Applied Intelligence,
Journal Year:
2024,
Volume and Issue:
54(17-18), P. 8296 - 8346
Published: June 25, 2024
Abstract
Economic
dispatch
is
an
important
issue
in
the
management
of
power
systems
and
current
focus
specialists.
In
this
paper,
a
new
metaheuristic
optimization
algorithm
proposed,
named
Social
Small
Group
Optimization
(SSGO),
inspired
by
psychosocial
processes
that
occur
between
members
small
groups
to
solve
real-life
problems.
The
starting
point
SSGO
philosophical
conception
similar
social
group
(SGO)
algorithm.
novelty
lies
introduction
concept
modeling
individuals’
evolution
based
on
influence
two
or
more
group.
This
conceptual
framework
has
been
mathematically
mapped
through
set
heuristics
are
used
update
solutions,
best
solutions
retained
employing
greedy
selection
strategy.
applied
economic
problem
considering
some
practical
aspects,
such
as
valve-point
loading
effects,
sources
with
multiple
fuel
options,
prohibited
operating
zones,
transmission
line
losses.
efficiency
was
tested
several
mathematical
functions
(unimodal,
multimodal,
expanded,
composition
functions)
varying
sizes
(ranging
from
10-units
1280-units).
compared
SGO
other
algorithms
belonging
various
categories
(such
as:
evolution-based,
swarm-based,
human
behavior-based,
hybrid
algorithms,
etc.),
results
indicated
outperforms
terms
quality
stability
well
computation
time.
Biomimetics,
Journal Year:
2023,
Volume and Issue:
9(1), P. 8 - 8
Published: Dec. 25, 2023
This
research
paper
develops
a
novel
hybrid
approach,
called
particle
swarm
optimization–teaching–learning-based
optimization
(hPSO-TLBO),
by
combining
two
metaheuristic
algorithms
to
solve
problems.
The
main
idea
in
hPSO-TLBO
design
is
integrate
the
exploitation
ability
of
PSO
with
exploration
TLBO.
meaning
“exploitation
capabilities
PSO”
manage
local
search
aim
obtaining
possible
better
solutions
near
obtained
and
promising
areas
problem-solving
space.
Also,
“exploration
abilities
TLBO”
means
TLBO
global
preventing
algorithm
from
getting
stuck
inappropriate
optima.
methodology
such
that
first
step,
teacher
phase
combined
speed
equation
PSO.
Then,
second
learning
improved
based
on
each
student
selected
has
value
for
objective
function
against
corresponding
student.
presented
detail,
accompanied
comprehensive
mathematical
model.
A
group
benchmarks
used
evaluate
effectiveness
hPSO-TLBO,
covering
various
types
as
unimodal,
high-dimensional
multimodal,
fixed-dimensional
multimodal.
In
addition,
CEC
2017
benchmark
problems
are
also
utilized
evaluation
purposes.
results
clearly
demonstrate
performs
remarkably
well
addressing
functions.
It
exhibits
remarkable
explore
exploit
space
while
maintaining
balanced
approach
throughout
process.
Furthermore,
comparative
analysis
conducted
performance
twelve
widely
recognized
algorithms.
experimental
findings
illustrates
consistently
outperforms
competing
across
functions,
showcasing
its
superior
performance.
successful
deployment
four
engineering
challenges
highlights
tackling
real-world
applications.
Energies,
Journal Year:
2024,
Volume and Issue:
17(13), P. 3148 - 3148
Published: June 26, 2024
The
growing
popularity
of
plug-in
hybrid
electric
vehicles
(PHEVs)
is
due
to
their
environmental
advantages.
But
uncoordinated
charging
a
large
number
PHEVs
can
lead
significant
surge
in
peak
loads
and
higher
costs
for
PHEV
owners.
To
end
this,
this
paper
introduces
an
innovative
approach
address
the
issue
by
proposing
multi-objective
weighting
control
coordinated
future
smart
grid,
which
aims
find
economically
optimal
solution
while
also
considering
load
stabilization
with
large-scale
penetration.
Technical
constraints
related
owner’s
demand
power
limitations
are
considered.
In
proposed
approach,
behavior
owners
modeled
normal
distribution.
It
observed
that
typically
start
when
they
arrive
home
stop
go
workplace.
cost
then
calculated
based
on
tiered
electricity
price
power.
By
adjusting
factor
stability
function,
grid
allows
flexible
weight
selection
between
two
objectives.
This
effectively
encourages
actively
participate
scheduling,
sets
it
apart
from
existing
works.
algorithm
offers
better
robustness
adaptability
penetration,
making
highly
relevant
grid.
Finally,
numerical
simulations
presented
demonstrate
desirable
performance
theory
simulation.
Applied Intelligence,
Journal Year:
2024,
Volume and Issue:
54(17-18), P. 8296 - 8346
Published: June 25, 2024
Abstract
Economic
dispatch
is
an
important
issue
in
the
management
of
power
systems
and
current
focus
specialists.
In
this
paper,
a
new
metaheuristic
optimization
algorithm
proposed,
named
Social
Small
Group
Optimization
(SSGO),
inspired
by
psychosocial
processes
that
occur
between
members
small
groups
to
solve
real-life
problems.
The
starting
point
SSGO
philosophical
conception
similar
social
group
(SGO)
algorithm.
novelty
lies
introduction
concept
modeling
individuals’
evolution
based
on
influence
two
or
more
group.
This
conceptual
framework
has
been
mathematically
mapped
through
set
heuristics
are
used
update
solutions,
best
solutions
retained
employing
greedy
selection
strategy.
applied
economic
problem
considering
some
practical
aspects,
such
as
valve-point
loading
effects,
sources
with
multiple
fuel
options,
prohibited
operating
zones,
transmission
line
losses.
efficiency
was
tested
several
mathematical
functions
(unimodal,
multimodal,
expanded,
composition
functions)
varying
sizes
(ranging
from
10-units
1280-units).
compared
SGO
other
algorithms
belonging
various
categories
(such
as:
evolution-based,
swarm-based,
human
behavior-based,
hybrid
algorithms,
etc.),
results
indicated
outperforms
terms
quality
stability
well
computation
time.
