Optimal sizing and placement of hybrid PV-storage systems in microgrids using Bald Eagle Search Algorithm

This study proposes an enhanced Bald Eagle Search (BES) optimization framework for optimal allocation and sizing of photovoltaic (PV) and battery energy storage systems (BESS) in active distribution networks. The objective is to minimize total operating cost and energy losses while improving voltage stability under deterministic load and generation conditions. The proposed approach is validated on IEEE 33-bus and IEEE 69-bus test systems under two scenarios: PV-only and integrated PV–BESS deployment. A comprehensive comparative assessment is conducted against Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA) under identical operating conditions. The results demonstrate that the proposed BES algorithm consistently outperforms the benchmark methods. For the IEEE 69-bus system, BES achieves up to 41% and 55% reduction in daily energy losses for PV-only and PV–BESS cases, respectively, while improving the minimum bus voltage to 0.951 p.u. For the IEEE 33-bus system, BES yields 41.3% and 52% loss reductions under PV-only and PV–BESS configurations, respectively, and enhances the minimum voltage from 0.941 p.u. to 0.962 p.u. In both systems, BES also achieves the lowest operating cost among all compared methods. These findings confirm the robustness, scalability, and effectiveness of the proposed framework across different distribution network topologies.