Optimal Sensor Placement for Hybrid State Estimation in Smart Grid

Li, X., Scaglione, A., Chang, T-H

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5253,5257, 26-31 May 2013.

Visit Publisher Online Entry:

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.

Publication Status:
Publication Type:
Publication Date:
Copyright Notice:

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

  1. The following copyright notice applies to all of the above items that appear in IEEE publications: "Personal use of this material is permitted. However, permission to reprint/publish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE."

  2. The following copyright notice applies to all of the above items that appear in ACM publications: "© ACM, effective the year of publication shown in the bibliographic information. This file is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the journal or proceedings indicated in the bibliographic data for each item."

  3. The following copyright notice applies to all of the above items that appear in IFAC publications: "Document is being reproduced under permission of the Copyright Holder. Use or reproduction of the Document is for informational or personal use only."