A PROFICIENT SENSOR NETWORK BASED SMART METER MULTI-DEMAND RESPONSE SYSTEM USING IOT

1. ICISAS 2023
International Conference on Innovation, Sustainability and
Applied Sciences (ICISAS 2023)
A PROFICIENT SENSOR NETWORK BASED SMART METER MULTI-
DEMAND RESPONSE SYSTEM USING IOT
9-10 December 2023
Curtin University Dubai, Dubai International Academic City, UAE
Organized by
1
Presented by
I. Aravindaguru (Assistant Professor)
C.Mathan (Assistant Professor)
M.Nagarajapandian (Assistant Professor)
P. Veeramani (Assistant Professor)
Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu, India
R.Prathap (Assistant Professor)
Bannari Amman Institute of Technology, Sathyamangalam
E.Mukunthan (Incubation Scientist)
EDII-Anna Business Incubation Research Foundation

2. ABSTRACT
● Electricity distribution networks have undergone rapid change with the
introduction of smart meter technology.
● So here we design the advanced sensing smart meter and communications
capabilities, resulting in improved measurement and control functions.
● The purpose of this framework is to identify the fault at home demand, reduce
the energy theft cases and auto bill energy cut ON/OFF process.
● Also the effective maintains for a group of energy distribution using a limited
number of maintenance crews.
● The output prototype significantly improves efficiency compared to existing
systems, while providing anonymity and identification.

3. OBJECTIVE
● The main objective of the proposed work is to develop a wireless sensor network
based smart energy meter with quick demand responses.
● To make the bill payment automatically by which the automatic cut OFF/ON of the
current can be controlled.
● To ensure that whether the theft is occurred or not by comparing the current from the
distributed end and the consumers end.

4. INTRODUCTION
● At present, Electricity is the essential commodity in the world for human life.
● Today every home, offices, companies, industries requires electricity connection for
their functioning.
● According to that, accurate metering, detection of theft and implementation of proper
billing system would manage the consumption of electrical energy.
● Electricity theft can be defined as “an illegal usage of electricity equipment or service
with the intention to avoid billing charges”.
● This project mainly focuses on IoT based automatic theft detection, power failure or
fault detection and billing over due cut-off control, also providing the relevant energy
consumption information to user.

5. LITERATURE SURVEY
S. No Authors Title of Paper Name of the
journal
Observations
1
M.Prathik,
K.Anitha,
V.Anitha
Smart Energy Meter
Surveillance Using
IoT
2018 International
Conference on
Power Energy,
Control and
Transmission
System (IEEE).
To control and
calculate the energy
consumption of
consumers and the
data will be
uploaded to a cloud.
2
Naziya Sulthana,
Rashmi N, Prakyathi N
Y, Bhavana S, K B
Shiva Kumar
Smart Energy Meter
and Monitoring
System using IoT
2020
International
Journal Of
Engineering
Research and
Technology
(IJERT).
The IoT collects the
data of automatic
objects and help the
machine learn where
it needs.
3
Prithvi
Nath Saranu,
G Abirami,
S Sivakumar
Theft Detection
System using PIR
Sensor
2018 4th
International
Conference on
Electrical Energy
Systems (IEEE).
It provides a smart
home automation
system for theft
detection.

6. S. No Authors Title of Paper
Name of the
journal Observations
4
Adikeshavamurthy S.
M., Swapnalaxmi K.,
Apurva P., Sandhya M.
S., Nagaraj E
Automatic Theft
Detection
2019
International
Journal Of
Engineering
Research and
Technology
(IJERT).
Theft detection is
alerted at
management end and
disconnection of load
whenever theft
occurs.
5
Shreyas H N, Prakash P
,
Nikhil Aatrei M,
Sumesh Iyer
Automated Electric Bill
Generation System
Using Internet of
Things
2018
International
Symposium on
Signal Processing
and Intelligent
Recognition
Systems (SIPAG).
It uses an
efficient method to
read the electric
energy in terms of
pulse
and converts them
into units.
6
Pramod Ashtankar,
Akshay Damah,
Akshay Maske, Arati
Admane
Zigbee Based
Automatic Electric Bill
Meter & Tampering
Detection
2017
International
Journal of
Engineering
Science and
Computing
(IJESC).
The data
transmission takes
place from one place
to another using
wireless
communication
network.

7. S. No Authors Title of Paper Name of the
journal
Observations
7 Weixian Li,
Thillainathan
Logenthiran, , Van-
Tung Phan
A Novel Smart Energy
Theft System (SETS)
For IoT Based Smart
Home
2019 IEEE
Internet of Things
Journal, pp. 5531-
5539.
This paper develops
an smart theft system
which uses machine
learning and
statistical models to
train the data.
8 Weixian Li ,
Thillainathan
Logenthiran , Van-
Tung Phan,
Housing Development
Building Management
System (HDBMS) For
Optimized Electricity
Bills.
2017 Transactions
on Environment
and Electrical
Engineering
(TEEE).
This paper is
developed to
generate optimised
electricity bills and it
also provides optimal
energy usage.

