Contributions of artificial intelligence and digitization in achieving clean and affordable energy
Intelligent Systems with Applications,
Год журнала:
2024,
Номер
22, С. 200389 - 200389
Опубликована: Май 19, 2024
Concerned
by
the
continuous
decline
in
quality
of
life,
poverty,
environmental
degradation,
and
escalated
war
conflicts,
United
Nations
2015
instituted
17
Sustainable
Development
Goals
(SDGs)
169
targets.
Access
to
clean,
modern,
affordable
energy,
also
known
as
SDG
7,
is
one
goals.
Universal
access
electricity
metrics
for
measuring
a
good
life
it
fundamentally
affects
education,
healthcare,
food
security,
job
creation,
other
socioeconomic
indices.
To
achieve
this
goal
targets,
there
has
been
increased
traction
research,
development,
actionable
plans,
policies,
activities
governments,
scientific
community,
environmentalists,
development
experts,
stakeholders
achieving
goal.
This
review
presents
various
avenues
which
AI
digitization
can
provide
impetus
7.
The
global
trends
attaining
clean
electricity,
cooking
fuel,
renewable
energy
efficiency,
international
public
financial
flows
between
2005
2021
are
reviewed
while
contribution
towards
meeting
7
highlighted.
study
concludes
that
deployment
into
sector
will
catalyze
attainment
2030,
provided
ethical
issues,
regulatory
concerns,
manpower
shortage,
shortcomings
effectively
handled.
recommends
adequate
infrastructural
upgrades,
modernization
data
collection,
storage,
analysis
capabilities,
improved
awareness
professional
collaborative
innovation,
promotion
legal
issues
ways
advancing
universal
2030.
Going
forward,
more
collaborations
academic
research
institutions
producers
help
produce
experts
professionals
propel
innovative
digital
technologies
sector.
Язык: Английский
Smart Grids in the Context of Smart Cities: A Literature Review and Gap Analysis
Energies,
Год журнала:
2025,
Номер
18(5), С. 1186 - 1186
Опубликована: Фев. 28, 2025
Cities
host
over
50%
of
the
world’s
population
and
account
for
nearly
75%
energy
consumption
80%
global
greenhouse
gas
emissions.
Consequently,
ensuring
a
smart
way
to
organize
cities
is
paramount
quality
life
efficiency
resource
use,
with
emphasis
on
use
management
energy,
under
context
trilemma,
where
objectives
sustainability,
security,
affordability
need
be
balanced.
Electrification
associated
renewable
generation
increasingly
seen
as
most
efficient
reduce
impact
GHG
emissions
natural
depletion.
poses
significant
challenges
development
electrical
infrastructure,
requiring
deployment
Smart
Grids,
which
emerge
key
Cities.
Our
review
targets
intersection
between
Grids.
Several
components
City
in
Grids
are
reviewed,
including
elements
such
metering,
IoT,
sources
other
distributed
resources,
grid
monitoring,
artificial
intelligence,
electric
vehicles,
or
buildings.
Case
studies
pilots
metrics
concerning
existing
deployments
identified.
A
portfolio
16
solutions
that
may
contribute
bringing
Grid
level
city
urban
settings
identified,
well
11
gaps
effective
deployment.
We
place
these
trilemma
Architecture
Model.
posit
depending
characteristics
setting,
size,
location,
geography,
mix
economic
activities,
topology,
appropriate
set
can
an
indicative
roadmap
built.
Язык: Английский
Overview of Startups Developing Artificial Intelligence for the Energy Sector
Applied Sciences,
Год журнала:
2024,
Номер
14(18), С. 8294 - 8294
Опубликована: Сен. 14, 2024
The
energy
industry
is
experiencing
a
major
change
due
to
fast
progress
in
artificial
intelligence
(AI).
Startup
companies
this
revolution
use
AI
technologies
like
Machine
Learning
(ML),
predictive
analytics,
and
optimization
algorithms
improve
efficiency,
optimize
grid
management,
incorporate
renewable
sources.
