Thesis supervisor: Bálint Hartmann
Location of studies (in Hungarian): Department of Electric Power Engineering Abbreviation of location of studies: VET
Description of the research topic:
Being omnipresent and entrenched in the socio-economic landscape, power grids are taken for granted and are considered an important precondition for modernity. Their evolution is the result of one of the most significant intersectoral collaborations in recent history. The grids, belonging to the largest man-made infrastructures, are an especially interesting real-world case of complex networks. Despite their massive scale and rich history, power grids have not received significant attention thus show great potential for study, especially with the appearance and rapid development of data analysis techniques based on modern machine learning.
The task of the early-career research candidate is to perform interdisciplinary research that connects the fields of power engineering, computer sciences and network sciences.
Key areas include but not limited to the following:
• use of graph neural networks to capture the dynamics of power system operation
• use of graph neural networks for prediction purpose, including state estimation and network development
• use of coupled oscillators (Kuramoto-modell) to study the dynamics stability of heterogeneous power systems
• use of complex network indicators to assess vulnerability of the power system
References
[1] B. Hartmann, How does the vulnerability of an evolving power grid change?, ELECTRIC POWER SYSTEMS RESEARCH, 200, Paper: 107478 (2021)
[2] B. Hartmann, V. Sugár, Searching for small-world and scale-free behaviour in long-term historical data of a real-world power grid, SCIENTIFIC REPORTS, 11, Paper: 6575 (2021)
[3] G. Ódor, B. Hartmann, Power-Law Distributions of Dynamic Cascade Failures in Power-Grid Models, ENTROPY, 22, Paper: 666 (2020)
[4] G. Ódor, B. Hartmann, Heterogeneity effects in power grid network models, PHYSICAL REVIEW, 98, Paper: 022305 (2018)
Required language skills: English Number of students who can be accepted: 1