Optimal Reconfiguration of Unbalanced Distribution Systems Considering Electric Vehicles

Document Type : Research article

Authors

1 Department of electrical engineering, Firouzabad higher education center, Shiraz university of technology, Shiraz, Iran.

2 Department of Electrical Engineering, Firouzabad higher education center, Shiraz university of technology, Shiraz, Iran

3 Department of Electrical Engineering, Firouzabad higher education center, Shiraz university of technology, Shiraz, Iran.

4 Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran

10.61882/jgeri.2026.2068409.1067
Abstract
The growth of industrial centers and loads in distribution systems results in increased system losses and unacceptable voltage deviations, imposing significant costs on electric power distribution companies. Distribution System Reconfiguration (DSR) to achieve real power loss reduction at minimal cost is a cost-effective approach to overcome these issues. Furthermore, with the increasing use of Plug-in Electric Vehicles (PEVs), the demand in the distribution system will further rise which have negative impacts on the distribution system in terms of losses and voltage drops. In this paper, the DSR considering electric vehicles and Distributed Generation (DG) is performed. The reconfiguration is accomplished using DIgSILENT PowerFactory software to achieve the minimum real power losses at minimal cost based on finding optimized open ring points. The results show that reconfiguration with and without the presence of electric vehicles can improve the technical performance indices and utilizing the Vehicle-to-Grid (V2G) system and DG units improve system operational performance. Simulation results on the IEEE 69-bus test system show that network reconfiguration reduces power losses more than 50% in the base case and in V2G operation. Moreover, in the simultaneous presence of electric vehicles and distributed generation, power losses are reduced from 66.76 kW to 48.00 kW, confirming the effectiveness of the proposed method even in highly distributed and unbalanced operating conditions.

Keywords



Articles in Press, Accepted Manuscript
Available Online from 24 February 2026

  • Receive Date 09 August 2025
  • Revise Date 17 December 2025
  • Accept Date 24 February 2026
  • Publish Date 24 February 2026