Dynamic Reconfiguration Strategies for Improved Electric Vehicle Integration in Power Distribution Networks
Power distribution networks face significant challenges, including high active and reactive power losses, especially with the increasing integration of electric vehicles (EVs). These issues not only reduce system efficiency but also escalate operational costs and compromise voltage stability, impacting the quality of electricity delivered to end-users. Addressing this, this study explores the application of Binary Particle Swarm Optimization (BPSO) to optimize the reconfiguration of a 20 kV distribution network. By strategically adjusting switch configurations, the method aims to minimize power losses and improve voltage profiles. The results demonstrate a substantial reduction in active power loss from 0.70873 kW to 0.046596 kW and reactive power loss from 0.30033 kVAR to 0.054893 kVAR, underscoring the efficacy of BPSO in achieving energy efficiency and voltage stability. This research validates BPSO as a practical tool for real-time network reconfiguration, offering significant potential for enhancing the reliability and efficiency of modern power distribution systems.
Authors
- Novian Patria Uman Putra (ORCID: https://orcid.org/0000-0001-9354-0054)
- Ni Ketut Aryani (ORCID: https://orcid.org/0009-0006-4892-7130)
- Vicky Andria Kusuma (ORCID: https://orcid.org/0000-0002-6315-1696)
- Dimas Fajar Uman Putra (ORCID: https://orcid.org/0000-0001-6760-2637)
- Wahyu Setyo Pambudi (ORCID: https://orcid.org/0000-0001-7180-1102)
- Aji Akbar Firdaus (ORCID: https://orcid.org/0000-0001-5731-6629)
- Misbahul Munir (ORCID: https://orcid.org/0000-0002-4373-6662)
Institutions
- Sepuluh Nopember Institute of Technology (ID)
- Institut Teknologi Kalimantan (ID)
- Institut Teknologi Adhi Tama Surabaya (ID)
Publication Details
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/isriti64779.2024.10963364
- Citations
- 1
- Primary Topic
- Electric and Hybrid Vehicle Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.20