Identification of Dynamic Equivalents for MicroGrids with High Penetration of Solar Energy using Artificial Neural Networks

dc.contributor.author Carlos Moreira en
dc.contributor.author Fernanda Resende en
dc.contributor.author João Peças Lopes en
dc.date.accessioned 2017-11-16T12:18:56Z
dc.date.available 2017-11-16T12:18:56Z
dc.date.issued 2006 en
dc.description.abstract Dissemination of small size dispersed microgeneration, connected to Low Voltage (LV) distribution systems is expected to become an effective mean to face the continuous demand growth. Dynamic behaviour analysis is required in Medium Voltage (MV) distribution grids with dispersed generation if islanding operation is allowed. When large scale integration of Photovoltaics (PV) in LV grids occurs a special care is needed when performing these simulations. This paper describes an approach based on nonlinear modelling and identification of dynamic systems using Artificial Neural Networks (ANN) used to build dynamic equivalents for Micro Grids (MG), which can be integrated in dynamic simulation tools. A test system with high penetration of PV is used to evaluate the performance of this approach. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/1404
dc.language eng en
dc.relation 4442 en
dc.relation 1103 en
dc.relation 4643 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Identification of Dynamic Equivalents for MicroGrids with High Penetration of Solar Energy using Artificial Neural Networks en
dc.type other en
dc.type Publication en
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