Intelligent Power Distribution Restoration Based on a Multi-Objective Bacterial Foraging Optimization Algorithm

Carlos Henrique Valério de Moraes, Jonas Lopes de Vilas Boas, Germano Lambert-Torres, Gilberto Capistrano Cunha de Andrade and Claudio Inácio de Almeida Costa
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Carlos Henrique Valério de Moraes: Institute of Systems Engineering and Information Technology, Itajuba Federal University, Itajuba 37500-903, Brazil
Jonas Lopes de Vilas Boas: Institute of Systems Engineering and Information Technology, Itajuba Federal University, Itajuba 37500-903, Brazil
Germano Lambert-Torres: R&D Department, Gnarus Institute, Itajuba 37500-052, Brazil
Gilberto Capistrano Cunha de Andrade: R&D Department, Gnarus Institute, Itajuba 37500-052, Brazil
Claudio Inácio de Almeida Costa: R&D Department, Gnarus Institute, Itajuba 37500-052, Brazil

Energies, 2022, vol. 15, issue 4, 1-23

Abstract: The importance of power in society is indisputable. Virtually all economic activities depend on electricity. The electric power systems are complex, and move studies in different areas are motivated to make them more efficient and solve their operational problems. The smart grids emerged from this approach and aimed to improve the current systems and integrate electric power using alternative and renewable sources. Restoration techniques of these networks are being developed to reduce the impacts caused by the usual power supply interruptions due to failures in the distribution networks. This paper presents the development and evaluation of the performance of a multi-objective version of the Bacterial Foraging Optimization Algorithm for finding the minor handling switches that maximize the number of buses served, keeping the configuration radial system and within the limits of current in the conductors and bus voltage. An electrical system model was created, and routines were implemented for the network verification, which was used as a function of the Multi-Objective Bacterial Foraging Optimization Hybrid Algorithm. The proposed method has been applied in two distribution systems with 70 buses and 201 buses, respectively, and the algorithm’s effectiveness to solve the restoration problem is discussed.

Keywords: bio-inspired algorithms; multi-objective optimization; network reconfiguration; distribution system; smart grids (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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