Optimal PMU Placement for Kalman Filtering of DAE Power System Models
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866916598511566848 |
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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 |