Abstract—Many areas in power systems require solving one
or more nonlinear optimization problems. While analytical
methods might suffer from slow convergence and the curse of
dimensionality, heuristics-based swarm intelligence can be an
efficient alternative. Particle swarm optimization (PSO), part
of the swarm intelligence family, is known to effectively solve
large-scale nonlinear optimization problems. This paper presents
a detailed overview of the basic concepts of PSO and its variants.
Also, it provides a comprehensive survey on the power system
applications that have benefited from the powerful nature of PSO
as an optimization technique. For each application, technical
details that are required for applying PSO, such as its type, particle
formulation (solution representation), and the most efficient
fitness functions are also discussed.