Power distribution network expansion planning to improve resilience
Abstract High‐impact, low‐probability events that cause significant annual damages seriously threaten the health of distribution networks. The effects of these events have made the expansion planning for distribution systems something beyond the traditional reliability criteria, so there is an ever‐...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-11-01
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| Series: | IET Generation, Transmission & Distribution |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/gtd2.12751 |
| _version_ | 1827773665462190080 |
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| author | Reza Saberi Hamid Falaghi Mostafa Esmaeeli Maryam Ramezani Ali Ashoornezhad Reza Izadpanah |
| author_facet | Reza Saberi Hamid Falaghi Mostafa Esmaeeli Maryam Ramezani Ali Ashoornezhad Reza Izadpanah |
| author_sort | Reza Saberi |
| collection | DOAJ |
| description | Abstract High‐impact, low‐probability events that cause significant annual damages seriously threaten the health of distribution networks. The effects of these events have made the expansion planning for distribution systems something beyond the traditional reliability criteria, so there is an ever‐increasing need for modifications in current planning approaches and focusing on the resilience in the expansion planning of distribution networks. The new attitude dealing with resilience and distributed generation sources in distribution networks necessitates a fundamental reconsidering of traditional distribution network planning methods. Here, by modelling common natural disasters such as floods and storms, an appropriate index is introduced to evaluate the distribution network resilience in the presence of distributed generation (DG) sources, including conventional gas‐fired and photovoltaic sources. Then, by presenting an appropriate model for load and photovoltaic production, the problem of comprehensive distribution network planning, including substations, feeders, and DG sources, is mathematically formulated as a multi‐objective optimization problem to improve resilience and optimize costs. Furthermore, a non‐dominated sorting genetic algorithm is used to solve the problem of comprehensively planning a resilient distribution network. Implementation of the proposed model on the IEEE 54‐bus sample network shows that network resilience can be improved with minimum cost by optimal network planning. |
| first_indexed | 2024-03-11T13:26:05Z |
| format | Article |
| id | doaj.art-073c8be9381f40f5a0c886f1abafcb8b |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-03-11T13:26:05Z |
| publishDate | 2023-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-073c8be9381f40f5a0c886f1abafcb8b2023-11-03T06:13:53ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952023-11-0117214701471610.1049/gtd2.12751Power distribution network expansion planning to improve resilienceReza Saberi0Hamid Falaghi1Mostafa Esmaeeli2Maryam Ramezani3Ali Ashoornezhad4Reza Izadpanah5Faculty of Electrical and Computer Engineering University of Birjand Birjand IranFaculty of Electrical and Computer Engineering University of Birjand Birjand IranFaculty of Computer and Industrial Engineering Birjand University of Technology Birjand IranFaculty of Electrical and Computer Engineering University of Birjand Birjand IranFaculty of Electrical and Computer Engineering University of Birjand Birjand IranSouth Khorasan Electricity Distribution Company Birjand IranAbstract High‐impact, low‐probability events that cause significant annual damages seriously threaten the health of distribution networks. The effects of these events have made the expansion planning for distribution systems something beyond the traditional reliability criteria, so there is an ever‐increasing need for modifications in current planning approaches and focusing on the resilience in the expansion planning of distribution networks. The new attitude dealing with resilience and distributed generation sources in distribution networks necessitates a fundamental reconsidering of traditional distribution network planning methods. Here, by modelling common natural disasters such as floods and storms, an appropriate index is introduced to evaluate the distribution network resilience in the presence of distributed generation (DG) sources, including conventional gas‐fired and photovoltaic sources. Then, by presenting an appropriate model for load and photovoltaic production, the problem of comprehensive distribution network planning, including substations, feeders, and DG sources, is mathematically formulated as a multi‐objective optimization problem to improve resilience and optimize costs. Furthermore, a non‐dominated sorting genetic algorithm is used to solve the problem of comprehensively planning a resilient distribution network. Implementation of the proposed model on the IEEE 54‐bus sample network shows that network resilience can be improved with minimum cost by optimal network planning.https://doi.org/10.1049/gtd2.12751distributed generation sourcesdistribution networkexpansion planninggenetic algorithmresilience |
| spellingShingle | Reza Saberi Hamid Falaghi Mostafa Esmaeeli Maryam Ramezani Ali Ashoornezhad Reza Izadpanah Power distribution network expansion planning to improve resilience IET Generation, Transmission & Distribution distributed generation sources distribution network expansion planning genetic algorithm resilience |
| title | Power distribution network expansion planning to improve resilience |
| title_full | Power distribution network expansion planning to improve resilience |
| title_fullStr | Power distribution network expansion planning to improve resilience |
| title_full_unstemmed | Power distribution network expansion planning to improve resilience |
| title_short | Power distribution network expansion planning to improve resilience |
| title_sort | power distribution network expansion planning to improve resilience |
| topic | distributed generation sources distribution network expansion planning genetic algorithm resilience |
| url | https://doi.org/10.1049/gtd2.12751 |
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