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SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
1R.Krishna Kumar, 2K.Nandhini, 3P.Vengatesh, 4J.Rajalakshmi, 5M.I.Mohamed Babul Farsin
1Assistant professor, Electronics and InstrumentaIon Engineering, Karpagam College of Engineering, Tamil Nadu 2,3,4,5 UG Scholar, Electronics and InstrumentaIon Engineering, Karpagam College of Engineering, Tamil Nadu
[email protected], [email protected], [email protected], [email protected], [email protected]
Abstract- Transformers are underlying and necessary consJtuent of Electrical distribuJon and transmission system. Examining of electrical transformers for fault occurrence can prevent costly overhaul interrupJon of smooth power supply. They are very expensive block of electricity distribuJon system as a result cost of power outage is also high. So as to ensure the safety and reliability of power operaJon of transformer, this paper studies the on-line monitoring and fault recogniJon technology of intelligent power transformer based on the "Internet”. This project mainly completes the hardware and soWware design of the intelligent measurement and control terminal for on-line monitoring of state parameters, which includes transformer voltage, current, oil temperature.
1. INTRODUCTION
Transformers have an important role to play by delivering
reliable power supply to shape up the smart cities.
Important reasons for the failure of distribution
transformers includes low oil level in the transformer,
overloading, unbalance loading, overheating of transformer
oil, defective breather and consequent ingress of moisture.
The main aim of, to develop these system is, to monitoring
the real status of the transformer, and also to reduce cost,
efficiency and improve services to customers. To reduce the
risk of unexpected failures and the ensuring unscheduled
outage, online monitoring has become the common practice
to assess the condition of the transformer and stable
operation is important.
2. PROPOSED SYSTEM
By implementing the IOT , the smart system will replace
the manpower position. Our proposed system consists of
various sensors such as Voltage sensor, Current sensor and
temperature sensor and an oil level sensor for monitoring
various parameters of a transformer All of the parameter
changes will be notified with the help of IOT using Blynk
App. An alarm will be ON if any changes occurs. Here we
have used current and voltage sensors to monitor voltage
and current parameter changes.
We use a Arduino UNO to share all the information to the
required person The Arduino Mega is a microcontroller
board based on the ATmega1280 datasheet. It has 54
digital input/output pins (of which 14 can be used as PWM
outputs), 16 analog inputs, 4 UARTs (hardware serial ports),
a 16 MHz crystal oscillator, a USB connection, a power jack,
an ICSP header, and a reset button. It contains everything
needed to support the microcontroller; simply connect it to
a computer with a USB cable or power it with a AC-to-DC
adapter or battery to get started. The Arduino Mega can be
powered via the USB connection or with an external power
supply. The power source is selected automatically
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Smart Transformer Monitoring System Using
IOT
978-81-933187-0-6 © 2021 SEEEPEDIA.ORG Society for Engineering Education Enrichment
SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
3. BLOCK DIAGRAM
FIGURE 1. Block Diagram of Proposed System
4. CIRCUIT DIAGRAM OF THE PROPOSED METHODOLOGY
FIGURE 2. Circuit Diagram of Proposed System
4.1 HARDWARE USED FOR THE PROPOSED METHODOLOGY
• Power Supply
• ATmega328
• Current sensor
• Voltage sensor
• Oil level sensor
• Temperature sensor
• Relay module
4.1.1 POWER SUPPLY
VIN: The input voltage to the Arduino board when it is using
an external source (as opposed to 5 Volts from the USB
connection or other regulated power source). You can
supply voltage through this pin or if supplying voltage via the
power jack, access it through this pin.
5V: The regulated power supply used to power the
microcontroller and other components on the board. This
can come either from VIN via an on-board regulator, or be
supplied by USB or another regulated 5V supply.
3V: A 3.3 Volt supply generated by the on-board FTDI chip.
Maximum current draw is 50 mA.
GND: Ground pins.
4.1.2 ATmega328
The Atmega280 has 128 KB of flash memory for storing
code (of which 4 KB is used for the boot loader), 8 KB of
SRAM and 4 KB of EEPROM (which can be read and written
with the EEPROM library). Each of the 54 digital pins on the
Mega can be used as an input or output, using pinMode (),
digitalWrite () and digitalRead () functions
Figure 3. Figure of current sensor
4.1.3 CURRENT SENSOR
A current sensor is a device that detects electric current (AC
or DC) in a wire, and generates a signal proportional to it.
