The
integrated
energy
system
(IES)
that
includes
renewable
distributed
generation
(RDG)
is
considered
an
efficient
to
support
low-carbon
supply,
offering
economic
and
environmental
benefits.
However,
the
operational
uncertainties
introduced
by
intermittent
different
forms
of
demands
bring
technical
challenges
management
IES.
This
paper
proposes
a
multi-stage
multi-timescale
framework
(EMF)
incorporating
spatio-temporal
correlations
RDGs
demands.
proposed
solution
encompasses
day-ahead
stage
intra-day
based
on
demand
prediction
using
feature
graph
convolutional
network
(STFGCN).
scheduling
model
aims
minimize
pre-economic
costs
carbon
emission
considering
ladder-type
trading
mechanism
(CTM)
achieve
scheduling.
predictive
control
(MPC)
dispatch
penalties
for
deviations
through
rolling
optimization.
method
extensively
assessed
experiments
against
benchmark
solutions,
numerical
results
confirmed
its
effectiveness
in
mitigating
impact
with
reduced
cost
emissions.
International Journal of Electrical Power & Energy Systems,
Journal Year:
2024,
Volume and Issue:
158, P. 109923 - 109923
Published: March 9, 2024
Power-to-gas
(P2G)
facilities
use
surplus
electricity
to
convert
natural
gas
in
integrated
energy
systems
(IES),
increasing
the
capacity
of
wind
power
be
consumed.
However,
limitation
P2G
and
anti-peaking
characteristic
make
abandonment
problem
still
exist.
Meanwhile,
oxygen
generated
by
electrolysis
is
not
fully
utilized.
Therefore,
this
study
proposes
a
low-carbon
economic
dispatch
model
considering
utilization
hydrogen
energy.
First,
two-stage
reaction
established,
paths
blending
oxygen-rich
deep
peaking
are
proposed.
Specifically,
blended
into
grid
supply
gas-fired
units,
assists
units
peaking.
Subsequently,
stochastic
optimization
used
deal
with
uncertainty
system,
objective
function
constraints
IES
given
establish
under
model.
Finally,
effectiveness
proposed
method
verified
based
on
modified
IEEE
39-node
electric
network,
20-node
network
6-node
heat
models.
International Journal of Electrical Power & Energy Systems,
Journal Year:
2024,
Volume and Issue:
156, P. 109777 - 109777
Published: Jan. 6, 2024
This
paper
proposes
the
research
on
dimension
reduction
for
visualization
of
simplified
security
region
integrated
energy
system
considering
renewable
access.
Reason:
Integrated
is
conducive
to
achieving
low-carbon
transition
and
efficient
utilization
energy.
As
penetration
increases,
faces
severe
challenges.
It
holds
significance
comprehensively
studying
N-1
test
method
in
operation
scenario
system,
impact
IES
model,
optimal
selection
observation
variables.
Methods:
Firstly,
a
model
interval
constructed,
according
safety
constraints
hub
key
equipment
pipeline.
The
imbalance
between
demand
supply
caused
by
uncertainty
defined
as
special
fault.
Then,
an
engineering
simplification
approach
proposed,
order
quantify
boundary,
distance,
total
capability.
On
basis,
based
variable
optimization
variables
help
expand
volume
area
unaffected
uncertainty.
Results:
To
existed
problem
current
research,
example
presented
verify
effectiveness
proposed
method,
which
brings
forward
analyzes
realizes
region.
Conclusions:
Interval
can
intuitively
estimate
status
operating
points
observe
boundaries.
satisfy
needs
calculating
precision.
Optimal
necessary,
be
effectively
increased.
International Journal of Electrical Power & Energy Systems,
Journal Year:
2024,
Volume and Issue:
158, P. 109942 - 109942
Published: March 22, 2024
In
this
work,
a
day-ahead
dispatch
optimization
model
with
energy-type,
power-type,
and
composite-type
energy
storage
systems
(ESSs)
is
established
to
participate
in
multiple
frequency
control
ancillary
services
(FCASs),
wind-energy-integrated
power
systems.
This
designed
better
handle
the
operational
uncertainties
of
wind
energy,
mitigate
risks
reduce
carbon
emissions.
Leveraging
complementary
features
different
types
ESSs,
proposed
operation
strategies
regulation
units
can
respond
FCASs
achieve
optimal
task
allocation
among
resources.
Various
uncertainty
handling
approaches
are
adopted
cope
randomness
step
disturbances
fluctuations.
Furthermore,
new
environmental
factor
devised
objective
time-of-use
carbon-price
emission
trading
(ToU-CET)
ladder-type
CET
(LT-CET)
models
developed.
They
incorporate
dynamic
prices
leverage
mechanisms
emissions
during
daily
operations.
The
effectiveness
verified
by
case
studies,
decisions
help
save
modern
generators
high
security
reliability.
International Journal of Low-Carbon Technologies,
Journal Year:
2025,
Volume and Issue:
20, P. 384 - 393
Published: Jan. 1, 2025
Abstract
To
improve
the
low-carbon
economic
dispatch,
we
introduced
a
big
data
twin
recombination
network
for
grid
dispatch
decision
optimization.
quantified
energy
structure
and
corrected
linear
regression
of
power
loads
to
boost
efficiency,
optimized
correlation
between
scheduling
generation
facilities
operational
strategies
by
mapping
decomposing,
expediting
cyclic
relevance
model.
Results
demonstrated
that
our
method
can
optimize
decision-making
establish
reliable
analysis
models
concerning
carbon
emissions,
costs,
utilization
load
matching
precision.
International Journal of Electrical Power & Energy Systems,
Journal Year:
2024,
Volume and Issue:
157, P. 109840 - 109840
Published: Feb. 6, 2024
The
task
of
carbon
emission
reduction
is
severe
in
the
power
industry
China
under
national
goal
"carbon
peaking
and
neutrality".
current
mainly
based
on
supply
side,
but
effect
limited.
To
solve
this
problem,
paper
proposed
a
coordinated
supply–demand
strategy
blockchain
technology.
Based
complementary
thermal
renewable
energy
trading
mechanism
users
are
made
to
participate
individual
level
with
help
technology,
demand
side
guided
through
market
mechanism,
thus
forming
collaborative
source
control
terminal
inhibition.
By
analyzing
decision
changes
both
sides
electricity
before
after
introduction
blockchain,
quantifying
influence
quantity,
price
users'
utility
turn,
establishing
personal
supported
by
game
model
two-side
interaction
between
was
constructed.
simulation
results
show
that
gives
full
play
potential
can
better
inhibit
emissions,
which
conducive
deep
industry.
