Advances in transdisciplinary engineering,
Journal Year:
2023,
Volume and Issue:
unknown
Published: Oct. 5, 2023
The
design
and
measurement
of
renewable
systems
for
installation
in
various
regions
require
extensive
research
across
multiple
fields,
including
design,
optimization,
energy
mapping,
climate,
meteorology.
As
can
be
costly,
it
is
crucial
to
measure
a
region’s
potential
production
as
the
first
step.
Analyzing
available
types
identifying
each
region
prerequisite
establishing
system.
To
create
an
economically
viable
system,
cost
system
should
calculated
by
utilizing
new
technologies
sources.
With
clean
sources
efficient
designs,
possible
meet
demands
electricity
production,
heating,
cooling,
freshwater,
hydrogen
fuel
production.
This
study
highlights
high-capacity
presents
its
results
improve
direction
research.
Currently,
are
primarily
used
production;
however,
exploring
other
applications,
such
could
lead
valuable
advancements
field.
Applied Energy,
Journal Year:
2024,
Volume and Issue:
364, P. 123130 - 123130
Published: April 5, 2024
Multi-Objective
Optimization
(MOO)
poses
a
computational
challenge,
particularly
when
applied
to
physics-based
models.
As
result,
only
up
three
objectives
are
typically
involved
in
simulation-based
optimization.
To
go
beyond
this
number,
Surrogate
Models
(SMs)
need
replace
such
high-fidelity
In
exploratory
study,
the
perform
comprehensive
regression
surrogate
modeling
and
conduct
MOO
for
Multi-Generation
System
(MGS).
The
most
suitable
SM
was
chosen
among
four
neural-network
models:
Artificial
Neural
Network
(ANN),
Convolutional
(CNN),
Long-Short
Term
Memory
(LSTM),
an
ensemble
model
developed
through
brute-force
search
using
aforementioned
final
found
be
superior
others,
achieving
R2
values
ranging
from
0.9830
0.9999.
Next,
optimization
problem
with
six
conflicting
defined
performed
at
distinct
of
Direct
Normal
Irradiation
(DNI),
time-dependent
feature.
This
aimed
provide
multi-criteria
decision-making
information
based
on
atmospheric
transparency.
new
understandings
were
gained:
(I)
exergy
efficiency,
production
cost,
freshwater
rate
highly
influenced
by
DNI,
(II)
critical
range
operation
observed
within
DNI
interval
100
400
W/m2.
Furthermore,
we
compared
result
six-objective
that
bi-objective
obtained
our
study
all
showed
improvements
1.9%
12.7%.
Finally,
findings
present
some
practical
recommendations
put
forward
applying
proposed
methodology
similar
MGSs.
Energies,
Journal Year:
2025,
Volume and Issue:
18(5), P. 1302 - 1302
Published: March 6, 2025
Advances
in
numerical
modeling
are
essential
for
heat-transfer
applications
electronics
cooling,
renewable
energy,
and
sustainable
construction.
This
review
explores
key
methods
like
Computational
Fluid
Dynamics
(CFD),
the
Finite
Element
Method
(FEM),
Volume
(FVM),
multiphysics
modeling,
alongside
emerging
strategies
such
as
Adaptive
Mesh
Refinement
(AMR),
machine
learning
(ML),
reduced-order
(ROM),
high-performance
computing
(HPC).
While
these
techniques
improve
accuracy
efficiency,
they
also
increase
computational
energy
demands,
contributing
to
a
growing
carbon
footprint
sustainability
concerns.
Sustainable
practices,
including
energy-efficient
algorithms
renewable-powered
data
centers,
offer
potential
solutions.
Additionally,
increasing
consumption
highlights
need
optimization
mitigate
environmental
impact.
Future
directions
point
quantum
computing,
adaptive
models,
green
pathways
thermal
management
modeling.
study
systematically
reviews
latest
advancements
and,
first
time,
provides
an
in-depth
exploration
of
roles
management.
outlines
roadmap
efficient,
environmentally
responsible
models
meet
evolving
demands.
Energy Reports,
Journal Year:
2023,
Volume and Issue:
10, P. 4824 - 4848
Published: Nov. 1, 2023
Recently,
Numerous
metaheuristic
techniques
have
been
utilized
for
the
expedient
identification
of
Proton
Exchange
Membrane
Fuel
Cells
(PEMFCs)
models.
The
reported
can
inspect
fickle
in
a
wide
search
space
finding
optimal
solutions
at
appropriate
time.
In
this
paper,
recent
optimization
are
intended
to
better
identify
unknown
parameters
various
PEMFCs.
Three
neoteric
Gazelle
algorithm
(GOA),
Prairie
Dog
Optimization
Algorithm
(PDO),
and
Reptile
Search
(RSA)
applied
evaluated.
proposed
algorithms
validated
identifying
three
PEMFCs:
BCS
500
W
PEMFC,
SR-12
250
PEMFC
stack.
sum
squared
errors
(SSE)
between
estimated
voltage
corresponding
measured
data
was
formulated
as
objective
function
(OF).
MATLAB/Simulink
has
employed
validate
methods.
results
showed
that
solve
Cell
(FC)
problem.
Moreover,
there
insignificant
distinctions
methods
with
regard
their
value
function.
finest
technique
considering
average
is
GOA
W-PEM
0.0115,
while
worst
PDO
0.0112.
Additionally,
statistical
prove
100%,
99.99%,
100%
tracking
efficiencies
GOA,
PDO,
RSA,
respectively,
according
30
individual
launches
W-PEM.
evaluated
via
those
published
articles.
I/V
curves
achieved
employing
RSA
provided
good
agreement
ones
superiority
relating
convergence
speed,
efficiency,
metrics,
estimation
accuracy.
Energies,
Journal Year:
2024,
Volume and Issue:
17(19), P. 4807 - 4807
Published: Sept. 25, 2024
The
global
shift
towards
sustainable
energy
has
positioned
photovoltaic
(PV)
systems
as
a
critical
component
in
the
renewable
landscape.
However,
maintaining
efficiency
and
longevity
of
these
requires
effective
fault
detection
diagnosis
mechanisms.
Traditional
methods,
relying
on
manual
inspections
standard
electrical
measurements,
have
proven
inadequate,
especially
for
large-scale
solar
installations.
emergence
machine
learning
(ML)
deep
(DL)
sparked
significant
interest
developing
computational
strategies
to
enhance
identification
classification
PV
system
faults.
Despite
advancements,
challenges
remain,
particularly
due
limited
availability
public
datasets
complexity
existing
artificial-intelligence
(AI)-based
methods.
This
study
distinguishes
itself
by
proposing
novel
AI-based
approach
that
optimizes
systems,
addressing
gaps
AI-driven
detection,
terms
thermal
imaging
current–voltage
(I-V)
curve
analysis.
comprehensive
survey
identifies
emerging
trends
highlights
most
advanced
methodologies,
proposes
capabilities.
findings
aim
advance
state
technology
this
field,
offering
insights
into
more
efficient
practical
solutions
management.
