In
order
to
establish
a
feasible
trading
framework
between
the
energy
supply
and
demand
sides
within
multi-virtual
power
plants
(MVPP)
explore
potential
of
low-carbon
operation.
Based
on
cooperative
game
theory,
this
paper
studies
MVPP
problem
interaction
involving
virtual
plant
(VPP)
operators
load
aggregator
(LA).
Additionally,
it
investigates
capacity
integrated
hydrogen
utilization
system
that
include
natural
gas
doping.
Firstly,
dual
model
VPPs
LA
are
proposed.
Secondly,
for
single
VPP,
multi-energy
collaboration
VPP
considering
doping
is
constructed.
The
non-convex
nonlinear
decomposed
into
two
subproblems
distributed
by
alternating
direction
multiplier
method
(ADMM)
effectively
protect
privacy
each
participant.
simulation
results
show
enhances
comprehensive
utility
users,
facilitates
complementarity
MVPP.
Furthermore,
higher
ratio
units
under
operation,
better
performance
system.
2022 7th Asia Conference on Power and Electrical Engineering (ACPEE),
Год журнала:
2024,
Номер
unknown, С. 301 - 310
Опубликована: Апрель 11, 2024
In
the
context
of
new
power
system,
virtual
plants
participate
in
various
market-oriented
transactions
by
integrating
distributed
energy
resources,
storage
devices
and
adjustable
loads,
use
price
mechanism
to
ensure
security.
This
paper
proposes
a
two-stage
bidding
model
for
plant
(VPP)
under
joint
electricity-carbon
market.
First,
VPP
submits
day-ahead
market
strategy
dispatching
agency
Phase
1,
considering
impact
electric
vehicles
incentive-based
demand
responses.
Subsequently,
auction
results
1
are
transferred
2,
carbon
green
certificate
revenue
on
plants,
real-time
strategies
formulated
time-by-time
basis.
Finally,
CPLEX
solver
is
used
solve
constructed
mixed
integer
linear
programming
problem.
The
simulation
Lingang
area
Pudong,
Shanghai,
shows
that
can
maximize
benefits
minimize
cost
process
market,
meet
environmental
protection
sustainability
goals.
It
provides
basis
building
business
with
as
core.
Frontiers in Energy Research,
Год журнала:
2024,
Номер
12
Опубликована: Окт. 29, 2024
Compared
to
traditional
resources,
user-side
resources
are
of
various
types
and
have
more
significant
uncertainty
about
their
regulatory
capacity,
leading
difficulties
in
coordinating
decisions
simultaneous
participation
the
electric
energy
peaking
ancillary
services
markets.
This
paper
proposes
a
joint
bidding
decision-making
method
for
day-ahead
electricity
peak
shaving
auxiliary
service
market
based
on
distributed
robust
opportunity
constraints,
which
addresses
problem
difficulty
using
an
accurate
probability
density
distribution
represent
process
resources.
Firstly,
data-driven
characterizing
load
regulation
capacity
is
investigated,
fuzzy
sets
constructed
without
assuming
specific
distributions
random
variables.
Then,
minimize
risk
expectation
cost
customer
side,
strategy
that
considers
proposed.
Finally,
example
simulation
verifies
reasonableness
effectiveness
proposed
method,
results
show
model
overcomes
over-conservatism
model,
computational
adaptability
better
than
stochastic
achieves
balance
between
robustness
economy.
