SSRG International Journal of Electrical and Electronics Engineering
ISSN: 2348-8379/ https://doi.org/10.14445/23488379/IJEEE-V10I5P121
Volume 10 Issue 5, 227-239, May 2023
© 2023 Seventh Sense Research Group®
Original Article
A Model Design of Green Communication for
Smart Grid Systems
Vinod Patil1, Namita Shinde2, Payal Kadam3, Sudhir Bussa4, Sudhir Kadam5, A. Prabhakar6,
Chetan More7, Pooja Deshmukh8
1, 2, 3, 4, 5, 6, 7, 8
Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India
1Corresponding
Received: 20 March 2023
Author : vhpatil@bvucoep.edu.in
Revised: 30 April 2023
Accepted: 27 May 2023
Published: 31 May 2023
Abstract - The electricity grid's upcoming update will be called Smart Grid. It covers all power production,
management, transmission, distribution, and use aspects. It uses a variety of renewable resources to produce
energy. The user and control unit can communicate in multiple directions. For smart grid applications, various
wired and wireless technologies are available. We prefer wireless technology to wired technology because it has
many advantages. Key wireless technology features are critical for rapid deployment, mobility, and inexpensive
installation costs. This work uses solar cells, wind turbines, and water turbines to produce energy. Energy is
produced by the generation unit and sent to the control unit. After that, the control unit gives to the user by their
instructions. The critical attribute of the smart grid is that it improves the economy, agility, efficiency, reliability,
and security.
Keywords - Prediction, Data mining, Decision tree, Random forest, Regression process.
1. Introduction
A GRID network comprises various lines that
cross one another to form a matrix. Electricity travels
along the lines, which are electrical cables. These
grids can be classified as old grids and smart grids.
Power is distributed via cable lines in the old grid.
There were a few significant lines through which the
power was distributed. Feeders are the term for these
lines. To deliver electricity to users, they had switches
that had to be manually closed and opened. Every time
a short circuit occurs, one must manually check
everything, which is dangerous and would need much
time to patch again. We discovered the POWER
GRID or SMART GRID to solve this problem. The
future of electricity and data transmission lies in the
Smart grid [1]. An electrical system that uses various
operational and energy-saving technologies, such as
smart meters, smart appliances, and renewable energy
sources, is known as a "smart grid." Essential
components of the smart grid include electronic power
conditioning [2], production unit control [3], and
distribution of electricity [4, 5]. The applications
where smart grid is used are shown in figure no. 1. It
shows the diverse applications of the smart grid,
highlighting its versatility and impact across different
sectors and industries. The smart grid offers numerous
benefits and possibilities, from enhanced energy
management to improved reliability.
Fig. 1 Smart grid applications
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
improved energy efficiency and reduced energy
consumption. In conclusion, the model designs
discussed above promise to improve energy
efficiency, reduce greenhouse gas emissions, and
increase network lifetime in smart grid systems.
However, more research is needed to determine their
feasibility and scalability in real-world smart grid
systems.
Given the rising importance of environmental
sustainability, green communication in smart grid
systems has gained significant attention. The
integration of renewable energy sources and the need
to reduce greenhouse gas emissions have driven the
exploration of eco-friendly communication models for
the smart grid.
2. Literature Survey
Based on the literature review, there are gaps in
the current smart grid communication system. The
traditional communication systems may not be able to
handle the growing demand for renewable energy
sources and the need to reduce greenhouse gas
emissions. New communication systems are needed to
integrate renewable energy sources and facilitate
green communication in smart grid systems. The
literature survey presented above highlights the
importance of green communication in smart grid
systems and provides insights into various model
designs that can facilitate sustainable and efficient
communication.
Green communication for smart grid systems has
become an increasingly important topic in recent years
due to the rapid development of renewable energy and
the need to reduce greenhouse gas emissions [6]. This
literature review will examine various model designs
for green communication in smart grid systems and
their potential benefits. One proposed model design
for green communication in smart grid systems uses
energy-efficient routing algorithms. In a study by
Zhang et al. (2018), a routing algorithm based on
particle swarm optimization was proposed to
minimize energy consumption in wireless sensor
networks for smart grids [7, 8]. The results showed
that the proposed algorithm outperformed other
algorithms regarding energy efficiency.
