Sustainable Cities and Society,
Journal Year:
2023,
Volume and Issue:
98, P. 104870 - 104870
Published: Aug. 16, 2023
This
paper
studies
the
implementation
of
twin
transition,
i.e.,
combination
digital
technologies
and
European
Green
Deal
goals,
to
achieve
sustainable
solutions
supporting
creation
impactful,
net-zero
carbon
a
resilient
built
environment
with
focus
on
Northern
Europe,
specifically
Finland.
The
subject
was
examined
from
policies,
technology
market
perspectives.
Numerous
regulations
policies
are
driving
transition
since
many
them
include
obligatory
requirements
for
member
states.
Technologies
combinations
exist
support
in
Nordic
environment.
It
assessed
that
energy
most
important
control,
monitoring
automation
second
category
transition.
In
addition,
individual
technologies'
maturity
relevance
cold
climates
were
evaluated.
By
analyzing
case
studies,
it
found
markets
not
mature
enough
lead
but
external
boosts
needed.
However,
this
can
also
be
seen
as
an
opportunity
service
business.
results
focused
legislation
supports
international
SDGs.
Sustainable Cities and Society,
Journal Year:
2021,
Volume and Issue:
76, P. 103445 - 103445
Published: Oct. 13, 2021
The
efficiency,
flexibility,
and
resilience
of
building-integrated
energy
systems
are
challenged
by
unpredicted
changes
in
operational
environments
due
to
climate
change
its
consequences.
On
the
other
hand,
rapid
evolution
artificial
intelligence
(AI)
machine
learning
(ML)
has
equipped
buildings
with
an
ability
learn.
A
lot
research
been
dedicated
specific
applications
for
phases
a
building's
life-cycle.
reviews
commonly
take
specific,
technological
perspective
without
vision
integration
smart
technologies
at
level
whole
system.
Especially,
there
is
lack
discussion
on
roles
autonomous
AI
agents
training
boosting
process
complex
abruptly
changing
environments.
This
review
article
discusses
system-level
presents
overview
that
make
independent
decisions
building
management.
We
conclude
buildings’
adaptability
can
be
enhanced
system
through
AI-initiated
processes
using
digital
twins
as
greatest
potential
efficiency
improvement
achieved
integrating
solutions
timescales
HVAC
control
electricity
market
participation.
Advances in Applied Energy,
Journal Year:
2023,
Volume and Issue:
9, P. 100123 - 100123
Published: Jan. 13, 2023
Machine
learning
has
been
widely
adopted
for
improving
building
energy
efficiency
and
flexibility
in
the
past
decade
owing
to
ever-increasing
availability
of
massive
operational
data.
However,
it
is
challenging
end-users
understand
trust
machine
models
because
their
black-box
nature.
To
this
end,
interpretability
attracted
increasing
attention
recent
studies
helps
users
decisions
made
by
these
models.
This
article
reviews
previous
that
interpretable
techniques
management
analyze
how
model
improved.
First,
are
categorized
according
application
stages
techniques:
ante-hoc
post-hoc
approaches.
Then,
analyzed
detail
specific
with
critical
comparisons.
Through
review,
we
find
broad
faces
following
significant
challenges:
(1)
different
terminologies
used
describe
which
could
cause
confusion,
(2)
performance
ML
tasks
difficult
compare,
(3)
current
prevalent
such
as
SHAP
LIME
can
only
provide
limited
interpretability.
Finally,
discuss
future
R&D
needs
be
accelerate
management.
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.
