Energies,
Journal Year:
2024,
Volume and Issue:
17(22), P. 5537 - 5537
Published: Nov. 6, 2024
The
building
sector
contributes
significantly
to
energy
consumption
and
greenhouse
gas
emissions,
with
many
buildings
being
inefficient.
In
response,
the
European
Green
Deal
promotes
improving
efficiency
support
decarbonization
goals.
However,
managing
integrating
data
from
multiple
sources
presents
challenges,
especially
for
large
portfolios.
This
study
introduces
a
novel
methodology
designed
optimize
renovation
strategies,
balancing
technical,
financial,
maintenance
considerations.
is
implemented
in
CERPlan
1.0,
web-based
decision-support
platform
that
combines
on
performance,
costs,
needs.
Through
simulations,
1.0
helps
decision-makers
prioritize
retrofit
interventions
based
economic
criteria
while
leveraging
synergies
between
improvements
regular
maintenance.
Application
of
this
real
estate
portfolios
reveals
opportunities
enhance
cost-effectiveness
savings.
results
show
into
planning
reduces
payback
times
allows
more
comprehensive
strategies.
conclusions
highlight
1.0’s
potential
improve
decision-making,
making
renovations
efficient
sustainable.
Buildings,
Journal Year:
2024,
Volume and Issue:
14(9), P. 2820 - 2820
Published: Sept. 7, 2024
The
Logarithmic
Mean
Divisia
Index
(LMDI)
method
is
widely
applied
in
research
on
carbon
emissions,
urban
energy
consumption,
and
the
building
sector,
useful
for
theoretical
evaluation.
approach
especially
beneficial
combating
climate
change
encouraging
transitions.
During
method’s
development,
there
are
opportunities
to
develop
advanced
formulas
improve
accuracy
of
studies,
as
indicated
by
past
research,
that
have
yet
be
fully
explored
through
experimentation.
This
study
reviews
previous
LMDI
context
offering
a
comprehensive
overview
its
application.
It
summarizes
technical
foundations,
applications,
evaluations
analyzes
major
trends
common
calculation
methods
used
25
years
LMDI-related
field.
Moreover,
it
use
energy,
emissions
discusses
other
methods,
such
Generalized
Method
(GDIM),
Decision
Making
Trial
Evaluation
Laboratory
(DEMATEL),
Interpretive
Structural
Modeling
(ISM)
techniques.
explores
compares
advantages
disadvantages
these
their
sector
LMDI.
Finally,
this
paper
concludes
highlighting
future
possibilities
LMDI,
suggesting
how
can
integrated
with
models
more
analysis.
However,
current
still
lack
an
extensive
driving
factors
low-carbon
city
development.
related
studies
often
focused
single
or
specific
domains
without
interdisciplinary
understanding
interactions
between
factors.
traditional
decomposition
face
challenges
handling
large-scale
data
highly
depend
quality.
Together
estimation
kernel
density
spatial
correlation
analysis,
enhanced
overcomes
drawbacks
review
drivers
usage
emissions.
Integrating
machine
learning
big
technologies
enhance
data-processing
capabilities
analytical
accuracy,
scientific
policy
recommendations
practical
tools
Through
particular
case
indicates
effectiveness
approaches
proposes
measures
include
optimizing
design,
enhancing
efficiency,
refining
energy-management
procedures.
These
efforts
aim
promote
smart
cities
achieve
sustainable
development
goals.