AI-powered
solutions
allow
for
more
accurate
prediction
of
demand,
immediate
monitoring,
automated
decision-making
processes,
significantly
enhancing
operational
efficiency
sustainability.
Through
promoting
effective
system,
these
advancements
play
vital
role
the
worldwide
battle
against
climate
carbon
dioxide
emissions.
Adding
AI,
quantum
computing
(QC)
shows
great
potential
despite
being
nascent
area.
collaboration
QC
poised
transform
by
offering
unmatched
computational
capabilities.
This
blend
can
tackle
intricate
obstacles
power
grids
battery
storage,
which
traditional
computers
cannot
currently
handle.
Combining
with
speeds
up
innovation,
providing
advanced
that
resilience
networks.
paper
discusses
latest
advancements,
possible
effects,
upcoming
paths
new
leading
innovations
within
industry.
Their
joint
responsibility
highlighted
advancing
sustainable
intelligent
future,
as
well
tackling
crucial
environmental
issues
lessening
impact
change.
Язык: Английский
Featuring Wave and Tidal Energy Transformation With Artificial Intelligence and Machine Learning in Urban Growth and Living
Advances in environmental engineering and green technologies book series,
Год журнала:
2025,
Номер
unknown, С. 395 - 420
Опубликована: Фев. 21, 2025
Harnessing
raw
energy
from
the
sea
for
sustainable
urban
living,
driven
by
Artificial
Intelligence
(AI)
and
Machine
Learning
(ML),
through
wave
tidal
conversion
could
be
a
paradigm-shifting
breakthrough.
These
renewable
sources
are
able
to
utilize
non-stop
movement
of
oceans
tides,
which
will
work
in
decreasing
carbon
footprints
cities.
Through
AI
ML
algorithms,
capture,
storage,
distribution
process
is
made
way
efficient
predicting
patterns
or
enhancing
grid
integration.
Together,
these
technologies
provide
fast
online
decisions,
dependability
scalability
units.
AI-based
solutions
waves
conversion,
therefore,
can
become
key
signaling
point
addressing
an
ever-increasing
demand
most
modern-day
infrastructural
platforms
as
well
means
forces
global
climate
change
mitigation
consider
their
toward
providing
smarter
greener
futures
our
communities.
Язык: Английский
Artificial Intelligence and Energy Market Quartile Spillovers: Implications for China's Renewable Energy and High Emission Sectors
Опубликована: Янв. 1, 2025
Язык: Английский
Analysis for the Implementation of Distributed Renewable Energy Generation Systems for Areas of High Vulnerability Due to Hillside Movements: Case Study of Marianza-Cuenca, Ecuador
Energies,
Год журнала:
2024,
Номер
17(7), С. 1633 - 1633
Опубликована: Март 28, 2024
This
research
presents
a
renewable
energy
system
that
takes
advantage
of
the
potential
available
in
territory.
study
emerges
as
relevant
option
to
provide
solutions
geological
risk
areas
where
there
are
buildings
that,
due
emergency
situations
at
certain
times
year
during
deep
winter,
target
danger
and
its
inhabitants
would
find
it
difficult
abandon
their
properties.
The
record
mass
movements
covering
city
Cuenca-Ecuador
part
province
has
shown
main
triggering
factor
this
type
movement
comprises
characteristics
tertiary
formations
characterized
by
lithological
components
become
unstable
presence
water
slopes
being
pronounced.
Hybrid
systems
effective
distributed
electricity
generation,
especially
when
comes
helping
people
great
need
required
generation
is
basic.
A
hybrid
photovoltaic,
wind
hydrokinetic
been
designed
supplies
electrical
specific
area
on
opposite
geographical
side
completely
safe.
connected
public
grid
site;
however,
event
an
disconnected
for
safety
only
will
work
with
support
battery
backup
system.
In
study,
Homer
Pro
simulation
tool
was
used
results
indicate
include
PV,
HKT
WT
elements
economically
viable,
COE
USD
0.89/kWh.
