Steady-state analysis of parallel-connected self-excited induction generators with hybrid excitation using fixed-point iteration method
COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 18, 2025
Purpose
This
study
aims
to
present
a
comprehensive
steady-state
analysis
of
parallel-connected
self-excited
induction
generators
(SEIGs)
with
hybrid
excitation,
addressing
critical
challenges
in
voltage
stability
and
power
quality
for
renewable
energy
applications.
Design/methodology/approach
The
research
uses
mathematical
modeling
approach
based
on
the
equivalent
circuit
model,
transforming
excitation
system
into
an
star
configuration
simplify
analysis.
fixed-point
iteration
method
(FPIM)
is
implemented
solve
system’s
nonlinear
equations
through
systematic
convergence
stages,
requiring
250–300
iterations
O(n)
computational
complexity
solution.
methodology
integrates
magnetizing
characteristics,
terminal
regulation
current
distribution
SEIGs.
analytical
framework
experimentally
validated
using
test
setup
two
SEIGs
(2.2
kW
5.5
kW)
under
conditions.
Findings
improves
from
−8.4%
0%,
SEIG
delivering
5,510
W
while
maintaining
50
Hz
±
0.2%
frequency
stability.
Current
shows
11.1
A
4.8
2.2
SEIG,
stabilizing
at
415
V
2%.
achieves
40%
reduction
neutral
compared
conventional
configurations,
factor
optimization
between
0.92
0.95.
Research
limitations/implications
Future
could
explore
dynamic
performance
transient
conditions
further
enhance
reliability,
regulation,
load
sharing,
stability,
grid
integration
methodologies.
Originality/value
provides
novel
contribution
by
integrating
SEIGs,
offering
detailed
their
behavior
various
findings
superior
over
Newton–Raphson
(500+
iterations)
binary
search
(400–450
handling
unbalanced
loads
up
30%
variation.
Language: Английский
Multiple firing patterns, energy conversion and hardware implementation within Hindmarsh-Rose-improved neuron model
Physica Scripta,
Journal Year:
2024,
Volume and Issue:
99(5), P. 055265 - 055265
Published: April 25, 2024
Abstract
The
transmission
of
information
between
neurons
is
accomplished
in
living
organisms
through
synapses.
memristor
an
electronic
component
that
simulates
the
tunability
strength
biological
synaptic
connections
artificial
neural
networks.
This
article
constructs
a
novel
type
locally
active
and
verifies
by
nonlinear
theoretical
analysis,
analysis
circuit
simulation.
designed
simulated
as
autapse
Hindmarsh-Rose(HR)
neuron
to
obtain
improved
HR
model
memristive
autapse,
Hamilton
energy
obtained
according
Helmholtz
theorem.
By
varying
external
forcing
current
strength,
this
analyses
changes
explores
its
self-excited
hidden
firing
behavior.
analog
simulation
digital
implementation
confirm
consistency
mathematical
actual
behavior,
which
can
advance
field
neuroscience
intelligence.
Language: Английский