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

We 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.