Energy Reports,
Journal Year:
2024,
Volume and Issue:
11, P. 4423 - 4451
Published: April 18, 2024
In
recent
times,
the
landscape
of
power
systems
has
undergone
significant
evolution,
particularly
with
integration
diverse
renewable
energy
sources
(RESs).
This
advancement
presents
an
invaluable
opportunity
to
enhance
efficiency
in
modern
grid,
primarily
by
bolstering
role
stochastic
RESs.
The
challenge
lies
optimal
flow
(OPF),
a
multifaceted
and
non-linear
optimization
that
grows
more
complex
inclusion
RESs
aims
optimize
allocation
system
resources
minimize
operational
cost
while
maintaining
stability
security
system.
Addressing
this,
current
study
introduces
innovative
approach,
Multi-Objective
RIME
(MORIME)
algorithm.
Drawing
inspiration
from
physical
phenomenon
rime-ice,
called
RIME,
MORIME
seeks
effectively
tackle
OPF
issues.
algorithm
enhances
solution
accuracy
smartly
dividing
non-dominated
sorting
crowding
distance
mechanism.
proposed
model
incorporates
three
types
RESs:
solar
photovoltaic,
wind
small-scale
hydropower
units.
While
uncertainties
speed
irradiation
are
managed
through
Monte
Carlo
simulations,
small
hydro
unit
is
considered
constant
source.
efficacy
tested
on
IEEE
30
bus
results
indicate
method
identifies
for
multi-objective
problem
satisfying
constraints,
thereby
proving
its
effectiveness
superiority
over
MOWOA,
MOGWO,
MOALO,
MOMRFO
MOAGDE
terms
Hyper
Volume
(HV)
reciprocal
Pareto
Sets
Proximity
(1/PSP)
metrices.
source
code
available
at:
https://github.com/kanak02/MORIME
IEEE Internet of Things Journal,
Journal Year:
2024,
Volume and Issue:
11(11), P. 20605 - 20618
Published: March 5, 2024
An
innovative
method
to
raise
wireless
communication
systems'
efficiency
is
use
Reconfigurable
Intelligent
Surface
(RIS).
Unfortunately,
determining
the
quantity
and
locations
of
RIS
elements
continues
be
difficult,
requiring
a
clever
optimization
framework.
Concerning
practical
overlap
between
related
multi-RISs
in
systems,
this
paper
attempts
minimize
number
RISs
while
considering
average
possible
data
rate
technological
constraints.
In
regard,
novel
Enhanced
Artificial
Rabbits
Algorithm
(EARA)
developed
installed.
The
EARA
inspired
by
natural
survival
strategies
rabbits,
including
detour
eating
random
concealment.
A
more
effective
exploring
search
space
around
best
solution
so
far
produced
suggested
combining
an
upgraded
Collaborative
Searching
Operator
(CSO)
arrangement.
Also,
adaptive
time
function
included
increase
effect
exploitation
tactic
increasing
iterations.
simulation
results
show
that
highly
efficient
reaching
maximum
success
producing
smallest
under
various
feasible
threshold
settings.
When
compared
standard
Optimizer
(ARO),
Growth
(GO),
Ecosystem
(AEO),
Particle
Swarm
Optimization
(PSO),
improved
5.32%,
6.7%,
16.73%,
20.06%,
respectively.
Furthermore,
according
data,
outperforms
AEO,
GO,
ARO,
PSO
terms
at
δ=1.4
6.66%,
45.43%,
99%,
