Security-Constrained Optimal Power Flow Solved With a Dynamic Multichain Particle Swarm Optimizer

This paper presents a dynamic multichain particle swarm optimization (DMCPSO) algorithm to solve the security-constrained optimal power flow (SCOPF) problem, which aims to minimize the predefined cost while taking both system capacity requirements and operating security constraints into account. The DMCPSO is based on a dynamic multichain topology and an adaptive parameter control mechanism. The dynamic multichain topology organizes the swarm population in the chain structure at both the individual and subpopulation levels. Different particles can play different roles in this topology to enhance both exploration and exploitation via local and global communication mechanisms. Moreover, to boost the benefits brought by this topology, three types of parameters, i.e., the inertia weight w, scaling factor F, and mutation probability $p$ are controlled in an adaptive manner to further boost exploration and exploitation. Numerical results demonstrate the superior performance of the proposed DMCPSO over three reference PSO algorithms in the literature.