8. EXISTING SYSTEM
● Broadly, electricity theft is ardent in the utilization domain via physical
intervention that includes direct hooking or meter tampering.
● The traditional electrical energy meter data collection is such that a person
from the utility provider visits the consumer sites periodically to note the
meter reading.
● An automatic feature extraction method making use of load profiles with
support vector machine (SVM) to identify customers with abnormalities
and fraud activities.
● However, it requires historical energy consumption data from different
consumers.

9. PROBLEM IDENTIFICATION AND
PROPOSED SOLUTION
Problem Identification Proposed Solution
•Generally maintenance is required to monitor whether the energy
meter is working properly or whether there is any fault in the
transmission line.
•The present system of energy billing is error prone, time
consuming and laborious.
•Errors get introduced at every stage of energy billing like errors
with electro-mechanical meters, human errors while noting down
the meter reading.
•These errors can be overcome by using the smart energy meter.
•In this project, an efficient anonymous identification (power theft
and fault detection) scheme for demand response management is
designed.
•The advanced smart meters report the consumption information
of all consumers to the power provider anonymously for dynamic
decision systems.
•All these information are sent in the form of message and mail
alerts to the consumer mobile phone.

10. PROPOSED SYSTEM
The proposed IoT based energy meter system basically consists of four
major feature namely
○ Fault Detection
○ Over due ON/OFF Control
○ Theft detection
○ Bill Calculation

11. PROPOSED BLOCK DIAGRAM-TRANSMITTER

12. RECEIVER BLOCK DIAGRAM
Power Supply
PC
Serial - USB
ZigBee

13. CIRCUIT DIAGRAM

14. RESULTS AND DISCUSSION
HARDWARE SETUP

15. Power Cut due to Overdue Message to the Mail

16. Result of Bill Generation of the Monthly Usage

17. Dashboard view of the Smart Meter

18. CONCLUSION
● In this project, a novel secure anonymous identification scheme for demand-response
management in smart grids has been presented.
● It has been shown that, the scheme provides strong anonymity and identification against
privacy leaking and power overloading.
● Hence a secured and accurate smart meter has been implemented to meet the demands of
the consumers.
● These information are updated to the consumers by sending them an alert message through
their registered mail Id or mobile number.
● The security analysis proves that FSI can achieve unlinkability, strong anonymity, non-
frame ability, identification and integrity.
● To the best of our knowledge, there is no previous work on anonymous identification
schemes that can simultaneously fulfil these requirements in smart grids.

19. REFERENCES
1. Weixian Li, Thillainathan Logenthiran, , Van-Tung Phan , “A Novel Smart Energy Theft System
(SETS) for IoT based Smart Home,” IEEE Internet of Things Journal, pp. 5531-5539, 2019.
2. W. Li, T. Logenthiran, V. T. Phan, and W. L. Woo, “Implemented iot based self-learning home
management system (shms) for singapore,” IEEE Internet of Things Journal, pp. 1–1, 2018.
3. Weixian Li , Thillainathan Logenthiran , Van-Tung Phan, “Housing development building management
system (hdbms) for optimized electricity bills,” Transactions on Environment and Electrical Engineering,
vol. 2, no. 2, pp. 64–71, 2017.
4. C. Yang, J. Yao, W. Lou, and S. Xie, “On demand response management performance optimization for
microgrids under imperfect communication constraints,” IEEE Internet of Things Journal, 2017.
5. T.-C. Chiu, Y.-Y. Shih, A.-C. Pang, and C.-W. Pai, “Optimized day-ahead pricing with renewable
energy demand-side management for smart grids,” IEEE Internet of Things Journal, vol. 4, no. 2, pp.
374–383, 2017.

20. REFERENCES
6. J. Siryani, B. Tanju, and T. J. Eveleigh, “A machine learning decision support system improves the
internet of things smart meter operations,” IEEE Internet of Things Journal, vol. 4, no. 4, pp. 1056–
1066, 2017.
7. D. Minoli, K. Sohraby, and B. Occhiogrosso, “Iot considerations, requirements, and architectures for
smart buildings–energy optimization and next generation building management systems,” IEEE
Internet of Things Journal, 2017.
8. Y. Liu, Y. Zhou, and S. Hu, “Combating coordinated pricing cyber-attack and energy theft in smart
home cyber-physical systems,” IEEE Transactions on Computer-Aided Design of Integrated Circuits
and Systems, 2017.
9. S. K. Viswanath, C. Yuen, W. Tushar, W.-T. Li, C.-K. Wen, K. Hu, C. Chen, and X. Liu, “System
design of the internet of things for residential smart grid,” IEEE Wireless Communications, vol. 23,
no. 5, pp. 90–98, 2016.
10. G. Xu, W. Yu, D. Griffith, N. Golmie, and P. Moulema, “Toward integrating distributed energy
resources and storage devices in smart grid,” IEEE Internet Things J., vol. 4, no. 1, pp. 192–204, Feb.
2017.

21. THANK YOU