The generated signal could be analog voltage or current or
even digital output. It can be then utilized to display the
measured current in an ammeter or can be stored for
further analysis in a data acquisition system or can be
utilized for control purpose.
SPECIFICATIONS Input Current: 0~30A AC
Output Mode: DC 0~1V
Non-linearity：2-3%
Build-in sampling resistance（RL): 62Ω
Turn Ratio: 1800:1
Resistance Grade: Grade B
Work Temperature: -25°C ~ ﹢70°C
Dielectric Strength(between shell and output): 1000V AC/
1min 5mA
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SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
Figure 4. Figure of current sensor
FIGURE 5. OUTPUT CHARACTERISTICS OF THE CURRENT
SENSOR
4.1.4 VOLTAGE SENSOR
Ideal for circumstances where power quality is an issue
Voltage sensors encourage checking of supply voltage levels.
They recognize under voltage or overvoltage concerns and
help ensure basic engines and gadgets. Since they have an
industry-standard 4–20 mA yield they are handily coupled to
an information lumberjack board meter or PLC for ongoing
observing and detailing.
Figure 5. Voltage sensor
FIGURE 6. OUTPUT CHARACTERISTICS OF THE VOLTAGE
SENSOR
4.1.5 OIL LEVEL SENSOR
Oil level sensors measure the oil content in transformer.
An oil level sensor probe is made up of multiple oil sensors
Oil level sensors work constant manner that ancient float
switches work, aside from they work with oil rather than
water. Oil level sensors use magnetic reed switches that are
hermitically sealed in a very stainless steel or plastic stem, to
find oil levels and mechanically activate or off oil pumps.
The read switch moves up and down the stem to open or
break circuits (turn on or off oil pumps) in keeping with oil
levels rising and falling. Once the oil within the tank reaches
its lowest predicted point (closed position) the reed switch
can produce a circuit and mechanically send a symptom to
your pump to begin filling your tank up with oil once more.
The magnetic reed switch can then open the circuit
copy once more (open position) once the oil level has
reached most fill capacity.
Figure 7. Oil Level Sensor
Figure 8.Oil Level Sensor
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SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
4.1.6 TEMPERATURE SENSOR (LM35)
The LM35 series are precision integrated-circuit temperature
sensors, whose output voltage is linearly proportional to the
Celsius (Centigrade) temperature. The
LM35 thus has an advantage over linear temperature
sensors calibrated in Kelvin, as the user is not required to
subtract a large constant voltage from its output to obtain
convenient Centigrade scaling.
Basic Centigrade Temperature Sensor (+2°C to +150°C)
Calibrated directly in ° Celsius (Centigrade)
Linear + 10.0 mV/°C scale factor
0.5°C accuracy guaranteble (at +25°C)
Rated for full −55° to +150°C range
Suitable for remote applications
Low cost due to wafer-level trimming
Operates from 4 to 30 volts
Less than 60 μA current drain
Low self-heating, 0.08°C in still air
Nonlinearity only ±1⁄4°C typical
Low impedance output, 0.1 W for 1 mA load
Figure 9. Temperature sensor LM35
FIGURE 6 GENERAL OUTPUT CHARACTERISTICS OF
TEMPERATURE
4.1.7 RELAY MODULE
A relay is an electromagnetic switch that's
accustomed to activate and switch off a circuit by an
occasional power signal, or wherever many circuits should
be controlled by one signal.
The main operation of a relay comes in places wherever
solely a low-power signal are often accustomed
management a circuit. it's additionally employed in places
wherever just one signal are often accustomed management
a great deal of circuits.
Relays have the precise operating of a switch. A relay is
alleged to modify one or a lot of poles. Every pole has
contacts that may be thrown in principally 3 ways. They are
• Normally Open Contact (NO) – NO contact is additionally
known as a build contact. It closes the circuit once the relay
is activated. It disconnects the circuit once the relay is
inactive.
• Normally Closed Contact (NC) – NC contact is additionally
referred to as break contact. this can be opposite to the NO
contact. Once the relay is activated, the circuit disconnects.
