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

Area of Science:

• Electrical Engineering
• Optimization Algorithms
• Renewable Energy Systems

Background:

• Active distribution networks require efficient integration of renewable energy sources.
• Optimal placement and sizing of photovoltaic (PV) and battery energy storage systems (BESS) are crucial for grid stability and cost reduction.
• Existing optimization methods may not fully address the complexities of PV-BESS integration.

Purpose of the Study:

• To propose an enhanced Bald Eagle Search (BES) optimization framework.
• To determine the optimal allocation and sizing of PV and BESS in active distribution networks.
• To minimize total operating cost and energy losses while enhancing voltage stability.

Main Methods:

• Implementation of an enhanced Bald Eagle Search (BES) algorithm.
• Validation on IEEE 33-bus and IEEE 69-bus test systems.
• Comparative analysis against Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA).

Main Results:

• BES algorithm demonstrated superior performance over GA and WOA.
• Significant reductions in daily energy losses (up to 55%) and operating costs achieved.
• Improved minimum bus voltage in both PV-only and PV-BESS scenarios across test systems.

Conclusions:

• The proposed BES framework is robust, scalable, and effective for optimal PV-BESS integration.
• BES offers a promising solution for enhancing the efficiency and stability of active distribution networks.
• The study confirms the effectiveness of BES in minimizing costs and energy losses.