Improved Direct-Model Predictive Control with a Simple Disturbance Observer for DFIGs

Mohamed Abdelrahem, Christoph Hackl, Jose Rodriguez, Ralph Kennel

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

Resumen

In this paper, a computationally-efficient and robust direct-model predictive control (DMPC) technique for doubly-fed induction generators in variable-speed wind turbines systems is proposed. In order to avoid several predictions of the rotor currents, the reference voltage (RV) is directly computed from the reference currents, which notably reduces the calculation load. Furthermore, the disturbances due to parameters mismatches and un-modeled dynamics are considered in the RV calculation. Accordingly, the sensitivity to mismatches in the model parameters is avoided and a zero steady-state error is realized. Finally, based on the location of this RV, the quality function is evaluated for only two times to find the best switching state, which is applied to the power converter in the next sample. The performance of the suggested DMPC is experimentally validated and compared with the convention DMPC.

Idioma originalInglés
Título de la publicación alojada2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9789075815368
DOI
EstadoPublicada - sep 2020
Evento22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe - Lyon, Francia
Duración: 7 sep 202011 sep 2020

Serie de la publicación

Nombre2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe

Conferencia

Conferencia22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe
País/TerritorioFrancia
CiudadLyon
Período7/09/2011/09/20

Áreas temáticas de ASJC Scopus

  • Ingeniería energética y tecnologías de la energía
  • Ingeniería eléctrica y electrónica
  • Seguridad, riesgos, fiabilidad y calidad
  • Control y optimización

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