A Comparison Study for the Estimation of SOFC Internal Dynamic States in Complex Power Systems Using Filtering Algorithms

Abstract

This paper enumerates three commonly used filtering algorithms and shows the detailed steps of their incorporation with general nonlinear systems for dynamic state estimation. The mathematical model of a stand-alone solid oxide fuel cell (SOFC) is briefly discussed and derived, which is then mathematically connected to a multiarea, diverse-generator, interconnected complex test system. The mathematical representation of the entire power system is tailored into a certain compact form to provide suitability for the implementation of filtering algorithms for the design of dynamic state estimators. With the utilization of phasor measurement units, the state estimators are able to work in a decentralized manner with the mere knowledge of local noisy voltage and current measurements. Successfully estimating the internal dynamic states of SOFC connected to complex power systems offers a novel methodology for the acquisition of the internal unmeasurable states of SOFC, which will facilitate future controller designs that may require the otherwise inaccessible states.