Reconfiguration Strategy for DC Distribution Network Fault Recovery Based on Hybrid Particle Swarm Optimization

Minsheng Yang, Jianqi Li, Jianying Li, Xiaofang Yuan and Jiazhu Xu
Additional contact information
Minsheng Yang: College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
Jianqi Li: College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
Jianying Li: College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
Xiaofang Yuan: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Jiazhu Xu: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Energies, 2021, vol. 14, issue 21, 1-15

Abstract: DC distribution network faults seriously affect the reliability of system power supply. Therefore, this paper proposes a fault recovery reconfiguration strategy for DC distribution networks, based on hybrid particle swarm optimization. The original particle swarm algorithm is improved by simplifying the distribution network structure, introducing Lévy Flight, and designing an adaptive coding strategy. First, the distribution network structure is equivalently simplified to reduce the problem dimensionality. Further, the generated branch groups are ensured to satisfy the radial constraints based on the adaptive solution strategy. Subsequently, Lévy flight is introduced to achieve intra-group optimality search for each branch group. The method is simulated in several distribution systems and analyzed in comparison with the particle swarm algorithm, genetic algorithm, and cuckoo algorithm. Finally, the results validate the accuracy and efficiency of the proposed method.

Keywords: adaptive coding strategy; DC distribution network; fault recovery reconfiguration; Lévy flight; particle swarm algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/21/7145/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/21/7145/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:21:p:7145-:d:669783

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().