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Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm (CROSBI ID 277525)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Jakus, Damir ; Čađenović, Rade ; Vasilj, Josip ; Sarajčev, Petar Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm // Energies (Basel), 13 (2020), 7; 1544, 21. doi: 10.3390/en13071544

Podaci o odgovornosti

Jakus, Damir ; Čađenović, Rade ; Vasilj, Josip ; Sarajčev, Petar

engleski

Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm

This paper describes the algorithm for optimal distribution network reconfiguration using the combination of a heuristic approach and genetic algorithms. Although similar approaches have been developed so far, they usually had issues with poor convergence rate and long computational time, and were often applicable only to the small scale distribution networks. Unlike these approaches, the algorithm described in this paper brings a number of uniqueness and improvements that allow its application to the distribution networks of real size with a high degree of topology complexity. The optimal distribution network reconfiguration is formulated for the two different objective functions: minimization of total power/energy losses and minimization of network loading index. In doing so, the algorithm maintains the radial structure of the distribution network through the entire process and assures the fulfilment of various physical and operational network constraints. With a few minor modifications in the heuristic part of the algorithm, it can be adapted to the problem of determining the distribution network optimal structure in order to equalize the network voltage profile. The proposed algorithm was applied to a variety of standard distribution network test cases, and the results show the high quality and accuracy of the proposed approach, together with a remarkably short execution time.

distribution network reconfiguration ; energy losses minimization ; load balancing ; heuristic approach ; genetic algorithm

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Podaci o izdanju

13 (7)

2020.

1544

21

objavljeno

1996-1073

10.3390/en13071544

Povezanost rada

Elektrotehnika

Poveznice
Indeksiranost