Optimizing the Operation of Shopping Malls using Commercial Demand Response Aggregator to Reduce Consumption in the Day-Ahead Market
Smart Grids and Sustainable Energy,
Год журнала:
2025,
Номер
10(1)
Опубликована: Янв. 18, 2025
Язык: Английский
A two-stage probabilistic flexibility management model for aggregated residential buildings
Energy and Buildings,
Год журнала:
2025,
Номер
unknown, С. 115404 - 115404
Опубликована: Фев. 1, 2025
Язык: Английский
Demand Response Strategy Optimization Method Based on Differentiated Comprehensive Benefit Model of Air-Conditioning Customers
Buildings,
Год журнала:
2025,
Номер
15(7), С. 1065 - 1065
Опубликована: Март 26, 2025
Air-conditioning
systems
are
critical
demand
response
(DR)
resources,
yet
conventional
temperature
adjustment
strategies
based
on
fixed
setpoints
often
neglect
users’
heterogeneous
economic
and
comfort
requirements.
This
paper
proposes
a
DR
strategy
optimization
method
user-specific
comprehensive
benefit
evaluation.
Firstly,
quantitative
model
integrating
benefits
thermal
loss
is
established
through
the
mechanism.
Subsequently,
with
indoor
as
variables
to
maximize
benefits.
Finally,
comparative
simulations
involving
15
customers
varying
parameters
(basic
profitability
labor
elasticity
coefficients)
demonstrate
proposed
strategy’s
superiority
in
load
reduction
customers’
over
traditional
setpoint
methods.
The
results
indicate
following:
(1)
optimized
achieves
greater
under
most
scenarios
than
fixed-setpoint
strategies;
(2)
all
participants
obtain
enhanced
compared
(3)
lower
less
dependency
show
better
responsiveness.
study
improves
participation
incentives
by
balancing
benefits,
providing
theoretical
support
for
designing
demand-side
management
policies
smart
building
applications.
Язык: Английский
Energy resilience enhancement against grid outages for a zero-emission hotel building via optimal energy management of onshore and offshore energy storages
Energy Nexus,
Год журнала:
2025,
Номер
unknown, С. 100431 - 100431
Опубликована: Май 1, 2025
Язык: Английский
Review of Optimization Control Methods for HVAC Systems in Demand Response (DR): Transition from Model-driven to Model-free Approaches and Challenges
Building and Environment,
Год журнала:
2025,
Номер
unknown, С. 113045 - 113045
Опубликована: Май 1, 2025
Язык: Английский
Data-Driven Ventilation and Energy Optimization in Smart Office Buildings: Insights from a High-Resolution Occupancy and Indoor Climate Dataset
Sustainability,
Год журнала:
2024,
Номер
17(1), С. 58 - 58
Опубликована: Дек. 25, 2024
This
paper
explores
innovative
approaches
to
reducing
energy
consumption
in
building
ventilation
systems
through
the
implementation
of
adaptive
control
strategies.
Using
a
publicly
available
high-resolution
dataset
spanning
full
year,
study
integrates
real-time
data
on
occupancy,
CO2
levels,
temperature,
window
state,
and
external
environmental
conditions.
Notably,
occupancy
derived
from
computer
vision-based
detection
using
YOLOv5
algorithm
provides
an
unprecedented
level
granularity.
The
evaluates
five
energy-saving
strategies:
Demand-Controlled
Ventilation
(DCV),
occupancy-based
control,
time-based
off-peak
reduction,
window-open
temperature-based
control.
Among
these,
strategy
achieved
highest
savings,
power
by
50%,
while
yielded
significant
37.27%
reduction.
paper’s
originality
lies
its
holistic
analysis
multiple
dynamic
strategies,
integrating
diverse
operational
variables
rarely
combined
prior
research.
findings
highlight
transformative
potential
advanced
algorithms
optimize
HVAC
performance.
establishes
new
benchmark
for
energy-efficient
management
offering
practical
recommendations
laying
groundwork
predictive
models,
renewable
integration,
occupant-centric
systems.
Язык: Английский