Cross-Scale Performance Analysis of Metaheuristic Algorithms for Simultaneous DG and DSTATCOM Placement in Radial Distribution Networks

Abstract

The problem of simultaneous placement of distributed generators and DSTATCOMs in radial distribution networks (RDNs) is a combinatorial mixed-integer optimization problem whose scalability with growing decision dimensionality has been insufficiently explored. A cross-scale analysis of seven metaheuristic algorithms, GWO, SCA, PSO, WOA, GA, HHO and SMA, is conducted on the IEEE 33-bus, 69-bus, and 136-bus systems at three problem dimensions \( d = 4, 8, 12 \), with 30 independent runs per configuration being validated through Wilcoxon and Friedman tests. Mean-performance statistics are extended with a Catastrophic Failure Rate (CFR) metric. The main result will be that dimensional scaling serves as a behavioral discriminator. The Friedman \( χ^2 \) rises with the dimensionality, reaching its maximum value of \( χ^2 = 143.79 \) in the 136-bus at \( d = 12 \) that corresponds to the progressive phase separation of the algorithms into two clusters of high and low performance. GA is the best performer in terms of the lowest rank in all the configurations. SCA has low variance but convergence to increasingly sub-optimal solutions. HHO exhibits catastrophic instability at all scales. Perhaps most strikingly, GA and PSO obtain a \( 3.3\% \) CFR on the 136-bus at \( d = 12 \) while the 33-bus at identical dimensionality has a \( 73\%-83\% \) CFR, showing that topology influences the reliability in a manner that is not captured by single-system measures.