Efficient convex optimization for optimal PMU placement in large distribution grids

Conference Paper (2019)
Author(s)

Miguel Picallo (ETH Zürich)

Adolfo Anta (AIT Austrian Institute of Technology)

B. De Schutter (TU Delft - Delft Center for Systems and Control, TU Delft - Team Bart De Schutter)

Research Group
Team Bart De Schutter
DOI related publication
https://doi.org/10.1109/PTC.2019.8810467
More Info
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Publication Year
2019
Language
English
Research Group
Team Bart De Schutter
ISBN (electronic)
978-1-5386-4722-6

Abstract

The small amount of measurements in distribution grids makes their monitoring difficult. Topological observability may not be possible, and thus, pseudo-measurements are needed to perform state estimation, which is required to control elements such as distributed generation or transformers at distribution grids. Therefore, we consider the problem of optimal sensor placement to improve the state estimation accuracy in large-scale, 3-phase coupled, unbalanced distribution grids. This is an NP-hard optimization problem whose optimal solution is unpractical to obtain for large networks. For that reason, we develop a computationally efficient convex optimization algorithm to compute a lower bound on the possible value of the optimal solution, and thus check the gap between the bound and heuristic solutions. We test the method on a large test feeder, the standard IEEE 8500-node, to show the effectiveness of the approach.

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