Reconfiguring Smart Grid Systems for Low-Cost and High Performance via Optimal DG and Capacitor Placement Considering DR and BESS
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s42835-026-02997-1
- Dergi Adı: JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Compendex, INSPEC, Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Erciyes Üniversitesi Adresli: Evet
Özet
The static structure and limited control capabilities of traditional distribution networks are increasingly insufficient to meet the growing and variable energy demands of today. Therefore, there is a need for smart grid solutions that can enhance the flexibility, stability, reliability, and economic performance of distribution systems. In the literature, studies have examined distributed generation (DG) units and capacitors in conjunction with network reconfiguration (NR); however, smart grid components such as battery energy storage system (BESS) and demand response (DR) are often neglected. In this study, the optimization of DG and capacitor placement along with NR is carried out in a smart grid considering the presence of BESS and DR. The main objective of this work is to improve the technical and economic performance of an 86-bus distribution system by minimizing the total system cost and voltage deviation. The total system cost includes the installation, purchase, and operational costs of DG and capacitors, as well as the cost associated with active power losses. Optimization studies are performed under peak load conditions using Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Salp Swarm Algorithm (SSA). The results indicate that the PSO algorithm provides the best objective function values across all considered scenarios. PSO based optimization of NR, DG, and capacitor placement incorporating BESS and DR leads to an approximately 82% improvement in the objective function value compared to the conventional Case 1 scenario.