The increasing use of renewable energy sources
and the need to reduce greenhouse gas emissions have
made it necessary to develop new communication
systems that can handle the complexity of smart grid
networks. Therefore, the need for a new system of
green communication for smart grid systems is
essential to address the limitations of traditional
communication systems and achieve sustainable and
efficient smart grid networks. The proposed model
designs provide a foundation for developing a
comprehensive framework that integrates different
aspects of smart grid communication, such as
renewable energy sources, energy-efficient routing,
and communication protocols, to achieve a sustainable
and efficient smart grid communication system.
Systems-of-systems make up smart cities, including
energy, transportation, and others. Since the city is a
complex entity [12, 13] and each of its systems is
autonomous in its structure, operation, and behaviour
while connected and cooperating to produce the
emergent global features the city displays, one must
speak of systems of systems [14].
Another proposed model design is the use of
energy-efficient communication protocols. In a study
by Nasrin et al. (2018), an energy-efficient
communication protocol was proposed for smart grid
systems using a hierarchical routing approach. The
results showed that the proposed protocol reduced
energy consumption and improved network lifetime
[9].
Furthermore, using renewable energy sources to
power smart grid systems has also been proposed as a
model design for green communication. In a study by
Han et al. (2018), a renewable energy-powered
wireless sensor network was proposed for smart grid
systems. The results showed that the proposed system
could reduce greenhouse gas emissions and improve
energy efficiency [10].
Moreover, machine learning algorithms have been
proposed as a model design for green communication
in smart grid systems. In a study by Singh et al.
(2020), a machine learning-based energy-efficient
routing algorithm was proposed for smart grid systems
[11]. The results showed that the proposed algorithm
We can analyze the intelligence of smart cities at
least three different levels [15].
1) Technical intelligence at the component level:
228
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
used for optimal control of all grid components. To
handle such vast data flow, the smart grid must have
upgraded, reliable and robust communication
infrastructure
to
provide
real-time
secure
communications. The communication infrastructure
must have wide bandwidth to ensure a high rate of
information flow. Furthermore, the communication
infrastructure must be self-healing and automatically
adaptive to changes [21].
All components can become "smarter" by a)
extending access to input data, such as that from
sensors, relevant for situational awareness
regarding its operational conditions; b)
processing the input data in a predictive or
adaptive manner; and c) transmitting the output
information to the pertinent command and
control units, and the final actuators necessary for
carrying out the needed actions.
2) System intelligence is a system's ability to
perform tasks autonomously by coordinating and
synchronizing the actions of its numerous
components while communicating with other
systems. The smart system satisfies various
demands,
including
cost,
energy,
and
environmental goals [16].
There are certain benefits of the smart grid over
an outdated system. Because we have used wireless
technology, the smart grid is more dependable because
it enhances mistake detection and enables the network
to self-heal [22]. Network topology flexibility is vital
since traditional grids were built for one-way
communication while smart grids are built for twoway communication. Thus, it is more adaptable than a
traditional grid. Load adjustment depends on the user's
needs; the load may be raised or changed over time.
To generate additional loads using various renewable
resources, the smart grid will alert the user about the
current load [23].
3) System-of-systems intelligence: Systems-ofsystems
comprise
several
independent,
autonomous systems collaborating to achieve
larger objectives. In this sense, a smart city is a
system of systems that integrates energy,
transportation, water, and building systems. Its
smartness refers to its ability to manage, connect,
and adapt its various resources and functionalities
(including technical, economic, and social
factors) to achieve those objectives [6]. A smart
grid would employ a smart meter to detect
consumer needs and send requests to the
generation unit by those needs [17,18].
Wireless communication has created a path
between the user and the distributor. Wireless
communication sends data or power to numerous
locations that are not wired together. Radio waves, for
example, are frequently utilised in wireless technology
[24]. These radio waves can cut distances by hundreds
of meters for Bluetooth and millions of kilometres for
deep-space communication. It includes several mobile
and portable applications, including wireless
networking, cell phones, and two-way radio. There are
various ways to create wireless communication,
including using sound, light, or other wireless
technologies like a magnetic, electric, or electric field.
Wireless technology transfers data without the usage
of wires [25, 26]. Smart grid uses bi-directional
information flow to modify smart applications on the
customers' side to save energy intake and lose the
subsequent outflow. Meanwhile, grows network
stability and transparency [27]. Smart metering and
tracking structures assist in establishing feedback to
manipulate mechanisms for actual-time power intake
and correspond with the call for to/from utilities [28].
