Solar Power Plant Tracker Upgrade and MPPT Control with Internet of

Things

Didik Notosudjono

, Hazairin Samaulah

Muhamad Nopriansy

, Bagus Dwi Ramadhon

, Dimas

Fiddiansyah

, Asri

Universitas Pakuan, Indonesia

Universitas Tridinanti Palembang, Indonesia

Keywords:

LDR, solar panel, dual-axis tracker, Atmega328P-PU, MPPT, IoT, Internet of Things.

Abstract:

To maximize sunlight absorption by forming a perpendicular axis between the sun and the solar panel. A

method which could be implemented on the solar panel system that could follow the sun’s movement is

needed. On this design, the system uses a light diode sensor (LDR) that functions as the light detector, an

Atmega238P-PU microcontroller as the command logic storage, and a servo motor as a mover to dislocate the

position of the solar panel with Internet of Things (IoT). In the solar panel test which runs for 11 hours using

the dual-axis solar panel tracker has yield a power of 9.4 W and after passing the MPPT control battery, it

gives an average of 10.6 W. Compared to using a static solar panel method, it only yields a power of 6.8 Watt,

and after passing the MPPT control battery, it gives an average power of 9.25 W.w

1 INTRODUCTION

1.1 Background

To maximize the absorption of sunlight, a method

which forms a perpendicular axis between solar panel

and sunlight is needed. Hence the need to make a

model that could be implemented into a solar panel

system that could follow the sun’s direction is crucial.

There is also an excess power from the solar panel

into the battery itself, so a MPPT (Maximum Power

Point Tracker) control battery is also needed. While

the use of dual-axis solar tracker is already discussed

in past studies, the implementation of said dual-axis

tracker using Internet of Things (IoT) to be remotely

controlled through a website haven’t been developed.

1.2 Model Simulation

The methodology used in this study is to design a pro-

totype Solar Power Plant Tracker with the IoT-based

MPPT battery using ATMEGA328P-PU microcon-

troller. The system are designed to calculate the sun

position at anytime, at any location, and any day of

the year.

2 THEORETICAL BASIS

2.1 Photovoltaic (Solar Cell)

Photovoltaics are able to convert photon energy into

electrical energy. One solar cell usually could pro-

duce DC voltage around 0.5 – 2 V when illuminated.

Several solar cells will need to be arranged in a se-

ries to get a larger desired voltage(Notosudjono and

Adzikri, 2018).

2.2 Solar Panel Tracker System

Each square meters in the solar panel surface area

that faces the sun could harvest around 1000 W solar

power (assuming 100% efﬁciency). Thus, to increase

the solar panel’s energy efﬁciency, a simple but accu-

rate solar detector mechanism is needed as seen in the

Figure 1 below, known as tracker mechanism.

Notosudjono, D., Samaulah, H., Nopriansy, M., Ramadhon, B., Fiddiansyah, D. and Asri, .

Solar Power Plant Tracker Upgrade and MPPT Control with Internet of Things.

DOI: 10.5220/0009881602190223

In Proceedings of the 2nd International Conference on Applied Science, Engineering and Social Sciences (ICASESS 2019), pages 219-223

ISBN: 978-989-758-452-7

219

(Prinsloo and Dobson, 2015) In the following ﬁg-

ure is the solar trajectory illustration.

Figure 1: Solar trajectory illustration.

The Sun follows a certain path when seen from a

geographical location. A sun tracker mechanism is

used to ﬁnd the sun’s position in a certain location

to keep the solar panel perpendicular against the sun.

(Prinsloo and Dobson, 2015) Solar declination can

also be deﬁned as the angle between the line joining

the centers of the Sun and the Earth and its projection

on the equatorial plane. The solar declination changes

mainly due to the rotation of Earth about an axis. It’s

maximum value is 23.4°Con December and the min-

imum is -23.4°C on June 21st (Mansour et al., 2015;

Elsherbiny et al., 7 09).

2.3 Automatic Photovoltaic Tracking

System

Automatic Photovoltaic system is designed using

dual-axis tracker. Dual axis trackers have two de-

grees of freedom that act as axes of rotation. These

axes are typically normal to one another. Two-axis

tracker tracks the daily east to west movement of

the sun and the daily declination movement of the

sun. Two common implementations are TTDAT (tip-

tilt dual axis trackers) and AADAT (azimuth-altitude

dual-axis trackers) (Elsherbiny et al., 7 09).

This tracker gives the possibility for automatic

measuring of direct solar radiation with a pyrheliome-

ter. In the active operation mode, the tracker uses

the signal of a sun detecting linear sensor to control

the pointing (Roth et al., 2005). Two stepper motors

move the instrument platform, keeping the sun’s beam

at the center of the sensor.Duarte, et al. (Duarte et al.,

2011) designed a two axis sun tracking system. Fig-

ure 2 below shows Dual axis tracker.

space

Figure 2: Dual axis tracker.

2.4 Servo Motor

Servo motors have been around for a long time and are

used in many applications. They are small in size but

powerful and are very energy efﬁcient. Servos con-

trol by sending an electrical pulse of variable width

(or pulse width modulation (PWM)) through control

wire. Servo motor could only turn 90°C in either di-

rection for a total of 180°C movement. The position

where the servo has the same amount of potential ro-

tation both in the clockwise or counterclockwise di-

rection is deﬁned as the servo motor’s neutral position

(Ramadhan et al., 2018).

