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Dynamic identification of external equivalents in distribution networks

a novel methodology for evaluating the external equivalent model of a distributed network is presented. The proposed method is based on a non-linear parameter identification process which involves an artificial dynamic system, whose dynamics are explicitly designed to be stable by adopting the Lyapunov theory. This dynamic identification method is competitive with existing reduction methods, since it does not require system linearization or any a priori information about the system under study. Few measurements at boundary nodes are required to obtain the essential information regarding the external system. Even if these measurements are strongly corrupted by noise, the algorithm is quite insensible to it. Due to its ability to be auto-adaptive at any changes in the system operating conditions and to its great speed convergence, the identification procedure can be usefully applied for real-time applications.



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