Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Misyris, George S."'
Varying power-infeed from converter-based generation units introduces great uncertainty on system parameters such as inertia and damping. As a consequence, system operators face increasing challenges in performing dynamic security assessment and taki
Externí odkaz:
http://arxiv.org/abs/2004.04026
We propose a localized protection scheme based on modal analysis in multi-terminal modular multilevel converter (MMC) based high voltage DC (HVDC) systems. The paper addresses the issues of localized protection scheme based DC fault identification, s
Externí odkaz:
http://arxiv.org/abs/2003.10145
This paper introduces a framework to capture previously intractable optimization constraints and transform them to a mixed-integer linear program, through the use of neural networks. We encode the feasible space of optimization problems characterized
Externí odkaz:
http://arxiv.org/abs/2003.07939
This paper introduces for the first time, to our knowledge, a framework for physics-informed neural networks in power system applications. Exploiting the underlying physical laws governing power systems, and inspired by recent developments in the fie
Externí odkaz:
http://arxiv.org/abs/1911.03737
Publikováno v:
In Electric Power Systems Research August 2021 197
Autor:
Misyris, George S., Marinopoulos, Antonios, Doukas, Dimitrios I., Tengnér, Tomas, Labridis, Dimitris P.
Publikováno v:
In Electric Power Systems Research October 2017 151:115-124
Publikováno v:
Nougain, V, Mishra, S, Misyris, G S, Chatzivasileiadis, S & Chatzivasileiadis, S 2021, ' Multi-Terminal DC Fault Identification for MMC-HVDC Systems based on Modal Analysis-A Localized Protection Scheme ', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 9, no. 6, pp. 6650-6661 . https://doi.org/10.1109/JESTPE.2021.3068800
For the purpose of DC fault identification in multi-terminal modular multilevel converter (MMC) high voltage DC (HVDC) systems, the proposed work addresses the issues of localized protection schemes. The proposed work is focused on selectivity issues
Publikováno v:
Murzakhanov, I, Venzke, A, Misyris, G S & Chatzivasileiadis, S 2022, Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow . in Proceedings of 11th Bulk Power Systems Dynamics and Control Sympositum 2022 . 11th Bulk Power Systems Dynamics and Control Symposium, Banff, Alberta, Canada, 25/07/2022 .
This paper introduces a framework to capture previously intractable optimization constraints and transform them to a mixed-integer linear program, through the use of neural networks. We encode the feasible space of optimization problems characterized
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1202::bfd9a60e6f79287c7e901a7b3c9ec4e6
https://orbit.dtu.dk/en/publications/458c4a22-122d-4955-b283-7328136af0af
https://orbit.dtu.dk/en/publications/458c4a22-122d-4955-b283-7328136af0af
Akademický článek
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Autor:
Misyris, George S., Andreas Venzke
Publikováno v:
Technical University of Denmark Orbit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::58a4d0ab43ac381d52e01fbc4ba487f6
https://orbit.dtu.dk/en/publications/62759496-a534-454f-8c6f-fa70c4daa8fa
https://orbit.dtu.dk/en/publications/62759496-a534-454f-8c6f-fa70c4daa8fa