Optimal PMU Placement for Kalman Filtering of DAE Power System Models

Fuente: arXiv
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Main Authors: Katanic, Milos, Guo, Yi, Lygeros, John, Hug, Gabriela
Format: Preprint
Published: 2025
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author Katanic, Milos
Guo, Yi
Lygeros, John
Hug, Gabriela
author_facet Katanic, Milos
Guo, Yi
Lygeros, John
Hug, Gabriela
contents Optimal sensor placement is essential for minimizing costs and ensuring accurate state estimation in power systems. This paper introduces a novel method for optimal sensor placement for dynamic state estimation of power systems modeled by differential-algebraic equations. The method identifies optimal sensor locations by minimizing the steady-state covariance matrix of the Kalman filter, thus minimizing the error of joint differential and algebraic state estimation. The problem is reformulated as a mixed-integer semidefinite program and effectively solved using off-the-shelf numerical solvers. Numerical results demonstrate the merits of the proposed approach by benchmarking its performance in phasor measurement unit placement in comparison to greedy algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2502_03338
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal PMU Placement for Kalman Filtering of DAE Power System Models
Katanic, Milos
Guo, Yi
Lygeros, John
Hug, Gabriela
Systems and Control
Optimal sensor placement is essential for minimizing costs and ensuring accurate state estimation in power systems. This paper introduces a novel method for optimal sensor placement for dynamic state estimation of power systems modeled by differential-algebraic equations. The method identifies optimal sensor locations by minimizing the steady-state covariance matrix of the Kalman filter, thus minimizing the error of joint differential and algebraic state estimation. The problem is reformulated as a mixed-integer semidefinite program and effectively solved using off-the-shelf numerical solvers. Numerical results demonstrate the merits of the proposed approach by benchmarking its performance in phasor measurement unit placement in comparison to greedy algorithms.
title Optimal PMU Placement for Kalman Filtering of DAE Power System Models
topic Systems and Control
url https://arxiv.org/abs/2502.03338