i-manager’s Journal on Electrical Engineering,
Год журнала:
2024,
Номер
18(2), С. 14 - 14
Опубликована: Янв. 1, 2024
This
paper
addresses
the
urgent
need
for
environmentally
sustainable
transportation
by
introducing
an
advanced
Microcontroller-Based
Electric
Vehicle
(EV)
model.
The
model
aims
to
optimize
energy
consumption,
improve
reliability,
and
promote
environmental
sustainability.
It
incorporates
self-driving
technology,
utilizing
a
Joystick,
Bluetooth
device,
Ultrasonic
Sensor
obstacle
detection,
with
Microcontroller
receiving
feedback
signals
that
influence
motor
operation
based
on
proximity
obstacles.
To
enhance
efficiency,
integrates
non-conventional
sources,
including
Solar
Wind
Energy.
A
Panel,
control
circuit,
DC
Converter
capture
solar
power
vehicle
through
Arduino
UNO
Motor
Driver
L298.
Weight-Based
Energy
Consumption
module
ensures
optimal
use.
vehicle's
battery
can
be
charged
using
USB
Cable
or
TP4056
charge
controller
managing
transition
between
charging
discharging.
In
case
of
emergencies,
serves
as
alternative
source.
address
fluctuation,
Storage
System
(ESS)
within
wind
turbine's
link,
supported
supercapacitors,
smooths
wind-generated
power,
mitigates
voltage
variations,
improves
fault
tolerance.
fuzzy
logic-based
scheme
efficiently
turbine
ESS
conditions,
validation
performed
computational
simulations.
proposed
offers
significant
advancements
in
electric
providing
flexibility,
adaptability
various
scenarios.
PLoS ONE,
Год журнала:
2024,
Номер
19(10), С. e0307810 - e0307810
Опубликована: Окт. 3, 2024
At
present,
renewable
energy
sources
(RESs)
and
electric
vehicles
(EVs)
are
presented
as
viable
solutions
to
reduce
operation
costs
lessen
the
negative
environmental
effects
of
microgrids
(μGs).
Thus,
rising
demand
for
EV
charging
storage
systems
coupled
with
growing
penetration
various
RESs
has
generated
new
obstacles
efficient
administration
these
μGs.
In
this
regard,
paper
introduces
a
multi-objective
optimization
model
minimizing
total
cost
μG
its
emissions,
considering
effect
battery
system
(BSS)
station
load.
A
day-ahead
scheduling
is
proposed
optimal
management
(EM)
investigated,
which
comprises
photovoltaics
(PVs),
fuel
cells
(FCs),
wind
turbines
(WTs),
BSSs,
stations,
shed
light
on
viability
benefits
connecting
BSS
stations
in
μG.
Analyzing
three
case
studies
depending
objective
function-Case
1:
execute
EM
minimize
maximize
profits
BSS,
Case
2:
emission
from
μG,
3:
cost,
emissions
The
main
aim
strategy
achieve
best
possible
balance
between
reducing
expenses
lessening
impact
greenhouse
gas
emissions.
krill
herd
algorithm
(KHA)
used
find
while
nonlinear
constraints.
To
demonstrate
validity
effectiveness
solution,
study
utilizes
KHA
compares
obtained
results
those
achieved
by
other
methods.
It
was
demonstrated
that
such
integration
significantly
enhances
μG's
operational
efficiency,
reduces
operating
costs,
minimizes
impact.
findings
underscore
combining
infrastructure
meet
increasing
sustainably.
novelty
work
lies
approach,
μGs,
comparison
methods,
emphasis
sustainability
addressing
through
utilization
EVs.
Sustainability,
Год журнала:
2024,
Номер
16(6), С. 2432 - 2432
Опубликована: Март 14, 2024
A
novel
distributed
feedback
optimization-based
controller
for
electric
vehicle
(EV)
chargers
and
renewable
energy
sources
(RESs)
in
distribution
systems
is
proposed.
