Application of robust model predictive control to a renewable hydrogen-based microgrid


Abstract:

In order to cope with uncertainties present in the renewable energy generation, as well as in the demand consumer, we propose in this paper the formulation and comparison of three robust model predictive control techniques, i.e., multi-scenario, tree-based, and chance-constrained model predictive control, which are applied to a nonlinear plant-replacement model that corresponds to a real laboratory-scale plant located in the facilities of the University of Seville. Results show the effectiveness of these three techniques considering the stochastic nature, proper of these systems.

Año de publicación:

2016

Keywords:

    Fuente:

    scopusscopus

    Tipo de documento:

    Conference Object

    Estado:

    Acceso restringido

    Áreas de conocimiento:

    • Energía
    • Energía renovable

    Áreas temáticas de Dewey:

    • Física aplicada
    Procesado con IAProcesado con IA

    Objetivos de Desarrollo Sostenible:

    • ODS 7: Energía asequible y no contaminante
    • ODS 13: Acción por el clima
    • ODS 9: Industria, innovación e infraestructura
    Procesado con IAProcesado con IA