Optimizing the Size and Siting of Distributed Generation in Unbalanced Distribution Systems with Multi-objective Reptile Search Algorithm - Arabian Journal for Science and Engineering

Optimizing the Size and Siting of Distributed Generation in Unbalanced Distribution Systems with Multi-objective Reptile Search Algorithm is a research-focused study on improving how distributed generation (DG) is placed and sized in unbalanced distribution systems. The paper reviews multiple optimization strategies, starting with Big Bang-Big Crunch methods to minimize energy losses and extending earlier work to reduce peak-hour grid energy costs. It discusses firefly algorithms for identifying ideal DG locations and capacities, and fuzzy membership functions to merge objectives such as investment cost, voltage stability, unbalance reduction, and reliability into a single objective formulation. The approach uses sensitivity-based solution strategies and can reduce computation by narrowing feasible DG placement to subsets of buses. Additional comparisons include hybrid grey wolf and particle swarm optimization, PSO combined with the analytical 2/3 rule, and methods pairing EDM with steepest descent. A chaotic Big Bang-Big Crunch variant is introduced to improve loss and voltage fluctuation outcomes via chaos-driven initialization and search.