Energy Reports,
Год журнала:
2024,
Номер
11, С. 982 - 1005
Опубликована: Янв. 3, 2024
Optimal
power
flow
(OPF)
problem
solution
is
a
crucial
task
for
the
operators
and
decision
makers
to
assign
best
setting
of
system
components
obtain
most
economic,
environmental,
technical
suitable
state.
Artificial
Hummingbird
Algorithm
recent
optimization
algorithm
that
has
been
applied
solving
several
problems.
In
this
paper,
Modified
(MAHA)
proposed
improving
performance
orignal
as
well
effectivelly
solve
OPF
problem.
The
MAHA
based
on
searching
capability
by
boosting
exploitation
using
bandwidth
motion
around
solution,
while
exploration
process
improved
Levy
flight
distribution
fitness-distance
balance
selection.
This
modified
version
helps
overcome
issues
such
stagnation,
premature
convergence,
propensity
local
optima
when
tackling
complex,
nonlinear,
non-convex
problems
like
OPF.
order
confirm
effectiveness
algorithm,
series
tests
are
conducted
23
standard
benchmark
functions,
including
CEC2020.
resulting
outcomes
then
compared
those
obtained
other
algorithms
selection-based
stochastic
fractal
search
(FDBSFS),
antlion
optimizer
(ALO),
whale
(WOA),
sine-cosine
(SCA),
learning
artificial
bee
colony
(FDB-TLABC),
traditional
hummingbird
(AHA).The
evaluated
with
multiple
objective
functions
IEEE
30-bus
system.
These
objectives
include
fuel
cost,
cost
valve
loading
effects,
losses,
emissions,
voltage
profile.
Additionally,
algorithm's
further
assessed
testing
it
single
medium
large-scale
57
118-bus
networks.The
results
demonstrate
its
superiority
,
surpassing
reported
techniques.
Scientific Reports,
Год журнала:
2023,
Номер
13(1)
Опубликована: Апрель 1, 2023
In
this
paper,
Squid
Game
Optimizer
(SGO)
is
proposed
as
a
novel
metaheuristic
algorithm
inspired
by
the
primary
rules
of
traditional
Korean
game.
game
multiplayer
with
two
objectives:
attackers
aim
to
complete
their
goal
while
teams
try
eliminate
each
other,
and
it
usually
played
on
large,
open
fields
no
set
guidelines
for
size
dimensions.
The
playfield
often
shaped
like
squid
and,
according
historical
context,
appears
be
around
half
standard
basketball
court.
mathematical
model
developed
based
population
solution
candidates
random
initialization
process
in
first
stage.
are
divided
into
groups
offensive
defensive
players
player
goes
among
start
fight
which
modeled
through
movement
toward
players.
By
considering
winning
states
both
sides
calculated
objective
function,
position
updating
conducted
new
vectors
produced.
To
evaluate
effectiveness
SGO
algorithm,
25
unconstrained
test
functions
100
dimensions
used,
alongside
six
other
commonly
used
metaheuristics
comparison.
independent
optimization
runs
algorithms
pre-determined
stopping
condition
ensure
statistical
significance
results.
Statistical
metrics
such
mean,
deviation,
mean
required
function
evaluations
calculated.
provide
more
comprehensive
analysis,
four
prominent
tests
including
Kolmogorov-Smirnov,
Mann-Whitney,
Kruskal-Wallis
used.
Meanwhile,
ability
suggested
SGOA
assessed
cutting-edge
real-world
problems
newest
CEC
2020,
demonstrate
outstanding
performance
dealing
these
complex
problems.
overall
assessment
indicates
that
can
competitive
remarkable
outcomes
benchmark
