83 research outputs found
Software Defined Networks based Smart Grid Communication: A Comprehensive Survey
The current power grid is no longer a feasible solution due to
ever-increasing user demand of electricity, old infrastructure, and reliability
issues and thus require transformation to a better grid a.k.a., smart grid
(SG). The key features that distinguish SG from the conventional electrical
power grid are its capability to perform two-way communication, demand side
management, and real time pricing. Despite all these advantages that SG will
bring, there are certain issues which are specific to SG communication system.
For instance, network management of current SG systems is complex, time
consuming, and done manually. Moreover, SG communication (SGC) system is built
on different vendor specific devices and protocols. Therefore, the current SG
systems are not protocol independent, thus leading to interoperability issue.
Software defined network (SDN) has been proposed to monitor and manage the
communication networks globally. This article serves as a comprehensive survey
on SDN-based SGC. In this article, we first discuss taxonomy of advantages of
SDNbased SGC.We then discuss SDN-based SGC architectures, along with case
studies. Our article provides an in-depth discussion on routing schemes for
SDN-based SGC. We also provide detailed survey of security and privacy schemes
applied to SDN-based SGC. We furthermore present challenges, open issues, and
future research directions related to SDN-based SGC.Comment: Accepte
Deep Learning Based Proactive Optimization for Mobile LiFi Systems with Channel Aging
This paper investigates the channel aging problem of mobile light-fidelity
(LiFi) systems. In the LiFi physical layer, the majority of the optimization
problems for mobile users are non-convex and require the use of dual
decomposition or heuristics techniques. Such techniques are based on iterative
algorithms, and often, cause a high processing delay at the physical layer.
Hence, the obtained solutions are no longer optimal since the LiFi channels are
evolving. In this paper, a proactive-optimization (PO) approach that can
alleviate the LiFi channel aging problem is proposed. The core idea is to
design a long-short-term-memory (LSTM) network that is capable of predicting
posterior positions and orientations of mobile users, which can be then used to
predict their channel coefficients. Consequently, the obtained channel
coefficients can be exploited to derive near-optimal transmission-schemes prior
to the intended service-time, which enables real-time service. Through various
simulations, the performance of the designed LSTM model is evaluated in terms
of prediction error and time, as well as its application in a practical LiFi
optimization problem
Dynamic Load Altering EV Attacks Against Power Grid Frequency Control
Driven by the necessity to combat climate change, Electric Vehicles (EV) are
being deployed to take advantage of their ability in reducing emissions
generated by the transportation sector. This deployment has left the power grid
vulnerable to attacks through the EV infrastructure. This paper is written from
an attacker\'s perspective and proposes a dynamic load altering strategy
through manipulating EV charging to destabilize the grid. The attack is
formulated based on feedback control theory, i.e., designing an attack based on
Linear Matrix Inequalities (LMIs). After the stability metric and controller
design have been established, we demonstrate our attack method against the
Kundur 2 area grid. The attack scenario includes a cap of 200 MW EV load
controlled by the attacker. However, the results show that even with this
limitation, the attacker would be successful in pushing the grid toward
instability and blackout.Comment: "\c{opyright} 2022 IEEE. Personal use of this material is permitted.
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