Simulation of the Effect of False Data Injection Attacks on SCADA using PSCAD/EMTDC

Lingaraju, Kaushik; Gui, Jianzhong; Johnson, Brian K.; Chakhchoukh, Yacine

doi:10.1109/naps50074.2021.9449681

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…� PSCAD/EMTDC: It is a commercial tool used for power system simulators that simulates power from generation to distribution, giving the user the ability to analyse a power system comprehensively. Moreover, this tool can be integrated with other tools, such as MATLAB, for research/ experiment purposes [182][183][184]. � Power System Simulation Toolbox: An open-source tool developed by [185] [188].…”

Section: ✓ ✓mentioning

confidence: 99%

“… PSCAD/EMTDC: It is a commercial tool used for power system simulators that simulates power from generation to distribution, giving the user the ability to analyse a power system comprehensively. Moreover, this tool can be integrated with other tools, such as MATLAB, for research/experiment purposes [182–184]. Power System Simulation Toolbox: An open‐source tool developed by [185] written in Python code is used for Agent‐Based Modelling of Electricity Systems. OpenDSS: Open Distribution System Simulator is an open‐source tool used for power system simulation and can be integrated with other tools due to the availability of the communication (i.e., COM) interface [186].…”

Section: Modelling Simulation and Evaluationmentioning

confidence: 99%

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A review: Monitoring situational awareness of smart grid cyber‐physical systems and critical asset identification

Alrowaili

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Srivastava

et al. 2023

IET Cyber-Phy Sys Theory & Ap

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Cyber‐Physical Systems (CPSs) are becoming more automated and aimed to be as efficient as possible by enabling integration between their operations and Information Technology (IT) resources. In combination with production automation, these systems need to identify their assets and the correlation between them; any potential threats or failures alert the relevant user/department and suggest the appropriate remediation plan. Moreover, identifying critical assets in these systems is essential. With numerous research and technologies available, assessing IT assets nowadays can be straightforward to implement. However, there is one significant issue of evaluating operational technology critical assets since they have different characteristics, and traditional solutions cannot work efficiently. This study presents the necessary background to attain the appropriate approach for monitoring critical assets in CPSs' Situational Awareness (SA). Additionally, the study presents a broad survey supported by an in‐depth review of previous works in three important aspects. First, it reviews the applicability of possible techniques, tools and solutions that can be used to collect detailed information from such systems. Secondly, it covers studies that were implemented to evaluate the criticality of assets in CPSs, demonstrates requirements for critical asset identification, explores different risks and failure techniques utilised in these systems and delves into approaches to evaluate such methods in energy systems. Finally, this paper highlights and analyses SA gaps based on existing solutions, provides future directions and discusses open research issues.

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Section: ✓ ✓mentioning

confidence: 99%

Section: Modelling Simulation and Evaluationmentioning

confidence: 99%

A review: Monitoring situational awareness of smart grid cyber‐physical systems and critical asset identification

Alrowaili

Saxena

Srivastava

et al. 2023

IET Cyber-Phy Sys Theory & Ap

View full text Add to dashboard Cite

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Transmission Adaptive Capacity-Based Resilience Metrics for Power Grid Contingency Analysis

Gui

Lei

Chakhchoukh

et al. 2021

2021 North American Power Symposium (NAPS)

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Meticulously Intelligent Identification System for Smart Grid Network Stability to Optimize Risk Management

2021

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The heterogeneous and interoperable nature of the cyber-physical system (CPS) has enabled the smart grid (SG) to operate near the stability limits with an inconsiderable accuracy margin. This has imposed the need for more intelligent, predictive, fast, and accurate algorithms that are able to operate the grid autonomously to avoid cascading failures and/or blackouts. In this paper, a new comprehensive identification system is proposed that employs various machine learning architectures for classifying stability records in smart grid networks. Specifically, seven machine learning architectures are investigated, including optimizable support vector machine (SVM), decision trees classifier (DTC), logistic regression classifier (LRC), naïve Bayes classifier (NBC), linear discriminant classifier (LDC), k-nearest neighbor (kNN), and ensemble boosted classifier (EBC). The developed models are evaluated and contrasted in terms of various performance evaluation metrics such as accuracy, precision, recall, harmonic mean, prediction overhead, and others. Moreover, the system performance was evaluated on a recent and significant dataset for smart grid network stability (SGN_Stab2018), scoring a high identification accuracy (99.90%) with low identification overhead (4.17 μSec) for the optimizable SVM architecture. We also provide an in-depth description of our implementation in conjunction with an extensive experimental evaluation as well as a comparison with state-of-the-art models. The comparison outcomes obtained indicate that the optimized model provides a compact and efficient model that can successfully and accurately predict the voltage stability margin (VSM) considering different operating conditions, employing the fewest possible input features. Eventually, the results revealed the competency and superiority of the proposed optimized model over the other available models. The technique also speeds up the training process by reducing the number of simulations on a detailed power system model around operating points where correct predictions are made.

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Simulation of the Effect of False Data Injection Attacks on SCADA using PSCAD/EMTDC

Cited by 3 publications

References 18 publications

A review: Monitoring situational awareness of smart grid cyber‐physical systems and critical asset identification

A review: Monitoring situational awareness of smart grid cyber‐physical systems and critical asset identification

Transmission Adaptive Capacity-Based Resilience Metrics for Power Grid Contingency Analysis

Meticulously Intelligent Identification System for Smart Grid Network Stability to Optimize Risk Management

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