<![CDATA[This paper presents an Improved Blue Monkey (IBM) optimization algorithm for enhancing voltage stability and reducing power losses in distribution networks through optimal placement and sizing of Distribution Static Var Compensators (D-SVCs). The IBM algorithm modifies the original Blue Monkey metaheuristic by incorporating a random inertia weight to accelerate convergence and improve exploration-exploitation balance. Benchmark function tests demonstrated the IBM’s superiority over the original BM and Particle Swarm Optimization (PSO) in solution accuracy, stability, and convergence speed. The proposed method was applied to the IEEE 33-bus system under varying load conditions, achieving optimal D-SVC placements at buses 7, 14, and 31, with reductions of 22.17% and 18.15% in active and reactive power losses, respectively, and an increase in minimum voltage from 0.9131 p.u. to 0.9590 p.u. Comparative analysis with the Modified Artificial Rabbit Optimization (MARO) method confirmed the IBM’s consistent performance advantage, including better Fast Voltage Stability Index (FVSI) values. The results validate the IBM algorithm as an effective and robust tool for reactive power compensation optimization in modern power distribution systems.]]>
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