Quantum microgrid state estimation

Fei Feng; Peng Zhang; Yifan Zhou; Zefan Tang

doi:10.1016/j.epsr.2022.108386

Quantum microgrid state estimation

Fei Feng
, Peng Zhang
, Yifan Zhou
, Zefan Tang

Stony Brook University

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

This paper investigates the feasibility and efficiency of quantum-circuit-based algorithms for microgrid state estimation. Our new contributions include: (1) a general quantum state estimation (GQSE) formulation is devised for swing-bus-contained microgrids through the quantized Gaussian–Newton iteration, (2) a preconditioned quantum linear solver (PQLS) is developed for tackling the ill-conditioned GQSE with limited quantum resources, and (3) an enhanced quantum state estimation (EQSE) algorithm is further established for hierarchical-control-based microgrids with exogenous disturbances. Extensive case studies demonstrate the correctness of GQSE, PQLS and EQSE in two typical microgrids. The robustness and convergence performance of EQSE are also verified.

Original language	English
Article number	108386
Journal	Electric Power Systems Research
Volume	212
DOIs	https://doi.org/10.1016/j.epsr.2022.108386
State	Published - Nov 2022

Keywords

Hierarchical control
Microgrid
Quantum computing
State estimation

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10.1016/j.epsr.2022.108386

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title = "Quantum microgrid state estimation",

abstract = "This paper investigates the feasibility and efficiency of quantum-circuit-based algorithms for microgrid state estimation. Our new contributions include: (1) a general quantum state estimation (GQSE) formulation is devised for swing-bus-contained microgrids through the quantized Gaussian–Newton iteration, (2) a preconditioned quantum linear solver (PQLS) is developed for tackling the ill-conditioned GQSE with limited quantum resources, and (3) an enhanced quantum state estimation (EQSE) algorithm is further established for hierarchical-control-based microgrids with exogenous disturbances. Extensive case studies demonstrate the correctness of GQSE, PQLS and EQSE in two typical microgrids. The robustness and convergence performance of EQSE are also verified.",

keywords = "Hierarchical control, Microgrid, Quantum computing, State estimation",

author = "Fei Feng and Peng Zhang and Yifan Zhou and Zefan Tang",

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AU - Feng, Fei

AU - Zhang, Peng

AU - Zhou, Yifan

AU - Tang, Zefan

PY - 2022/11

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N2 - This paper investigates the feasibility and efficiency of quantum-circuit-based algorithms for microgrid state estimation. Our new contributions include: (1) a general quantum state estimation (GQSE) formulation is devised for swing-bus-contained microgrids through the quantized Gaussian–Newton iteration, (2) a preconditioned quantum linear solver (PQLS) is developed for tackling the ill-conditioned GQSE with limited quantum resources, and (3) an enhanced quantum state estimation (EQSE) algorithm is further established for hierarchical-control-based microgrids with exogenous disturbances. Extensive case studies demonstrate the correctness of GQSE, PQLS and EQSE in two typical microgrids. The robustness and convergence performance of EQSE are also verified.

AB - This paper investigates the feasibility and efficiency of quantum-circuit-based algorithms for microgrid state estimation. Our new contributions include: (1) a general quantum state estimation (GQSE) formulation is devised for swing-bus-contained microgrids through the quantized Gaussian–Newton iteration, (2) a preconditioned quantum linear solver (PQLS) is developed for tackling the ill-conditioned GQSE with limited quantum resources, and (3) an enhanced quantum state estimation (EQSE) algorithm is further established for hierarchical-control-based microgrids with exogenous disturbances. Extensive case studies demonstrate the correctness of GQSE, PQLS and EQSE in two typical microgrids. The robustness and convergence performance of EQSE are also verified.

KW - Hierarchical control

KW - Microgrid

KW - Quantum computing

KW - State estimation

UR - https://www.scopus.com/pages/publications/85134430929

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DO - 10.1016/j.epsr.2022.108386

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SN - 0378-7796

VL - 212

JO - Electric Power Systems Research

JF - Electric Power Systems Research

M1 - 108386

ER -

Quantum microgrid state estimation

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Keywords

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