The
proposed
utilizes
the
flexibility
EV
chargers’
active
reactive
power
consumption
to
offer
desirable
vehicle-to-grid
services.
Instead
of
using
conventional
cascaded
PI
controllers,
a
new
approach
control
RESs
track
their
injection
setpoints.
formulates
targets
as
single
constrained
optimization
problem,
i.e.,
minimize
critical
bus
voltage
magnitude
deviations
while
driving
follow
setpoints,
thereby
fulfilling
charging
requirements
regulating
outputs
magnitudes
stay
within
limits.
algorithm
designed
steer
system
trajectories
towards
optimal
solution
formulated
problem.
Simulation
results
show
that
can
always
test
advantages
real-time
compensation
are
also
demonstrated.
Maritime Business Review,
Год журнала:
2024,
Номер
9(3), С. 263 - 291
Опубликована: Авг. 19, 2024
Purpose
This
study
aims
to
provide
a
comprehensive
review
of
electric
tugboat
deployment
in
maritime
transportation,
including
an
in-depth
assessment
its
advantages
and
disadvantages.
Along
with
the
identification
disadvantages
deployment,
present
research
also
managerial
insights
into
economic
viability
different
alternatives
that
can
guide
future
investments
following
years.
Design/methodology/approach
A
detailed
literature
was
conducted,
aiming
gain
broad
operations
focusing
on
aspects,
accidents
safety
issues,
scheduling
berthing
tugboats,
life
cycle
diesel
tugboats
their
alternatives,
hybrid
environmental
impacts
others.
Moreover,
set
interviews
conducted
leading
experts
industry,
DAMEN
Shipyards
Port
Auckland.
Econometric
analyses
were
performed
as
well
evaluate
financial
performance
(i.e.
conventional
tugboats).
Findings
The
encompass
decreased
emissions,
reduced
operating
expenses,
improved
energy
efficiency,
lower
noise
levels
potential
for
digital
transformation
through
automation
data
analytics.
However,
high
initial
costs,
infrastructure
limitations,
training
requirements
restricted
range
need
be
addressed.
alternative
seems
best
option
scenarios
low
interest
rate
values
increasing
negatively
impact
salvage
value
tugboats.
It
is
expected
long-term
planning,
will
become
preferential
since
they
have
annual
costs
than
Practical
implications
outcomes
this
practical
point
needs,
battery
improvements,
cost
reduction,
development,
legislative
regulatory
changes
sources.
advancement
technology
has
significantly
dynamics
associated
essential
do
further
monitor
advancements
analyze
corresponding
ramifications.
closely
industry’s
shift
toward
prices
more
affordable.
Originality/value
industry
rapidly
transforming
facing
pressing
challenges
related
sustainability
digitization.
Electric
represent
promising
innovative
solution
could
address
some
these
zero-emission
operations,
enhanced
efficiency
integration
technologies.
Considering
provides
extensive
evaluation
relevant
literature,
supporting
econometric
analyses.
benefit
governmental
agencies,
policymakers
other
transportation
stakeholders.
Energies,
Год журнала:
2024,
Номер
17(15), С. 3843 - 3843
Опубликована: Авг. 4, 2024
In
this
work,
we
consider
a
problem
from
the
field
of
power-aware
scheduling
in
which
fleet
electric
vehicles
have
to
be
charged
minimum
time.
Each
vehicle
is
equipped
with
lithium-ion
battery
given
capacity.
The
initial
power
used
for
charging
each
known,
whereas
it
assumed
that
drops
zero
at
moment
when
gets
fully
loaded.
usage
function
linear
and
decreasing.
jobs
are
nonpreemptable
independent,
total
available
amount
limited.
objective
minimize
schedule
length.
paper,
analyze
case
identical
already
cover
wide
variety
practical
situations.
By
employing
inverses
natural
numbers,
similar
harmonic
series,
prove
two
properties
case,
also
discuss
phenomenon
stabilization
difference
between
start
times
successive
schedule.
We
take
under
examination
few
special
cases
problem.
Some
conclusions
directions
future
research
given.
