Dynamic Integration of Shading and Ventilation: Novel Quantitative Insights into Building Performance Optimization
Buildings,
Год журнала:
2025,
Номер
15(7), С. 1123 - 1123
Опубликована: Март 30, 2025
Buildings
consume
nearly
40%
of
global
energy,
necessitating
innovative
strategies
to
balance
energy
efficiency
and
occupant
comfort.
While
shading
ventilation
are
critical
sustainable
design,
they
often
studied
independently,
leaving
gaps
in
understanding
their
combined
potential.
This
study
provides
a
novel
quantitative
analysis
dynamic
strategies,
using
dataset
5000
simulations
IDA
Indoor
Climate
Energy
(IDA
ICE)
reveal
the
synergies
trade-offs
building
performance.
Four
distinct
scenarios
analyzed:
minimal
limited
(shading
factor
Sf
=
0.0,
ACH
0.5),
optimized
moderate
(Sf
0.5,
1.5),
enhanced
dynamically
adjusted,
2.5),
high
with
maximum
1.0,
3.0).
The
results
show
progressive
reduction
thermal
discomfort,
predicted
percentage
dissatisfied
(PPD)
decreasing
from
>80%
first
scenario
~25%
~15%
scenario.
demand
increases
by
up
highest
scenario,
highlighting
trade-offs.
These
findings
underscore
importance
integrating
ventilation,
providing
actionable
recommendations
such
as
night
cooling
that
can
reduce
discomfort
improve
30%.
By
bridging
research
gaps,
this
advances
design
offers
robust
framework
for
creating
energy-efficient,
comfortable
buildings.
Язык: Английский
Implementation of adaptive hysteresis current controller in grid tied multilevel converter with battery storage system
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Май 23, 2025
Язык: Английский
Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions
Energies,
Год журнала:
2025,
Номер
18(11), С. 2960 - 2960
Опубликована: Июнь 4, 2025
In
a
photovoltaic
(PV)
system,
shading
caused
by
weather
and
environmental
factors
can
significantly
impact
electricity
production.
For
over
decade,
artificial
intelligence
(AI)
techniques
have
been
applied
to
enhance
energy
production
efficiency
in
the
solar
sector.
This
paper
demonstrates
how
AI-based
control
systems
improve
output
power
plant
under
conditions.
The
findings
highlight
that
AI
contributes
sustainable
development
of
Specifically,
maximum
point
tracking
(MPPT)
systems,
utilizing
metaheuristic
computer-based
algorithms,
enable
PV
arrays
mitigate
impacts
effectively.
effect
on
module
is
also
simulated
using
MATLAB
R2018b.
Using
actual
data
from
plant,
outputs
are
compared
two
scenarios:
(I)
without
system
(II)
equipped
with
MPPT
boards.
System
Advisor
Model
(SAM)
employed
calculate
monthly
case
study.
results
confirm
technology
generate
more
those
MPPTs.
Язык: Английский