A Novel ALTSRCFNN-STSMC Approach for Enhancing Ride-Through in Hybrid Renewable Systems
Abstract
This
paper
proposes
an
innovative
Adaptive
Least
Squares
Recursive
Chebyshev
Fuzzy
Neural
Network
(ALTSRCFNN)
combined
with
Super-Twisting
Sliding-Mode
Control
(STSMC)
for
improving
the
low-voltage
ride-through
(LVRT)
capability
and
stability
of
hybrid
generation
systems
(HGS)
under
grid
faults.
The
integration
Static
Synchronous
Compensators
(STATCOM)
enhances
system
robustness
by
mitigating
oscillations
stabilizing
bus
voltage
during
transient
conditions.
Simulation
results
demonstrate
that
proposed
method
significantly
outperforms
conventional
PID
controllers
other
neural
network-based
methods
in
terms
accuracy,
response
speed,
regulation.
ALTSRCFNN-STSMC
effectively
reduces
fluctuations,
restores
steady-state
conditions
within
shorter
timeframes,
ensures
sufficient
active
reactive
power
delivery
various
environmental
These
findings
indicate
approach’s
potential
practical
applications
modern
systems,
particularly
addressing
challenges
renewable
energy
integration.
Research Square (Research Square), Год журнала: 2025, Номер unknown
Опубликована: Фев. 11, 2025
Язык: Английский