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Modelado y Simulación de Sistemas de Control Predictivos para la Generación Eléctrica en Redes Inteligentes

  • Checa, Gabriel [1] ; Cabrera, Ana [2] ; Sampietro, José [2] ; Valencia, Nakira [3] ; Ulloa, Raúl [3]
    1. [1] Pontificia Universidad Católica del Ecuador

      Pontificia Universidad Católica del Ecuador

      Quito, Ecuador

    2. [2] Universidad Tecnológica Ecotec

      Universidad Tecnológica Ecotec

      Guayaquil, Ecuador

    3. [3] Universidad Técnica Luis Vargas Torres, Facultad de Ingenierías, Esmeraldas, Ecuador
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  • Localización: Revista Politécnica, ISSN-e 2477-8990, Vol. 54, Nº. 2, 2024 (Ejemplar dedicado a: Revista Politécnica), págs. 7-20
  • Idioma: español
  • DOI: 10.33333/rp.vol54n2.01
  • Títulos paralelos:
    • Modeling and Simulation of Predictive Control Systems for Power Generation in Smart Grids
  • Enlaces
  • Resumen
    • español

      Las redes eléctricas inteligentes (RI) son reconocidas como un componente tecnológico fundamental para enfrentar el aumento de la demanda energética, mejorando la confiabilidad y sostenibilidad de los sistemas eléctricos. El presente estudio incluye en la RI elementos de almacenamiento que permiten disminuir la potencia suministrada por las fuentes de generación principales durante las horas de mayor demanda. Esto asegura que la demanda siempre se cubra y a la vez que se opera dentro de los rangos de mayor eficiencia. Se propone el uso de la herramienta de cómputo Matlab, mediante el Toolbox de YALMIP, enfocado en la modelización y resolución de problemas de optimización y control, para desarrollar una estrategia de Control Predictivo de Modelos (MPC) que gestione los recursos energéticos de una RI y permita cumplir la demanda de energía, y que respete las restricciones del controlador. Se destaca el uso de tres fuentes de generación, dentro de las cuales dos son consideradas principales, siendo las mismas: la energía eólica y energía solar y la tercera es considerada como un sistema de almacenamiento conformado por baterías. Los resultados indican que al incorporar un MPC, podremos disminuir los costes de generación, derivados del maximizar la vida útil de los elementos y del almacenar energía durante el periodo de producción.

       

    • English

      Smart Grids (SG) are recognized as a fundamental technological component to address the increase in energy demand, improving the reliability and sustainability of electricity systems. The present study includes in the SG storage elements that allow decreasing the power delivered by the main generation sources during peak demand hours. This ensures that the demand is always met while operating within the highest efficiency ranges. The use of the Matlab computational tool, through the YALMIP Toolbox, focused on modeling and solving optimization and control problems, is proposed to develop a Model Predictive Control (MPC) strategy that manages the energy resources of an SG and allows meeting the energy demand, and respects the controller constraints. The use of three generation sources is highlighted, two of which are considered to be the main ones, being wind and solar energy, and the third one is considered to be a storage system made up of batteries. The results indicate that by incorporating an MPC, we will be able to reduce generation costs, derived from maximizing the useful life of the elements and storing energy during the production period.

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