Journal of Energy Storage,
Journal Year:
2023,
Volume and Issue:
69, P. 107795 - 107795
Published: June 8, 2023
Battery
energy
storage
systems
(BESSs)
play
a
key
role
in
the
renewable
transition.
Meanwhile,
BESSs
along
with
other
electric
grid
components
are
leveraging
Internet-of-things
paradigm.
As
downside,
they
become
vulnerable
to
cyberattacks.
The
detection
of
cyberattacks
against
is
becoming
crucial
for
system
redundancy.
We
identified
gap
existing
BESS
defense
research
and
formulated
new
types
attacks
their
methods.
attack
divided
into
forecast-based
approach
long-term
pattern
analysis.
perform
main
factor
analysis
machine-learning-based
methods
forecast
behavior
BESS.
In
addition,
we
observe
approaches
that
can
be
adapted
cyber
secure
design.
To
provide
thorough
investigation,
classified
based
on
targeted
battery
service
data
features
targets.
Journal of Energy Resources Technology,
Journal Year:
2024,
Volume and Issue:
146(9)
Published: May 10, 2024
Abstract
The
issues
in
integrating
renewable
energy
sources
(RES)
into
distribution
grid
structures
are
thoroughly
examined
this
research.
It
highlights
how
important
integration
is
to
updating
the
system
and
attaining
environmental
goals.
study
explores
specific
problems
confronted
by
means
of
on-grid
power
structures,
along
with
overall
performance
metrics
compatibility
issues.
Additionally,
it
presents
a
thorough
assessment
attributes
various
RES
hybrid
systems,
together
technology
from
fields
solar,
wind,
batteries,
biomass.
To
be
able
spotlight
significance
innovative
solutions
inside
dispersed
environment,
combined
heat
investigated.
This
addresses
numerous
better
comprehend
their
intricacies.
viability
supported
real-world
case
studies
that
provide
operational
examples
generation
systems.
concludes
discussing
technical,
financial,
grid-related
associated
distributed
generating
systems'
limits
highlighting
contribution
cutting-edge
artificial
intelligence
removal.
In
conclusion,
report
development
toward
smarter
grids
improved
capacities
as
essential
component
robust
sustainable
future.
Energies,
Journal Year:
2024,
Volume and Issue:
17(1), P. 254 - 254
Published: Jan. 3, 2024
The
rapid
advancement
in
technology
and
rise
energy
consumption
have
motivated
research
addressing
Demand-Side
Management
(DSM).
In
this
research,
a
novel
design
for
Home
Energy
(HEM)
is
proposed
that
seamlessly
integrates
Battery
Storage
Systems
(BESSs),
Photovoltaic
(PV)
installations,
Electric
Vehicles
(EVs).
Leveraging
Mixed-Integer
Linear
Programming
(MILP)
approach,
the
system
aims
to
minimize
electricity
costs.
optimization
model
takes
into
account
Real-Time
Pricing
(RTP)
tariffs,
facilitating
efficient
scheduling
of
household
appliances
optimizing
patterns
BESS
charging
discharging,
as
well
EV
discharging.
Both
individual
multiple
Smart
(SH)
case
studies
showcase
noteworthy
reductions
SHs,
remarkable
cost
reduction
46.38%
was
achieved
compared
traditional
SH
scenario
lacking
integration
PV,
BESS,
EV.
Electronics,
Journal Year:
2023,
Volume and Issue:
12(4), P. 797 - 797
Published: Feb. 5, 2023
The
modern
smart
grid
(SG)
is
mainly
a
cyber-physical
system
(CPS),
combining
the
traditional
power
infrastructure
with
information
technologies.
SG
frequently
threatened
by
cyber
attacks
such
as
False
Data
Injection
(FDI),
which
manipulates
states
of
systems
adding
malicious
data.
To
maintain
reliable
and
secure
operation
grid,
it
crucial
to
detect
FDI
in
along
their
exact
location.
conventional
Bad
Detection
(BDD)
algorithm
cannot
stealthy
attacks.
So,
motivated
most
recent
deep
learning
(DL)
developments
data-driven
solutions,
new
transformer-based
model
named
XTM
proposed
identify
locations
data
intrusions
real-time
scenarios.
XTM,
combines
transformer
long
short-term
memory
(LSTM),
first
hybrid
DL
that
explores
performance
transformers
this
particular
research
field.
First,
threshold
selection
scheme
introduced
presence
FDI,
replacing
need
for
BDD.
Then,
intrusion
point
attack
located
using
multilabel
classification
approach.
A
formally
verified
constraints
satisfaction-based
vector
was
used
manipulate
set.
In
work,
considering
temporal
nature
system,
both
hourly
minutely
sensor
are
train
evaluate
IEEE-14
bus
achieving
detection
accuracy
almost
100%.
row
(RACC)
metric
also
evaluated
location
module,
values
92.99%
99.99%
datasets,
respectively.
Moreover,
technique
compared
other
models
well,
showing
outperforms
state-of-the-art
methods
mentioned
literature.
Journal of Energy Storage,
Journal Year:
2023,
Volume and Issue:
69, P. 107795 - 107795
Published: June 8, 2023
Battery
energy
storage
systems
(BESSs)
play
a
key
role
in
the
renewable
transition.
Meanwhile,
BESSs
along
with
other
electric
grid
components
are
leveraging
Internet-of-things
paradigm.
As
downside,
they
become
vulnerable
to
cyberattacks.
The
detection
of
cyberattacks
against
is
becoming
crucial
for
system
redundancy.
We
identified
gap
existing
BESS
defense
research
and
formulated
new
types
attacks
their
methods.
attack
divided
into
forecast-based
approach
long-term
pattern
analysis.
perform
main
factor
analysis
machine-learning-based
methods
forecast
behavior
BESS.
In
addition,
we
observe
approaches
that
can
be
adapted
cyber
secure
design.
To
provide
thorough
investigation,
classified
based
on
targeted
battery
service
data
features
targets.
