Multi-Objective Placement and Sizing of multiple DGs and DSTATCOMs in Unbalanced Distribution Network using CPSOS Approach.

This paper introduces a Multi-Objective Chaotic Particle Swarm Optimization with Sigmoid-based (MO-CPSOS) acceleration coefficient approach for optimal placement and sizing of Distributed Generators (DG) and DSTATCOMs in an unbalanced radial distribution network The MO-CPSOS approach utilizes a logistic map to generate well-distributed initial particles efficiently and employs sigmoid-based acceleration coefficients to balance global search and convergence. By integrating exploration and exploitation, this approach enhances both global and local search capabilities of the particle swarm optimization (PSO) algorithm. The study formulates the optimization problem as a multi-objective function, targeting the reduction of total real power loss, enhancement of voltage balance, and improvement of the voltage profile through optimal placement and sizing of DG and DSTATCOM devices. Computational efficiency and performance of the MO-CPSOS approach are conducted, comparing its efficacy against the standard PSO method across various test cases. The validity of the proposed approach is demonstrated through simulations conducted on the IEEE 37 bus test systems.