Optimal location and sizing of distributed generators in dc networks using a hybrid method based on parallel pbil and pso

This paper addresses the problem of the locating and sizing of distributed generators (DGs) in direct current (DC) grids and proposes a hybrid methodology based on a parallel version of the Population-Based Incremental Learning (PPBIL) algorithm and the Particle Swarm Optimization (PSO) method. The...

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Autores:
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Ramos-Paja, Carlos Andrés
Hernandez-Escobedo, Quetzalcoatl
Perea-Moreno, Alberto-Jesus
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/9996
Acceso en línea:
https://hdl.handle.net/20.500.12585/9996
https://www.mdpi.com/2079-9292/9/11/1808
Palabra clave:
Direct current grids
Distributed generation
Combinatorial optimization
Parallel processing tool
Optimal power flow analysis
Power loss reduction
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description
Summary:This paper addresses the problem of the locating and sizing of distributed generators (DGs) in direct current (DC) grids and proposes a hybrid methodology based on a parallel version of the Population-Based Incremental Learning (PPBIL) algorithm and the Particle Swarm Optimization (PSO) method. The objective function of the method is based on the reduction of the power loss by using a master-slave structure and the consideration of the set of restrictions associated with DC grids in a distributed generation environment. In such a structure, the master stage (PPBIL) finds the location of the generators and the slave stage (PSO) finds the corresponding sizes. For the purpose of comparison, eight additional hybrid methods were formed by using two additional location methods and two additional sizing methods, and this helped in the evaluation of the effectiveness of the proposed solution. Such an evaluation is illustrated with the electrical test systems composed of 10, 21 and 69 buses and simulated on the software, MATLAB. Finally, the results of the simulation demonstrated that the PPBIL–PSO method obtains the best balance between the reduction of power loss and the processing time.