Research on Fault Location Method of Distribution Network Based on Archimedes Optimization Algorithm

To address the challenges of high dimensionality, nonlinearity, and multiple constraints in distribution network fault location, where traditional intelligent optimization algorithms are prone to local optima and slow convergence, this paper proposes a fault location method based on the Archimedes O...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Processes Ročník 13; číslo 11; s. 3715
Hlavní autoři: Zhang, Jiajun, Zhang, Haifeng, Lin, Runzi, Zhou, Shuyu, Yan, Jing, Li, Juan, Zhang, Fang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 18.11.2025
Témata:
Algorithms
Archimedes
Convergence
Exploitation
Fault location
Fault tolerance
Mathematical optimization
Methods
Nonlinear systems
Optimization
Optimization algorithms
ISSN:2227-9717, 2227-9717
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:To address the challenges of high dimensionality, nonlinearity, and multiple constraints in distribution network fault location, where traditional intelligent optimization algorithms are prone to local optima and slow convergence, this paper proposes a fault location method based on the Archimedes Optimization Algorithm (AOA). By constructing a fault state encoding model for the distribution network, the fault location problem is transformed into a binary optimization problem. Leveraging the global search capability and convergence characteristics of the AOA, rapid and accurate location of faulty sections is achieved. Simulation experiments based on the IEEE 33-node system under various fault scenarios, including single-point and multi-point faults, demonstrate that the proposed method outperforms comparative algorithms in terms of convergence speed.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2227-9717
2227-9717
DOI:10.3390/pr13113715