Power Factor Detection and Data Analytics

International Research Journal of Engineering and Technology (IRJET)
© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 846
Power Factor Detection and Data Analytics
1Student, Dept. of Electrical & Electronics Engineering, PES University, Bangalore
5 Assistant Professor, Dept. of Electrical & Electronics Engineering, PES University, Bangalore
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - With the growing power demand and
increasing usage of energy, the traditional electricity
transmission and distribution network can be improved into
an interactive service or a smart grid. Smart meters are one
of the main proposed solutions for the smart grid. Hence, the
implementation of this can contribute to the detection of
power factor value as well as other power parameters. This
information can be useful if available to users directly, as it
allows for comparison and analysis of the load's efficiency.
The aim of the project is to provide a medium for this data
transfer from server to the client in a secure and efficient
manner. Thus involving data security and analytics. With
the use of a personalized android application, the user can
access the data easily.
Key Words: Power Factor, Efficiency, Smart Grid, Android
Application.
1.INTRODUCTION
With the growing power demand, the traditional
electricity transmission and distribution network can be
improved into an interactive service or a smart grid. Smart
meters are one of the main proposed solutions for the
smart grid.
The implementation of this network can contribute to the
detection of power factor value as well as other power-
parameters. This information can be useful if available to
users directly, as it allows for comparison and analysis of
the load's efficiency. The aim of the project is to establish a
secure and an effective medium to transfer data from the
server to the client. The involvement of data encryption
will further enhance the system. With the use of a
personalized android application, the user can access the
data effortlessly.
2. POWER FACTOR
The primary motive of any mechanized industry is the
efficient utilization of energy. The power factor of any
electrical system plays a significant role in determining
how efficient it is to do the useful work. The main
definition of power factor (PF) of an AC electrical power
system is “the ratio of the real power flowing to the load,
to the apparent power in the circuit”. Real power (kW) is
considered as the capacity of the circuit for performing
work in a particular time whereas apparent power (kVA)
is the product of the current and voltage of the circuit.
Reactive power is the power that isn’t used to do work on
load.
The formula of power factor can be expressed as follows -
(1)
The ideal power factor is known to be unity, or one. It is
the most desirable power factor value and anything less
than unity means that extra power is required to achieve
the same output.
3. ZERO CROSSING METHOD
The main method used in the project to determine the
power factor of an industrial load is the zero-crossing
method. Zero crossing detection (ZCD) is the most
common method for measuring the frequency or the
period of a periodic signal. When the frequency of a signal,
usually the number of cycles of a reference signal is
measured over one or more time periods of the signal
being measured.
Measuring multiple periods helps to reduce errors caused
by phase noise by making the perturbations in zero
crossings small relative to the total period of the
measurement.
The net result is an accurate measurement at the expense
of slow measurement rates. ZCD is one of the ways that
can be used to find the power factor of a given load. The
voltage and current wave-forms are recorded. From
multiple cycles : each of 20ms (50Hz), the zero crossing
point is determined. Since a 10 bit ADC is used (it has
e-ISSN: 2395-0056
Volume: 10 Issue: 03 | Mar 2023 www.irjet.net p-ISSN: 2395-0072
S Vaishnav Ghautham1, Sai Namrata Kottur2, Ron CM3, Michael Aishan Rao J4, Suma S 5

International Research Journal of Engineering and Technology (IRJET)
1024 values), the zero crossing point found from the
sensor is always around 512.
4. SIGNIFICANCE OF DATA SECURITY
The main intention of data security is to ensure that only
the authorized users can read, write and change the data
that is being transferred or received. In the project one of
our main goals is to safe-guard the data being sent
between the server and client. To avoid data breaching, we
have incorporated the concept of Firebase Real-Time
Database security rules and an encryption algorithm. Its
security rules determine who has read and write access to
your database, how your data is structured, and what
indexes exist. Data values like the voltage, current and
power readings will be shared via the firebase database.
5. METHODOLOGY
The complete integration of the hardware and software
architecture is done for the detection of power factor in an
industrial environment.
The power factor values are found using the zero crossing
method. The raw sensor values recorded from the current
and voltage sensors are plotted. The graph obtained has
two sinusoidal waveforms, one being the voltage and one
being current. The zero crossing point of both the
waveforms are found and then, the time difference is
found between them. The smart meter will send the
calculated values (Power, Power factor, Penalty factor,
Power consumption) in an encrypted format to the online
database where the data will be stored. This encrypted
data will then be available for access to the user on
another database, where individual values will be
decrypted and shown accordingly. the user with the help
of an android application can view the collected data from
the loads considered in an organized manner.
Fig 1: Circuit Diagram of the Smart meter
6. HARDWARE ARCHITECTURE
This product's hardware revolves around the design and
operation of a smart meter. The smart meter that we have
built can take two loads into consideration (working in
tandem). A voltage sensor (ZMPT101B) and two current
sensors (ACS712) are used to record the V and I values
respectively. The voltage sensor is connected in parallel to
both the loads, whereas two current sensors are used
individually for each load (connected in series).
The raw sensor voltage will be converted to current this
way: raw voltage * resolution. This will be subtracted by
2.45 (offset value). We divide the final voltage by 0.185
which is the sensitivity for acs712, as given in the
datasheet.
We take 235 current values which when combined
contribute to a current waveform. We then find the peak
current value out of the 235 recorded data sets. So the
maximum current value is Im, which when divided by
√ gives us the rms value of current.
The rms current value can be further used to determine
the power factor values.
Fig 2 : Hardware Implementation of the Circuit
n addition to current parameters, raw voltage sensor
values are recorded. Since a 10 bit ADC is used
(ATMEGA328P), there are 1024 analog values. It is
understood that the zero crossing point of the sensor will
be around 512, which when compared with the operating
voltage of the sensor (5V), is 2.5V. So by default, 512 is
subtracted from the analog value read from the sensors.
Each recorded value is squared, 1000 such values are
considered where each value is read every 1 or 2 ms. The
mean value of the 1000 values is found and the square
root of the same is calculated. Which when multiplied with
1.5 (amplification factor) gives out the Root Mean Square
Voltage.
e-ISSN: 2395-0056

