Impact of Artificial Intelligence on the Planning and Operation of Distributed Energy Systems in Smart Grids
Energies,
Год журнала:
2024,
Номер
17(17), С. 4501 - 4501
Опубликована: Сен. 8, 2024
This
review
paper
thoroughly
explores
the
impact
of
artificial
intelligence
on
planning
and
operation
distributed
energy
systems
in
smart
grids.
With
rapid
advancement
techniques
such
as
machine
learning,
optimization,
cognitive
computing,
new
opportunities
are
emerging
to
enhance
efficiency
reliability
electrical
From
demand
generation
prediction
flow
optimization
load
management,
is
playing
a
pivotal
role
transformation
infrastructure.
delves
deeply
into
latest
advancements
specific
applications
within
context
systems,
including
coordination
resources,
integration
intermittent
renewable
energies,
enhancement
response.
Furthermore,
it
discusses
technical,
economic,
regulatory
challenges
associated
with
implementation
intelligence-based
solutions,
well
ethical
considerations
related
automation
autonomous
decision-making
sector.
comprehensive
analysis
provides
detailed
insight
how
reshaping
grids
highlights
future
research
development
areas
that
crucial
for
achieving
more
efficient,
sustainable,
resilient
system.
Язык: Английский
Data preprocessing and machine learning method based on ameliorated mathematical models for inferring the power generation of photovoltaic system
Energy Conversion and Management,
Год журнала:
2025,
Номер
333, С. 119793 - 119793
Опубликована: Апрель 12, 2025
Язык: Английский
Renewable-Energy-Based EV Charging Infrastructures
Studies in Infrastructure and Control,
Год журнала:
2025,
Номер
unknown, С. 71 - 86
Опубликована: Янв. 1, 2025
Язык: Английский
Solving multi-objective probabilistic optimal power flow with renewable energy sources and Battery energy storage in transmission networks using Quasi Oppositional Sine Cosine algorithm
Journal of Energy Storage,
Год журнала:
2025,
Номер
122, С. 116411 - 116411
Опубликована: Апрель 16, 2025
Язык: Английский
Multi-objective Optimization of Power Networks Integrating Electric Vehicles and Wind Energy
Intelligent Systems with Applications,
Год журнала:
2024,
Номер
unknown, С. 200452 - 200452
Опубликована: Окт. 1, 2024
Язык: Английский
Innovative Photovoltaic-Aeration Integration: Enhancing Energy Efficiency and Grid Stability in Wastewater Treatment
Journal of energy resources technology.,
Год журнала:
2024,
Номер
1(3)
Опубликована: Дек. 6, 2024
Abstract
This
paper
presents
a
detailed
investigation
into
enhancing
the
energy
efficiency
of
wastewater
treatment
plants
(WWTPs)
by
integrating
photovoltaic
(PV)
systems,
emphasizing
power
flow
analysis
and
experimental
validation.
Recognizing
substantial
demands
aeration
processes
in
WWTPs,
this
study
proposes
an
innovative
integration
PV
panels
with
tanks.
approach
generates
renewable
optimizes
use
through
thermal
interaction
between
Key
findings
demonstrate
15%
overall
increase
5%
improvement
due
to
aeration-induced
cooling,
along
reduction
voltage
fluctuations
up
30%
during
high-demand
periods.
Additionally,
offsets
approximately
20%
WWTP's
total
consumption.
The
research
is
structured
two
main
components:
comprehensive
using
digsilent
powerfactory
laboratory
experiment
validate
integration's
effectiveness.
evaluates
electrical
impact
on
grid,
focusing
scenarios
such
as
load
fluctuations,
grid
disturbances,
synchronization
generation
plant
needs.
simulation
results
indicate
that
significantly
enhances
stability
plant's
system,
reducing
reliance
traditional
sources.
Concurrently,
explored
practical
effects
systems
demonstrated
cooling
effect
provided
tanks
leads
increased
notable
savings.
These
align
findings,
confirming
efficacy
integrated
approach.
introduces
novel
methodology
for
technologies
industrial
processes,
showcasing
potential
significant
savings
improved
operational
WWTPs.
Future
will
focus
scaling
strategy
assessing
its
long-term
impacts
Язык: Английский
Advanced Energy Management in a Sustainable Integrated Hybrid Power Network Using a Computational Intelligence Control Strategy
Energies,
Год журнала:
2024,
Номер
17(20), С. 5040 - 5040
Опубликована: Окт. 10, 2024
The
primary
goal
of
a
power
distribution
system
is
to
provide
nominal
voltages
and
with
minimal
losses
meet
consumer
demands
under
various
load
conditions.
In
the
system,
loss
voltage
uncertainty
are
common
challenges.
However,
these
issues
can
be
resolved
by
integrating
distributed
generation
(DG)
units
into
network,
which
improves
overall
quality
network.
If
DG
unit
an
appropriate
size
not
inserted
at
location,
it
might
have
adverse
impact
on
system’s
operation.
Due
arbitrary
incorporation
units,
some
occur
such
as
more
fluctuations
in
voltage,
losses,
instability,
been
observed
networks
(DNs).
To
address
problems,
essential
optimize
placement
sizing
balance
variations,
reduce
improve
stability.
An
efficient
reliable
strategy
always
required
for
this
purpose.
Ensuring
stable,
safer,
dependable
operation
requires
careful
examination
optimal
location
when
integrated
As
result,
should
most
way
possible
enhance
dependability,
quality,
performance
reducing
improving
profile.
order
using
integration,
there
several
optimization
techniques
take
consideration.
Computational-intelligence-based
one
best
options
finding
solution.
research
work,
computational
intelligence
approach
proposed
find
sizes
placements
newly
introduced
different
types
DGs
network
optimized
multi-objective
framework.
This
framework
prioritizes
stability,
minimizes
profiles.
method
simple,
robust,
efficient,
converges
faster
than
conventional
techniques,
making
powerful
tool
inspiration
optimization.
check
validity
technique
standard
IEEE
14-bus
30-bus
benchmark
test
systems
considered,
feasibility
analyzed
tested
them.
Detailed
simulations
performed
“MATLAB”,
results
show
that
enhances
efficiently
compared
methods.
Язык: Английский