Processes,
Journal Year:
2024,
Volume and Issue:
12(12), P. 2850 - 2850
Published: Dec. 12, 2024
In
order
to
enhance
the
carbon
reduction
potential
of
a
park,
low-carbon
economic
dispatch
method
applicable
zero-carbon
parks
is
proposed
optimize
energy
park
at
multiple
timescales;
this
achieved
by
introducing
flexible
response
mechanism
for
source–load
bilaterals,
so
as
achieve
low-carbon,
economic,
and
efficient
operation.
First,
model
that
accounts
flow
characteristics
distribution
hub
established.
Then,
based
on
operation
supply
equipment
multi-type
integrated
demand
response,
bilaterally
multi-timescale
scheduling
framework
are
proposed;
mechanisms
coordination
electricity–carbon
coupling
analyzed
in
depth.
Finally,
with
objective
optimal
system
economy,
established
three
timescales,
namely,
day-ahead,
intraday,
real-time
scheduling.
The
output
optimized
step
according
prediction
information
results
each
stage.
simulation
show
can
effectively
utilize
source
load
resources
participate
reduce
emissions
while
ensuring
realizing
system.
Therefore,
study
provides
new
theoretical
basis
practical
solution
parks,
which
helps
promote
development
economy.
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(9), P. 4820 - 4820
Published: April 26, 2025
This
paper
introduces
a
novel
weighted
fusion
methodology
for
grid-level
short-term
load
forecasting
that
addresses
the
critical
limitations
of
direct
aggregation
methods
currently
used
by
regional
dispatch
centers.
Traditional
approaches
accumulate
provincial
forecasts
without
considering
heterogeneity
in
characteristics,
data
quality,
and
capabilities.
Our
implements
comprehensive
evaluation
index
system
quantifies
forecast
trustworthiness
through
three
key
dimensions:
reliability,
impact,
complexity.
The
core
innovation
lies
our
principal
component
analysis
(PCA)-based
mechanism
dynamically
adjusts
weights
according
to
their
evaluated
further
enhancing
time-varying
adapt
changing
patterns
throughout
day.
Experimental
validation
across
representative
seasonal
periods
(moderate
temperature,
high
winter
conditions)
substantiates
approach
consistently
outperforms
aggregation,
achieving
24.67%
improvement
overall
MAPE
(from
3.09%
2.33%).
Performance
gains
are
particularly
significant
during
peak
periods,
with
up
62.6%
error
reduction
under
high-temperature
conditions.
verifies
remarkable
adaptability
different
temporal
scales,
variations,
maintaining
superior
performance
from
ultra-short-term
(1
h)
medium-term
(168
horizons.
Analysis
weight
dynamics
reveals
intelligent
redistribution
seasons,
summer
months
characterized
Jiangsu
dominance
(0.30–0.35)
shifting
increased
Anhui
contribution
winter.
provides
grid
centers
computationally
efficient
solution
integration
heterogeneous
diverse
regions,
leveraging
complementary
strengths
individual
systems
while
supporting
safer
more
economical
power
operations
requiring
modifications
existing
infrastructure.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 25, 2024
Abstract
Grid-level
dispatching
is
generally
based
on
the
accumulation
of
independent
load
forecasting
data
from
provincial
and
municipal
dispatch
centers.
However,
differences
in
economic
development
levels
frequency
result
updates
among
provinces
cities
lead
to
certain
limitations
direct
method,
affecting
accuracy
integrated
results.
To
address
this,
this
paper
proposes
a
short-term
method
for
power
grid
i-Transformer
model.
First,
dataset
constructed
through
preprocessing
feature
engineering,
followed
by
training
optimizing
model
parameters.
Further,
considering
results
reported
centers,
principal
component
analysis
used
determine
weights
cities,
thereby
effectively
integrating
different
weighting.
The
case
study
shows
that
outperforms
traditional
statistical
machine
learning
algorithms
multiple
evaluation
metrics,
integration
has
considerable
potential
handling
multi-source
heterogeneous
improving
accuracy.
This
provides
new
means
ensuring
safe,
high-quality,
economical
operation
system.
