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Computer Science > Artificial Intelligence

arXiv:2205.10126 (cs)
[Submitted on 14 May 2022]

Title:On Evaluating Power Loss with HATSGA Algorithm for Power Network Reconfiguration in the Smart Grid

Authors:Flavio Galvao Calhau, Alysson Pezzutti, Joberto S. B. Martins
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Abstract:This paper presents the power network reconfiguration algorithm HATSGA with a "R" modeling approach and evaluates its behavior in computing new reconfiguration topologies for the power network in the Smart Grid context. The modeling of the power distribution network with the language "R" is used to represent the network and support the computation of distinct algorithm configurations towards the evaluation of new reconfiguration topologies. The HATSGA algorithm adopts a hybrid Tabu Search and Genetic Algorithm strategy and can be configured in different ways to compute network reconfiguration solutions. The evaluation of power loss with HATSGA uses the IEEE 14-Bus topology as the power test scenario. The evaluation of reconfiguration topologies with minimum power loss with HATSGA indicates that an efficient solution can be reached with a feasible computational time. This suggests that HATSGA can be potentially used for computing reconfiguration network topologies and, beyond that, it can be used for autonomic self-healing management approaches where a feasible computational time is required.
Comments: 7 pp
Subjects: Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:2205.10126 [cs.AI]
  (or arXiv:2205.10126v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2205.10126
Journal reference: Proceedings of the IV International Workshop on ADVANCEs in ICT Infrastructures and Services 2017
Related DOI: https://doi.org/10.5281/zenodo.1066496

Submission history

From: Joberto Martins Prof. Dr. [view email]
[v1] Sat, 14 May 2022 22:05:15 UTC (399 KB)
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