A detailed description of ICT's role in enhancing grid
automation in each power area is provided in the
following sub-sections [29, 30]. The power flow and
information flow are shown in figure no. 2.
2.1. Collation of Communication Infrastructure
Between the Legacy Grid and The Smart Grid
The current communication infrastructure, a
legacy power grid, is used only in unidirectional
power flow from central power plants toward
consumers, with limited efficiency and information
sharing. These systems are primarily used for data
acquisition with restricted sensors in the main
transmission and distribution points, faults detection
and a limited number of control signals transmission.
The data acquisition is performed by Supervisory
Control and Data Acquisition Systems (SCADA) [19,
20]. The smart grid has a much greater number of
sensors and actuators than the legacy grid. They are
dep-loved at all levels of the grid components: Power
plants and substation equipment, generators,
transformers, and home users. The sensors are used
for data acquisition and information exchange
between equipment and data centers. The actuators are
229
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
are insufficient to charge, smart grids function
similarly to a controller and switch to charger
mode to charge the batteries. However, after the
battery is fully charged, the relay creates a circuit
to allow a user to use the power efficiently.
3. Hardware
The generation unit, a crucial component of a
smart grid, was created using three renewable
resources. They are as mentioned below:
•
•
•
•
•
•
•
•
Solar panels: Solar panels are a renewable energy
source that has been incorporated into the
generation unit of the smart grid. It will provide 6
volts of power. As it will only use sunshine to
produce power, solar panel plays a crucial part in
smart grids because of their poor expression
capability.
Four users have been used in this unit. They are
fans - as our first users, we used a fan. The fan's motor
requires 5 volts to operate, which is why the fan is
fixed.
We have a second user of led-led. It dissipates
0.05 watts of power and has a forward current of 20
Ma; 5 volts would make it.
Windmills: As a renewable energy source that has
been incorporated into the smart grid and as a
readily available resource for power grid
generation, windmills are also a highly significant
and practical part of power generation for the
smart grid. It will produce 3 volts of power.
Hydraulic power plants: These plants use water to
produce electricity. The pump will produce 12
volts of power as we increase the pressure inside
of it using water (max). We can increase and
reduce the hydraulic power plant's power based
on the water pressure. It is utilized in the smart
grid's generation unit.
When all three are combined, power may be
produced to charge two 18-volt batteries.
Control unit: This unit would regulate the flow of
energy and, if more were to be produced, would
store it in the battery. The primary critical unit is
this. A. The Arduino is a gadget that regulates the
production and transfer of power.
When we supplied 55 volts to Arduino, the output
displayed 5 volts.
Wireless communication has been done using the
USRP (universal software radio peripheral).
Software frequently uses it to define radio. There
are two ports on it, one of which is a transmitter
and the other a transceiver. Although a transceiver
has been used to transmit and receive
information, the transmitter can only send data.
Through USRP, the antenna has been utilized to
transmit and receive data. Depending on the
length of the antenna, we can send and receive
data. USRP can serve applications that operate
between DC and 6 GHz.
Relays function as switches because they open
and close circuits as needed. Therefore, a relay
controls an electrical circuit. When the batteries
4. Software
A tool called Laboratory Virtual Instrument
Engineering Workbench (LabVIEW), created by the
national instrument, is used to develop environments
and design systems using graphical programming. It is
crucial to distinguish G-code from the graphical
language. The system design process uses this
software. This is used on various operating systems,
including Windows, Linux and UNIX versions,
industrial automation, instrument control, and data
collection. LabVIEW 2018 is the most recent version,
made available in May 2018.
4.1. Data Flow Programming
The G programming language, a dataflow
programming language, has been utilized. The
program in this language takes the shape of a
graphical block diagram, on which the programmer
connects the various function nodes by drawing wires.
These wires propagate variables, and once all the
node's data is available, any node can be used to carry
out the operation. Given that numerous nodes may
experience this simultaneously, G can complete
inherently in parallel. The built-in scheduler has
automatically utilized a variety of multiprocessing and
multithreading hardware to multiplex several OS
threads among the nodes prepared for execution.
Connects the various function nodes by drawing
wires. These wires propagate variables, and once all
the node's data is available, any node can be used to
carry out the operation. Given that numerous nodes
may experience this simultaneously, G can complete
inherently in parallel.
