Reduced-Order Models for Representing Converters in Power System Studies

Abstract

A reduced-order model that preserves physical meaning is important for generating insight in large-scale power system studies. The conventional model-order reduction for a multiple-timescale system is based on discarding states with fast (short timescale) dynamics. It has been successfully applied to synchronous machines, but is inaccurate when applied to power converters because the timescales of fast and slow states are not sufficiently separated. In the method proposed here, several fast states are at first discarded but a representation of their interaction with the slow states is added back. Recognizing that the fast states of many converters are linear allows well-developed linear system theories to be used to implement this concept. All the information of the original system relevant to system-wide dynamics, including nonlinearity, is preserved, which facilitates judgments on system stability and insight into control design. The method is tested on a converter-supplied mini power system and the comparison of analytical and experiment results confirms high preciseness in a broad range of conditions.