Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

Jorge SABATTIN; Guillermo FUERTES; Miguel ALFARO; Luis QUEZADA; Manuel VARGAS

Article Details

Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

Authors:

Jorge SABATTIN | Guillermo FUERTES | Miguel ALFARO | Luis QUEZADA | Manuel VARGAS

Publisher:

TUBITAK

Journal:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2648-2660

Document Type:

Article

Publication Date:

9/2018

Document Language:

Turkish

Document ID (Org No.):

2000734822

Frequency:

Bimonthly

eISSN:

1303-6203

pISSN:

1300-0632

Abstract:

 

The study of electrical distribution of primary networks design is oriented to reduce the construction costs and the energy losses by transmission. The topology for the implementation of distribution networks may vary according to the geographical characteristics of the final users and requires specialized optimization solutions with metaheuristics to improve the energy performance of the electrical power systems. A parallel genetic algorithm (PGA) is proposed to optimize a tree-based topology for large-scale electric power distribution networks. The proposed PGA uses the dandelion code, which allows obtaining tree-feasible solutions within each iteration of the PGA. This cannot be achieved with other metaheuristic approaches directly. Eight cores are used simultaneously. We achieve a 22.05 % improvement when compared to the tree-feasible solutions obtained with its sequential version. Moreover, the computational time required by the PGA is on average 23 times lower than the sequential version. Finally, we find feasible solutions for instances of the problem with up to 50,000 nodes.

Article Details

Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

Authors: Jorge SABATTIN | Guillermo FUERTES | Miguel ALFARO | Luis QUEZADA | Manuel VARGAS

Publisher: TUBITAK

Journal: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2648-2660

Document Type: Article

Publication Date: 9/2018

Document Language: Turkish

Document ID (Org No.): 2000734822

Frequency: Bimonthly

eISSN: 1303-6203

pISSN: 1300-0632

Issues

Authors:

Jorge SABATTIN | Guillermo FUERTES | Miguel ALFARO | Luis QUEZADA | Manuel VARGAS

Publisher:

TUBITAK

Journal:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2648-2660

Document Type:

Article

Publication Date:

9/2018

Document Language:

Turkish

Document ID (Org No.):

2000734822

Frequency:

Bimonthly

eISSN:

1303-6203

pISSN:

1300-0632