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Fig 3: Final Setup of the Prototype
7. SOFTWARE DEVELOPMENT
Android Studio is a reliable platform to create android
projects/apps that can be accessed on devices like
smartphones, tablets, etc. Android Studio along with its
Gradle-based build system extends a consolidated
environment where we can develop for various android
devices and hence, provides extensive testing tools and
frameworks.
In the app developed, we have established a connection
between the Android Application and the firebase
database. The application will retrieve data values from
the firebase in a secure encrypted format, and as a result it
will display the analyzed data in an interactive-unique
style for the end user to view.
The smart meter will send the calculated values (Power,
Power factor, Penalty factor, Power consumption) in an
encrypted format to the online database where the data
will be stored. This encrypted data will then be available
for access to the user on another database, where
individual values will be decrypted and shown
accordingly. the user with the help of an android
application can view the collected data from the loads
considered in an organized manner.
Fig 4: Android Application: User authentication
Fig 5: Android Application: Consumption Details

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Fig 6: Android Application: Analyzed Output
8. CALCULATIONS
The power factor calculations can be done according to the
approach implemented below:
Time Difference = 20 ms => Phase Difference = 360
degrees
Time Difference =2 ms => Phase Difference
= =
Therefore, power factor = cos( ) = 0.8
If the power factor is found to be less than 0.85 , a
surcharge of 30 paise per unit consumed will be taxed for
every reduction of Pf by 0.01, below 0.85. For example, if
the averaged power factor was 0.75 for 1 unit, the penalty
factor would be:
The energy charges are considered from Bangalore
Electric Supply board’s Documentation for 2022 - 2023
period. Since the proposed product finds power
parameters for loads individually, a mean value of the
above tariff rates is considered for simplicity. So, for one
unit, the cost would be:
9. CONCLUSION
This project deals with the design and implementation of a
model which enables users to directly access the power
figures and efficiency of the load used. The model also
permits the comparative analysis between two different
apparatus running in tandem. With the help of an android
application, we have given the user a medium to access all
the necessary information and the added feature of cost
and penalty factor based on power consumption. The
transfer and storage of such important information, made
it susceptible to malware and cyber-attacks, and thus we
have also implemented an encryption and decryption
process thus making the data transfer safe and secure. The
main reason as to why our model is so efficient is because
the entire process happens on a real time basis and is
automatically updated after every time interval.
10. FUTURE SCOPE
With the help of the proof of concept explained, the project
can be extended to industry standards and provide an
online platform to perform effective data analytics on
power parameters which will prove to be very useful in
different applications.
11. REFERENCES
[1] Herrmann, Christoph & Posselt, Gerrit & Zein, André.
(2010). Industrial Smart Metering – Application of
Information Technology Systems to Improve Energy
Efficiency in Manufacturing.
[2] A. R. Al-Ali, I. A. Zualkernan, M. Rashid, R. Gupta and M.
Alikarar, "A smart home energy management system using
IoT and big data analytics approach," in IEEE Transactions
on Consumer Electronics, vol. 63, no. 4, pp. 426-434,
November 2017, doi: 10.1109/TCE.2017.015014.
[3] Mishra, Nikhil & Kumar, Vinay & Bhardwaj, Garima.
(2019). Role of Cloud Computing in Smart Grid. 252-255.
10.1109/ICACTM.2019.8776750.
[4] Xun Li, Qingwu Gong, Member IEEE, Xiao Zheng,“The
application of IOT in power systems”, in IEEE 2011, 978-1-
4577-1002-5/11
[5] Deepak K. D. and Pawan D.,―Performance Comparison
of Symmetric Data Encryption Techniques‖ ISSN: 2278 –
1323 International Journal of Advanced Research in
Computer Engineering & Technology Volume 1, Issue 4
June 2012.

Power Factor Detection and Data Analytics

More Related Content

Similar to Power Factor Detection and Data Analytics (20)

More from IRJET Journal (20)

Recently uploaded (20)

Power Factor Detection and Data Analytics