Язык: Английский
Abundance Ocean Wave Energy to Electricity With Artificial Intelligence and IoT Solutions
Practice, progress, and proficiency in sustainability,
Год журнала:
2024,
Номер
unknown, С. 274 - 298
Опубликована: Июль 26, 2024
Artificial
intelligence
(AI)
and
machine
learning
(ML)
are
becoming
essential
tools
for
increasing
the
efficiency
sustainability
of
this
renewable
energy
source
ocean
industry
has
made
significant
strides
in
recent
years.
The
early
stages
industry's
research
development
when
AI
ML
first
started
to
emerge
space.
development,
management,
upkeep
maritime
systems
have
all
changed
as
a
result
these
innovations.
An
enormous,
unexplored
resource
that
potential
make
an
important
contribution
world's
mix
is
wave
energy.
In
order
maximize
efficacy
conversion,
chapter
explores
incorporation
artificial
internet
things
(IoT)
technologies.
It
looks
at
technologies'
ability
support
clean
solutions
build
sustainable
environment
particularly
context
smart
cities.
Язык: Английский
A Contiguous Temporal Chebyshev Convolutional Optimized Network (CoC-TemNet) Model for Energy Prediction in IoT Enabled Smart City Networks
IEEE Internet of Things Journal,
Год журнала:
2024,
Номер
11(13), С. 23630 - 23643
Опубликована: Апрель 10, 2024
Smart
cities
are
having
the
ability
to
monitor
and
manage
their
environments
in
real
time
due
emergence
of
Internet
Things
technology.
In
context
energy
management,
prediction
can
be
carried
out
by
monitoring
evaluating
dynamic
environmental
data
from
user
side.
The
decision-making
process
related
production
then
aided
this
information
order
achieve
flexible
avoid
an
excess
or
insufficient
supply
energy.
quantity
variety
IoT
makes
it
difficult
create
efficient
forecast
system
that
effectively
captures
changing
conditions
environment.
This
research
aims
guarantee
management
networks
smart
cities.
Here,
unique
framework,
called
as,
Contiguous
Temporal
Chebyshev
Convolutional
Optimized
Network
(CoC-TemNet)
is
developed
for
load
forecasting
IoT-enabled
city
applications.
For
choosing
list
crucial
properties
computing
function,
Non-Spiritual
Model
(CN2M)
used
instance.
Then,
Convolution
(CTCN)
model
with
accuracy
using
chosen
features.
Hybrid
Leaping
Lizard
Immune
Optimization
(HLIO)
technique
calculate
objective
function
improving
process.
proposed
method
was
validated
on
multiple
datasets:
Southern
China,
IHEPC,
AEP,
ISO-NE.
Outperforms
baseline
models
low
RMSE,
MSE,
MAE
values,
28.1%
MAPE.
Significantly
lower
execution
times:
0.98ms
IHEPC
0.11ms
AEP
dataset.
Язык: Английский
AI-Driven Green Campus: Solar Panel Fault Detection Using ResNet-50 for Solar-Hydrogen System in Universities
Опубликована: Июль 1, 2024
Язык: Английский
Featuring Wave and Tidal Energy Conversion With Artificial Intelligence and Machine Learning
Practice, progress, and proficiency in sustainability,
Год журнала:
2024,
Номер
unknown, С. 59 - 82
Опубликована: Ноя. 1, 2024
Artificial
intelligence
(AI)
and
machine
learning
(ML)
are
becoming
indispensable
tools
for
increasing
the
efficiency
sustainability
of
this
renewable
energy
source
ocean
industry
has
made
significant
strides
in
recent
years.
The
initial
stages
research
development
when
AI
ML
first
started
to
emerge
wave
tidal
space.
development,
management,
upkeep
maritime
systems
have
all
changed
as
a
result
these
innovations.
An
massive,
unexplored
resource
that
potential
make
an
important
contribution
world's
mix
is
energy.
In
order
maximize
efficacy
conversion,
chapter
focuses
on
incorporation
artificial
technologies.
It
looks
at
technologies'
capability
support
clean
solutions
build
sustainable
environment
particularly
context
urban
living.
Язык: Английский