Loop-Based Encoding and Decoding Algorithms for Distribution Network Reconfiguration

The distribution network reconfiguration (DNR) improves the operational efficiency of the distribution network (DN) through changing the open/closed status of switches. However, since numerous switches are complexly connected, topology analysis to determine whether it is radial requires a lot of tim...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on power delivery Jg. 38; H. 4; S. 2573 - 2584
Hauptverfasser: Kim, Hyun-Woo, Ahn, Seon-Ju, Yun, Sang-Yun, Choi, Joon-Ho
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Artificial intelligence
Distribution network reconfiguration
Distribution networks
genetic algorithm
Genetic algorithms
global optimal configuration
Global optimization
loop based
loss minimization
Network topology
Optimization
Reconfiguration
Search problems
Searching
Switches
Topology
topology analysis
ISSN:0885-8977, 1937-4208
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The distribution network reconfiguration (DNR) improves the operational efficiency of the distribution network (DN) through changing the open/closed status of switches. However, since numerous switches are complexly connected, topology analysis to determine whether it is radial requires a lot of time and effort. This paper proposes an encoding and decoding algorithm based on the loop, the fundamental structure of the DN, for effectively finding the global optimal configuration in any DN. The encoding algorithm consisted of reduction, simplification, and loop search systematically organizes the DN, and significantly reduces the search space for the DNR problem. The decoding algorithm consisted of branch switch set (BSS) selection criteria and data modification provides the methods for strategically selecting the switches that satisfy the radial structure. Additionally, the independent operations of multiple sources can be applied to proposed algorithms easily through the virtual branch. The validity and performance of the proposed algorithms are verified through the DNR case study using a genetic algorithm (GA) in the IEEE 33, 69, and 118 bus DNs. In addition, a two-stage GA algorithm is implemented to improve the convergence speed and global optimization search rate. Finally, the performance of the proposed algorithm is compared to other methods.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2023.3247826