Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

25 Scopus Citations
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Author(s)

  • Nuwan Ganganath
  • Jing V. Wang
  • Xinzhi Xu
  • Chi-Tsun Cheng
  • Chi K. Tse

Detail(s)

Original languageEnglish
Article number8166784
Pages (from-to)3325-3333
Journal / PublicationIEEE Transactions on Industrial Informatics
Volume14
Issue number8
Online published6 Dec 2017
Publication statusPublished - Aug 2018
Externally publishedYes

Abstract

After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems, which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of the partitioning process. The second step ensures the satisfaction of modeled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

Research Area(s)

  • Agglomerative clustering, network partitioning, parallel restoration, power systems, sectionalizing, smart grid

Citation Format(s)

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration. / Ganganath, Nuwan; Wang, Jing V.; Xu, Xinzhi; Cheng, Chi-Tsun; Tse, Chi K.

In: IEEE Transactions on Industrial Informatics, Vol. 14, No. 8, 8166784, 08.2018, p. 3325-3333.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review