An artificial insurance framework for a hydrogen-based microgrid to detect the advanced cyberattack model DOI Creative Commons

Mahan Fakhrooeian,

Ali Basem, Mostafa Gholami

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 30, 2025

Microgrid systems have evolved based on renewable energies including wind, solar, and hydrogen to make the satisfaction of loads far from main grid more flexible controllable using both island- grid-connected modes. Albeit microgrids can gain beneficial results in cost energy schedules once operating mode, such are vulnerable malicious attacks viewpoint cybersecurity. With this mind, paper explores a novel advanced attack model named false transferred data injection (FTDI) aiming manipulatively alter power flowing microgrid upstream raise voltage usability probability. One crucial piece information that uses change system cause greatest amount damage while concealing attacker's view is stability index. Saying transaction between within broad scope bilateral exchange at any given moment noteworthy. Put otherwise, with respect FTDI assault, microgrid's direction just as significant detection value. Therefore, running detector needs concurrently detect changes value power. To overcome problem, presents learning generative network model, adversarial (GAN) paradigm, recognize probability values maliciously aimed. end, studied wind turbine, photovoltaic, storage, tidal fuel cell units performed tested 24-bus IEEE satisfy local load demands. Comparative analysis indicates notable gains, scores 0.95%, 0.92%, 0.7%, 10% for Hit rate, C.R. F.A. Miss rate order evaluate GAN-based microgrid.

Language: Английский

Energy Supply Chains in the Digital Age: A Review of Current Research and Trends DOI Creative Commons
Agnieszka Tubis, Honorata Poturaj

Energies, Journal Year: 2025, Volume and Issue: 18(2), P. 430 - 430

Published: Jan. 19, 2025

(1) Background: Digital transformation is critical in further developing the energy supply chain. The attainment of successive levels digital maturity by chain participants translates into numerous benefits related to efficiency, cost, and effectiveness flows implemented. However, increasing degree digitalisation automation generates an increased risk cyberattacks other challenges operation smart grid. This paper presents results a literature review describing phenomenon (2) Methods: was performed using two methods. First, systematic conducted PRISMA method. due unsatisfactory results, this supplemented search supporting narrative review. (3) Results: Analysing identified publications made it possible distinguish nine leading research trends These were characterised based on described all articles classified corresponding categories. (4) Conclusions: presented provide interesting material for building resilience selected Industry 4.0 tools assessing managing risks associated with sector.

Language: Английский

Citations

0
An artificial insurance framework for a hydrogen-based microgrid to detect the advanced cyberattack model DOI Creative Commons

Mahan Fakhrooeian,

Ali Basem, Mostafa Gholami

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 30, 2025

Microgrid systems have evolved based on renewable energies including wind, solar, and hydrogen to make the satisfaction of loads far from main grid more flexible controllable using both island- grid-connected modes. Albeit microgrids can gain beneficial results in cost energy schedules once operating mode, such are vulnerable malicious attacks viewpoint cybersecurity. With this mind, paper explores a novel advanced attack model named false transferred data injection (FTDI) aiming manipulatively alter power flowing microgrid upstream raise voltage usability probability. One crucial piece information that uses change system cause greatest amount damage while concealing attacker's view is stability index. Saying transaction between within broad scope bilateral exchange at any given moment noteworthy. Put otherwise, with respect FTDI assault, microgrid's direction just as significant detection value. Therefore, running detector needs concurrently detect changes value power. To overcome problem, presents learning generative network model, adversarial (GAN) paradigm, recognize probability values maliciously aimed. end, studied wind turbine, photovoltaic, storage, tidal fuel cell units performed tested 24-bus IEEE satisfy local load demands. Comparative analysis indicates notable gains, scores 0.95%, 0.92%, 0.7%, 10% for Hit rate, C.R. F.A. Miss rate order evaluate GAN-based microgrid.

Language: Английский

Citations

0