GA based H∞ optimal model reduction: Application to power systems

Complex large scale power systems usually require high dimensional models to well represent them. Analysis, simulation and design methods based on this high order model leads to complicated control strategies requiring very complex logic or large amounts of computation. In this paper, genetic algorithms are used to find reduced order state space model representations of complex high order power systems using H
_∞
norm.