Renewable and Sustainable Energy Reviews,
Journal Year:
2024,
Volume and Issue:
193, P. 114283 - 114283
Published: Jan. 9, 2024
Because
of
their
low
computational
costs,
surrogate
models
(SMs),
also
known
as
meta-models,
have
attracted
attention
simplified
approximations
detailed
simulations.
Besides
conventional
statistical
approaches,
machine-learning
techniques,
such
neural
networks
(NNs),
been
used
to
develop
models.
However,
based
on
NNs
are
currently
not
developed
in
a
consistent
manner.
The
development
process
the
is
adequately
described
most
studies.
There
may
be
some
doubt
regarding
abilities
due
lack
documented
validation.
In
order
address
these
issues,
this
paper
presents
protocol
for
systematic
NN-based
and
how
procedure
should
reported
justified.
covers
model
sample
generation,
data
processing,
SM
training
validation,
report
implementation,
justify
modeling
choices.
critically
review
quality
SMs
prediction
building
energy
consumption.
Sixty-eight
papers
reviewed,
details
summarized.
developing
procedures
were
evaluated
using
criteria
proposed
protocol.
results
show
that
selection
number
neurons
best-implemented
step
with
justification,
followed
by
determination
architecture,
mostly
justified
discussion
way.
While
greater
focus
given
dataset
especially
input
variables
selection,
considering
independence
check
clear
validation
test
data.
Also,
preprocessing
strongly
recommended.
Energy Reports,
Journal Year:
2021,
Volume and Issue:
8, P. 334 - 361
Published: Dec. 16, 2021
Industrial
development
with
the
growth,
strengthening,
stability,
technical
advancement,
reliability,
selection,
and
dynamic
response
of
power
system
is
essential.
Governments
companies
invest
billions
dollars
in
technologies
to
convert,
harvest,
rising
demand,
changing
demand
supply
patterns,
efficiency,
lack
analytics
required
for
optimal
energy
planning,
store
energy.
In
this
scenario,
artificial
intelligence
(AI)
starting
play
a
major
role
market.
Recognizing
importance
AI,
study
was
conducted
on
seven
different
energetics
systems
their
variety
applications,
including:
i)
electricity
production;
ii)
delivery;
iii)
electric
distribution
networks;
iv)
storage;
v)
saving,
new
materials,
devices;
vi)
efficiency
nanotechnology;
vii)
policy,
economics.
The
main
drivers
are
four
key
techniques
used
current
AI
technologies,
fuzzy
logic
systems;
neural
genetic
algorithms;
expert
systems.
developed
countries,
industry
has
started
using
connect
smart
meters,
grids,
Internet
Things
devices.
These
will
lead
improvement
management,
transparency,
usage
renewable
energies.
recent
decades/years,
technology
brought
significant
improvements
how
devices
monitor
data,
communicate
system,
analyze
input–output,
display
data
unprecedented
ways.
New
applications
become
feasible
when
these
developments
incorporated
into
industry.
But
contrary,
much
more
investment
needed
global
research
data-driven
models.
terms
supply,
can
help
utilities
provide
customers
affordable
from
complex
sources
secure
manner,
while
at
same
time
providing
opportunity
use
own
efficiently.
Moreover,
policy
recommendations,
opportunities,
4.0
improve
sustainability
have
been
briefly
described.
Sustainability,
Journal Year:
2022,
Volume and Issue:
14(8), P. 4832 - 4832
Published: April 18, 2022
With
population
increases
and
a
vital
need
for
energy,
energy
systems
play
an
important
decisive
role
in
all
of
the
sectors
society.
To
accelerate
process
improve
methods
responding
to
this
increase
demand,
use
models
algorithms
based
on
artificial
intelligence
has
become
common
mandatory.
In
present
study,
comprehensive
detailed
study
been
conducted
applications
Machine
Learning
(ML)
Deep
(DL),
which
are
newest
most
practical
Artificial
Intelligence
(AI)
systems.
It
should
be
noted
that
due
development
DL
algorithms,
usually
more
accurate
less
error,
these
ability
model
solve
complex
problems
field.
article,
we
have
tried
examine
very
powerful
problem
solving
but
received
attention
other
studies,
such
as
RNN,
ANFIS,
RBN,
DBN,
WNN,
so
on.
This
research
uses
knowledge
discovery
databases
understand
ML
systems’
current
status
future.
Subsequently,
critical
areas
gaps
identified.
addition,
covers
efficient
used
field;
optimization,
forecasting,
fault
detection,
investigated.
Attempts
also
made
cover
their
evaluation
metrics,
including
not
only
important,
newer
ones
attention.
Case Studies in Thermal Engineering,
Journal Year:
2021,
Volume and Issue:
27, P. 101250 - 101250
Published: July 15, 2021
In
the
present
research,
Grey
Wolf
Optimizer
(GWO)
was
used
to
minimize
yearly
energy
consumption
of
an
office
building
in
Seattle
weather
conditions.
The
GWO
is
a
meta-heuristic
optimization
method,
which
inspired
by
hunting
behavior
grey
wolfs.
method
coded
and
coupled
with
EnergyPlus
codes
perform
task.
impact
algorithm
settings
on
performance
explored,
it
found
that
could
provide
best
using
40
optimized
solutions
were
compared
other
algorithms
literature,
lead
excellent
optimum
solution
efficiently.
One
methods
literature
Particle
Swarm
Optimization
(PSO),
led
objective
function
133.5,
while
resulted
value
133.
multi-objective
also
examined
GWO.
results
showed
archive
non-dominant
solutions.
Sustainable Energy Technologies and Assessments,
Journal Year:
2021,
Volume and Issue:
44, P. 101020 - 101020
Published: Feb. 1, 2021
Building
retrofitting
towards
nearly
zero
energy
building
(nZEB)
with
comfortable
visual
and
thermal
conditions,
requires
a
comprehensive
parametric
analysis
of
retrofit
measures.
This
paper
presented
an
optimization
method
to
automate
the
procedure
finding
best
combination
measures
minimizing
use
achieving
nZEB
target
while
enhancing
both
comfort
conditions.
The
study
was
performed
by
coupling
Indoor
climate
simulation
software
(IDA-ICE)
generic
tool
(GenOpt)
through
Graphical
Script
interface
applied
typical
office
located
in
Norway.
adopted
allowed
concurrent
envelope,
supply,
fenestration,
shading
device
material,
control
methods.
Two
constraint
functions
including
criteria
were
considered.
Afterwards,
PV
panels
integrated
site
for
on-site
production
electricity
ZEB
level.
Findings
demonstrated
that
inclusive
approach
could
significantly
decrease
use,
up
77%,
improve
simultaneously.
Furthermore,
performance
optimal
solution
achieved
when
window
opening
methods
functioned
solar
radiation
indoor
air
temperature
setpoints.
