Power system stabilizers design using optimal reduced order models. I. Model reduction

The authors examine the design of power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. It is shown that well-known model reduction techniques can give erroneous results. An algorithm to obtain optimal reduced-order models to deal with these problems is developed. The reduced order model retains the modes that mostly affect some desired variables (which are usually the available or measurable variables). Here, these variables are torque angles and angular frequencies. Optimization of a steady-state error criterion is utilized to compensate for the other modes instead of simple omission or the neglection of dynamics