2.5 Maximum Power Point Tracker

(MPPT) Method

Tracking the maximum power point (MPP) of a pho-

tovoltaic array is an essential stage of a PV system

(Femia et al., 2008) . As such, many MPPT meth-

ods have been introduced and numerous variants of

each method have been proposed to overcome spe-

ciﬁc disadvantages. The methods all vary in complex-

ity, number of sensors required, digital or analogue

implementation, convergence speed, tracking ability,

and cost effectiveness(Babaa et al., 2014).

2.6 ATMEGA328P-PU Microcontroller

Pin Conﬁguration

Atmega328P-PU has the ability to separate memory

for program code and for memory so that it can max-

imize work in parallelism, or commonly called Har-

vard architecture which only requires 5Vdc.

2.7 Internet of Things (IoT) Concept

The Internet of Things is envisioned to allow for the

interconnectivity of anyone and anything at anytime

and in anyplace. This connectivity should ideally be

possible using any service over any conduit, path or

ICASESS 2019 - International Conference on Applied Science, Engineering and Social Science

220

network. This is popularly referred to as The IoT

6A Connectivity Concept (Takpor et al., July; Perera

et al., 2013).

The IEEE IoT Community deﬁnes the Internet of

Things as: “. . . a self-conﬁguring and adaptive sys-

tem consisting of networks of sensors and smart ob-

jects whose purpose is to interconnect “all” things,

including every day and industrial objects, in such

a way as to make them intelligent, programmable

and more capable of interacting with humans” (IEEE,

2015).

Figure 3. shows a structure of the connectivity

concept of IoT and some of IoT’s application areas.

Figure 3: IoT’s connectivity concept and application areas.

3 TESTING AND ANALYSIS

3.1 Solar Panel and Control MPPT Test

The Solar Panel Test and Control Battery Test with

MPPT method are conducted to determine the amount

of power output from the solar panel, before and after

passing MPPT control. In the MPPT control test, we

observe the current and the voltage detected by the

current and voltage sensors on the LCD display. This

is done by measuring directly on the output pin from

this MPPT control electrical circuit. Fig. 4 below

shows the output pin of the MPPT control.

Figure 4: MPPT Control Output pin measurement.

To determine the comparison or difference be-

tween the resulting voltage and current values where

the main source is the solar panel, the measurement

on the input pin of the MPPT control is needed so it is

not solely based on the current and voltage values dis-

played by the LCD. Fig. 5 below shows the input pin

of the control before passing through MPPT control.

Figure 5: MPPT Control Input pin measurement.

After the current and voltage data from using

tracker method and static method with and without

the MPPT control is obtained, we can obtain the the-

oretical power value from the solar panel by using Voc

and Isc as seen in the eq. 1 below :

SolarCellOut putPower = V

∗ I

(1)

The following 10 Wp solar panel test result using

the tracker method for 11 hours in the Figure 6 and

Figure 7 :

Solar Power Plant Tracker Upgrade and MPPT Control with Internet of Things

221

space

Figure 6: Solar Panel Tracker and MPPT Control Test for

11 hours.

Figure 7: Solar Panel Tracker and MPPT Control Test for

11 hours (extension).

As seen in the Figure 6 and Figure 7 above, the

average power from running the test for 11 hours can

be measured from 07.00 – 17.00 (Indonesian Western

Time) with a capacity of 10 W, 21.6 V open circuit

voltage (Voc) , and 0.61 A short circuit current (Isc).

Using the static method without the MPPT control

for 11 hours, it generates 6.8 W by having a loss of

3.2 W = 10 W – 6.8 W. However, after passing MPPT

control battery, the power output becomes 9.25 W by

only having a 0.75 W loss.

In comparison by using a tracker method which

follows the same 11 hours test period from 07.00 –

17.00 (Indonesian Western Time), it can be seen that

the output voltage varies and that it generates a higher

power of 9.4 W with only a 0.6 W loss compared to

6.8 W using the static method. A 2.6 W difference

can be observed between them.

3.2 IoT with ESP8266 Module and

Thingspeak Web Test

ESP8266 Module automatically uploads data to the

web (http://thingspeak.com) periodically. In the fol-

lowing Fig. 8 is a program to connect the WiFi net-

work to ESP8266 to be uploaded to thingspeak web.

Figure 8: Program code using ESP8266.

The uploaded data is the voltage value data from

the solar panel according to time as seen in Fig. 9

below:

Figure 9: Voltage data uploaded using ESP8266.

4 CONCLUSION

After conducting observation and instrument test, it

can summarized as below:

1. In the solar panel test for 11 hours (07.00 – 17.00

Indonesian Western Time) using the dual-axis so-

lar panel tracker method has obtained the average

power output of 9.4 W before passing through the

MPPT control battery and 10.6 W after passing

through the MPPT control battery which matches

the maximum power on the solar panel of 10 W

2. In the solar panel test for 11 hours (07.00 – 17.00

Indonesian Western Time) using the static solar

panel method has obtained the average power out-

put of 6.8 W before passing through the MPPT

control battery and 9.25 W after passing through

the MPPT control battery which is close to the

maximum power on the solar panel of 10 W

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3. The Solar panel that uses the dual-axis tracker

method generates a higher power output of 9.4

W compared to 6.8 W generated by static method

which gives a difference of 2.6 W. This is due to

the static solar panel method not always perpen-

dicular to the sun, this problem could be solved

using the dual-axis tracker solar panel to ensure

the solar panel always perpendicular to the sun.

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