A critical task in smart grid is to gain situational awareness by performing state estimation. In this paper, we consider the problem of placing a type of special sensors, called Phasor Measurement Units (PMU), to optimize the performance and convergence of state estimation. We derive a metric to evaluate how the placement impacts the convergence and accuracy of state estimation solved by Gauss-Newton (GN) algorithm. Using the proposed metric, we formulate and solve the placement problem as a semi-definite program (SDP). Simulations of the IEEE 30 and 118 systems corroborate our analysis, showing that the proposed placement stabilizes and accelerates state estimation, while maintaining optimal estimation performance.
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Optimal sensor placement for hybrid state estimation in smart grid
Semantic Scholar · Engineering · 2013
Abstract
A critical task in smart grid is to gain situational awareness by performing state estimation. In this paper, we consider the problem of placing a type of special sensors, called Phasor Measurement Units (PMU), to optimize the performance and convergence of state estimation. We derive a metric to evaluate how the placement impacts the convergence and accuracy of state estimation solved by Gauss-Newton (GN) algorithm. Using the proposed metric, we formulate and solve the placement problem as a semi-definite program (SDP). Simulations of the IEEE 30 and 118 systems corroborate our analysis, showing that the proposed placement stabilizes and accelerates state estimation, while maintaining optimal estimation performance.