230
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
Power Flow
Supply
Elect
Demand
Response
Manageme
nt
Solar Panel
&
Wind Mill
Transmission
Distribution
Utilization
Demand
Meter Data
Management
Index
WAN
Data
Aggregate
Unit
Gateway
Smart
Meter
Data
Aggregate
Unit
Gateway
Smart
Meter
Data
Aggregate
Unit
Gateway
Smart
Meter
HAN
NAN
Information
Flow
Fig. 2 Information and power flow in smart grid
The built-in scheduler has automatically utilized a
variety of multiprocessing and multithreading
hardware to multiplex several OS threads among the
nodes prepared for execution.
The block diagram will show terminals for items
placed on the front panel. Additionally, several
structures and functions in this back panel or block
diagram area operate on controls and provide
information to indicators. The top of the back panel
can be used to position the function palette, which is a
palette that contains all the structures and functions.
Nodes are referred to as such because they contain all
the indicators, structures, controls, and functions. Two
indicators and four controls can be attached to the
subtraction function for the indicator to display the
output as the difference of four controls utilizing one
indication at a time. The front panel of a virtual
instrument may therefore be used to define the inputs
and outputs for the node when it is dropped as a node
into a block diagram or run as a program with the
front panel acting as the user interface. This
demonstrates the ability to test every VI before
including it as a function in a more extensive program.
4.2. Graphical Programming
Creating user interfaces, often known as front
panels, is integrated into the development process by
LabVIEW—the LabVIEW program subroutine for
virtual instruments. Three parts comprise a virtual
instrument: a block diagram, a front panel, and a
connector panel. In the block diagram of others, they
are referred to as VIS; the connector panel is utilized
to depict the VI. Two items, such as controls and
indicators, are on the front panel. The control section
receives inputs, enabling the user to transmit data to
the VI. Indicators provide output as they do or exhibit
or display the outcomes depending on the input given
to the VI. The entire graphical code is included in a
panel known as the rear panel.
231
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
the transmitter and receiver, the two primary
components of the LabVIEW communication suite,
for our smart grid.
This method of creating programs graphically by
dragging and dropping virtual representations, which
they are highly familiar with from lab equipment, is
for non-programmers. Because it has so many
examples and documentation, is a little application
and is extremely easy, anyone can understand this
LabVIEW programming. This is one of the
advantages, but one should not believe that
understanding or learning it will be simple; highquality G programming requires specialists.
5. Methodology
This flowchart in figure no. 3 outlines the
capabilities of the smart grid concept that we
developed.
5.1. Users Generating Requests
This block covers a variety of procedures that are
essential to the user's request for efficient operation. It
comprises several gadgets the user uses to request the
necessary units. After processing, it is given to them
in generation-by-generation units. Here, the many
methods employed include Requesting something
from the control unit and getting the control unit's
generated power. First, the user will timely request the
power consumption he needs, which can range from 0
to 600 units. The control unit will get the request to
produce the required power.
Depending on the goal, algorithms can be either
sophisticated or straightforward; thus, a programmer
must be well-versed in the unique LabVIEW syntax
and the memory management architecture. Largescale coding for complex algorithms will be required,
and it must be done carefully. This LabVIEW
program can create an independent application.
Additionally, this LabVIEW application software
makes it simple to design a distributed application.
Since the client-server architecture would be used to
communicate with these distributed apps, it is simpler
to construct due to G's inherent parallelism.
Second, the control block will communicate the
necessary amount of electricity to the user, which the
generation unit produces. In an emergency, the
remaining power can be routed from RPS, but only
this quantity of power is what the user needs.
4.3. LabVIEW Communication Suite
When LabVIEW communication is used with
LabVIEW NXG and its tools, one may quickly
demonstrate wireless communication. NI real-time
operating systems, FPGAs, and general-purpose
processors are just a few examples of the hardware
targets that LabVIEW makes it easy to design, build,
and deploy wireless communication systems too. The
most crucial aspect is that a graphical programming
technique can shorten the time required to authorize
an algorithm with signals over the air (OTA). We have
saved time by utilizing graphical programming in a
single environment for LabVIEW communication.
