Sustainability,
Journal Year:
2024,
Volume and Issue:
16(12), P. 4959 - 4959
Published: June 10, 2024
This
paper
presents
an
in-depth
exploration
of
the
application
Artificial
Intelligence
(AI)
in
enhancing
resilience
microgrids.
It
begins
with
overview
impact
natural
events
on
power
systems
and
provides
data
insights
related
to
outages
blackouts
caused
by
Estonia,
setting
context
for
need
resilient
systems.
Then,
delves
into
concept
role
microgrids
maintaining
stability.
The
reviews
various
AI
techniques
methods,
their
further
investigates
how
can
be
leveraged
improve
microgrids,
particularly
during
different
phases
event
occurrence
time
(pre-event,
event,
post-event).
A
comparative
analysis
performance
models
is
presented,
highlighting
ability
maintain
stability
ensure
a
reliable
supply.
comprehensive
review
contributes
significantly
existing
body
knowledge
sets
stage
future
research
this
field.
concludes
discussion
work
directions,
emphasizing
potential
revolutionizing
system
monitoring
control.
Applied Sciences,
Journal Year:
2022,
Volume and Issue:
12(16), P. 8081 - 8081
Published: Aug. 12, 2022
In
the
era
of
fourth
industrial
revolution,
several
concepts
have
arisen
in
parallel
with
this
new
such
as
predictive
maintenance,
which
today
plays
a
key
role
sustainable
manufacturing
and
production
systems
by
introducing
digital
version
machine
maintenance.
The
data
extracted
from
processes
increased
exponentially
due
to
proliferation
sensing
technologies.
Even
if
Maintenance
4.0
faces
organizational,
financial,
or
even
source
repair
challenges,
it
remains
strong
point
for
companies
that
use
it.
Indeed,
allows
minimizing
downtime
associated
costs,
maximizing
life
cycle
machine,
improving
quality
cadence
production.
This
approach
is
generally
characterized
very
precise
workflow,
starting
project
understanding
collection
ending
decision-making
phase.
paper
presents
an
exhaustive
literature
review
methods
applied
tools
intelligent
maintenance
models
Industry
identifying
categorizing
projects
challenges
encountered,
type
maintenance:
condition-based
(CBM),
prognostics
health
management
(PHM),
remaining
useful
(RUL).
Finally,
novel
workflow
presented
including
decision
support
phase
wherein
recommendation
platform
presented.
ensures
fluid
communication
between
equipment
throughout
their
context
smart
Energies,
Journal Year:
2023,
Volume and Issue:
16(10), P. 4025 - 4025
Published: May 11, 2023
The
use
of
machine
learning
and
data-driven
methods
for
predictive
analysis
power
systems
offers
the
potential
to
accurately
predict
manage
behavior
these
by
utilizing
large
volumes
data
generated
from
various
sources.
These
have
gained
significant
attention
in
recent
years
due
their
ability
handle
amounts
make
accurate
predictions.
importance
particular
momentum
with
transformation
that
traditional
system
underwent
as
they
are
morphing
into
smart
grids
future.
transition
towards
embed
high-renewables
electricity
is
challenging,
generation
renewable
sources
intermittent
fluctuates
weather
conditions.
This
facilitated
Internet
Energy
(IoE)
refers
integration
advanced
digital
technologies
such
Things
(IoT),
blockchain,
artificial
intelligence
(AI)
systems.
It
has
been
further
enhanced
digitalization
caused
COVID-19
pandemic
also
affected
energy
sector.
Our
review
paper
explores
prospects
challenges
using
provides
an
overview
ways
which
constructing
can
be
applied
order
them
more
efficient.
begins
description
role
operations.
Next,
discusses
systems,
including
benefits
limitations.
In
addition,
reviews
existing
literature
on
this
topic
highlights
used
Furthermore,
it
identifies
opportunities
associated
methods,
quality
availability,
discussed.
Finally,
concludes
a
discussion
recommendations
research
application
future
grid-driven
powered
IoE.
Renewable and Sustainable Energy Reviews,
Journal Year:
2023,
Volume and Issue:
183, P. 113444 - 113444
Published: June 9, 2023
Renewable
energy
sources
have
emerged
globally
as
a
key
lever
to
ensure
security
and
promote
climate
mitigation.
Cities
need
exploit
this
transition,
but
how
they
are
building
their
strategies
actions
is
undetermined.
