Secure Sampled-Data Observer-Based Control for Wind Turbine Oscillation Under Cyber Attacks

Amini, Amir; Ghafouri, Mohsen; Mohammadi, Arash; Hou, Ming; Asif, Amir; Plataniotis, Konstantinos N.

doi:10.1109/tsg.2022.3159582

Cited by 20 publications

(5 citation statements)

References 41 publications

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“…Wind-based energy units were once considered immune to cyber-attacks, but in March 2019, a wind power facility in Salt Lake City, USA, fell victim to an attack that disrupted control over 500 megawatts of wind turbines. This incident highlighted the need for robust cyber security measures in the wind energy sector, leading the U.S. Department of Energy to prioritise strategies for protecting wind units against cyber threats [50]. Denial of service (DoS) and deception attacks, such as false data injection, are common types of adversarial actions targeting power and networked control systems.…”

Section: Data Security and Privacy Concernsmentioning

confidence: 99%

“…When DFIG-based wind power plants are connected to series compensated transmission systems, a phenomenon known as sub-synchronous interaction (SSI) can occur, posing security risks to wind turbines. However, there are several challenges related to SSI damping [50]:…”

Section: Data Security and Privacy Concernsmentioning

confidence: 99%

“…When DFIG‐based wind power plants are connected to series compensated transmission systems, a phenomenon known as sub‐synchronous interaction (SSI) can occur, posing security risks to wind turbines. However, there are several challenges related to SSI damping [50]: The existing SSI damping methods rely on continuous‐time measurement and control updates, which impose restrictive assumptions. The current SSI damping schemes assume a secure, attack‐free environment, which may not hold true in the presence of DoS and deception threats. The feasibility of using fuzzy controllers for SSI damping in DFIG‐based wind power plants has not been extensively studied. …”

Section: Challenges and Limitationsmentioning

confidence: 99%

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A comprehensive review on enhancing wind turbine applications with advanced SCADA data analytics and practical insights

Pandit,

Wang

2024

IET Renewable Power Gen

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The aim of this study is to explore the potential and economic benefits of utilising Supervisory Control and Data Acquisition (SCADA) data to improve wind turbine operation and maintenance activities. The review identifies a gap in the current understanding of how to effectively use SCADA data in wind turbine applications. It emphasises the need for pre‐processing SCADA data to ensure data integrity by addressing outliers and employing interpolation techniques. Additionally, it highlights the challenges associated with early fault detection methods using SCADA data, including the development of physical models, data‐driven machine learning models, and statistical regression models. The review also recognises the limitations caused by the lack of public data from wind turbine developers and the imbalance between normal operation data samples and abnormal data samples, negatively impacting model accuracy. The key findings of the review demonstrate that SCADA data‐driven techniques can lead to significant improvements in wind turbine operations and maintenance. The application of data‐driven technologies based on SCADA data has proven effective in reducing operation and maintenance costs and enhancing wind power generation. Moreover, the development of robust decision support systems using SCADA data minimises the need for frequent maintenance interventions in offshore wind farms. To bridge the gap and further enhance wind turbine applications using SCADA data, several recommendations are provided. These include encouraging greater openness in sharing SCADA data to improve the robustness and accuracy of AI models, adopting transfer learning techniques to overcome the scarcity of quality datasets, establishing unified standards and taxonomies, and providing specialised resources such as software applications with interactive graphical user interfaces for easier storage, annotation, and analysis of SCADA data.The authors’ review paper identifies a gap in the current understanding of how to effectively utilise SCADA data in wind turbine applications. It emphasises the importance of pre‐processing SCADA data to ensure data integrity by addressing outliers and employing interpolation techniques. Furthermore, the authors highlight the challenges associated with early fault detection methods using SCADA data, including the development of physical models, data‐driven machine learning models, and statistical regression models.

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Section: Data Security and Privacy Concernsmentioning

confidence: 99%

Section: Data Security and Privacy Concernsmentioning

confidence: 99%

Section: Challenges and Limitationsmentioning

confidence: 99%

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A comprehensive review on enhancing wind turbine applications with advanced SCADA data analytics and practical insights

Pandit,

Wang

2024

IET Renewable Power Gen

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“…The event-triggered controller has the role of decreasing occupation of the communication channel when attacks happen. Another paper on the use of observers to detect cyber attacks on wind energy systems is [74]. Reference [75] presents an observer designed for a wind-battery energy storage hybrid system.…”

Section: Observers For Wind Turbine Energy Systemsmentioning

confidence: 99%

Linear, Nonlinear, and Distributed-Parameter Observers Used for (Renewable) Energy Processes and Systems—An Overview

Radisavljevic-Gajic,

Karagiannis,

Gajic

2024

Energies

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Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade.

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“…These cooperative tasks mainly include formation control, leader-following, containment, and consensus. Consensus has attracted overwhelming attention due to its vast applications in many areas such as estimation in sensor networks (Meng and Chen, 2014), attitude alignment for spacecrafts (Ren, 2007), and control of microgrids Amini et al, 2022a), to name a few. This article studies the consensus problem for general linear MASs under a class of distributed cyber attacks, namely denial of service, and an advanced class of event-based control scheme referred to as the dynamic event-triggering control.…”

Section: Introductionmentioning

confidence: 99%

Secure dynamic event-triggering control for consensus under asynchronous denial of service

Amini,

Mohammadi,

Hou

et al. 2024

Front. Comput. Sci.

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IntroductionThis article proposes a secure implementation for consensus using a dynamic event-triggered control (DETC) scheme for general autonomous multi-agent systems (MAS) under asynchronous (distributed) denial of service (DoS) attacks. The asynchronous DoS attacks can block each communication channel independently in an unknown pattern. Depending on the impact of DoS on the communication topology, the attacks are categorized into (i): connectivity-preserved DoS (CP-DoS), and (ii): connectivity-broken DoS (CB-DoS). In CP-DoS, the operating communication topology remains connected. On the other hand, in CB-DoS the adversary breaks the communication graph into isolated sub-graphs.MethodsThe DETC scheme is employed to reduce the control updates for each agent. To guarantee consensus under both the CP-DoS and CB-DoS, a linear matrix inequality (LMI) based optimization approach is proposed, which simultaneously designs all the unknown DETC parameters as well as the state feedback control gain.ResultsThe proposed optimization method prioritizes the minimum inter-event interval (MIET) between consecutive control updates. The trade-off between relevant features of the MAS, namely the consensus convergence rate, intensity of control updates, and level of resilience to DoS can be handled by the proposed optimization.DiscussionSimulation results quantify the effectiveness of the proposed approach, showcasing its ability to maintain secure consensus in MAS under varying DoS attack scenarios.

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Secure Sampled-Data Observer-Based Control for Wind Turbine Oscillation Under Cyber Attacks

Cited by 20 publications

References 41 publications

A comprehensive review on enhancing wind turbine applications with advanced SCADA data analytics and practical insights

A comprehensive review on enhancing wind turbine applications with advanced SCADA data analytics and practical insights

Linear, Nonlinear, and Distributed-Parameter Observers Used for (Renewable) Energy Processes and Systems—An Overview

Secure dynamic event-triggering control for consensus under asynchronous denial of service

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