5.2. Control System
To make up the control unit, one can first obtain a
request from the user and then send it to the
generating block after obtaining the necessary powergenerated acknowledgement from the generation
block. In the digital realm of the smart grid, the
control unit functions as a translator, converting the
user's power requirements into a language that the
generating block understands. It ensures clear
communication and accurate power delivery, enabling
a seamless user experience. The control unit conveys
the user's power transmission needs with precision and
clarity through its communication format. The address
signifies the destination of the electricity, while the
number of units reflects the specific power
requirement, leaving no room for ambiguity. The
control unit completes the feedback loop by delivering
the
requested
power
and
providing
an
acknowledgement, reassuring users that their
electricity needs have been met. It instils confidence
in the smart grid system, fostering trust and reliability.
The best part is that all the necessary components
are included so that we can create your design,
implement it in software, and quickly implement it in
hardware if the design is successful. It supports a
variety of devices, including FGPA hardware. We
have designed the transmitter and receiver, the two
primary components of the LabVIEW communication
suite, for our smart grid. Implement our design in
software, and if the design is successful, quickly
implement it in hardware. It supports a variety of
devices, including FGPA hardware. We have designed
232
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
(Reserved power system). The output voltage of a
solar panel is directly proportional to light intensity
(LUX).
User Block
Request
RPS
Exception
5.4. Power Reserve System
The control unit then passes the units to the user
when the generating unit generates the necessary
number of units as requested. When the generation
unit produces the necessary number of units, more
may be produced than the user requested. Thus, those
units are transferred to the system of reserved power.
In an emergency, you can use this power that has been
reserved. The RPS enters the picture if the user needs
additional units, if demand unexpectedly rises, or
possibly if there is a sudden demand for the units in
terms of the unit. Additionally, it stores any power the
user may produce for their usage. It serves as a reserve
for all the units, preventing waste and enabling use in
the event of an unexpected rise in demand. The abovedefined blocks are the main parts of a smart grid
model. The software also supports these blocks. These
blocks and the programs designed in this software
make the unit.
Control Unit
/ Sever
Control
Generation
Block
Fig. 3 Capabilities of smart grid
Giving us recognition for the power we have
generated. First, the control block in this situation
oversees receiving the user's request for generating
electricity. The generating block receives the request
from the control block and gives it to it. Second, as
soon as the generation block receives the user request,
it generates the closest high-order number and gives
the user the necessary power, reserving the additional
power produced in the RPS (Reserved Power System).
The control unit subsequently distributes the generated
power to the user so that true smart power
transmission occurs. After the excess power is stored
in the RPS, the generated power, as the user requested
and acknowledged, is delivered to the control unit.
The control unit then communicates data in the
following format: First, the address where the power
is to be transmitted, followed by a semicolon, the
number of units needed, and again followed by a
semicolon.
The LABVIEW Communication Suite 2.0 and
LABVIEW software is the heart of this smart grid
model. LabVIEW (Laboratory Virtual Instrument
Engineering Workbench) is a widely used system
design and development platform. It provides a
graphical programming environment where engineers
and scientists can create applications by connecting
functional nodes in a block diagram structure.
LabVIEW includes strong data visualization, analysis,
and presentation features. It has several built-in
graphical user interface (GUI) components that allow
users to design interfaces to display obtained data,
analyse outcomes, and generate reports. There are
several VI that together combined work as a single
unit to run this model.
5.3. Unit of Generation
The generation block's primary purpose can be
summed up as taking note of the control unit's request,
producing the necessary number of units, or delivering
the created unit along with an acknowledgement to the
control unit. An essential component of the smart grid
architecture is the generation unit. The energygenerating equipment uses water turbines, windmills,
and solar panels to produce electricity without
harming the environment. When the generation unit
receives the information from the control unit, it
immediately generates the required amount of
electricity for the user. When the energy is produced,
the control unit receives the energy requested by the
user, while the excess energy is stored in the RPS
The programs written in LABVIEW OR
LABVIEW Communication Suite 2.0 are known as
VI. The software domain is subdivided into three main
VI. Those VI are as follows:
• The VI for transmission of message (at user end)
• The VI for receiving a message (at the control unit)
• The VI is for controlling the hardware.
• The VI for transmission of the message (at the user
end)
233
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
Fig. 4 VI LabVIEW communication suite 2.0
same. After designing the format for the generation
message, as shown in figure no. 4, we designed the
modulation technique to convert the information from
text to code that can be transmitted using the antennas.
Further, we configured the USRP to transmit the code.
For
designing
this,
VI
LABVIEW
Communication suite 2.0 software was used. The
primary function of this transmission VI is to transmit
user data or generate a user request.
