1,721,040 research outputs found
Evaluation of the Impact of Cyber-Attacks Against Electric Vehicle Charging Stations in a Low Voltage Distribution Grid
No full textElectric Vehicles (EVs) are getting widely adopted in cities in order to move towards a more sustainable transport system. However, with the increased penetration of EVs and their charging infrastructure, the distribution grid becomes more vulnerable to cyber-attacks. Therefore, it is essential to analyse the impact that cyber-attacks can cause on a low-voltage distribution grid. This paper aims to evaluate the effect produced by a cyber-attack against EV charging stations in the pan-European context. The IEEE European Low-Voltage Test Feeder (ELVTF) is used as a standard model for this study. The simulations are carried out using MATLAB/Simulink platform. The results from different attack locations in the model are used to draw out the final conclusions
Cybersecurity Issues in Electrical Protection Relays: A Systematic Review
No full textThe increasing digitalization of power systems has revolutionized the functionality and efficiency of electrical protection relays. These digital relays enhance fault detection, monitoring, and response mechanisms, ensuring the reliability and stability of power networks. However, their connectivity and reliance on communication protocols introduce significant cybersecurity risks, making them potential targets for malicious attacks. Cyber threats against digital protection relays can lead to severe consequences, including cascading failures, equipment damage, and compromised grid security. This paper presents a comprehensive review of cybersecurity challenges in digital electrical protection relays, focusing on four key areas: (1) a taxonomy of cyber attack models targeting protection relays, (2) the associated risks and their potential impact on power systems, (3) existing mitigation strategies to enhance relay security, and (4) future research directions to strengthen resilience against cyber threats
Securing Virtual Power Plants: Attack Vector Analysis of Cybersecurity Vulnerabilities in Ancillary Grid Services
No full textVirtual Power Plants (VPPs) have emerged as critical infrastructure for grid stability, aggregating diverse Distributed Energy Resources (DERs) to provide essential ancillary services, including frequency regulation, voltage support, and emergency response capabilities. However, the technical requirements that enable VPPs to deliver these time-critical services simultaneously create unique cybersecurity vulnerabilities that distinguish them from traditional power generation and conventional smart grid systems. This paper establishes systematic connections between VPP technical requirements and cybersecurity threats through the integrated application of NIST and MITRE frameworks. The objective is to reveal critical threats specifically pertaining to ancillary services, comprehensive attack vector classification using MITRE ATT&CK techniques adapted for VPP environments, and mitigation strategies that maintain operational performance while addressing identified vulnerabilities
Robust predictive control for the management of multi-echelon distribution chains
No full textThe problem of robust inventory control for multiechelon distribution chains is addressed by using predictive control. Since the future demand of goods is assumed to be uncertain, we focus on a worst-case planning strategy that is consistent with the demand predictions and minimizes the maximum of a performance objective function. The resulting optimal decisions concern the delivery of goods in such a way to reduce the overall costs as to holding, transportation, and backlogs. As compared with previous works, the proposed approach allows one to deal with distribution chains of much larger dimension because of its intrinsic scalability. Of course, such an appreciable feature is paid in terms of loss of optimality.
However, a convenient tradeoff can be achieved, as shown by means of simulations
Towards privacy-preserving anomaly-based intrusion detection in energy communities
No full textEnergy communities consist of decentralized energy production, storage, consumption, and distribution and are gaining traction in modern power systems. However, these communities may increase the vulnerability of the grid to cyber threats. We propose an anomaly-based intrusion detection system to enhance the security of energy communities. The system leverages LSTM autoencoders to detect deviations from normal operational patterns in order to identify anomalies induced by attacks or faults. Operational data for training and evaluation are derived from a Simulink-based model of an energy community. The results show that the autoencoder-based intrusion detection system achieves good detection performance across multiple attack scenarios, up to 0.9270 and 0.9735 in precision and recall respectively. We also demonstrate potential for real-world application of the system by training a federated model that enables distributed intrusion detection while preserving data privacy
- …
