<![CDATA[This work presents a comparative evaluation of adaptive particle swarm optimization (PSO) variants for the optimal placement and sizing (OPS) of photovoltaic-based distributed generation (PV-DG) and DSTATCOM units in the standard IEEE 33-bus radial distribution network (RDN). Five adaptive PSO algorithms are investigated, namely adaptive acceleration coefficients PSO (AAC-PSO), autonomous particle groups PSO (APG-PSO), nonlinear dynamic acceleration coefficients PSO (NDAC-PSO), sine-cosine acceleration coefficients PSO (SCAC-PSO), and time-varying acceleration PSO (TVA-PSO). The optimization framework is structured as a single-objective problem focused on maximizing the active power loss index (APLI), which is used as a normalized indicator associated with active power loss reduction. To further assess the technical quality of the obtained solutions, two additional performance indicators are considered, namely the total voltage deviation (TVD) and the voltage stability index (VSI). The simulation outcomes indicate that the TVA-PSO algorithm exhibits superior overall performance compared to other evaluated variants in terms of convergence behavior and solution quality. In particular, it achieves the highest APLI value of 92.52%, corresponding to an active power loss reduction of 91.91%, with active power losses (APL) reduced from 210.99 kW to 17.07 kW. In addition, the obtained solution significantly improves the network voltage profile (VP) and enhances voltage stability. These findings provide evidence that the effectiveness of adaptive PSO strategies for optimizing PV-DG and DSTATCOM integration in RDN.]]>
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