The user data comprises the user address and the
units required by the user for daily use. Initially, we
used the block in our software to generate a format for
the user request. This is done so that the transmission
and the receiving of the data are not a problem, and
the programming at the user end also depends on the
USRP is an essential hardware tool that is
responsible for the transmission and reception of
message signals. The modulated text is converted into
a queue and transmitted bit by bit to prevent packet
loss and maintain the code's positional composition.
234
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
ease of operation. Figure 8 shows Power Generation
Unit, Whereas figure 9 shows Control Unit shows
User Request.
Block Diagram Panel of current data that is being
processed. The user can enter data here, convert it into
packets and then send it to the VI at the control unit
with the help of a tool known as USRP. For designing
this VI, we, too, used the LABVIEW Communication
suite 2.0 software. In layman's terms, the all-over
working of this VI is the reception of the user request.
So, to receive the user request, we first configured the
USRP to receive the user request.
After the configuration, the next task is to sense
the type of modulation used to send the signal by the
transmitter. After confirming the modulation
technique and automatically changing the settings, we
defined a mechanism to receive the message packet by
packet.
As shown in Figure 6, the message received is
logged into a file for our VI controlling the hardware
domain to work with after this process. As shown in
figure no.7, this is the front end of the block diagram
that controls and makes it easier for a user to control
the entire block diagram. With an intuitive design and
interactive features, users can effortlessly navigate and
command the various components of the block
diagram, empowering them with complete control and
As shown in Figure 9, the message received is
logged into a file for our VI controlling the hardware
domain to work with after this process. Figure 4 is the
front end of the block diagram that controls and makes
it easier for a user to control the entire block diagram.
Receiver. We can see user received power in figure
no.8.
Fig. 5 The VI for the reception of the message (at the control unit)
235
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
Fig. 6 The VI for the reception of the message (at the control unit)
Fig. 7 User received power
Fig. 8 Power generation unit
236
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
The relays are like a switch that completes the
circuit if and only if supplied with a threshold voltage.
This threshold voltage controls the flow in and out of
the relay. If the voltage is supplied, the relay will
complete the circuit, leaving the circuit completely
broken. Figure no. 7 shows Control Unit shows User
Request Receiver. This shows the current data being
processed and the reserve battery voltage that RPS,
the place where the data is logged and from where the
VI can abstract data, the renewably generated voltage,
and it gives the idea of the units required by the user.
6. Future Scope
India is the world's third-largest transmission and
distribution network and still faces problems of
inadequate electricity supply, poor quality, network
losses and reliability. To overcome these problems,
the smart grid is the best solution as it generates
energy from various renewable resources such as
wind, water, and solar. In the current generation, we
are taking energy from the government according to
the consumption we are paying them. However, for
the future, we are proposing a smart grid system that
will encourage an individual to generate energy. Due
to the rules and regulations of India, we cannot
directly use that energy. We will transmit that
generated energy to the government grid. We must
pay for the energy according to the total generation
and consumption. Let us assume that if we are
generating more energy than our consume, then the
government will pay us for that extra energy that we
are generating. If we are generating less energy than
our consumption, then we must pay for that extra
energy that we are consuming.
Fig. 9 Control unit shows user request receiver
Fig. 10 User request transmitter
5.5. The VI to Control the Hardware
For this VI, we used the LABVIEW software and
first configured the Arduino with the LABVIEW
software. This is done to make the Arduino work as
directed by the VI design. The data that this VI then
accesses the VI logs in for reception for further
processing. This is followed by a unit solely dedicated
to data parsing, i.e., acquiring valuable data for further
use. First, the address is abstracted from the message,
and then the unit request is extracted from the
message signal, as shown in Figure 7. After
abstracting the data, the primary process starts. Where
the unit by the users is compared, and then the main
battery is supplied with specified power. Then this is
forwarded to the battery at the relay side. This transfer
of the units from the main battery to the battery at the
user end is controlled via relays.
