Analysis of Maximum Power Tracking and Battery SoC in Grid
Integrated Microgrid Using Fuzzy Logic Controller
Hima Bindu Eluri
1a
, M. Thirupathaiah
2b
and D. Krishna
3c
1
Department of EEE, Geethanjali College of Engineering and Technology, Hyderabad, India
2
Department of EEE, NITTE Meenkashi Institute of Technology, Bengaluru, India
3
Department of EEE, Anurag University, Hyderabad, India
Keywords: Energy Management, Microgrid, Grid Reliability, Intelligent Controllers, MATLAB/SIMULINK.
Abstract: Conventional power systems are currently undergoing significant change as a result of development of
modern micro grids, which include interconnected microgrids with high levels of energy storage, increasing
penetration of renewable energy in contemporary distribution networks. An integrated grid with many
dispersed sources is developed to provide dependable, effective solution for generation, distribution of
electricity. This manuscript focuses on energy management strategy for a hybrid renewable micro-grid system.
This kind of control strategies are employed for grid reliability, resiliency voltage regulation. Because
renewable energy sources are intermittent, predictive strategy explains energy availability, modifies system
operation is required. In this proposed work the main objectives are to improve maximum power, battery
charge/discharge by adopting intelligent controllers which can handle complex uncertainties-linear behaviour
by MATLAB/SIMULINK. The outcome proposed research which could be in form of results are improving
PV voltage, current with P&O method by applying PI, FLC controllers are compared
1 INTRODUCTION
Modern energy demands, developing nations,
electrical generation like fossil fuels with sustainable
energy(Sarkar, Minai, et al. , 2024), (Rao, Reddy, et
al. , 2021). In need of energy every day, world is
quickly becoming into global village for human
economic development (Nair, Gopika, et al. , 2024),
(Seedadan, Wongsathan, et al. , 2024). One important
tactic being used to address energy crisis,
environmental degradation is utilization of renewable
energy sources (RES) (Amirullah and Adiananda,
2024), (Nair, Gopika, et al. , 2024). Similar to solar,
wind, and biomass, using RES won't reduce their
availability. The ever-growing need for energy is met
by using sunlight, a steady source of energy
(Rishikesh, Kumar, et al. , 2024).
A viable way to sustain power supply, demand
response is to incorporate RES into the power system.
Integration of RES to utility grid depends on scale of
power generation. Integrating renewable energy into
a
https://orcid.org/0000-0003-2283-4455
b
https://orcid.org/ 0000-0003-3483-4428
c
https://orcid.org/0000-0001-9834-0254
grid poses challenges (Eluri and Naik, 2022). The
integration of distributed sources (DER’s) with grids
throws different kinds of challenges like
uncertainties, power quality, voltage stability,
frequency stability (Ajit and Agrawal, 2024), (Shi,
Liu, et al. , 2024). Distribution System
Operators(DSOs) are responsible for efficient
management of DER’s, optimization of grid
operations. A viable option for a modernized electric
infrastructure is microgrid (MG), which is notion of
DER. coupled to single power subsystem combines
conventional, renewable resources (Padmaja,
Tammali, et al. , 2022). The MG is operated in grid-
connected, islanded mode of operation (Hema,
Maheshprabhu, et al. , 2023), (Asnil, Nazir, et al. ,
2024). The hybrid MG is to reduce quantity of
conversion phases. Interface components where
system dependability and overall efficiency might be
increased (Eluri, and, Naik, 2023), (Sivakumar,
Selvaraj, et al. , 2024). Hybrid MGs may combine
both AC. DC loads (Reddy, and, Kumar, 2019). The
basic structure basic grid consisting of solar, wind
Eluri, H. B., Thirupathaiah, M. and Krishna, D.
Analysis of Maximum Power Tracking and Battery SoC in Grid Integrated Microgrid Using Fuzzy Logic Controller.
DOI: 10.5220/0013608000004664
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 3, pages 19-25
ISBN: 978-989-758-763-4
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.
19

