DG, SOP, and EVCS deployment in a distribution system: Multi-Scenario analysis using HHO and TLBO

The rapid integration of distributed energy resources and power-electronic-interfaced loads requires sophisticated planning techniques for modern radial distribution systems (RDS). In this paper, we propose a comprehensive multi-objective optimization framework for the coordinated placement and size of electric vehicle charging stations (EVCS), distributed generations (DGs), and soft open points (SOPs) in RDS. The developed objective function concurrently minimizes loss, improves the voltage profile, enhances the power factor, reduces harmonic distortion, and maximizes the utilization of substation capacity, subject to operational and technical constraints. Teaching Learning Based Optimization (TLBO) and Harris Hawks Optimization (HHO) were used and compared to evaluate solution resilience and convergence efficiency. The outcomes showed that system coordination consistently improved network efficiency, voltage stability, feeder balance, and power quality. Coordinated multi-device integration delivered better technical performance and ensured steady operation within regulatory voltage and harmonic limits. The robustness and dependability of the suggested optimization framework were validated through statistical analysis, which showed that HHO outperformed TLBO in terms of convergence behavior and solution quality. In addition to improving technical performance, the suggested framework supports the development of sustainable power systems by encouraging the integration of renewable energy sources, grid modernization, and the adoption of electrified transportation. The study supports SDGs 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure), 11 (Sustainable Cities and Communities), and 13 (Climate Action). Overall, the suggested coordinated optimization approach offers a scalable and long-lasting solution for active distribution networks prepared for the future.