7. Conclusion
A smart grid is a next-generation power grid. It
includes
power
generation,
management,
transmission, distribution, and utilization. The main
features of a smart grid are that it is highly efficient,
reliable, and secure. There are various wired and
wireless technologies available for smart grid
applications. In this project, we are using wireless
technology-based Lab View software. Power
distribution in the smart grid is simulated using Lab
View. In this project, we generate energy through
solar, wind and water turbine. The solar panel will
generate 6V power; Windmill will generate 2V power,
and the water turbine will generate 6V power. The
237
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
control of power distribution in the smart grid. This
enhances the grid's efficiency by optimizing the
allocation of energy resources and minimizing
wastage. In conclusion, implementing a smart grid
with wireless technology-based Lab View software
and renewable energy sources offers numerous
benefits. It promotes sustainable energy generation
and improves grid efficiency, reliability, and security.
By harnessing the power of advanced technologies,
we can pave the way for a greener and more
sustainable future.
control unit will distribute this generated energy to the
users according to their request if generated energy is
more significant than the consumed energy. The
excess energy can be stored in energy storage systems
such as batteries or fed back into the primary power
grid. This allows for efficient utilization of renewable
energy sources and reduces reliance on traditional
fossil fuel-based power generation.
Furthermore, wireless technology-based Lab
View software enables real-time monitoring and
References
[1] Ruilong Deng et al., “Sensing-Performance Trade-off in Cognitive Radio Enabled Smart Grid,” IEEE Transactions on
Smart Grid, vol. 4, no. 1, pp. 302-310, 2013. [CrossRef] [Google Scholar] [Publisher Link]
[2] Juval Portugali, Self-Organization and the City, New York, NY, USA: Springer-Verlag, 2000. [Google Scholar]
[Publisher Link]
[3] Colin Harrison, and Ian Abbott Donnelly, “A Theory of Smart Cities,” Proceedings of the 55th Annual Meeting of the
ISSS, vol. 55, no. 1, 2011. [Google Scholar] [Publisher Link]
[4] D. Han et al., “A Renewable Energy Powered Wireless Sensor Network for Smart Grid,” Journal of Renewable and
Sustainable Energy, vol. 10, no. 1, p. 013301, 2018.
[5] T. Nasrin et al., “An Energy-Efficient Communication Protocol for Smart Grid Using Hierarchical Routing Approach,”
IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference, IEEE, pp. 641-646,
2018.
[6] P. Singh, V. Kumar, and D. S. Chauhan, “A Machine Learning-Based Energy-Efficient Routing Algorithm for Smart
Grid Systems,” 11th International Conference on Computing, Communication and Networking Technologies, IEEE, pp.
1-5, 2020.
[7] Q. Zhang et al., “An Energy-Efficient Routing Algorithm for Wireless Sensor Networks of Smart Grid Based on Particle
Swarm Optimization,” Mobile Networks and Applications, vol. 23, no. 2, pp. 305-311, 2018.
[8] H. R. Sridevi et al., “Voltage Regulation in an Islanded Microgrid using a GA based Optimization Technique,”
International Journal of Engineering Trends and Technology, vol. 70, no. 4, pp. 15-20, 2022. [CrossRef] [Google
Scholar] [Publisher Link]
[9] Marcelo Masera et al., “Smart (Electricity) Grids for Smart Cities: Assessing Roles and Societal Impacts,” Proceedings
of the IEEE, vol. 106, no. 4, pp. 613-625, 2018. [CrossRef] [Google Scholar] [Publisher Link]
[10] Xi Fang et al., “Smart Grid-The New and Improved Power Grid: A Survey,” IEEE Communications Surveys & Tutorials,
vol. 14, no. 4, pp. 944–980, 2012. [CrossRef] [Google Scholar] [Publisher Link]
[11] G. Dileep, “A Survey on Smart Grid Technologies and Applications,” Renewable Energy, vol. 146, pp. 2589–2625, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Vinod H. Patil et al., “A Testbed Design of Spectrum Management in Cognitive Radio Network using NI USRP and
LabVIEW,” International Journal of Recent Technology and Engineering, vol. 8, no. 2S8, 2019. [CrossRef] [Publisher
Link]
[13] M. Faheem et al., “Smart Grid Communication and Information Technologies in the Perspective of Industry 4.0:
Opportunities and Challenges,” Computer Science Review, vol. 30, pp. 1–30, 2018. [CrossRef] [Google Scholar]
[Publisher Link]
[14] Gouri R. Barai, Sridhar Krishnan, and Bala Venkatesh, “Smart Metering and Functionalities of Smart Meters in Smart
Grid-A Review,” IEEE Electrical Power and Energy Conference, pp. 138-145, 2015. [CrossRef] [Google Scholar]
[Publisher Link]
[15] Songlin Chen et al., “Internet of Things Based Smart Grids Supported by Intelligent Edge Computing,” IEEE Access, vol.
