Bi-level energy co-optimization of regional integrated energy system with electric vehicle to generalized-energy conversion framework and flexible hydrogen-blended gas strategy
Applied Energy,
Год журнала:
2025,
Номер
390, С. 125868 - 125868
Опубликована: Апрель 11, 2025
Язык: Английский
Dynamic gold rush optimizer: fusing worker adaptation and salp navigation mechanism for enhanced search
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Май 6, 2025
Abstract
The
Dynamic
Gold
Rush
Optimizer
(DGRO)
is
presented
as
an
advanced
variant
of
the
original
(GRO),
addressing
its
inherent
limitations
in
exploration
and
exploitation.
While
GRO
has
demonstrated
efficacy
solving
optimization
problems,
susceptibility
to
premature
convergence
suboptimal
solutions
remains
a
critical
challenge.
To
overcome
these
limitations,
DGRO
introduces
two
novel
mechanisms:
Salp
Navigation
Mechanism
(SNM)
Worker
Adaptation
(WAM).
SNM
enhances
both
exploitation
by
dynamically
guiding
population
through
stochastic
strategy
that
ensures
effective
navigation
solution
space.
This
mechanism
also
facilitates
smooth
transition
between
exploitation,
enabling
algorithm
maintain
diversity
during
early
iterations
refine
later
stages.
Complementing
this,
WAM
strengthens
phase
promoting
localized
interactions
among
individuals
within
population,
fostering
adaptive
learning
promising
search
regions.
Together,
mechanisms
significantly
improve
DGRO’s
ability
converge
toward
global
optima.
A
comprehensive
experimental
evaluation
was
conducted
using
benchmark
functions
from
Congress
on
Evolutionary
Computation
(CEC)
CEC2013
CEC2020
test
suites
across
30
50-dimensional
spaces,
alongside
seven
complex
engineering
problems.
Statistical
analyses,
including
Wilcoxon
Rank-Sum
Test
(WRST)
Friedman
Rank
(FRT),
validate
superior
performance,
demonstrating
significant
advancements
capability
stability.
These
findings
underscore
effectiveness
competitive
robust
algorithm.
Язык: Английский
Identification of Transformer Parameters Using Dandelion Algorithm
Applied System Innovation,
Год журнала:
2024,
Номер
7(5), С. 75 - 75
Опубликована: Авг. 29, 2024
Researchers
tackled
the
challenge
of
finding
right
parameters
for
a
transformer-equivalent
circuit.
They
achieved
this
by
minimizing
difference
between
actual
measurements
(currents,
powers,
secondary
voltage)
during
transformer
load
test
and
values
predicted
model
using
different
parameter
settings.
This
process
considers
limitations
on
what
can
have.
research
introduces
application
new
effective
optimization
algorithm
called
dandelion
(DA)
to
determine
these
parameters.
Information
from
real-time
tests
(single-
three-phase
transformers)
is
fed
into
computer
program
that
uses
DA
find
best
aforementioned
difference.
Tests
confirm
reliable
accurate
tool
estimating
It
achieves
excellent
performance
stability
in
optimal
precisely
reflect
how
behaves.
The
significantly
lower
fitness
function
value
0.0136101
case,
while
single-phase
case
it
reached
0.601764.
indicates
substantially
improved
match
estimated
measured
electrical
model.
By
comparing
with
six
competitive
algorithms
prove
well
each
method
minimized
predictions,
could
be
shown
outperforms
other
techniques.
Язык: Английский
Improved Dujiangyan Irrigation System Optimization (IDISO): A Novel Metaheuristic Algorithm for Hydrochar Characteristics
Processes,
Год журнала:
2024,
Номер
12(7), С. 1321 - 1321
Опубликована: Июнь 26, 2024
Hyperparameter
tuning
is
crucial
in
the
development
of
machine
learning
models.
This
study
introduces
nonlinear
shrinking
factor
and
Cauchy
mutation
mechanism
to
improve
Dujiangyan
Irrigation
System
Optimization
(DISO),
proposing
improved
algorithm
(IDISO)
for
hyperparameter
learning.
The
optimization
capabilities
convergence
performance
IDISO
were
validated
on
87
CEC2017
benchmark
functions
varying
dimensions
nine
real-world
engineering
problems,
demonstrating
that
it
significantly
outperforms
DISO
terms
speed
accuracy,
ranks
first
overall
among
seventeen
advanced
metaheuristic
algorithms
being
compared.
To
construct
a
robust
generalizable
prediction
model
hydrochar
element
characteristics,
this
utilized
fine-tune
parameters
XGBoost
model.
experimental
results
show
IDISO-XGBoost
achieved
an
average
0.95,
which
represents
4%
improvement
over
DISO-XGBoost
These
indicate
has
significant
potential
value
practical
applications.
Язык: Английский
A Comprehensive Review on Selective Harmonic Elimination Techniques and Its Permissible Standards in Electrical Systems
IEEE Access,
Год журнала:
2024,
Номер
12, С. 141966 - 141998
Опубликована: Янв. 1, 2024
Selective
harmonic
elimination
techniques
have
developed
a
crucial
feature
in
the
domain
of
power
electronics
and
innumerable
drives
control
schemes.
The
main
intention
this
review
paper
is
to
make
readers
delve
into
numerous
methods
employed
SHE
techniques,
formulations
its
applications,
challenges
faced
grid
allowable
standards
harmonics
provided
by
various
like
IEEE
IEC.
By
exploring
mathematical
formulations,
historical
development
comparison
optimization
algorithms
as
well
applications
sectors,
attempts
impart
complete
understanding
importance
electrical
engineering.
Furthermore,
work
will
also
analyze
existing
met
it
emphasizes
potential
future
target
for
exploration
advancement
field.
Язык: Английский
Boosting Walrus Optimizer Algorithm based on ranking-based update mechanism for parameters identification of photovoltaic cell models
Electrical Engineering,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 9, 2024
Язык: Английский
PSSs Layout using Dandelion Optimization Approach
WSEAS TRANSACTIONS ON ELECTRONICS,
Год журнала:
2024,
Номер
15, С. 157 - 165
Опубликована: Дек. 30, 2024
This
paper
develops
an
optimal
Power
System
Stabilizers
(PSSs)
design
employing
the
Dandelion
Optimization
Algorithm
(DOA)
implemented
in
a
multimachine
system.
The
synthesizing
of
PSS
parameters
is
shaped
as
DOA-addressed
optimization
matter.
An
objective
equation
invoked
by
eigenvalue,
incorporating
lightly
damped
electromechanical
modes,
damping
ratio,
and
factor,
utilized
for
layout.
functioning
suggested
DOA-based
PSSs
(DOAPSS)
evaluated
against
Differential
Evolution-based
(DEPSS)
under
various
running
requirements
disturbances.
supremacy
DOAPSS
validated
across
time-domain
analysis,
eigenvalues,
indices,
demonstrating
its
superiority
over
DE
approach.
Язык: Английский