### Abstract

Original language | English |
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Title of host publication | IEEE International Symposium on Industrial Electronics Proceedings |

Publisher | IEEE, Institute of Electrical and Electronics Engineers |

Pages | 20-25 |

Volume | 2015-September |

ISBN (Print) | 9781467375542 |

DOIs | |

Publication status | Published - 2015 |

Event | A case study on optimizing an electrical distribution network using a genetic algorithm - Buzios, Rio de Janeiro Duration: 1 Jan 2015 → … |

### Conference

Conference | A case study on optimizing an electrical distribution network using a genetic algorithm |
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Period | 1/01/15 → … |

### Fingerprint

### Cite this

*IEEE International Symposium on Industrial Electronics Proceedings*(Vol. 2015-September, pp. 20-25). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISIE.2015.7281437

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*IEEE International Symposium on Industrial Electronics Proceedings.*vol. 2015-September, IEEE, Institute of Electrical and Electronics Engineers, pp. 20-25, A case study on optimizing an electrical distribution network using a genetic algorithm, 1/01/15. https://doi.org/10.1109/ISIE.2015.7281437

**A case study on optimizing an electrical distribution network using a genetic algorithm.** / Fletcher, James; Fernando, Tyrone; Iu, Ho Ching; Reynolds, Mark; Fani, S.

Research output: Chapter in Book/Conference paper › Conference paper

TY - GEN

T1 - A case study on optimizing an electrical distribution network using a genetic algorithm

AU - Fletcher, James

AU - Fernando, Tyrone

AU - Iu, Ho Ching

AU - Reynolds, Mark

AU - Fani, S.

PY - 2015

Y1 - 2015

N2 - © 2015 IEEE. This paper presents an evolutionary approach for optimizing the topology of rural electrical distribution networks. The primary objective of this project is to determine if the rural distribution network for a case study has expanded in an optimal manner through finding the shortest weighted path between network customers, thereby establishing the cost. Currently, there are large portions of the distribution network assets in rural areas that are nearing end of life and will need to be replaced in the near future. This presents the opportunity to redesign the routing of the network through the consideration of all customers, with the expectation that the length of the network and thus the level of investment will be reduced. The minimum spanning tree (MST) and genetic algorithm (GA) are used to compute the optimized path throughout a constraint weighted area. The results indicate that the optimized path of the network produces a considerable reduction in the total cost.

AB - © 2015 IEEE. This paper presents an evolutionary approach for optimizing the topology of rural electrical distribution networks. The primary objective of this project is to determine if the rural distribution network for a case study has expanded in an optimal manner through finding the shortest weighted path between network customers, thereby establishing the cost. Currently, there are large portions of the distribution network assets in rural areas that are nearing end of life and will need to be replaced in the near future. This presents the opportunity to redesign the routing of the network through the consideration of all customers, with the expectation that the length of the network and thus the level of investment will be reduced. The minimum spanning tree (MST) and genetic algorithm (GA) are used to compute the optimized path throughout a constraint weighted area. The results indicate that the optimized path of the network produces a considerable reduction in the total cost.

U2 - 10.1109/ISIE.2015.7281437

DO - 10.1109/ISIE.2015.7281437

M3 - Conference paper

SN - 9781467375542

VL - 2015-September

SP - 20

EP - 25

BT - IEEE International Symposium on Industrial Electronics Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

ER -