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In recent times, Distributed Generation (DG) penetration, especially, through Renewable Energy Sources (RES) has been growing immensely due to marginal carbon footprints. Furthermore, they make system more reliable by minimizing the voltage deviation of the distribution network. Nevertheless, to exploit the DGs in the best manner, they need to be sited and rated optimally. Diverse solutions exist for the problem mainly classified as: analytical approaches, classical non-linear optimization algorithms and meta-heuristic methods. With the objective of minimizing power loss, this manuscript proposes a novel hybrid meta-heuristics approach: Particle Swarm Optimization-Coral Reef Optimization (PSO-CRO) for identifying an optimum positioning and rating of Type-1, Type-2 &#x0026; Type-3 DGs (at 0.82 optimal power factor) in IEEE 33, 69 &#x0026; 118 bus Radial Distributed System (RDS). Furthermore, the results from the proposed hypothesis are compared with its prevalent peers, namely, PSO, CRO, Gravitational Search Algorithm (GSA), PSO-GSA and PSO-Grey Wolf Optimization (PSO-GWO) etc. The results of the proposed algorithm are also compared with the results of GAMS/CONOPT commercial solver. The simulation results prove the robustness, higher efficacy and faster convergence of the proposed method when applied to larger distribution systems.

Novel Real Valued Improved Coral-Reef Optimization Algorithm for Optimal Integration of Classified Distributed Generators