Once the relay is deactivated, the circuit connects.
• Change-over (CO) / Double-throw (DT) Contacts – this kind
of contacts are accustomed management 2 styles of circuits.
they're accustomed management a NO contact and
additionally a NC contact with a standard terminal consistent
with their kind they're known as by the names break before
build and build before break contacts.
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SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
Figure 10.Relay module
Figure 11.Relay connection diagram 5. SIMULATED OUTPUT
6. SOFTWARE USED TO CONNECT WITH IOT
Figure 12.Application inside Image of the Blynk app
7. CONCLUSIONS
The IOT wireless open typical technology is being designated
in this paper as the energy management and efficiency
technology of choice. Employing the system for real time
monitoring of power line with an open standard such as IOT
helps to keep costs down and condensed power
consumption. We can observe from this project that sensors
can be employed for monitoring of different parameter of
the transformer. It can be concluded that our model showing
results on internet. Using IOT for monitoring different
parameter of distribution transformer, human labor will be
minimized. With the use of IOT our power system would
become more accurate and reliable. In this project a
conceptual framework for intelligent power distribution
transformers is proposed. With a rapid urbanization and
industrialization, there is a high demand for uninterrupted
power supply. Frequent failures of transformers will lead to
interruptions in power supply and also generates big
revenue loss to power distributors. The present
transformers’ health monitoring systems mainly use IoT
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SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
technology.
8. FUTURE SCOPE
When we combine IoT with AI it will more effective and IoT
devices will take decision on their own. The combo of AI and
IoT devices makes the IoT devices in the transformer to
analyze data locally, predicts the malfunctioning of
transformer and fix the transformers and power supply
before they break, which save from disasters that will occur.
Since this proposal is only a conceptual one, implementation
of this approach in a real environment is left for feature.
9. REFERENCE
(1) Chan, W. L, So, A.T.P. and Lai, L., L.; “Interment Based
Transmission Substation Monitoring”, IEEE Transaction
on Power Systems, Vol. 14, No. 1, February 2014, pp.
293-298.
(2) Performance Monitoring of Transformer Parameters in
(IJIREEICE) Vol. 3, Issue 8, August 2015.
(3) Gsm based transformer monitoring” in “International
Journal of Advance Research in Computer and
Communication Engineering, Vol.2, Issue3, JAN 3.
(4) Distributed Transformer Monitoring System”
International Journal of Engineering Trends and
Technology (IJETT) - Vol.4 (5)- May 2013. (5) Microcontroller Based Substation Monitoring and
Control System with Gsm Modem’’ IOSR Journal of
Electrical and Electronics Engineering (IOSRJEEE) ISSN:
2278-1676 Volume 1, Issue 6 (July-Aug. 2012).
(6) Agalya, A. and Nagaraj, B., 2013. Certain investigation
on concentration control of CSTR—a comparative
approach. Int J Adv Soft Comput Appl, 5(2), pp.1-14.
(7) Nagaraj, B. and Vijayakumar, P., 2011. Soft computing
based PID controller tuning and application to the pulp
and paper industry. Sensors & Transducers, 133(10),
p.30.
(8) Arunkumar, R. and Balakrishnan, N., 2018. Medical
image classification for disease diagnosis by DBN
methods. Pakistan Journal of Biotechnology, 15(1),
pp.107-110.
(9) Ravishankar Tularam Zanzad, Prof. Nikita Umare, and
Prof Gajanan Patle “ZIGBEE Wireless Transformer
M o n i t o r i n g , P r o t e c t i o n a n d C o n t r o l
System”,International Journal of Innovative Research in
Computer and Communication Engineering (An ISO
3297: 2007 Certified Organization), Vol. 4, Issue 2,
February 2016.
(10) N Maheswara Rao, Narayanan R, B R Vasudevamurthy,
and Swaraj Kumar Das, ‘‘Performance Requirements of
Present-Day Distribution Transformers for Smart Grid’’,
IEEE ISGT Asia 2013 1569815481.
(11) Mohamed Ahmed Eltayeb Ahmed Elmustafa Hayati,
and Sherief F. Babiker,, Design and Implementation of
Low-Cost SMS Based Monitoring System of
Distribution Transformers, 2016 Conference of Basic
Sciences and Engineering Studies (SGCAC).
