Reconfiguration of 123-bus unbalanced power distribution network analysis by considering minimization of current & voltage unbalanced indexes and power loss


NACAR ÇIKAN N., ÇIKAN M.

International Journal of Electrical Power and Energy Systems, vol.157, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 157
  • Publication Date: 2024
  • Doi Number: 10.1016/j.ijepes.2024.109796
  • Journal Name: International Journal of Electrical Power and Energy Systems
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: 123-Bus Unbalanced Power Distribution Test System, OpenDSS, Reconfiguration, Slime Mould Algorithm, Voltage and Current Unbalance Index
  • Çukurova University Affiliated: Yes

Abstract

Reconfiguration is an efficient solution for loss minimization and system improvement in the power distribution network (PDN). Although reconfiguration has been studied for a long time, most works to date approach the problem considering the system balanced with constant PQ-load, while real PDNs are unbalanced due to uneven loads. On the other hand, unbalanced loadings can lead to increased energy losses, violate capacity limits, and affect power quality, resulting in voltage and current unbalance (CVU). Therefore, methods that mitigate the adverse effects of CVU are necessary. In this paper, the slime mould algorithm (SMA) is used to solve the reconfiguration problem (RecPrb) in a 123-bus unbalanced system with the objectives of minimization of power loss, the current unbalance index (CUI), and voltage unbalance index (VUI). The system is evaluated in two parts by considering many cases where power losses and unbalanced indexes are gradually minimized with the presented scenarios. A three-phase unbalanced backward-forward-load-flow Matlab script is written, and all simulations are run in the Matlab environment. The test system is built in OpenDSS and Matlab/Simulink to verify the script's correctness, and the obtained results are also validated with the IEEE-PES data. The effectiveness of the SMA method is further assessed by comparing it with well-known EO and DE algorithms using over 15 statistical methods to find the most efficient algorithm that solves the RecPrbs of unbalanced test systems. The results demonstrate the robustness and efficiency of the SMA method in minimizing losses, limiting unbalanced indexes, and improving the system's voltage profile.