A
new
dataset,
collected
through
the
European
100
Climate-Neutral
Smart
Mission,
offers
unique
insights
on
362
cities
which
expressed
ambition
reach
neutrality
by
2030.
Insights
include
level
of
preparedness,
ambition,
capacity
risks
envisaged
in
pursuit
zero-emission
greener
futures.
This
study
focuses
particular
role
renewable
across
high
greenhouse
gas
emitting
sectors
(e.g.
buildings,
mobility,
waste
industry).
It
analyses
i)
status
quo
for
generation,
consumption,
policymaking,
ii)
measures
enhance
upscale
deployment
near
future,
iii)
policies
relevant
instruments
will
evolve
curb
emissions
accelerate
transition.
The
that
emerge
from
analysis
discussed
relation
existing
evidence,
inform
future
research
strands
forms
assistance
cities.
Overall,
deliver
large
projects,
efforts
be
intensified,
barriers
lifted
multi-governance
approaches
must
operationalised.
Next Sustainability,
Journal Year:
2024,
Volume and Issue:
4, P. 100041 - 100041
Published: Jan. 1, 2024
This
comprehensive
review
explores
the
nexus
between
AI
and
pursuit
of
net-zero
emissions,
highlighting
potential
in
driving
sustainable
development
combating
climate
change.
The
paper
examines
various
threads
within
this
field,
including
applications
for
net
zero,
AI-driven
solutions
innovations,
challenges
ethical
considerations,
opportunities
collaboration
partnerships,
capacity
building
education,
policy
regulatory
support,
investment
funding,
as
well
scalability
replicability
solutions.
Key
findings
emphasize
enabling
role
optimizing
energy
systems,
enhancing
modelling
prediction,
improving
sustainability
sectors
such
transportation,
agriculture,
waste
management,
effective
emissions
monitoring
tracking.
also
highlights
related
to
data
availability,
quality,
privacy,
consumption,
bias,
fairness,
human-AI
collaboration,
governance.
Opportunities
building,
investment,
are
identified
key
drivers
future
research
implementation.
Ultimately,
underscores
transformative
achieving
a
sustainable,
provides
insights
policymakers,
researchers,
practitioners
engaged
change
mitigation
adaptation.
Frontiers in Energy Research,
Journal Year:
2022,
Volume and Issue:
10
Published: March 18, 2022
The
building
energy
(BE)
management
has
an
essential
role
in
urban
sustainability
and
smart
cities.
Recently,
the
novel
data
science
data-driven
technologies
have
shown
significant
progress
analyzing
consumption
demand
sets
for
a
smarter
management.
machine
learning
(ML)
deep
(DL)
methods
applications,
particular,
been
promising
advancement
of
accurate
high-performance
models.
present
study
provides
comprehensive
review
ML
DL-based
techniques
applied
handling
BE
systems,
it
further
evaluates
performance
these
techniques.
Through
systematic
taxonomy,
advances
are
carefully
investigated,
models
introduced.
According
to
results
obtained
forecasting,
hybrid
ensemble
located
high
robustness
range,
SVM-based
good
limitation,
ANN-based
medium
limitation
linear
regression
low
limitations.
On
other
hand,
DL-based,
hybrid,
ensemble-based
provided
highest
score.
ANN,
SVM,
single
LR-based
lower
In
addition,
load
higher
score
Renewable and Sustainable Energy Reviews,
Journal Year:
2022,
Volume and Issue:
170, P. 112651 - 112651
Published: Oct. 3, 2022
In
recent
years,
digitalisation
has
rendered
machine
learning
a
key
tool
for
improving
processes
in
several
sectors,
as
the
case
of
electrical
power
systems.
Machine
algorithms
are
data-driven
models
based
on
statistical
theory
and
employed
to
exploit
data
generated
by
system
its
users.
Energy
communities
emerging
novel
organisations
consumers
prosumers
distribution
grid.
These
may
operate
differently
depending
their
objectives
potential
service
community
wants
offer
operator.
This
paper
presents
conceptualisation
local
energy
basis
review
25
projects.
Furthermore,
an
extensive
literature
applications
was
conducted,
these
were
categorised
according
forecasting,
storage
optimisation,
management
systems,
stability
quality,
security,
transactions.
The
main
reported
analysed
classified
supervised,
unsupervised,
reinforcement
algorithms.
findings
demonstrate
manner
which
supervised
can
provide
accurate
forecasting
tasks.
Similarly,
interesting
capabilities
terms
control-related
applications.
