Demand Response-based Multi-Layer Peer-to-Peer Energy Trading Strategy for Renewable-powered Microgrids with Electric Vehicles
Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 135206 - 135206
Published: Feb. 1, 2025
Language: Английский
Game theory-based peer-to-peer energy storage sharing for multiple bus charging stations: A real-time distributed cooperative framework
Journal of Energy Storage,
Journal Year:
2025,
Volume and Issue:
109, P. 115148 - 115148
Published: Jan. 1, 2025
Language: Английский
Optimal sizing and operation of microgrid considering renewable energy uncertainty based on scenario generation
Dingding Hu,
No information about this author
Yinchao Fan,
No information about this author
Wenbin Shao
No information about this author
et al.
Journal of Energy Storage,
Journal Year:
2024,
Volume and Issue:
109, P. 115174 - 115174
Published: Dec. 30, 2024
Language: Английский
Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 18, 2025
Electric
Vehicle
Charging
Station
(EVCS)
security
is
a
growing
concern
in
today's
connected
world
due
to
the
complexity
and
frequency
of
cyber
threats.
Traditional
Intrusion
Detection
Systems
(IDS)
for
EV
chargers
struggle
detect
novel
or
unexpected
attacks
their
usage
predetermined
signatures
limited
detection
capabilities.
Existing
charging
station
systems
are
unable
identify
many
known
undiscovered
threats
since
they
primarily
rely
on
feature
selection
categorization
accuracy.
It
common
these
be
constructed
using
conventional
machine
learning
algorithms.
So
signs
ignored.
This
paper
proposes
Transfer
(TL)
framework
cyber-physical
attack
EVCS
order
overcome
difficulties
improve
both
accuracy
scalability.
The
weights
preserved
from
Deep
Neural
Network
(DNN)
model
after
implementing
data
normalization
min-max
scaling
techniques
utilized
training
used
initialize
new
termed
Learning.
study
also
provides
comparison
with
different
DL
models
such
as
Long
Short-Term
Memory
(LSTM),
Recurrent
Networks
(RNN),
Memory-Recurrent
(LSTM-RNN),
Gated
Unit
(GRU).
CICEVSE2024
(EVSE-A
EVSE-B)
datasets
assess
framework,
where
one
dataset
train
store
weights,
second
evaluate
learned
patterns
transfer
learning.
Several
evaluation
matrices
suggested
model.
experimental
results
demonstrate
that
TL
attained
93%
Consequently,
pre-train
high
degree
symmetry
between
malicious
attacks.
Language: Английский
Short-Term and Probability Scenario-Oriented Energy Management of Integrated Energy Distribution Systems with Considering Energy Market Interactions and End-User Participation
Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 135691 - 135691
Published: March 1, 2025
Language: Английский
Cyberspace enhancement of electric vehicle charging stations in smart grids based on detection and resilience measures against hybrid cyberattacks: A multi-agent deep reinforcement learning approach
Ali Rashid Ramul,
No information about this author
Atefeh Salimi Shahraki,
No information about this author
Naseer K. Bachache
No information about this author
et al.
Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 136038 - 136038
Published: April 1, 2025
Language: Английский
Hierarchical integrated energy system management considering energy market, demand response and uncertainties: A robust optimization approach
Saied Iranpour Mobarakeh,
No information about this author
Ramtin Sadeghi,
No information about this author
Hadi Saghafi
No information about this author
et al.
Computers & Electrical Engineering,
Journal Year:
2025,
Volume and Issue:
123, P. 110138 - 110138
Published: March 26, 2025
Language: Английский
Hybrid energy storage unit fed motoring and regenerative braking control of electric vehicle drivetrain
Journal of Power Sources,
Journal Year:
2024,
Volume and Issue:
626, P. 235761 - 235761
Published: Nov. 11, 2024
Language: Английский
Dynamic Energy Management and Control of Networked Microgrids based on Load to Grid Services and Incentive-Based Demand Response Programs: A Multi-Agent Deep Reinforcement Learning Approach
Sustainable Cities and Society,
Journal Year:
2024,
Volume and Issue:
117, P. 105957 - 105957
Published: Nov. 3, 2024
Language: Английский