Efficient convex optimization for optimal PMU placement in large distribution grids

Miguel Picallo, Adolfo Anta, Bart De Schutter

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE Power Tech Conference (PowerTech 2019)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-5386-4722-6
DOIs
Publication statusPublished - 2019
Event2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italy
Duration: 23 Jun 201927 Jun 2019

Conference

Conference2019 IEEE Milan PowerTech, PowerTech 2019
Country/TerritoryItaly
CityMilan
Period23/06/1927/06/19

Keywords

  • Distribution grid state estimation
  • Optimal design of experiments
  • Optimal sensor placement
  • Phasor measurement units
  • Projected gradient descent

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