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**Harvard**

Cadenovic, R., Jakus, D., Sarajcev, P. och Vasilj, J. (2017) *Optimal reconfiguration of distribution network using cycle-break/genetic algorithm*.

** BibTeX **

@conference{

Cadenovic2017,

author={Cadenovic, Rade and Jakus, Damir and Sarajcev, Petar and Vasilj, Josip},

title={Optimal reconfiguration of distribution network using cycle-break/genetic algorithm},

booktitle={2017 IEEE Manchester PowerTech, Powertech 2017; Manchester; United Kingdom; 18 June 2017 through 22 June 2017},

isbn={978-150904237-1},

abstract={This paper presents novel approach for optimal distribution network reconfiguration using the combination of cycle-break algorithm and genetic algorithms. Significant improvements are introduced in the phases of initial population generation as well as other general operations inside genetic algorithm. These improvements lead to better convergence rate and computational time reduction. Even though genetic algorithms are widely used, problems related to inapplicability for real-size are often present. These problems are related to the high individual rejection rate due to violation of system constraints and distribution network radial structure requirements. Utilization of combined cycle-break algorithm and genetic algorithm solves these issues and allow real-size network application. Acknowledging this fact, algorithm described in the paper is used to find optimal distribution network topology while fulfilling system constraints and maintaining radial network requirements in all solution steps. The proposed algorithm for optimal distribution network reconfiguration is tested on several standard IEEE test cases. Optimal distribution network reconfiguration can be found under minimum network loss or optimal network loading framework.},

year={2017},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 252101

A1 Cadenovic, Rade

A1 Jakus, Damir

A1 Sarajcev, Petar

A1 Vasilj, Josip

T1 Optimal reconfiguration of distribution network using cycle-break/genetic algorithm

YR 2017

T2 2017 IEEE Manchester PowerTech, Powertech 2017; Manchester; United Kingdom; 18 June 2017 through 22 June 2017

SN 978-150904237-1

AB This paper presents novel approach for optimal distribution network reconfiguration using the combination of cycle-break algorithm and genetic algorithms. Significant improvements are introduced in the phases of initial population generation as well as other general operations inside genetic algorithm. These improvements lead to better convergence rate and computational time reduction. Even though genetic algorithms are widely used, problems related to inapplicability for real-size are often present. These problems are related to the high individual rejection rate due to violation of system constraints and distribution network radial structure requirements. Utilization of combined cycle-break algorithm and genetic algorithm solves these issues and allow real-size network application. Acknowledging this fact, algorithm described in the paper is used to find optimal distribution network topology while fulfilling system constraints and maintaining radial network requirements in all solution steps. The proposed algorithm for optimal distribution network reconfiguration is tested on several standard IEEE test cases. Optimal distribution network reconfiguration can be found under minimum network loss or optimal network loading framework.

LA eng

DO 10.1109/PTC.2017.7980842

LK http://dx.doi.org/10.1109/PTC.2017.7980842

OL 30