Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi,
Journal Year:
2024,
Volume and Issue:
29(2), P. 798 - 822
Published: Aug. 20, 2024
Son
yıllarda,
sürdürülebilir
bir
dünya
için
yenilenemeyen
enerji
kaynaklarının
kullanımının
azaltılması
gerekliliği
giderek
daha
belirgin
hale
gelmektedir.
Fosil
yakıt
tüketiminden,
temiz
enerjiye
geçiş
döneminde,
yenilenebilir
kaynakları
hızla
gelişme
göstermektedir.
Bu
gelişmeler
ışığında
su
enerjisi
teknolojilerine
odak
artmaktadır.
Enerji
potansiyeli
gerekli
şartlar
karşılandığı
sürece;
kaynaklı
üretim
projelerinin
uygulanması
ülkelerin
refahına
katkı
sağlama
taşımaktadır.
Yenilenebilir
üretiminde
rekabete
konu
olan
üretimi
için;
literatürde
kıtalar
arası
enerjinin
incelendiği,
potansiyelinin
ölçüldüğü,
santraller
uygun
yer
seçiminin
yapıldığı,
dalga
–
iklim
ilişkisinin
okyanus
teknolojileri
konularını
içeren
çalışmalarda
geleneksel
teknikler
yanı
sıra
yapay
zekâ
tekniklerine
de
verilmektedir.
Deneysel
modelleme
saha
ölçüm
tekniklerinin
yüksek
maliyetli
olduğu,
sayısal
yöntemlerin
parametre
ve
girdi
hazırlık
sürecinin
zahmetli
olması
sebebiyle
çeşitli
yöntemleri,
teknolojisinde
yoğun
şekilde
kullanılmaktadır.
Yapay
sinir
ağları
da
bu
alanda
karşılaşılan
problemlerin
çözümünde
kullanılan
tekniklerden
birisi
olarak
almaktadır.
derlemede,
Asya
Avrupa
kıtasında
hakkında
yapılmış
mevcut
çalışmalardan
bahsedilmekte,
Türkiye’nin
potansiyelini,
literatür
incelenerek
ortaya
konulmaktadır.
Ayrıca
tekniklerinden
ağı
metodunun
teknolojilerinde
ne
hangi
ölçüde
kullanıldığı
yöntemlerle
ilgili
literatüre
verilmiştir.
Civil Engineering Journal,
Journal Year:
2024,
Volume and Issue:
10(2), P. 384 - 403
Published: Feb. 1, 2024
This
research
was
conducted
by
equipping
three
temporary
tidal
stations
located
in
places
inside
Palu
Bay
with
pressure-type
gauges.
The
recorded
series
fluctuations
for
4
months
a
5-minute
sampling
interval
(Dt).
Moreover,
the
simple
and
widely
used
least
squares
method
(LSM)
applied
to
separate
harmonic
constants
of
constituents,
including
amplitudes
(Hi)
phases
(gi),
from
observed
series.
A
total
11
dominant
constituents
were
selected
based
on
largest
magnitudes
generating
potential
(CE),
these
include
M2,
K1,
S2,
O1,
P1,
N2,
Mf,
K2,
Mm,
Q1,
Msf,
which
diurnal,
semidiurnal,
long-period
constituents.
results
showed
that
semidiurnal
generated
higher
than
diurnal
while
produced
quite
small
amplitudes.
Furthermore,
ratios
mainly
mixed
difference
between
predicted
values
small,
this
validity
measurement
at
stations.
performance
indicators
also
LSM
had
acceptable
accuracy
compared
other
methods.
datums
calculated
using
peak
approach,
average
range
(RA)
found
be
2.39
m.
Doi:
10.28991/CEJ-2024-010-02-03
Full
Text:
PDF
Journal of Engineering Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 1, 2024
The
deployment
and
development
of
wave
energy
systems
to
increase
sector
efficiency
is
essential
for
governments.
To
develop
maximize
the
exploitation
sources,
applying
appropriate
technologies
extremely
important.
design
decision-making
tools
identify
best
technology
developing
resources
optimally
one
primary
issues
in
sector.
In
this
article,
we
have
proposed
a
Multi-Criteria
Decision
Making
(MCDM)
model
select
suitable
among
eleven
harvesting
technologies:
OPT
PowerBuoy,
AquaBuoy,
Archimedes
Wave
Swing,
Salter's
Duck,
Aquamarine
PowerOyster,
Bio
Wave,
SEAREV,
Weptos,
Mighty
Whale,
dragon.
handle
conflicting
objectives
during
evaluation,
Fuzzy
AHP
method
used
calculate
weight
criteria.
Then,
ranked
using
TOPSIS
approach.
An
actual
case
study
from
Australia
was
examined
order
show
viability
suggested
methodology.
This
applies
valuable
reference
issue
selection;
Therefore,
managers
involved
can
use
problem-solving
approach
most
based
on
their
Research
results
that
optimal
sources
are
WET-05
WET-03
with
coefficients
0.852
0.806,
respectively.
Meanwhile,
two
considered
unsuitable
WET-06
WET-11
scores
0.375
0.381,
study,
combined
application
FAHP-FTOPSIS
methods
more
because
its
theoretical
ease
understanding
as
well
simplicity
robustness
results.
Computers, materials & continua/Computers, materials & continua (Print),
Journal Year:
2023,
Volume and Issue:
77(2), P. 2579 - 2594
Published: Jan. 1, 2023
Increasing
global
energy
consumption
has
become
an
urgent
problem
as
natural
sources
such
oil,
gas,
and
uranium
are
rapidly
running
out.
Research
into
renewable
solar
is
being
pursued
to
counter
this.
Solar
one
of
the
most
promising
sources,
it
potential
meet
world’s
needs
indefinitely.
This
study
aims
develop
evaluate
artificial
intelligence
(AI)
models
for
predicting
hourly
irradiation.
The
hyperparameters
were
optimized
using
Broyden-Fletcher-Goldfarb-Shanno
(BFGS)
quasi-Newton
training
algorithm
STATISTICA
software.
Data
from
two
stations
in
Algeria
with
different
climatic
zones
used
model.
Various
error
measurements
determine
accuracy
prediction
models,
including
correlation
coefficient,
mean
absolute
error,
root
square
(RMSE).
optimal
support
vector
machine
(SVM)
model
showed
exceptional
efficiency
during
phase,
a
high
coefficient
(R
=
0.99)
low
(MAE
26.5741
Wh/m2),
well
RMSE
38.7045
Wh/m²
across
all
phases.
Overall,
this
highlights
importance
accurate
energy,
which
can
contribute
better
management
planning.
