Modeling time-varying wide-scale distributed denial of service attacks on electric vehicle charging Stations

Aljohani, Tawfiq; Almutairi, Abdulaziz

doi:10.1016/j.asej.2024.102860

Cited by 4 publications

(1 citation statement)

References 33 publications

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“…As cyberattacks against energy infrastructures have significantly increased in recent years to advance political, social, or financial agendas, the cybersecurity of energy systems has become a central topic in research recently [45,46]. Intelligent FLCs can be leveraged to enhance the security of energy infrastructures against cyber threats such as Distributed Denial of Service (DDoS) attacks, a form of cyber threat that can successfully paralyze charging stations [47]. For instance, intelligent FLCs can monitor and respond to abnormal traffic patterns indicative of a DDoS attack targeting EV charging stations, thereby protecting the grid from disruptions.…”

Section: Discussionmentioning

confidence: 99%

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

Aljohani

2024

Energies

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The rapid integration of renewable energy sources (RES) and the electrification of transportation have significantly transformed modern energy infrastructures, emphasizing the need for efficient and flexible energy management systems. This study presents an intelligent, variable-fed, Type-2 Fuzzy Logic Controller (IT2FLC) designed for optimal management of Hybrid Microgrid (HMG) energy systems, specifically considering different modes of Electric Vehicles (EVs) integration. The necessity of this study arises from the challenges posed by fluctuating renewable energy outputs and the uncoordinated charging practices of EVs, which can lead to grid instability and increased operational costs. The proposed IT2FLC is based on comprehensive mathematical modeling that captures complex interactions among HMG components, including Doubly Fed Induction Generator (DFIG) units, photovoltaic (PV) systems, utility AC power, and EV batteries. Utilizing a yearly dataset for simulation, this work examines the HMG’s flexibility and adaptability under dynamic conditions managed by the proposed intelligent controller. A Simulink-based model is built for this study to replicate the dynamical operation of the HMG and test the precise and real-time decision-making capability of the proposed IT2FLC. The results demonstrate the IT2FLC’s superior performance, achieving a substantial cost avoidance of nearly $3,750,000 and efficient energy balance, affirming its potential to sustain optimal energy utilization under stochastic conditions. Additionally, the results attest that the proposed IT2FLC significantly enhances the resilience and economic feasibility of hybrid microgrids, achieving a balanced energy exchange with the utility grid and efficient utilization of EV batteries, proving to be a superior solution for optimal operation of hybrid grids.

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Section: Discussionmentioning

confidence: 99%

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

Aljohani

2024

Energies

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A comprehensive survey of cyberattacks on EVs: Research domains, attacks, defensive mechanisms, and verification methods

Aljohani,

Almutairi

2024

Defence Technology

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Multilayer Iterative Stochastic Dynamic Programming for Optimal Energy Management of Residential Loads with Electric Vehicles

Aljohani

2024

International Journal of Energy Research

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This work introduces a multilayer iterative stochastic dynamic programing (MISDP) framework for optimizing energy management in smart residential settings, incorporating electric vehicles to reduce energy costs while enhancing operational efficiency. The study investigates the complexities of managing residential loads with integrated EV batteries, set against the backdrop of unpredictable charging demands and fluctuating energy prices. The proposed method is designed to optimize charging and discharging schedules, ensuring cost‐effective energy consumption without compromising the longevity of EV’s battery operations. The proposed MISDP strategy encompasses multi‐iteration processes, both at internal and external levels, that not only highlight the method’s capacity for precise, real‐time decision‐making but also underscore its adaptability to the dynamic nature of energy systems. The external iteration primarily focuses on adapting to broader operational variables, such as fluctuating prices and demand patterns, setting a framework for optimization. Concurrently, the internal iteration updates the details of EV battery operation, fine‐tuning charging and discharging strategies to refine the control law sequence for each operational period, ensuring optimal energy management. Throughout the iteration process, the framework ensures the performance index function remains bounded, adhering strictly to the evolving control law sequence. Through comparative analysis, the MISDP framework is evaluated against different optimization techniques, demonstrating its superior capability in achieving significant energy cost savings and operational effectiveness while ensuring convergence under stochastic conditions.

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Modeling time-varying wide-scale distributed denial of service attacks on electric vehicle charging Stations

Cited by 4 publications

References 33 publications

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

A comprehensive survey of cyberattacks on EVs: Research domains, attacks, defensive mechanisms, and verification methods

Multilayer Iterative Stochastic Dynamic Programming for Optimal Energy Management of Residential Loads with Electric Vehicles

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