Enhancing Multi-Objective Performance of Radial Distribution Systems with the Equilibrium Optimizer

Distribution networks face challenges in effectively integrating Distributed Generations (DGs). Optimally determining DG locations and capacities can enhance the voltage profile (VP), reduce system losses (AL), and improve the Voltage Stability Index (VSI). This study aims to improve all these three objectives by strategically positioning and sizing DGs. It first improves VP and APL simultaneously, then further enhances both along with VSI. These parameters are crucial for network performance. To evaluate the results, the study employs a new algorithm called equilibrium optimizer (EO), combined with fuzzy decision-making and the weighted sum method to tackle the multi-objective problem. The proposed approach is tested on a 33bus system, with comparisons made against various evolutionary algorithms, including Sine Cosine Algorithm (SCA), Slime Mould Algorithm (SMA), Grasshopper Optimization Algorithm (GOA) and Artificial Bee Colony (ABC). The comparisons highlight the benefits of EO, such as improved computational efficiency, faster convergence, and easier application.