Metaheuristic-Based Optimization of Multi-DG Placement and Sizing for Improved Efficiency and Voltage Stability Under Weighting Factor Scenarios

Integrating distributed generation (DG) while maintaining grid efficiency and stability presents a critical challenge in modern power systems. The strategic placement and sizing of DG units are paramount, as suboptimal allocation can exacerbate power losses and voltage instability. This study evaluates optimal DG siting and sizing in radial distribution systems using metaheuristic algorithms to balance power loss reduction and voltage stability enhancement. Four algorithms, representing both evolutionary and swarm intelligence approaches, are evaluated under various weighting factor combinations (WFCs) to tackle this multi-objective optimization problem. Results exhibit that PSO consistently outperforms other algorithms across all WFCs, achieving excellent loss reduction while preserving voltage stability. Among WFCs, the loss-prioritized scheme yields the most balanced performance, effectively optimizing system efficiency without compromising voltage security. In contrast, stability-focused configurations exhibit very high losses, leading to suboptimal performance. For sensitivity analysis, PSO shows its robustness across WFCs for the power loss case, while FA shows similar characteristics for the voltage stability case. These findings approve PSO with lossprioritized WFCs for reliable DG optimization, helping utilities to enhance efficiency while avoiding reverse power flow risks.