Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm

Distributed generation (DG) is an important issue for distribution networks due to the improvement in power losses, but the location and size of generators could be a difficult task for exact techniques. The metaheuristic techniques have become a better option to determine good solutions and in this...

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Autores:
Candelo-Becerra, John Edwin
Hernández-Riaño, Helman
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60683
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60683
http://bdigital.unal.edu.co/59015/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
bat-inspired algorithm
distributed generation
particle swarm optimization
distribution system.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Distributed generation (DG) is an important issue for distribution networks due to the improvement in power losses, but the location and size of generators could be a difficult task for exact techniques. The metaheuristic techniques have become a better option to determine good solutions and in this paper the application of a bat-inspired algorithm (BA) to a problem of location and size of distributed generation in radial distribution systems is presented. A comparison between particle swarm optimization (PSO) and BA was made in the 33-node and 69-node test feeders, using as scenarios the change in active and reactive power, and the number of generators. PSO and BA found good results for small number and capacities of generators, but BA obtained better results for difficult problems and converged faster for all scenarios. The maximum active power injections to reduce power losses in the distribution networks were found for the five scenarios.