Colliding bodies optimization algorithm for optimal reactive power dispatch

This paper presents a novel, meta-heuristic optimization algorithm for the problem of optimal reactive power dispatch in the areas of power system operation and control. The optimal reactive power dispatch problem is huge, and is constrained by a wide range of non-linear and non-convex optimization problems. This optimal reactive power dispatch problem was formulated by generator output voltages (continuous variable), tap changing transformers and a number of switchable VAR devices (discrete variables). This algorithm was established on one-dimensional collisions between bodies, with each operator solution being treated as an object or body with mass. After the collision of two moving bodies with named masses and velocities, these bodies were detached with new velocities. This collision caused the operators to act towards superior positions in the search space. The optimization of the colliding bodies utilized simple formulations to find minimum or maximum of functions and did not depend on any internal parameter. The proposed colliding bodies optimization algorithm was tested on IEEE-6 bus and IEEE-14 bus systems. The improved result values were compared with Evolutionary programming, DE algorithm, dynamic particle swarm optimization, self-adaptive real coded genetic algorithm and modified Gaussian bare bones teaching-learning based optimization.