More Like this

1. A Remedial Action Scheme Against False Data Injection Cyberattacks Targeting ULTC Transformers in Smart Distribution Systems

   https://doi.org/10.1109/ICPSAsia61913.2024.10761531  

   Naderi, Ehsan; Asrari, Arash; Fajri, Poria (July 2024, IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia))

   This paper proposes an on-line remedial action scheme (OLRAS) in order to mitigate the voltage violations caused by false data injection attacks (FDIAs) targeting under load tap changing (ULTC) transformers in smart distribution systems. The FDIA framework contains two different phases. In the attack phase, distribution system operator (DSO), being in attacker's shoe, considers cyberattack scenarios through compromising the results of volt-var optimization problem in a radial distribution grid modified with distributed energy resources (DERs) such as photovoltaic (PV) units and wind turbines (WTs). The outcome of the attack phase will be the compromised voltage profile of the distribution grid showing different rates of voltage violations. In the reaction phase, the DSO rapidly identifies a customized distribution feeder reconfiguration (CDFR) in order to update the flows of active and reactive power throughout the targeted distribution system and recover the voltage profile. The objective functions of the proposed CDFR are defined to minimize the impacts of such cyberattacks targeting ULTCs within distribution grids. This will empower DSOs to react to severe cyberattacks, bypassing the detection stage, and address the voltage violations in a timely manner. The effectiveness of the proposed OLRAS is validated on an IEEE test system. 

   more » « less
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. 

   more » « less
3. Performance Evaluation of Bifacial PV Systems in Distribution Networks Operation: A CVR Study Considering Smart PV Inverter Control

   https://doi.org/10.1109/NAPS56150.2022.10012205  

   Ahanch, Mojtaba; Rouholamini, Mahdi; McCann, Roy; Wang, Caisheng (October 2022, 2022 North American Power Symposium (NAPS))

   Compared to a conventional mono-facial photovoltaic (PV) module, a bifacial one is more efficient as it receives light from not only the front but also the backside. The daily irradiance profile of a bifacial PV module is of a two-peak trajectory that almost coincides with the morning and evening peak demands. This interesting property helps distribution network operators better handle the issues caused by the abundance of conventional PVs during midday (i.e., Duck curve). Moreover, this two-humped profile can be incorporated into network operation strategies such as conservation voltage reduction (CVR). Thus, this paper proposes a new CVR framework that best uses the double-peak profile of bifacial PV modules to improve the voltage profile of a distribution network. The proposed framework optimally coordinates legacy voltage control devices, including on-load tap changers and voltage regulators, as well as Volt/VAr control of smart inverters. The effectiveness of the proposed framework is simulated and verified on the well-known modified 34-bus system using the Matlab-COM-OpenDSS platform. The results clearly demonstrate the advantages of bifacial PVs over their mono-facial counterparts. 

   more » « less
4. A Remediation Framework Against False Data Injection Cyberattacks Targeting ULTC Transformers to Avoid Voltage Collapse in Smart Distribution Networks

   https://doi.org/10.1109/TIA.2025.3542717  

   Naderi, Ehsan; Asrari, Arash (February 2025, IEEE Transactions on Industry Applications)

   False data injection (FDI) attacks targeting under-load tap changing (ULTC) transformers pose a significant threat to smart distribution networks by exploiting vulnerabilities in the volt-var optimization (VVO) process, leading to potential undervoltage and voltage collapse. The increased integration of renewable energy and cyber-physical systems has expanded the attack surface, making traditional detection methods inadequate. For example, in 2023, attacks on utilities and decentralized components in the United States rose by 200%, with overall cyber threats increasing by 104%, highlighting growing vulnerabilities in distribution systems. To this end, this article proposes a two-stage remediation framework for decentralized FDI (DFDI) attacks targeting ULTC transformers. In the attack stage, vulnerabilities in ULTCs and voltage regulators are scrutinized, risking voltage collapse or blackouts in the distribution system. In the remediation stage, the distribution system operator focuses on non-attacked ULTCs, voltage regulators, distributed generation (DG) units, and smart homes to minimize reliance on compromised components. In this regard, a distinctive formulation of distribution network resilience and load management (DNRLM) problem is introduced to identify a resilient network topology and determine a situational power balance strategy. The proposed framework focuses on minimizing the system's reliance on the attacked ULTCs and voltage regulator components, thereby avoiding the intended voltage collapse caused by such DFDIs. The simulation results verify that the proposed method reduces the voltage collapse proximity index by over 60%, enhancing system resilience under DFDI attacks. 

   more » « less
5. Real-time Assessment of Distribution Grid Security through Adaptive Smart Meter Measurements

   https://doi.org/10.1109/CDC56724.2024.10885867  

   Chen, Jiaqi; Roald, Line A (December 2024, IEEE)

   The rapid expansion of distributed energy resources is heightening uncertainty and variability in distribution system operations, potentially leading to power quality challenges such as voltage magnitude violations and excessive voltage unbalance. Ensuring the dependable and secure operation of distribution grids requires system real-time assessment. However, constraints in sensing, measurement, and communication capabilities within distribution grids result in limited awareness of the system’s state. To achieve better real-time estimates of distribution system security, we propose a real-time security assessment based on data from smart meters, which are already prevalent in most distribution grids. Assuming that it is possible to obtain a limited number of voltage magnitude measurements in real time, we design an iterative algorithm to adaptively identify a subset of smart meters whose real-time measurements allow us to certify that all voltage magnitudes remain within bounds. This algorithm iterates between (i) solving optimization problems to determine the worst possible voltage magnitudes, given a limited set of voltage magnitude measurements, and (ii) leveraging the solutions and sensitivity information from these problems to update the measurement set. Numerical tests on the IEEE 123 bus distribution feeder demonstrate that the proposed algorithm consistently identifies and tracks the nodes with the highest and lowest voltage magnitude, even as the load changes over time. 

   more » « less