Practical robust PSS design through identification of low-order transfer functions

This paper presents a low-order identification technique, which is based on standard Prony analysis. The technique has the ability to extract crucial dynamic characteristics from a system of any size (e.g., a large-scale power system), which then can be used for developing a robust controller. In this paper the proposed identification technique is coupled with a robust controller design technique based on genetic algorithm to simultaneously tune power system stabilizers (PSSs) for multiple operating conditions. To illustrate the proposed identification and controller design techniques three case studies are presented, including a two-area benchmark system, a 50-machine test system and a large-scale (23 300 bus) Eastern Interconnection power system. To allow the proposed tools to be applied to the large-scale power system, the authors developed an interface with a standard production grade transient stability analysis software package PSS/E.