Power distribution network expansion planning to improve resilience

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‐increasin...

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Veröffentlicht in:IET generation, transmission & distribution transmission & distribution, 2023-11, Vol.17 (21), p.4701-4716
Hauptverfasser: Saberi, Reza, Falaghi, Hamid, Esmaeeli, Mostafa, Ramezani, Maryam, Ashoornezhad, Ali, Izadpanah, Reza
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1751-8687
1751-8695
DOI:10.1049/gtd2.12751