npj Materials Degradation,
Journal Year:
2023,
Volume and Issue:
7(1)
Published: Feb. 22, 2023
Abstract
As
the
adoption
of
renewable
energy
sources,
particularly
photovoltaic
(PV)
solar,
has
increased,
need
for
effective
inspection
and
data
analytics
techniques
to
detect
early-stage
defects,
faults,
malfunctions
become
critical
maintaining
reliability
efficiency
PV
systems.
In
this
study,
we
analysed
thermal
defects
in
3.3
million
modules
located
UK.
Our
findings
show
that
36.5%
all
had
with
900,000
displaying
single
or
multiple
hotspots
~250,000
exhibiting
heated
substrings.
We
also
observed
an
average
temperature
increase
21.7
°C
defective
modules.
Additionally,
two
assets
19.25
8.59%
were
examined
degradation,
results
revealed
a
higher
degradation
rate
when
more
are
present.
These
demonstrate
importance
implementing
cost-effective
procedures
platforms
extend
lifetime
improve
performance
Journal of Modern Power Systems and Clean Energy,
Journal Year:
2022,
Volume and Issue:
10(2), P. 345 - 360
Published: Jan. 1, 2022
Deep
neural
networks
have
revolutionized
many
machine
learning
tasks
in
power
systems,
ranging
from
pattern
recognition
to
signal
processing.
The
data
these
are
typically
represented
Euclidean
domains.
Nevertheless,
there
is
an
increasing
number
of
applications
where
collected
non-Euclidean
domains
and
as
graph-structured
with
high-dimensional
features
interdependency
among
nodes.
complexity
has
brought
significant
challenges
the
existing
deep
defined
Recently,
publications
generalizing
for
systems
emerged.
In
this
paper,
a
comprehensive
overview
graph
(GNNs)
proposed.
Specifically,
several
classical
paradigms
GNN
structures,
e.
g.,
convolutional
networks,
summarized.
Key
such
fault
scenario
application,
time-series
prediction,
flow
calculation,
generation
reviewed
detail.
Further-more,
main
issues
some
research
trends
about
GNNs
discussed.
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 31778 - 31812
Published: Jan. 1, 2023
Renewable
energy
utilization
is
the
only
suitable
solution
to
diminish
increasing
level
of
greenhouse
gas
emissions,
fuel
costs,
and
crisis
in
next
generation.
Out
many
renewable
sources,
solar
sources
that
are
clean,
green,
emission-free
have
gained
wide
despite
their
intermittency
nature.
Several
photovoltaic
(PV)
panels
connected
series-parallel
achieve
demand.
In
such
a
system,
it
possible
each
panel
operates
differently
due
uneven
temperature
irradiation
results
uniform
partial
shading
conditions.
Thus,
unique
efficient
mechanism
required
extract
maximum
power
from
uniformly
partially
shaded
PV
systems.
Numerous
point
tracking
(MPPT)
methods
been
developed
increase
efficiency
lifetime
This
study
provides
unique,
in-depth,
organized
review
MPPT
under
four
categories:
classical,
intelligent,
optimization,
hybrid
techniques.
All
selection
benchmarks
considered
do
comprehensive
review,
which
not
deliberated
existing
literature.
Based
on
benchmarks,
advantages
disadvantages
technique
different
categories
summarized
tabulated
form.
To
address
research
gaps
for
further
investigation
this
field,
concise
discussion
included
at
end.
article
may
find
an
accessible
reference
engineers
understand
most
useful
method
undertake
extensive
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: April 18, 2024
A
substantial
level
of
significance
has
been
placed
on
renewable
energy
systems,
especially
photovoltaic
(PV)
given
the
urgent
global
apprehensions
regarding
climate
change
and
need
to
cut
carbon
emissions.
One
main
concerns
in
field
PV
is
ability
track
power
effectively
over
a
range
factors.
In
context
solar
extraction,
this
research
paper
performs
thorough
comparative
examination
ten
controllers,
including
both
conventional
maximum
point
tracking
(MPPT)
controllers
artificial
intelligence
(AI)
controllers.
Various
factors,
such
as
voltage,
current,
power,
weather
dependence,
cost,
complexity,
response
time,
periodic
tuning,
stability,
partial
shading,
accuracy,
are
all
intended
be
evaluated
by
study.
It
aimed
provide
insight
into
how
well
each
controller
various
circumstances
carefully
examining
these
broad
parameters.
The
goal
identify
recommend
best
based
their
performance.
notified
that,
techniques
like
INC,
P&O,
INC-PSO,
P&O-PSO,
achieved
accuracies
94.3,
97.6,
98.4,
99.6
respectively
while
AI
Fuzzy-PSO,
ANN,
ANFIS,
ANN-PSO,
PSO,
FLC
98.6,
98,
98.8,
98.2,
98
respectively.
results
study
add
significantly
our
knowledge
applicability
effectiveness
traditional
MPPT
which
will
help
industry
make
well-informed
choices
when
implementing
systems.
Applied Sciences,
Journal Year:
2021,
Volume and Issue:
11(16), P. 7550 - 7550
Published: Aug. 17, 2021
In
the
current
era,
Artificial
Intelligence
(AI)
is
becoming
increasingly
pervasive
with
applications
in
several
applicative
fields
effectively
changing
our
daily
life.
this
scenario,
machine
learning
(ML),
a
subset
of
AI
techniques,
provides
machines
ability
to
programmatically
learn
from
data
model
system
while
adapting
new
situations
as
they
more
by
are
ingesting
(on-line
training).
During
last
years,
many
papers
have
been
published
concerning
ML
field
solar
systems.
This
paper
presents
state
art
models
applied
energy’s
forecasting
i.e.,
for
irradiance
and
power
production
(both
point
interval
or
probabilistic
forecasting),
electricity
price
energy
demand
forecasting.
Other
into
photovoltaic
(PV)
taken
account
modelling
PV
modules,
design
parameter
extraction,
tracking
maximum
(MPP),
systems
efficiency
optimization,
PV/Thermal
(PV/T)
Concentrating
(CPV)
parameters’
optimization
improvement,
anomaly
detection
management
PV’s
storage
While
review
already
exist
regard,
usually
focused
only
on
one
specific
topic,
gathered
all
most
relevant
different
fields.
The
gives
an
overview
recent
promising
used
Energy Reports,
Journal Year:
2022,
Volume and Issue:
8, P. 4871 - 4898
Published: April 8, 2022
This
article
presents
a
comparative
analysis
of
the
latest
swarm-based
optimization
approaches
under
partial
shading
conditions
(PSCs)
for
maximum
power
point
tracking
(MPPT)
in
photovoltaic
(PV)
systems.
The
MPPT
algorithms
are
stochastic
meta-heuristic
that
have
become
very
popular
recently
various
applications
owing
to
drawbacks
conventional
different
operating
conditions.
A
comprehensive
review
recent
research
on
these
is
carried
out
particularly
focusing
PSCs.
advantages,
disadvantages,
applications,
computational
efficiency,
and
stability
critically
surveyed
detail.
Moreover,
analyze
performance
algorithms,
special
case
study
conducted
MATLAB/Simulink
environment
solar-powered
DC
load
with
boost
converter.
seven
techniques
evaluated
this
terms
their
settling
time,
convergence
speed,
overshoot,
efficiency
levels
statistical
30
simulation
runs
shows
heavier
conditions,
grasshopper
algorithm
(GOA)
salp
swarm
(SSA)
outperform
other
algorithms.
It
envisaged
work
will
be
one-stop
source
guidance
researchers
working
field
MPP
