Implementation of Automation for the Seamless Identification of Fault in Modern Smart Grids

International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 6 Issue 3, March-April 2022 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
@ IJTSRD | Unique Paper ID – IJTSRD49856 | Volume – 6 | Issue – 3 | Mar-Apr 2022 Page 1885
Implementation of Automation for the Seamless
Identification of Fault in Modern Smart Grids
Abdul Wahied Khan, Yuvraj Singh Ranawat, Deepak Kumar Joshi
Department of Electrical Engineering, Mewar University, Chittorgarh, Rajasthan, India
ABSTRACT
Every machine in the world runs on electricity so we cannot even
imagine the world without electric power. Electricity has a pivotal
role in our lives. Electricity is one of the aspect that leads to the
development of the country and help people to live their life
comfortably. Like power generation electric power distribution is
also a challenging aspect. The existing Indian distribution network is
also facing so many challenges such as the annual load growth is
increasing, the distribution network power losses are high,
distribution equipment failure due to over loading, poor voltage
profile of the system and the number of breakdowns and frequent
interruptions on distribution feeders are high. So there is a need for
electric utilities to make their distribution system a modern one, a
smart one and an agile one. These things necessitate the automation
of a distribution system to overcome the prevailing difficulties. The
paper presents a the distribution system Automation for a smart grid
that is analyzed and implemented using Multi Agent System (MAS)
for four significant issues of power system such as Fault
identification, isolation and restoration (FIIR) using Multiagent
system for a smart grid application.
How to cite this paper: Abdul Wahied
Khan | Yuvraj Singh Ranawat | Deepak
Kumar Joshi "Implementation of
Automation for the Seamless
Identification of Fault in Modern Smart
Grids" Published in
International Journal
of Trend in
Scientific Research
and Development
(ijtsrd), ISSN: 2456-
6470, Volume-6 |
Issue-3, April 2022,
pp.1885-1888, URL:
www.ijtsrd.com/papers/ijtsrd49856.pdf
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Scientific Research and Development
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INTRODUCTION
An electrical grid is an interconnected system for
delivering electricity from supplier to consumers. It
consists of generating stations that produce electrical
power, high-voltage transmission lines used to carry
power from distant sources to the demand center, and
distribution lines that connect individual consumers.
It is an indisputable reality that electric power is one
of the major and most important factors that led to the
rapid industrialization and globalization in the
twentieth century. In India, 15–20% of transmitting
power is lost in the transmission and distribution
network while 10 to 20% is lost to theft across the
utilities. As these losses have been decreasing slowly
over the recent years, But still there is a long way for
the utilities to achieve the desired state of operations.
India has also been lacking its generation
infrastructure expansion plans for the last few
decades. The smart grid delivers electricity to
consumers using two-way digital technology to
enable the more efficient management of
consumers/end users of electricity as well as to
identify and correct supply–demand imbalances of the
grid more efficiently and also instantaneously detect
faults in a “self-healing” process that increases
service quality, improves reliability, and reduces
costs. The significant vision of the smart grid includes
a wide set of applications includes software,
hardware, and technologies that enable utilities to
integrate, interface with, and intelligently control
innovations. The traditional power grids are generally
used to carry power from a few central generators to a
large number of consumers. In contrast, the smart grid
can use a two-way flow of electrical energy and
information to create an automated and distributed
advanced energy delivery network.
Literature Survey:
Various computing algorithms were used for solving
different power system applications. But all those
algorithms such as genetic algorithm, particle swarm
optimization, artificial neural networks etc; needs a
powerful central controller to handle a large amount
of data and transmission of global information with
the network. These centralized schemes are costly and
IJTSRD49856

