Heliyon,
Journal Year:
2024,
Volume and Issue:
10(3), P. e24920 - e24920
Published: Jan. 22, 2024
This
study
focuses
on
the
optimization
of
consequence
management
actions
in
urban
water
distribution
network.
The
EPANET
simulation
model
is
employed
combination
with
multi-objective
modified
seagull
algorithm
(MOMSOA)
based
archives
for
a
more
efficient
process.
Two
objective
functions
are
developed:
minimizing
reactive
activities
(cost
reduction)
and
consumed
pollution
mass.
utilization
shut-off
valves
hydrants
isolating
network
discharging
explored.
Without
management,
84.5
kg
consumed.
With
18
activities,
consumption
was
reduced
to
59.8
kg.
Also,
compare
proposed
method
other
algorithms,
interaction
curve
between
amount
pollutant
mass
obtained
using
methods,
including
MOSOA,
NSGA-II,
MOPSO,
MOSMA.
According
curve,
performed
better
reducing
pollution.
Extracting
optimal
MOMSOA
maximum
takes
about
80
min.
archive
technique
significantly
shortens
this
time
real-time
management.
approach
demonstrates
that
increasing
population
decreases
extraction
curves
objectives
by
up
60
%.
A
small
capacity
slightly
increases
required
extract
due
searching
similar
solutions.
However,
utilizing
enables
IET Renewable Power Generation,
Journal Year:
2024,
Volume and Issue:
18(6), P. 959 - 978
Published: Feb. 20, 2024
Abstract
The
pressing
need
for
sustainable
energy
solutions
has
driven
significant
research
in
optimizing
solar
photovoltaic
(PV)
systems
which
is
crucial
maximizing
conversion
efficiency.
Here,
a
novel
hybrid
gazelle‐Nelder–Mead
(GOANM)
algorithm
proposed
and
evaluated.
GOANM
synergistically
integrates
the
gazelle
optimization
(GOA)
with
Nelder–Mead
(NM)
algorithm,
offering
an
efficient
powerful
approach
parameter
extraction
PV
models.
This
investigation
involves
thorough
assessment
of
algorithm's
performance
across
diverse
benchmark
functions,
including
unimodal,
multimodal,
fixed‐dimensional
CEC2020
functions.
Notably,
consistently
outperforms
other
approaches,
demonstrating
enhanced
convergence
speed,
accuracy,
reliability.
Furthermore,
application
extended
to
single
diode
double
models
RTC
France
cell
model
Photowatt‐PWP201
module.
experimental
results
demonstrate
that
approaches
terms
accurate
estimation,
low
root
mean
square
values,
fast
convergence,
alignment
data.
These
emphasize
its
role
achieving
superior
efficiency
renewable
systems.
IEEE Access,
Journal Year:
2024,
Volume and Issue:
12, P. 30345 - 30361
Published: Jan. 1, 2024
Direct
current
(DC)
microgrids
are
becoming
increasingly
important
due
to
a
number
of
causes,
including
the
widespread
use
DC
loads,
integration
solar
photovoltaic
(PV)
and
energy
storage
devices
(ESDs),
absence
frequency
reactive
power
control
issues.
The
bus
voltage,
management,
effective
split
among
ESDs,
state
charge
(SoC)
restorations
in
microgrid.
However,
voltage
management
difficult
since
connect
several
distributed
generators
(DGs),
utility
grids,
ESDs
using
electronic
converters.
It
is
imperative
properly
manage
sources
loads
order
maintain
stability
reliability
microgrids.
can
be
controlled
by
employing
centralized,
decentralized,
distributed,
multi-level,
hierarchical
systems
ensure
safe
secure
operation.
Besides,
advanced
techniques,
such
as
nonlinear,
robust,
model
predictive,
artificial
intelligence,
many
others,
employed.
This
article
critically
reviews
two
main
aspects
microgrids:
management.
challenges
opportunities
for
discussed.
benefits
drawbacks
various
methods
have
been
thoroughly
documented,
making
this
great
resource
industry
professionals
academics
alike.
