Optimal partitioning in distributed state estimation considering a modified convergence criterion

Sajjad Asefi, Elena Gryazina, Helder Leite

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Distributed state estimation (DSE) is considered as a more robust and reliable alternative for centralized state estimation (CSE) in power system. Especially, taking into account the future power grid, so called smart grid in which bi-directional transfer of energy and information happens, and renewable energy sources with huge indeterminacy are applied more than before. Combining the mentioned features and complexity of the power network, there is a high probability that CSE face problems such as communication bottleneck or security/reliability issues. So, DSE has the potential to be considered as a solution to solve the mentioned issues. In this paper, first, a modified convergence criterion is proposed and has been tested for different approaches of DSE problem, considering the most important factors such as iteration number, convergence rate, and data needed to be transferred to/from each area. Then, an optimal partitioning technique has been implemented for clustering the system into different areas. Besides the detailed analysis and comparison of recent DSE methods, the proposed partitioning method's effectiveness and scalability has been shown in this paper.

Original languageEnglish
Title of host publicationSEST 2021 - 4th International Conference on Smart Energy Systems and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728176604
DOIs
Publication statusPublished - 6 Sep 2021
Event4th International Conference on Smart Energy Systems and Technologies, SEST 2021 - Virtual, Vaasa, Finland
Duration: 6 Sep 20218 Sep 2021

Publication series

NameSEST 2021 - 4th International Conference on Smart Energy Systems and Technologies

Conference

Conference4th International Conference on Smart Energy Systems and Technologies, SEST 2021
Country/TerritoryFinland
CityVirtual, Vaasa
Period6/09/218/09/21

Keywords

  • Distributed algorithms
  • Optimization
  • Partitioning
  • Power system control
  • State estimation

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