Enhancing stochastic planning in autonomous hybrid energy systems through an advanced arithmetic optimization algorithm and K-means data clustering
Energy Reports,
Год журнала:
2025,
Номер
13, С. 4375 - 4387
Опубликована: Апрель 11, 2025
Язык: Английский
Enhancing connectivity and coverage in wireless sensor networks: a hybrid comprehensive learning-Fick’s algorithm with particle swarm optimization for router node placement
Dina A. Amer,
Sarah A. Soliman,
Asmaa Hassan
и другие.
Neural Computing and Applications,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 14, 2024
Язык: Английский
Correction: Alanazi et al. An Improved Fick’s Law Algorithm Based on Dynamic Lens-Imaging Learning Strategy for Planning a Hybrid Wind/Battery Energy System in Distribution Network. Mathematics 2023, 11, 1270
Mathematics,
Год журнала:
2025,
Номер
13(7), С. 1206 - 1206
Опубликована: Апрель 7, 2025
In
the
published
publication
[...]
Язык: Английский
Photovoltaic/Hydrokinetic/Hydrogen Energy System Sizing Considering Uncertainty: A Stochastic Approach Using Two-Point Estimate Method and Improved Gradient-Based Optimizer
Sustainability,
Год журнала:
2023,
Номер
15(21), С. 15622 - 15622
Опубликована: Ноя. 4, 2023
In
this
paper,
stochastic
sizing
of
a
stand-alone
Photovoltaic/Hydrokinetic/Hydrogen
storage
energy
system
is
performed
with
aim
minimizing
the
cost
project
life
span
(COPL)
and
satisfying
reliability
index
as
probability
load
shortage
(POLS).
The
implemented
using
novel
framework
considering
two-point
estimate
method
(2m+1
PEM)
improved
gradient-based
optimizer
(IGBO).
2m+1
PEM
used
to
evaluate
impact
uncertainties
resource
generation
demand
on
problem.
utilizes
approximate
account
for
these
uncertainties.
order
avoid
premature
convergence,
(GBO),
meta-heuristic
algorithm
influenced
by
Newtonian
concepts,
enhanced
dynamic
lens-imaging
learning
approach.
size
devices,
which
determined
utilizing
IGBO
COPL
minimization
optimally
POLS,
one
optimization
variables.
results
three
hPV/HKT/FC,
hPV/FC,
hHKT/FC
configurations
are
presented
in
two
situations
deterministic
without
taking
uncertainty
into
consideration.
findings
showed
that
hPV/HKT/FC
configuration
better
than
other
techniques
like
conventional
GBO,
particle
swarm
(PSO),
artificial
electric
field
(AEFA)
achieve
lowest
POLS
(higher
reliability)
various
cases.
Additionally,
increased
7.63%,
7.57%,
7.65%,
respectively,
while
fell
5.01%,
4.48%,
4.59%,
contrasted
sizing,
according
based
PEM.
As
result,
indicate
model,
quantity
output
insufficient
meet
under
unknown
circumstances.
Applying
volatility
both
supply
can,
therefore,
be
an
economically
sound
way
demand.
Язык: Английский
Neural Network Algorithm with Reinforcement Learning for Microgrid Techno-Economic Optimization
Mathematics,
Год журнала:
2024,
Номер
12(2), С. 280 - 280
Опубликована: Янв. 15, 2024
Hybrid
energy
systems
(HESs)
are
gaining
prominence
as
a
practical
solution
for
powering
remote
and
rural
areas,
overcoming
limitations
of
conventional
generation
methods,
offering
blend
technical
economic
benefits.
This
study
focuses
on
optimizing
the
sizes
an
autonomous
microgrid/HES
in
Kingdom
Saudi
Arabia,
incorporating
solar
photovoltaic
energy,
wind
turbine
generators,
batteries,
diesel
generator.
