Power system state estimation (PSSE) is a critical task for grid operation efficiency and system stability. Physical laws dictate quadratic relationships between observable quantities and voltage state variables, hence rendering the PSSE problem nonconvex and NP-hard. Existing SE solvers largely rely on iterative optimization methods or semidefinite relaxation (SDR) techniques. Even when based on noiseless measurements, convergence of the former is sensitive to the initialization, while the latter is challenged by small-size measurements especially when voltage magnitudes are not available at all buses. At the price of running time, this paper proposes a novel feasible point pursuit (FPP)-based SE solver, which iteratively seeks feasible solutions for a nonconvex quadratically constrained quadratic programming reformulation of the weighted least-squares (WLS) SE problem. Numerical tests corroborate that the novel FPP-based SE markedly improves upon the Gauss-Newton based WLS and SDR-based SE alternatives, also when noisy measurements are available.
|Original language||English (US)|
|Title of host publication||2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|State||Published - Apr 19 2017|
|Event||2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States|
Duration: Dec 7 2016 → Dec 9 2016
|Name||2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings|
|Other||2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016|
|Period||12/7/16 → 12/9/16|
Bibliographical noteFunding Information:
The work of G.Wang and G. B. Giannakis was supported by NSF grants 1423316, 1442686, 1508993, and 1509040. The work of A. S. Zamzam and N. D. Sidiropoulos was partially supported by NSF under grants 1231504 and 1525194.
- Feasible point pursuit
- Nonconvex QCQP
- Power system state estimation