energies, battery, 3-phase rectifier, non-linear loads
and an Energy management system (EMS) which is
used to monitor, control grid connected MG
(Aldosary, 2024). The basic structure of grid is
depicted is in Figure 1.
This manuscript focuses on various MPPT
techniques, battery management system by adopting
various intelligent controllers like Fuzzy Logic
Controllers (FLC), Adaptive FLC and Fractional
order (FOFLC).
Figure 1: Basic Structure of Microgrid with EMS
This manuscript is structured as follows: Section
II includes MPPT techniques, Section III is Battery
Management Systems (BEMS) & Energy
Management Systems (EMS), Section IV includes
proposed controllers, Section V is results &
discussions, section VI is conclusion.
2 RELATED WORKS
By continuously adjusting solar panels' operating
point to their maximum power point, MPPT enables
system to maximize amount of energy can be
extracted from available sunshine. MPPT, is an
algorithm built into charge controllers that, under
specific circumstances, extracts the highest amount of
power possible from photovoltaic modules
(Mamatha, Neelima, et al. , 2020). A solar charge
controller utilizes MPPT to optimize current flowing
into battery from photovoltaic modules is known
MPPT solar charge controller (Boubaker, 2023).
2.1 P & O MPPT Algorithm
P&O method is change in power(dP),PV voltage(dV)
is verified. This leads to changes in duty cycle(D)
(Masry, Mohammed, et al. , 2023). The real point is
positioned on left side of power curve for positive
gradient, on right side of power curve for negative
gradient. (Jabbar, Mekhilef, et al. , 2023). P&O is
very popular because of simplicity (Messaoudi,
Farhani, et al. , 2024). The flow chart of P & O is
presented in Figure 2. The equations involved in P&O
are.
𝑃

𝑡

𝑉𝑡∗𝐼𝑡 (1)
∆𝑃  𝑃

𝑡

𝑃𝑡1 (2)
𝑉

𝑡

𝑉𝑡1∆𝑉 (3)
Figure 2: Flow chart of Perturb & Observe(P&O) method
2.2 Incremental Conductance (IC)
MPPT Algorithm
MPPT is a useful for raising PV power output. IC
tracks peak power under varying atmospheric
condition (Singh, Singh, et al. , 2022). IC regulates if
MPPT is reached MPP, stops perturbing operating
point. The equations involved in IC are.





𝐼𝑉


(4)
The IC is defined as follows
𝐺𝑑 


(5)
When operating within operational limitations,
output power rises as PV module terminal voltage
increases (dP/dV >0), output power decreases as PV
terminal voltage increases (dP/dV <0)[17]. The IC
flow chart of IC is shown in Figure 3.
INCOFT 2025 - International Conference on Futuristic Technology
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Figure 3: Flow chart of IC method
3 BATTERY MANAGEMENT
SYSTEM & EMS
The BMS's is to make sure battery operates safely by
managing charging, discharge procedure, cell
balancing, estimating state of charge (SoC),
providing over-temperature protection. When a cell
or module is fully charged, SOC is proportionate to
entire amount of charge available. The EMS has been
included into BMS of hybrid energy systems to
guarantee effective power supply. EMS involves
coordination of sources, loads for maximum
Figure 4: Flow chart of EM
utilization of available power. EMS is crucial for
optimal power balance in hybrid PV/Wind turbine
systems. The objective of EMS is for improving
transients, MPPT, EMS for grid. The flow chart for
an EMS is shown in Figure 4.
4 PROPOSED METHODS
4.1 PI Controllers
To achieve objectives like MPPT, Battery
performance in grids a conventional controller is used
which is nothing but Proportional controller (PI). PI
controllers eliminate steady state faults, oscillations
caused by closing of controller action. PI controllers
are frequently used in electrical systems due to simple
form, implementation is frequently used in AC, DC
applications in combination with coordinate
transformations to regulate slowly changing or
constant quantities. The design of PI controllers to
reduce impact of load disruptions using a process
model. maximizing integral gain is goal of several
works. Researchers have increasingly incorporated
intelligent optimization algorithms into PI for
parameter tweaking as result of advances in
intelligent control theory. The proposed PI reduces
grid energy consumption by an equivalent amount
while maintaining battery SoCs in an optimal
operating range. The applications of PI Controller are
speed control, liquid flow control, HVAC systems.
The proposed PI with MPPT is depicted in Figure 5.
Figure 5: PI controller
4.2 FLC Controllers
Fuzzy logic is frequently employed to regulate a
system's numerous parameters. The ability of FLC to
handle nonlinearities, uncertainties in variety of
technological environments is highlighted via review
of most recent advancements in FL applications
across crucial domains, like energy harvesting (EH),
ambient conditioning systems (ACS), robotics,
autonomous systems (RAS). FLC is not exclusively
Analysis of Maximum Power Tracking and Battery SoC in Grid Integrated Microgrid Using Fuzzy Logic Controller
21