The
innovative
reinforcement
learning
neural
network
algorithm
(RLNNA)
is
applied
to
minimize
annualized
system
cost
(ASC)
enhance
reliability,
utilizing
hourly
speed,
irradiance,
load
behavior
data
throughout
year.
validates
RLNNA
against
five
other
metaheuristic/soft-computing
approaches,
demonstrating
RLNNA’s
superior
performance
achieving
lowest
ASC
at
USD
1,219,744.
outperforms
SDO
PSO,
which
yield
1,222,098.2,
MRFO,
resulting
1,222,098.4,
while
maintaining
loss
power
supply
probability
(LPSP)
0%.
exhibits
faster
convergence
global
than
algorithms,
including
SDO,
show
ability
converge
optimal
solution.
concludes
by
emphasizing
effectiveness
HES
sizing,
contributing
valuable
insights
off-grid
regions.
Язык: Английский
Emulation Structures and Control of Wind-Tidal Turbine Hybrid Systems for Saudi Arabia Off-shore Development
Engineering Technology & Applied Science Research,
Год журнала:
2024,
Номер
14(4), С. 15251 - 15256
Опубликована: Авг. 2, 2024
This
paper
presents
the
principles
of
developing
an
electromechanical
emulator
based
on
original
hybridization
concept
a
wind
and
tidal
power
system.
Wind
horizontal
axis
turbines
showcase
functional
similarities
coupling
possibility.
Tidal
concepts
are
very
close
to
those
power.
turbine
technology
should
thus
reach
maturity
more
quickly
because
it
is
possible
for
rely
certain
number
reliable
proven
techniques
developed
The
proposed
hybrid
–
system
electromechanically
coupled
rotation
single
common
electric
generator.
An
experimental
simulation
wind-tidal
was
carried
out,
using
architecture
results
both
numerical
simulations
out
in
MATLAB/Simulink
environment
tests
obtained
employing
real-time
emulators.
Язык: Английский
Deep graphene based reconfigurable circularly polarized star-shaped microstrip antenna design at terahertz frequencies for biomedical application
Optical and Quantum Electronics,
Год журнала:
2023,
Номер
56(3)
Опубликована: Дек. 30, 2023
Язык: Английский
A bi-objective optimization framework for configuration of battery energy storage system considering energy loss and economy
Energy Exploration & Exploitation,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 11, 2024
To
address
a
bi-objective
optimization
configuration
problem
of
battery
energy
storage
system
(BESS)
in
distributed
(DES)
considering
loss
and
economy,
perturbation
observation
approach
(P&O)
is
proposed
this
article.
First,
DES,
the
model
BESS
established.
Then,
novel
way
designed
that
transforming
into
single
objective
with
variable
conditions.
And
P&O
process
method
presented.
Finally,
simulation
case,
compared
or
improves
5.71-fold
2.94-fold
each
direction,
respectively
effectively
balances
contradiction
between
them.
In
addition,
efficiency
electricity
cost
increasing,
rated
capacity
changes
by
approximately
10%.
location
key
factor
affecting
scheme
DES.
Язык: Английский
Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Дек. 5, 2024
The
quality
of
underwater
images
is
often
affected
by
light
scattering
and
attenuation,
resulting
in
a
loss
contrast
brightness.
To
address
this
issue,
paper
proposes
an
image
enhancement
method:
improved
Fick's
law
algorithm-based
optimally
weighted
histogram
framework
(IFLAHF).
method
incorporates
the
bi-histogram
equalization-based
three
plateau
limits
(BHE3PL)
technique
to
enhance
details
while
maintaining
However,
its
dependence
on
fixed
parameters
adaptability.
overcome
limitation,
introduces
algorithm
(FLA)
then
improves
it
optimize
parameters.
FLA
incorporating
Tent
chaotic
mapping
reverse
learning
increase
population
diversity,
Levy
flight
introduced
later
stages
exploitation.
Additionally,
color
correction
applied
correct
deviations
images,
leading
more
natural
appearance.
verify
performance
method,
compared
with
different
methods.
As
demonstrated
simulations,
proposed
outperforms
existing
algorithms
multiple
metrics.
Язык: Английский