### Abstract

The clustering of networks in order to optimise one or more given objectives is a highly researched field with many real-world applications. One of these applications is the clustering of a current or potential future electricity network in order to identify an optimised network topology that could consist of microgrids and stand-alone power systems. This research paper gives a brief overview of the current applications of network partitioning and the different methodologies found in the literature. Then, a novel evolutionary algorithm approach is presented which optimises the topology of rural electricity distribution networks considering a problem-specific objective cost function. Given a set of electricity customer loads and locations, the aim is to identify optimal microgrid and standalone power system formations to minimise the total network costs over a certain time period. The latter part entails a brief introduction to microgrids and some theoretical background, a description of the evaluated cost function, and an outline of the problem-specific evolutionary algorithm used for optimising the network.

Original language | English |
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Title of host publication | 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings |

Publisher | IEEE, Institute of Electrical and Electronics Engineers |

Pages | 2498-2505 |

Number of pages | 8 |

ISBN (Electronic) | 9781728121536 |

DOIs | |

Publication status | Published - 1 Jun 2019 |

Event | 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand Duration: 10 Jun 2019 → 13 Jun 2019 |

### Publication series

Name | 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings |
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### Conference

Conference | 2019 IEEE Congress on Evolutionary Computation, CEC 2019 |
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Country | New Zealand |

City | Wellington |

Period | 10/06/19 → 13/06/19 |

### Fingerprint

### Cite this

*2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings*(pp. 2498-2505). [8790232] (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CEC.2019.8790232

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*2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings.*, 8790232, 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, IEEE, Institute of Electrical and Electronics Engineers, pp. 2498-2505, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, Wellington, New Zealand, 10/06/19. https://doi.org/10.1109/CEC.2019.8790232

**Identifying Isolated Microgrids in Rural Areas : An Evolutionary Algorithm Approach for a Graph Clustering Problem.** / Rosenberg, Manou; Fletcher, James; Reynolds, Mark; French, Tim; While, Lyndon.

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

TY - GEN

T1 - Identifying Isolated Microgrids in Rural Areas

T2 - An Evolutionary Algorithm Approach for a Graph Clustering Problem

AU - Rosenberg, Manou

AU - Fletcher, James

AU - Reynolds, Mark

AU - French, Tim

AU - While, Lyndon

PY - 2019/6/1

Y1 - 2019/6/1

N2 - The clustering of networks in order to optimise one or more given objectives is a highly researched field with many real-world applications. One of these applications is the clustering of a current or potential future electricity network in order to identify an optimised network topology that could consist of microgrids and stand-alone power systems. This research paper gives a brief overview of the current applications of network partitioning and the different methodologies found in the literature. Then, a novel evolutionary algorithm approach is presented which optimises the topology of rural electricity distribution networks considering a problem-specific objective cost function. Given a set of electricity customer loads and locations, the aim is to identify optimal microgrid and standalone power system formations to minimise the total network costs over a certain time period. The latter part entails a brief introduction to microgrids and some theoretical background, a description of the evaluated cost function, and an outline of the problem-specific evolutionary algorithm used for optimising the network.

AB - The clustering of networks in order to optimise one or more given objectives is a highly researched field with many real-world applications. One of these applications is the clustering of a current or potential future electricity network in order to identify an optimised network topology that could consist of microgrids and stand-alone power systems. This research paper gives a brief overview of the current applications of network partitioning and the different methodologies found in the literature. Then, a novel evolutionary algorithm approach is presented which optimises the topology of rural electricity distribution networks considering a problem-specific objective cost function. Given a set of electricity customer loads and locations, the aim is to identify optimal microgrid and standalone power system formations to minimise the total network costs over a certain time period. The latter part entails a brief introduction to microgrids and some theoretical background, a description of the evaluated cost function, and an outline of the problem-specific evolutionary algorithm used for optimising the network.

KW - genetic algorithm

KW - graph clustering

KW - microgrid identification

KW - microgrids

KW - network clustering

KW - subgraph identification

UR - http://www.scopus.com/inward/record.url?scp=85071317871&partnerID=8YFLogxK

U2 - 10.1109/CEC.2019.8790232

DO - 10.1109/CEC.2019.8790232

M3 - Conference paper

T3 - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

SP - 2498

EP - 2505

BT - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

ER -