(12) Leibfried, T, “Online monitors keep transformers in
service”, Computer Applications in Power, IEEE,
Volume: 11 Issue: 3, July 1998 Page(s): 36 -42. (13) http://www.microchip.com/wwwproducts/en /
PIC18F4520. 907
(14) Xiao-hui Cheng, and Yang Wang, ‘‘The remote
monitoring system of transformer fault based on The
internet of Things’’, 2011 International Conference on
Computer Science and Network Technology.
(15) Abdul-Rahman AI-Ali, Abdul Khaliq & Muhammad
Arshad,” GSM Based Distribution Transformer
Monitoring System”, IEEE MELECON 2004, May
12-5,2004, Vol 3 Pages-9991002, Croatia.
(16) Muhammad Ali Mazidi , Janice Gillispie Mazidi, Rolin
D.Mckinlay, The 8051 Microcontroller And Embedded
Systems Using Assembly And C,Second Edition,
Pearson Education, 2008, India.
(17) K. Ibrahim, R. M. Sharkawy, H. K. Temraz and M. M. A.
Salama, "Selection criteria for oil transformer
measurements to calculate the Health Index," in IEEE
Transactions on Dielectrics and Electrical Insulation,
vol. 23, no. 6, pp. 3397-3404, Dec. 2016.
(18) W. Peng, W. Gao and J. Liu, "AI-Enabled Massive
Devices Multiple Access for Smart City," in IEEE
Internet of Things Journal, vol. 6, no. 5, pp. 7623-7634,
Oct. 2019. (19) D. Srivastava and M. M. Tripathi, "Transformer Health
Monitoring System Using Internet of Things," 2018 2nd
IEEE International Conference on Power Electronics,
Intelligent Control and Energy Systems (ICPEICES),
Delhi, India, 2018, pp. 903-908.
(20) D. S., Prathibha Suresh, T., Kouser Taj, "Oil Based
Transformer Health Monitoring System", International
Journal of Science and Research (IJSR) ISSN (Online):
2319–7064 Impact Factor, vol. 3.358, 2012
(21) Abu Jahal, C., ―Causes of transformer failures and
diagnostic methods – A review,‖ Renewable and
34
SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021
Sustainable Energy Reviews (2017), Volume 82, Part 1,
February 2018, Pages 1442-1456.
(22) A. Kumar, A. Raj, A. Kumar, S. Prasad, B. Kumar,
"Method for monitoring of distribution transformer",
Undergraduate Academic Research Journal (UARJ),
2012
(23) P.M. Sneha Angeline, ―Performance Monitoring of
Transformer Parameters, International Journal of
Innovative Research in Electrical, Electronics,
Instrumentation and Control Engineering, vol. 3, no. 8,
August 2015, pp. 49-51.
(24) Jeyakkannan, N. and Nagaraj, B., 2014. Online
Monitoring of Geological Methane Storage and
Leakage Based on Wireless Sensor Networks. Asian
Journal of Chemistry, 26.
(25) Nagaraj, B. and Vijayakumar, P., 2012. Soft computing
based PID controller design for consistency control in
papermaking. Int J Indian Pulp Paper Tech Assoc, 24(2),
pp.85-90.
(26) Balakrishnan, N., Rajendran, A. and Palanivel, K., 2019.
Meticulous fuzzy convolution C means for optimized
big data analytics: adaptation towards deep learning.
International Journal of Machine Learning and
Cybernetics, 10(12), pp.3575-3586.
(27) Sethuramalingam, T.K. and Nagaraj, B., 2015. A soft
computing approach on ship trajectory control for
marine applications. ARPN J Eng Appl Sci, 10(9),
pp.4281-4286.
(28) Nagaraj, B. and Vijayakumar, P., 2012. Bio inspired
algorithm for PID controller tuning and application to
the pulp and paper industry. Sensors & Transducers,
145(10), p.149.
(29) Nagaraj, B. and Vijayakumar, P., 2012. Evolutionary
computation based controller tuning—a comparative
approach. Int J Indian Pulp Paper Tech Assoc, 24(2),
pp.85-90.
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