Quantum Computing Methods for Dynamic State Estimation in Power Systems
IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), pp. 1–5
Abstract
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.
Authors 7
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Affiliation as printed
Institute for Automation of Complex Power Systems RWTH Aachen University,Aachen,Germany
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Forschungszentrum Jülich · Jülich Supercomputing Centre
Affiliation as printed
Jülich Supercomputing Centre Institute for Advanced Simulation Forschungszentrum Jülich,Jülich,Germany
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Affiliation as printed
Quantum Computing Analytics (PGI-12) Forschungszentrum Jülich,Jülich,Germany
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Affiliation as printed
Institute for Automation of Complex Power Systems RWTH Aachen University,Aachen,Germany
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Affiliation as printed
Institute for Automation of Complex Power Systems RWTH Aachen University,Aachen,Germany
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Forschungszentrum Jülich · Jülich Supercomputing Centre
Affiliation as printed
Jülich Supercomputing Centre Institute for Advanced Simulation Forschungszentrum Jülich,Jülich,Germany
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Affiliation as printed
Institute for Automation of Complex Power Systems RWTH Aachen University,Aachen,Germany
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