Developments in the Built Environment,
Journal Year:
2024,
Volume and Issue:
17, P. 100345 - 100345
Published: Jan. 28, 2024
The
building
energy
performance
gap
(EPG)
seriously
restricts
the
improvement
of
efficiency.
Currently,
although
many
studies
on
EPG,
it
is
not
yet
fully
understood
and
addressed.
To
fill
this
gap,
paper
conducted
an
extensive
review
EPG
research.
Firstly,
magnitude
was
summarized
from
case
studies,
results
showed
that
varied
greatly
among
types,
with
ratios
ranging
0.5
to
4
for
educational/research
buildings,
concentrated
between
2.5
residential
0
1
office
building.
Then,
fifteen
direct
causes
seven
in-depth
drivers
were
analyzed
simulation
lifecycle
perspectives,
linkages
them
established.
Furthermore,
solutions
summarized,
including
some
state-of-the-art
technical
"soft"
measures,
their
correspondence
underlying
causes.
Finally,
eight
future
research
recommendations
proposed
based
limitations
existing
strategies.
Energy and Buildings,
Journal Year:
2023,
Volume and Issue:
292, P. 113171 - 113171
Published: May 18, 2023
In
an
increasingly
digital
world,
there
are
fast-paced
developments
in
fields
such
as
Artificial
Intelligence,
Machine
Learning,
Data
Mining,
Digital
Twins,
Cyber-Physical
Systems
and
the
Internet
of
Things.
This
paper
reviews
discusses
how
these
new
emerging
areas
relate
to
traditional
domain
building
performance
simulation.
It
explores
boundaries
between
simulation
other
order
identify
conceptual
differences
similarities,
strengths
limitations
each
areas.
The
critiques
common
notions
about
domains
they
simulation,
reviewing
field
may
evolve
benefit
from
developments.
Renewable and Sustainable Energy Reviews,
Journal Year:
2023,
Volume and Issue:
182, P. 113396 - 113396
Published: May 30, 2023
Occupant
behavior
has
been
widely
considered
as
one
of
the
key
influencing
factors
on
building
energy
consumption.
The
complexity
its
formation
mechanism
and
dynamic
interaction
with
buildings
have
aroused
extensive
discussion.
However,
there
remains
a
lack
comprehensive
systematic
review
to
provide
panorama
occupant
consumption
research.
This
research,
therefore,
aims
(1)
explore
evolution
research;
(2)
investigate
knowledge
base
domains
(3)
identify
current
research
gaps
propose
future
directions.
Bibliometric
approach
content
analysis
were
applied
2791
relevant
articles
published
from
2001
2022.
It
was
found
that
focus
evolved
simple
discussion
individual
at
beginning
information-based
complex
behaviors.
A
total
45
keywords
10
clusters
identified.
Eight
directions
finally
recommended
based
identified
researcher
gaps,
including
algorithmic
innovation,
multi-source
heterogeneous
data
fusion,
interdisciplinary,
extension
standardization
behavioral
models,
diversification
types,
synergism
collective
perspective,
novel
intervention
strategies.
differs
previous
ones
because
it
could
minimize
subjectivity
bias
compared
traditional
manual
review.
results
this
can
potential
researchers
sufficient
in
field
inspire
them
directions,
which
contributes
further
achieving
energy-saving
goals
perspective
occupants'
buildings.
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(15), P. 8814 - 8814
Published: July 30, 2023
Buildings
consume
a
significant
amount
of
energy
throughout
their
lifecycle;
Thus,
sustainable
management
is
crucial
for
all
buildings,
and
controlling
consumption
has
become
increasingly
important
achieving
construction.
Digital
twin
(DT)
technology,
which
lies
at
the
core
Industry
4.0,
gained
widespread
adoption
in
various
fields,
including
building
analysis.
With
ability
to
monitor,
optimize,
predict
real
time.
DT
technology
enabled
cost
reduction.
This
paper
provides
comprehensive
review
development
application
energy.
Specifically,
it
discusses
background
information
modeling
(BIM)
optimization
buildings.
Additionally,
this
article
reviews
management,
indoor
environmental
monitoring,
efficiency
evaluation.
It
also
examines
benefits
challenges
implementing
analysis
highlights
recent
case
studies.
Furthermore,
emphasizes
emerging
trends
opportunities
future
research,
integrating
machine
learning
techniques
with
technology.
The
use
sector
gaining
momentum
as
efforts
optimize
reduce
carbon
emissions
continue.
advancement
technologies
expected
enhance
prediction
accuracy,
efficiency,
improve
processes.
These
advancements
have
focal
point
current
literature
potential
facilitate
transition
clean
energy,
ultimately
goals.