International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
easy to suffer from single-point failures. Furthermore,
centralized control scheme lacks additivity to
structure changes of power networks. When new
generators and loads are installed, the centralized
control scheme may need to be redesigned.
Considering the uncertainty of intermittent renewable
energy resources, generation fluctuation may result in
unintentional structure changes, which will further
increase the burden to centralized schemes. Since
distributed control scheme can overcome the above
mentioned shortcomings, distributed control scheme
looks like a better solution for the reliable operation
of power systems. Andreas Nader linger et al. (2011)
Proposed that the MATLAB presented an interface,
which is based exclusively on documented and
portable mechanisms supplied by Java and
MATLAB. The approach is based on asynchronous
communication between Java threads and MATLAB
and follows the producer/ consumer pattern. The
author also presented the performance measurements
and discussed the impact of an optimization for
calling MATLAB functions that return a result value
back to Java. Takeshi Nagata et al. (2004) Proposed a
multi-agent approach for a decentralized power
system restoration for a local distribution network.
The proposed method consists of agents such as Bus
Agents (BAGs) and Junction Agents (JCTs). The
proposed multi-agent system is a promising approach
to more large-scale power system networks. un Yan
et al. (2016) proposed a Q-learning based approach to
identify critical attack sequences with consideration
of physical system behaviors. Q-learning, improve the
damage of sequential topology attack towards system
failures with the least attack efforts. Case studies
based on three IEEE test systems have demonstrated
the learning ability and effectiveness of Q-learning
based vulnerability analysis. Yinliang Xu and Wenxin
Liu (2011) proposed the centralized schemes
followed by other soft computing algorithms which
suffer single point failures and lacks adaptability to
structure changes of power networks. Thus, the
proposed algorithm for distributed control scheme
overcomes the shortcoming of the centralized control.
Hongwei DU et al. (2012) given an important feature
of smart distribution different from the traditional
distribution network. It is used to support a large
number of distributed generation (DG) access. Effect
of DG on distribution network is analyzed first and
also given a DG access requirement for the
distribution automation system. Paulo Leitao et al.
(2013) given that the multi-agent technology and its
usage in the active power distribution system were
briefly explained with its use cases. Hosny Abbas et
al. (2015) proposed that the Multi-agent systems
(MAS) appeared as a new architectural style for
engineering complex and highlydynamic applications
such as SCADA systems. An approach for simply
developing flexible and interoperable SCADA
systems based on the integration of MAS and OPC
process protocol. Syrine Ben Meskina et al. (2016)
proposed that the failure propagation in smart grids
(SGs) complicates and prolongs the recovery time as
the faults to be resolved increase. The design and
implementation of a framework for SGs modeling,
simulation, and recovery. The proposed approach is
based on a multiagent system composed of static and
mobile agents to ensure local and remote resolutions.
The deployment of local distributed databases
updated at run-time ensure the effectiveness of the
proposed fault recovery strategy
METHODOLOGY:
The occurrence of a fault in a distribution system is
quite a common issue and it is unavoidable. When a
fault occurs in a system, the protection devices like
relays and circuit breakers are used to isolate the
faulty section from the healthy section.
Figure 1 Fault identification Algorithm
But, during this operation, some of the unfaulted
loads were also disconnected. Thus, it is necessary to
restore the unfaulted loads as early as possible to
restore the supply to the consumers and it is also
required to maintain the continuity of the supply. The
main objective of this paper is to create agents in
JADE and interface it with the distribution network
developed in MATLAB/Simulink.

Figure 2 Proposed 9-bus systems
Result:
The results were carried in Matlab.
MATLAB/SIMULINK software is used to add the
modeling and simulation features .Fig 3:- Simulation
of 9bus distribution system.
Fig 3 shows the simulation results.
The specific protective relaying concepts that go
beyond the level of detail originally provided by the
software. The MATLAB software package with
SIMULINK support and Power System Block set
(PSB) is utilized to develop customized model
libraries for teaching protective relaying concepts
Fig 4:- Line faultss
Conclusion:- The proposed power issue for power
distribution automation process for Fault
identification, isolation and restoration (FIIR) for
distribution automation for a smart grid using
Multivalent system is carried and analysis in
simulation results. In this analysis of FIIR for a
distribution system for distribution automation, a
practical 9-bus system was taken. Average consensus
algorithm and mean metropolis methods were used to
arrive the restoration strategy. This proves to be a
faster algorithm for the restoration process.
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