dependent on a mathematical model of plant, in
contrast to conventional control theory, an
approximate mathematical model aids in FLC fine
tuning. The FLC is examined in different loading
situations compared with PI controller. The three
fundamental building blocks of FLC are
defuzzification block, inference engine, fuzzification
block. Here, the power is determined by solar panel's
voltage, current. The use of essential fuzzy rules,
which offer semantic interpretability reasoning
process's understandability, is a fundamental
component of Fuzzy interference system (FIS). The
proposed FLC with MPPT is presented in Figure 6.
FIS is depicted in Figure 7.
Figure 6: FLC controller
Figure 7: Fuzzy Interference System
The membership functions for input1, input2 and
input1is explored in Figure 8., Figure 9., Figure 10.
Figure 8: Membership Functions for Input1
Figure 9: Membership Functions for Input2
Figure 10: Membership Functions for Output
The rule table FLC is depicted in TABLE1 which
explains the relationship between error and change in
error.
Table 1 Rule Table
E(K)/DE(K) NL NS ZE PS PL
NL NL NL NL NS ZE
NS NL NL NS ZE PS
ZE NL NS ZE PS PL
PS NS ZE PS PL PL
PL ZE PS PL PL PL
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5 RESULTS AND DISCUSSIONS
The results of proposed hybrid system by adopting PI,
FLC using P&O, IC method are explored in
Figure11-Figure 14.
Figure 11: V
PV
, I
PV
, V
DC
with PI using P & O method
Figure 12: V
PV
, I
PV
, V
DC
with PI using IC method
Figure13: V
PV
, I
PV
, V
DC
with FLC using P & O method
Figure 14: V
PV
, I
PV
, V
DC
with FLC using P & O method
The battery results of PI, FLC controllers are
resulted in Figure 15, Figure 16.
Figure 15: Power, Voltage, Currents with PI Controller
Figure 16: Power, Voltage, Currents with FLC Controller
6 CONCLUSIONS
This paper investigated solutions for Hybrid Micro
grid systems comprising various distributed energy
resources by using MATLAB/SIMULINK. The
proposed work focuses on various MPPT methods,
Battery results by adopting PI, FLC controllers. To
improve grid reliability, to increase maximum power
comparison with intelligent controller and PI is done
by simulation. FLC is multi-objective optimization
technique that is applied to identify optimal capacity
of EMS, schedule optimal power generation. The
proposed EMS is designed for smooth fluctuation of
grid. Researchers can extend this kind of work to
more intelligent controllers.
7 FUTURE SCOPE
By concentrating mostly on electric mobility,
stationary applications, it further investigates existing
gaps regarding the performance requirements of
BMS. This work can be expanded to assess the best
Analysis of Maximum Power Tracking and Battery SoC in Grid Integrated Microgrid Using Fuzzy Logic Controller
23

method for regulating DC bus voltage: an intelligent
controller that makes use of adaptive FLC. innovative
supervisory power management technique for
battery-powered PV systems. Additionally, the
research offers a framework for creating a new BMS
standard, with a focus on operational risk and BMS
safety. Future battery management systems will face
a number of general regulatory hurdles in addition to
application-specific safety requirements unique tasks
that a BMS must perform. A FLC-based approach for
coordinated BESS control with a modified AC
coupling topology can be developed from this
suggested study. Overshoot, settling time, total
harmonic distortion (THD) are factors that can be
adjusted in this regard.
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