Technical
issues
related
grid-connected
islanded
Key
research
gaps
identified,
which
could
filled
cutting-edge
technologies.
Readers
will
benefit
from
review
learning
about
need
further
research.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Feb. 9, 2025
In
this
study,
we
present
a
comparative
analysis
of
various
trajectory
optimization
algorithms
for
Unmanned
Aerial
Vehicles
(UAVs)
navigating
complex
environments.
The
performance
the
proposed
FOPID-TID
based
HAOAROA
(Hybrid
Archimedes
Optimization
Algorithm-Rider
Algorithm)
is
evaluated
against
traditional
methods
such
as
A*,
JPS,
Bezier,
and
L-BSGF
algorithms.
approach
integrates
advantages
fractional-order
control
with
hybrid
techniques
to
improve
UAV
planning.
Simulation
results
indicate
that
method
carries
significantly
better
than
respect
length,
smoothness,
overall
stability.
Remarkably,
yields
10%
reduced
length
smoother
while
also
being
more
computationally
efficient.
By
using
parameters,
dynamic
response
becomes
in
challenging
This
shows
disturbance
rejection
precision
are
much
superior
original
two
subroutines.
applications
presented
study
allow
future
growth
system
improvements
provide
proof
concept
improving
UAVs
dynamic,
PLoS ONE,
Journal Year:
2023,
Volume and Issue:
18(5), P. e0286060 - e0286060
Published: May 26, 2023
This
paper
discusses
the
merging
of
two
optimization
algorithms,
atom
search
and
particle
swarm
optimization,
to
create
a
hybrid
algorithm
called
(h-ASPSO).
Atom
is
an
inspired
by
movement
atoms
in
nature,
which
employs
interaction
forces
neighbor
guide
each
population.
On
other
hand,
intelligence
that
uses
population
particles
for
optimal
solution
through
social
learning
process.
The
proposed
aims
reach
exploration-exploitation
balance
improve
efficiency.
efficacy
h-ASPSO
has
been
demonstrated
improving
time-domain
performance
high-order
real-world
engineering
problems:
design
proportional-integral-derivative
controller
automatic
voltage
regulator
doubly
fed
induction
generator-based
wind
turbine
systems.
results
show
outperformed
original
terms
convergence
speed
quality
can
provide
more
promising
different
systems
without
significantly
increasing
computational
cost.
promise
method
further
using
available
competitive
methods
are
utilized
e-Prime - Advances in Electrical Engineering Electronics and Energy,
Journal Year:
2023,
Volume and Issue:
6, P. 100325 - 100325
Published: Oct. 16, 2023
Automatic
voltage
regulators
(AVRs)
are
essential
components
in
electrical
systems
to
maintain
stable
output,
ensuring
optimal
performance
and
equipment
protection.
The
effectiveness
of
AVRs
rely
on
key
parameters
such
as
regulation,
response
time,
stability,
efficiency.
Integrating
controllers
with
offers
centralized
monitoring
enhancing
output
This
study
therefore
first
discusses
various
controller
types
which
showcase
distinctive
capabilities
based
their
tuning
strategies
then
introduces
an
intelligent
optimization
approach
using
fractional-order
proportional-integral-derivative
double
derivative
(FOPIDD2)
tailored
for
AVRs.
adopts
the
artificial
rabbits
(ARO)
algorithm,
fortified
adaptive
local
search
(ALS)
mechanism
experience-based
perturbed
learning
(EPL)
strategy.
modified
version
(m-ARO)
enhances
solution
diversity
navigational
efficacy,
resulting
improved
quality.
study's
core
objective
is
demonstrate
superior
m-ARO-based
FOPIDD2
addressing
multifaceted
challenges
AVR
control,
outperforming
conventional
techniques
speed
response,
robustness,
To
validate
method's
a
comparative
analysis
conducted
existing
different
algorithms.
Results
indicate
that
proposed
achieves
metrics,
demonstrating
its
capability.
also
includes
wider
perspective
by
considering
nineteen
controllers,
reported
literature,
comprehensive
comparison.
Notably,
method
exhibits
best
further
affirming
effectiveness.