Home > Publications database > Quantum Computing Methods for Dynamic State Estimation in Power Systems > print

001     1050341
005     20260108204826.0
024 7 _ |a 10.1109/ISGTEurope64741.2025.11305506
|2 doi
037 _ _ |a FZJ-2026-00141
100 1 _ |a Stoyanova, Ivelina
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
111 2 _ |a 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)
|c Valletta
|d 2025-10-20 - 2025-10-23
|w Malta
245 _ _ |a Quantum Computing Methods for Dynamic State Estimation in Power Systems
260 _ _ |c 2025
|b IEEE
300 _ _ |a 5p.
336 7 _ |a CONFERENCE_PAPER
|2 ORCID
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a Output Types/Conference Paper
|2 DataCite
336 7 _ |a Contribution to a conference proceedings
|b contrib
|m contrib
|0 PUB:(DE-HGF)8
|s 1767877742_20481
|2 PUB:(DE-HGF)
520 _ _ |a This work investigates the applicability, limitations and advantages of six quantum computing methods for a dynamic state estimation scenario. The paper analyzes the computational challenges of a Kalman filter scenario to evaluate the feasibility of the quantum computing methods for this use case. The methods are introduced with their mathematical formulations and compared based on their level of maturity, their compatibility with existing hardware, the expected speedup and the caveats relevant to their applicability for the dynamic state estimation scenario. The central findings are that two of the methods are not applicable and two methods will not be further considered due to issues with the scalability. However, two methods seem promising for the application and will be used for more advanced studies on the matter.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 0
536 _ _ |a QuGrids - Quantum-based Energy Grids (QuGrids20231101)
|0 G:(MKW-NRW)QuGrids20231101
|c QuGrids20231101
|x 1
588 _ _ |a Dataset connected to CrossRef Conference
700 1 _ |a Şensebat, Orkun
|0 P:(DE-Juel1)195826
|b 1
|u fzj
700 1 _ |a Ji, Yanjun
|0 P:(DE-Juel1)204481
|b 2
|u fzj
700 1 _ |a Ganeshamurthy, Priyanka Arkalgud
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Kajganic, Sonja
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Willsch, Dennis
|0 P:(DE-Juel1)167542
|b 5
|u fzj
700 1 _ |a Monti, Antonello
|0 P:(DE-HGF)0
|b 6
770 _ _ |z 979-8-3315-2503-3
773 _ _ |a 10.1109/ISGTEurope64741.2025.11305506
856 4 _ |u https://juser.fz-juelich.de/record/1050341/files/Quantum_Computing_Methods_for_Dynamic_State_Estimation_in_Power_Systems.pdf
|y Restricted
909 C O |o oai:juser.fz-juelich.de:1050341
|p VDB
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)195826
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)204481
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|6 P:(DE-Juel1)167542
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 0
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
920 1 _ |0 I:(DE-Juel1)PGI-12-20200716
|k PGI-12
|l Quantum Computing Analytics
|x 1
980 _ _ |a contrib
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a I:(DE-Juel1)PGI-12-20200716
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21