Cyber-physical modeling and control of smart grids - a new paradigm

Shahid, Ahsan

doi:10.1109/isgt.2016.7781279

Cited by 13 publications

(4 citation statements)

References 8 publications

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“…Hybrid systems are widely applied in industries such as aerospace, energy systems, and industrial control to achieve various objectives by using feedback functions from a specific family [41] . A methodology for developing and accessing a supervisory hybrid control scheme for a microgrid system is presented in [41] , using a specialized configuration that includes wind power conversion technology [42,43] . The microgrid system is represented as a probabilistic hybrid system with many functions for energy management, as depicted in [44] .…”

Section: Research Backgroundmentioning

confidence: 99%

“…Several research possibilities exist to develop antennas with better radiation qualities and innovative ways for producing circular polarization radiation with a broad ARBW that is small in size and covers all necessary bands, as covered in [120]. In [41], the author highlighted a significant advancement approaching the potential implementation of smart grids., operating as a composite system based on cyber-physical concepts. The suggested modeling technique proposes an active paradigm for the management construction of complicated energy systems, aiming to help the environment, technical performance, and economic value.…”

Section: Research Backgroundmentioning

confidence: 99%

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A Review on the Evaluation of Feature Selection Using Machine Learning for Cyber-Attack Detection in Smart Grid

Mohammed,

Al-Jumaily,

Singh

et al. 2024

IEEE Access

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The Smart Grid is a modern power grid that relies on advanced technologies to provide reliable and sustainable electricity. However, its integration with various communication technologies and IoT devices makes it vulnerable to cyber-attacks. Such attacks can lead to significant damage, economic losses, and public safety hazards. To ensure the security of the smart grid, increasingly strong security solutions are needed. This paper provides a comprehensive analysis of the vulnerabilities of the smart grid and the different approaches for detecting cyber-attacks. It examines the different vulnerabilities of the smart grid, including system vulnerabilities and cyber-attacks, and discusses the vulnerabilities of all its elements. The paper also investigates various approaches for detecting cyber-attacks, including rule-based, signature-based, anomaly detection, and ma-chine learning-based methods, with a focus on their effectiveness and related research. Finally, prospective cybersecurity approaches for the smart grid, such as AI approaches and blockchain, are discussed along with the challenges and future prospects of cyberattacks on the smart grid. The paper's findings can help policymakers and stakeholders make informed decisions about the security of the smart grid and develop effective strategies to protect it from cyber-attacks.

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Section: Research Backgroundmentioning

confidence: 99%

Section: Research Backgroundmentioning

confidence: 99%

A Review on the Evaluation of Feature Selection Using Machine Learning for Cyber-Attack Detection in Smart Grid

Mohammed,

Al-Jumaily,

Singh

et al. 2024

IEEE Access

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“…Cyber-physical systems combine physical process dynamics with computation such as from software and communications; this integration enables comprehensive modeling, design, and analysis for the entire system [12]. Since the electric grid is increasingly more connected in cyberspace, as networking and computing devices are used to provided added functionality through smart grid technologies and other advancements, it is important to understand the intricacies and interactions between the cyber and physical components of the system [13][14][15].…”

Section: Network Communications In a Cyber-physical System: Propertie...mentioning

confidence: 99%

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

2021

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The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

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“…A smart grid possesses all the essential characteristics of a CPS [3], [4]. In terms of concepts, a roadmap is given in [5], and the frame and annotation of smart grid CPS are presented in [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Cyber-physical Power System Modeling for Timing-driven Control of Active Distribution Network

Wang

Liu

et al. 2020

Journal of Modern Power Systems and Clean Energy

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In a cyber-physical power system, active distribution network (ADN) facilitates the energy control through hierarchical and distributed control system (HDCS). Various researches have dedicated to develop the control strategies of primary devices of ADN. However, an ADN demonstration project shows that the information transmission of HDCS may cause time delay and response lag, and little model can describe both the ADN primary device and HDCS as a cyber-physical system (CPS). In this paper, a hybrid system based CPS model is proposed to describe ADN primary devices, control information flow, and HDCS. Using the CPS model, the energy process of primary devices and the information process of HDCS are optimized by model predictive control (MPC) methodology to seamlessly integrate the energy flow and the information flow. The case study demonstrates that the proposed CPS model can accurately reflect main features of HDCS, and the control technique can effectively achieve the operation targets on primary devices despite the fact that HDCS brings adverse effects to control process. Index Terms-Active distribution network (ADN), cyber-physical system (CPS), hybrid system, hierarchical and distributed control system.

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Cyber-physical modeling and control of smart grids - a new paradigm

Cited by 13 publications

References 8 publications

A Review on the Evaluation of Feature Selection Using Machine Learning for Cyber-Attack Detection in Smart Grid

A Review on the Evaluation of Feature Selection Using Machine Learning for Cyber-Attack Detection in Smart Grid

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

Cyber-physical Power System Modeling for Timing-driven Control of Active Distribution Network

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