Energy Reports,
Journal Year:
2023,
Volume and Issue:
10, P. 4198 - 4217
Published: Nov. 1, 2023
Global
solar
radiation
(GSR)
prediction
capability
with
a
reliable
model
and
high
accuracy
is
crucial
for
comprehending
hydrological
meteorological
systems.
It
vital
the
production
of
renewable
clean
energy.
This
research
aims
to
evaluate
performance
combined
variational
mode
decomposition
(VMD)
multi-functional
recurrent
fuzzy
neural
network
(MFRFNN)
quantile
regression
forests
(QRF)
models
GSR
in
daily
scales.
The
hybrid
VMD-MFRFNN
QRF
were
compared
standalone
MFRFNN,
random
forest
(RF),
extreme
gradient
boosting
(XGB),
M5
tree
(M5T)
across
Lund
Växjö
stations
Sweden.
data
from
2008
2017
used
train
models,
while
was
verified
by
using
2018
2021
under
five
different
input
combinations.
various
meteorological-based
scenarios
(including
are
air
temperatures
(Tmin,
Tmax,
T),
wind
speed
(WS),
relative
humidity
(RH),
sunshine
duration
(SSH),
maximum
possible
(N))
considered
as
predictor
models.
current
study
resulted
that
M5T
exhibited
higher
than
RF
XGB
showed
equivalent
at
both
sites.
MFRFNN
outperformed
all
combinations
best
when
fewer
variables
T,
WS
station
Tmin,
WS,
SSH,
RH
station)
prediction.
We
conclude
predicts
average
combining
RH,
N).
Journal of Electrical Engineering and Technology,
Journal Year:
2023,
Volume and Issue:
18(2), P. 719 - 733
Published: Jan. 12, 2023
With
increasing
demand
for
energy,
the
penetration
of
alternative
sources
such
as
renewable
energy
in
power
grids
has
increased.
Solar
is
one
most
common
and
well-known
existing
networks.
But
because
its
non-stationary
non-linear
characteristics,
it
needs
to
predict
solar
irradiance
provide
more
reliable
Photovoltaic
(PV)
plants
manage
supply
demand.
Although
there
are
various
methods
irradiance.
This
paper
gives
overview
recent
studies
with
focus
on
forecasting
ensemble
which
divided
into
two
main
categories:
competitive
cooperative
forecasting.
In
addition,
parameter
diversity
data
considered
also
preprocessing
post-processing
All
these
investigated
this
study.
end,
conclusion
been
drawn
recommendations
future
have
discussed.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Jan. 18, 2024
Abstract
At
present,
fossil
fuel-based
power
generation
systems
are
reducing
drastically
because
of
their
less
availability
in
nature.
In
addition,
it
produces
hazardous
gasses
and
high
environmental
pollution.
So,
this
work,
the
solar
natural
source
is
selected
for
generating
electricity.
Due
to
nonlinear
behavior
PV,
achieving
maximum
voltage
from
Photovoltaic
(PV)
system
a
more
tough
job.
various
hybrid
optimization
controllers
studied
tracing
working
point
PV
under
different
Partial
Shading
Conditions.
The
MPPT
methods
equated
terms
oscillations
across
MPP,
output
extraction,
settling
time
dependency
on
modeling,
operating
duty
value
converter,
error
finding
accuracy
MPPT,
algorithm
complexity,
tracking
speed,
periodic
tuning
required,
number
sensing
parameters
utilized.
Based
simulative
comparison
results,
has
been
observed
that
modified
Grey
Wolf
Optimization
based
ANFIS
method
provides
good
results
when
with
other
techniques.
Here,
conventional
converter
helps
increase
one
level
another
level.
proposed
investigated
by
using
MATLAB/Simulink
tool.
