An observer‐based composite identifier for online estimation of the Thévenin equivalent parameters of a power system

Abstract

AbstractWe consider a Thévenin equivalent circuit capturing the dynamics of a power grid as seen from the point of common coupling with a power electronic converter and propose a solution to the problem of online identification of the corresponding circuit parameters. For this purpose, we first derive a linear regression model in the conventional abc coordinates that, unfortunately, suffers from severe lack of identifiability properties. In spite of this fact, we design a bounded observer‐based composite identifier that, requiring only local measurements and knowledge of the grid frequency, ensures global boundedness of the parameters estimation error and convergence to a practically small residual set. An extension that guarantees exponential convergence of these errors to zero, in the case that the grid is dominantly inductive, is further provided. The performance of the proposed identifier, which subsumes a conventional gradient descent algorithm, is illustrated via detailed computer simulations.