7, pp. 74089–74102, 2019. [CrossRef] [Google Scholar] [Publisher Link]
238
Vinod Patil et al. / IJEEE, 10(5), 227-239, 2023
[16] Yasir Saleem et al., “Internet of Things-Aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and
Future Research Directions,” IEEE Access, vol. 7, pp. 62962–63003, 2019. [CrossRef] [Google Scholar] [Publisher Link]
[17] Ozgur B. Akan, Osman B. Karli, and Ozgur Ergul, “Cognitive Radio Sensor Networks,” IEEE Network, vol. 23, no. 4,
pp. 34-40, 2011. [CrossRef] [Google Scholar] [Publisher Link]
[18] Ian F. Akyildiz, Won-Yeol Lee, and Kaushik R. Chowdhury, “Spectrum Management in Cognitive Radio Ad Hoc
Networks,” IEEE Network, vol. 23, no. 4, pp. 6-12, 2012. [CrossRef] [Google Scholar] [Publisher Link]
[19] Rong Yu et al., “Cognitive Radio Based Hierarchical Communications Infrastructure for Smart Grid,” IEEE Network,
vol. 25, no. 5, pp. 6-14, 2011. [CrossRef] [Google Scholar] [Publisher Link]
[20] Saurabh S. Shingare, Prabodh Khampariya, and Shashikant Bakre, “Application of ANN-Based Approach for Fault
Location in Extra High Voltage Networks,” International Journal of Engineering Trends and Technology, vol. 71, no. 2,
pp. 440-449, 2023. [CrossRef] [Publisher Link]
[21] David Bailey, and Edwin Wright, Practical Scada for Industry, Elsevier Linacre House, Jordan Hill, Oxford, UK, 2003.
[Google Scholar] [Publisher Link]
[22] A. Ghassemi, S. Bavarian, and L. Lampe, “Cognitive Radio for Smart Grid Communications,” First IEEE International
Conference on Smart Grid Communications, pp. 297-302, 2010. [CrossRef] [Google Scholar] [Publisher Link]
[23] Vehbi C. Gungor, Bin Lu, and Gerhard P. Hancke, “Opportunities and Challenges of Wireless Sensor Networks in Smart
Grid,” IEEE Transactions on Industrial Electronics, vol. 57, no. 10, pp. 3557-3564, 2010. [CrossRef] [Google Scholar]
[Publisher Link]
[24] Khosrow Moslehi, and Ranjit Kumar, “Smart Grid: A Reliability Perspective,” Innovative Smart Grid Technologies, pp.
1-8, 2010. [CrossRef] [Google Scholar] [Publisher Link]
[25] Vinod H. Patil, and Shruti Oza, “Green Communication for Power Distribution Smart Grid,” International Journal of
Recent Technology and Engineering, vol. 8, no. 1, pp. 1035-1039, 2019. [Publisher Link]
[26] C. Aguguo Ihechukwu, Matthias Daniel, and E. O. Bennett, “Big Data Mining for Interesting Pattern using Map Reduced
Technique,” SSRG International Journal of Computer Science and Engineering, vol. 7, no. 7, pp. 26-33,
2020. [CrossRef] [Publisher Link]
[27] Rong Yu et al., “QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic
Programming Approach,” IEEE Transactions on Neural Network and Learning Systems, vol. 27, no. 2, pp. 435-443,
2016. [CrossRef] [Google Scholar] [Publisher Link]
[28] Rehmat Ullah, Yasir Faheem, and Byung-Seo Kim, “Energy and Congestion-Aware Routing Metric for Smart Grid AMI
Networks in Smart City,” IEEE Access, vol. 5, pp. 13799–13810, 2017. [CrossRef] [Google Scholar] [Publisher Link]
[29] M. Kamalakkannun, and N. D. Sridhar, “Optimum Power Flow Model and LMP for Unified Power Flow
Controller,” International Journal of Engineering Trends and Technology, vol. 71, no. 2, pp. 21-26, 2023. [CrossRef]
[Publisher Link]
[30] Yasir Saleem et al., “Internet of Things-Aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and
Future Research Directions,” IEEE Access, vol. 7, pp. 62962–63003, 2019. [CrossRef] [Google Scholar] [Publisher Link]
239