solar Cells Design and Characterizations, Microelectronics, and Micro sensors (MEMS), Power Systems and Power Electronics, Building Integrating Photovoltaic (BIPV) and Renewable Energy and Energy Conversion.

Ahad Ali is an Assistant Professor in Mechanical Engineering at the Lawrence Technological University. He earned B.S. in Mechanical Engineering from Bangladesh Institute of Technology, Khulna, Masters in Systems and Engineering Management from Nanyang Technological University, Singapore and PhD in Industrial Engineering from University of Wisconsin-Milwaukee. Dr. Ali was Assistant Professor in Industrial Engineering at the University of Puerto Rico - Mayaguez, Visiting Assistant Professor in Mechanical, Industrial and Manufacturing Engineering at the University of Toledo, Lecturer in Mechanical Engineering at the Bangladesh Institute of Technology, Khulna. Dr. Ali has published journal and conference papers. He is member of IEEE, IIE, INFORMS, and SME.