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1. Cyber-Physical Distribution Systems Resilience Against Cyberattacks via a Remediation Framework Based on Static VAR Compensators (SVCs)

   https://doi.org/10.1109/ACCESS.2024.3450631  

   Naderi, Ehsan; Asrari, Arash (August 2024, IEEE Access)

   This paper proposes a framework to optimally employ static VAR compensators (SVCs) within a customized reconfiguration of system topology, leading to remediation of voltage violations caused by false data injection (FDI) cyberattacks targeting smart distribution grids. The designed framework contains formulations associated with planning and operation phases. In the planning phase, the scrutinized system, modified by photovoltaic (PV) units, is enhanced by optimally allocating static VAR compensators (SVCs) to keep the unity power factor throughout the system. Then, distribution system operator (DSO), being in attacker’s shoe, examines relevant cyberattack scenarios leading to voltage violations within the distribution system. Finally, in the operation phase, DSO takes advantage of the optimally planned SVCs to identify proper vectors (i.e., remedial actions) to cope with such potential scenarios of cyberattacks. These (to be recognized) vectors are associated with the variable shunt susceptance of the mentioned SVCs, which will be identified by solving a customized distribution feeder reconfiguration (DFR) problem in the operation phase. The main objective of the customized DFR is to maximize the contributions of SVCs through enhancing the voltage profile of the targeted system. This will enable DSO to mitigate the negative impacts of the FDI attacks and recover the voltage profile of the smart distribution network. The effectiveness of the proposed RAS is validated on three different smart test systems (i.e., 33-bus, 95-bus, and 136-bus systems), which are modified to contain SVC components and renewable-based distributed generation (DG) units. 

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2. Stealthy False Data Injection Cyberattack Targeting Under Load Tap Changing Transformers in Smart Power Grid Causing Abnormal Voltage Profile

   https://doi.org/10.1109/ICPC2T60072.2024.10474991  

   Naderi, Ehsan; Asrari, Arash (March 2024, 2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T))

   In the process of protecting power systems against different types of cyberattacks, the primary step is to precisely model such frameworks from attacker's perspective. This paper investigates a false data injection (FDI) attack framework, which can target under-load tap changing (ULTC) transformers, resulting in manipulated voltage profile in radial smart distribution networks. The developed FDI model compromises the voltage profile of a distribution feeder through misleading the volt/var optimization, that optimally manages system-wide voltage profile and flow of reactive power. The presented attack model is formulated as a bi-objective optimization problem. The objective functions from the attacker's point of view are 1) minimizing the level of false data to be injected into the smart meters associated with load data and 2) maximizing the voltage deviation of the distribution grid. Negative impacts of such a cyberattack model have been validated and discussed in this work on an IEEE distribution test system, necessitating proper remedial actions, which will be elaborated in the next step of this research. 

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3. An Unsupervised Approach to Enhance Cyber Resiliency of Power Systems Against False Data Injection Attacks on Voltage Stability

   https://doi.org/10.18178/ijeetc.14.2.88-93  

   Fahim, Shahriar Rahman (January 2025, International Journal of Electrical and Electronic Engineering & Telecommunications)

   The digital transformation of power system introduces False Data Injection Attacks (FDIAs) on voltage stability that compromises the operational integrity of power grids. Existing detection mechanisms for FDIAs often fall short as they overlook the complexities of cyberattacks targeting voltage stability and rely on outdated models that do not capture the dynamic interplay between power system operations and potential threats. In response to these gaps, this paper proposes a novel FDIA detection method designed specifically for voltage regulation vulnerabilities, aiming to enhance the voltage stability index. The proposed method utilizes an unsupervised learning framework capable of identifying cyberattacks targeting voltage regulation. A bi-level optimization approach is put forward to concurrently optimize the objectives of both attackers and defenders in the context of voltage regulation. The effectiveness of this approach is validated through comprehensive training and testing on a variety of attack scenarios, demonstrating superior generalization across different conditions. Extensive simulations on the Iberian power system topology, with 486 buses, show that the proposed model achieves more than 93% detection rate. These results highlight the robustness and efficacy of the proposed strategy in strengthening the cyber resilience of power systems against sophisticated FDIA threats on voltage stability. 

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4. Recent Advances in Cyberattack Detection and Mitigation Techniques for Renewable Photovoltaic Distributed Energy CPS

   Jessica Whitaker and Danda B. Rawat (June 2023, Computing Conference)

   Cyberattacks targeted to the energy cyber-physical system (ECPS), also known as the smart grid, could interrupt the electricity supply with major ramifications. Attackers identify and exploit any vulnerable portion of the energy power grid, including the inverters with solar-powered photovoltaic (PV) panels. PV presents unique challenges as electricity consumers have also become providers of solar energy for utilities. As mandates require increased PV penetration across the world for positive environmental impacts, increased cyberattacks targeted at PV systems impact reliability and efficiency within the ECPS. The new technologies continuously being introduced to manage the ECPS and ensure bi-directional communications and energy flow between components also lead to more attack surfaces, system vulnerabilities, and heightened malicious attacks. Data integrity attacks are increasing within PV systems. In this paper, we present a survey of different methods that are proposed and explored for identifying and preventing cyberattacks targeted at PV systems. The attack detection methods include voltage control, data diodes, and voltage measurement algorithms. Furthermore, we present blockchain, cyber switching, and other attack mitigation techniques for PV systems. 

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5. Cyber Attack and Defense for Smart Inverters in a Distribution System

   Sun, C. C.; Zhu, R.; Liu, C. C. (June 2019, CIGRE Study Committee D2 Colloquium, Helsinki, Finland)

   The fast-growing installation of solar PVs has a significant impact on the operation of distribution systems. Grid-tied solar inverters provide reactive power capability to support the voltage profile in a distribution system. In comparison with traditional inverters, smart inverters have the capability of real time remote control through digital communication interfaces. However, cyberattack has become a major threat with the deployment of Information and Communications Technology (ICT) in a smart grid. The past cyberattack incidents have demonstrated how attackers can sabotage a power grid through digital communication systems. In the worst case, numerous electricity consumers can experience a major and extended power outage. Unfortunately, tracking techniques are not efficient for today’s advanced communication networks. Therefore, a reliable cyber protection system is a necessary defense tool for the power grid. In this paper, a signature-based Intrusion Detection System (IDS) is developed to detect cyber intrusions of a distribution system with a high level penetration of solar energy. To identify cyberattack events, an attack table is constructed based on the Temporal Failure Propagation Graph (TFPG) technique. It includes the information of potential cyberattack patterns in terms of attack types and time sequence of anomaly events. Once the detected anomaly events are matched with any of the predefined attack patterns, it is judged to be a cyberattack. Since the attack patterns are distinguishable from other system failures, it reduces the false positive rate. To study the impact of cyberattacks on solar devices and validate the performance of the proposed IDS, a realistic Cyber-Physical System (CPS) simulation environment available at Virginia Tech (VT) is used to develop an interconnection between the cyber and power system models. The CPS model demonstrates how communication system anomalies can impact the physical system. The results of two example cyberattack test cases are obtained with the IEEE 13 node test feeder system and the power system simulator, DIgSILENT PowerFactory. 

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