Energies,
Год журнала:
2024,
Номер
17(2), С. 416 - 416
Опубликована: Янв. 15, 2024
The
use
of
renewable
energy
sources
is
becoming
increasingly
widespread
around
the
world
due
to
various
factors,
most
relevant
which
high
environmental
friendliness
these
types
resources.
However,
large-scale
involvement
green
leads
creation
distributed
networks
that
combine
several
different
generation
methods,
each
has
its
own
specific
features,
and
as
a
result,
data
collection
processing
necessary
optimize
operation
such
systems
become
more
relevant.
Development
new
technologies
for
optimal
RES
one
main
tasks
modern
research
in
field
energy,
where
an
important
place
assigned
based
on
artificial
intelligence,
allowing
researchers
significantly
increase
efficiency
all
within
systems.
This
paper
proposes
consider
methodology
application
approaches
assessment
amount
obtained
from
intelligence
technologies,
used
optimization
control
processes
operating
with
integration
sources.
relevance
work
lies
formation
general
approach
applied
evaluation
solar
wind
technologies.
As
verification
considered
by
authors,
number
models
predicting
power
using
photovoltaic
panels
have
been
implemented,
machine-learning
methods
used.
result
testing
quality
accuracy,
best
results
were
hybrid
forecasting
model,
combines
joint
random
forest
model
at
stage
normalization
input
data,
exponential
smoothing
LSTM
model.
Energies,
Год журнала:
2023,
Номер
16(4), С. 1786 - 1786
Опубликована: Фев. 10, 2023
The
use
of
fossil-fueled
power
stations
to
generate
electricity
has
had
a
damaging
effect
over
the
years,
necessitating
need
for
alternative
energy
sources.
Microgrids
consisting
renewable
source
concepts
have
gained
lot
consideration
in
recent
years
as
an
because
they
advances
information
and
communication
technology
(ICT)
increase
quality
efficiency
services
distributed
resources
(DERs),
which
are
environmentally
friendly.
Nevertheless,
microgrids
constrained
by
outbreaks
faults,
impact
on
their
performance
necessitate
dynamic
management
optimization
strategies.
application
artificial
intelligence
(AI)
is
gaining
momentum
vital
key
at
this
point.
This
study
focuses
comprehensive
review
applications
strategies
hybrid
optimization,
enhancement,
analyses
fault
microgrids.
techniques
such
machine
learning
(ML),
genetic
algorithms
(GA),
neural
networks
(ANN),
fuzzy
logic
(FL),
particle
swarm
(PSO),
heuristic
bee
colony
(ABC),
others
reviewed
various
microgrid
regression
classification
study.
Applications
AI
together
with
benefits,
drawbacks,
prospects
future.
coordination
maximum
penetration
energy,
solar
PV,
wind
under
furthermore
reviewed.
Sustainability,
Год журнала:
2023,
Номер
15(22), С. 15863 - 15863
Опубликована: Ноя. 12, 2023
Water
pollution
by
heavy
metals
represents
a
significant
threat
to
both
the
environment
and
public
health,
with
pronounced
risk
of
stomach
cancer
fatalities
linked
consumption
metal-contaminated
water.
Consequently,
need
for
effective
governance
in
metal
remediation
is
paramount.
Employing
comprehensive
review
existing
literature,
this
study
delves
into
prevalent
models,
including
state-centric
governance,
market
network
voluntary
governance.
The
primary
objective
research
pinpoint
optimal
framework
most
efficient
model.
Through
an
analysis
informed
simplified
Multi-Criteria
Decision
Analysis
(MCDA)
method,
presents
key
findings,
offering
valuable
insights
policymakers,
environmental
agencies,
industries
seeking
holistic
strategies
combat
alleviate
its
detrimental
consequences.
These
findings
significantly
contribute
ongoing
global
efforts
safeguard
environment,
enhance
mitigate
adverse
impacts
contamination.
Energies,
Год журнала:
2024,
Номер
17(2), С. 416 - 416
Опубликована: Янв. 15, 2024
The
use
of
renewable
energy
sources
is
becoming
increasingly
widespread
around
the
world
due
to
various
factors,
most
relevant
which
high
environmental
friendliness
these
types
resources.
However,
large-scale
involvement
green
leads
creation
distributed
networks
that
combine
several
different
generation
methods,
each
has
its
own
specific
features,
and
as
a
result,
data
collection
processing
necessary
optimize
operation
such
systems
become
more
relevant.
Development
new
technologies
for
optimal
RES
one
main
tasks
modern
research
in
field
energy,
where
an
important
place
assigned
based
on
artificial
intelligence,
allowing
researchers
significantly
increase
efficiency
all
within
systems.
This
paper
proposes
consider
methodology
application
approaches
assessment
amount
obtained
from
intelligence
technologies,
used
optimization
control
processes
operating
with
integration
sources.
relevance
work
lies
formation
general
approach
applied
evaluation
solar
wind
technologies.
As
verification
considered
by
authors,
number
models
predicting
power
using
photovoltaic
panels
have
been
implemented,
machine-learning
methods
used.
result
testing
quality
accuracy,
best
results
were
hybrid
forecasting
model,
combines
joint
random
forest
model
at
stage
normalization
input
data,
exponential
smoothing
LSTM
model.
