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Optimization of the Heating System Use in Aged Public Buildings via Model Predictive Control

Author

Listed:
  • Edorta Carrascal

    (Automatic Control Group, Department of Thermal Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain)

  • Izaskun Garrido

    (Automatic Control Group, Department of Automatic Control and Systems Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain)

  • Aitor J. Garrido

    (Automatic Control Group, Department of Automatic Control and Systems Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain)

  • José María Sala

    (Enedi Research Group, Department of Thermal Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain)

Abstract

This work presents the implementation of a Model Predictive Control (MPC) scheme used to study the improvement of the thermal quality in aged residential buildings without any rehabilitation. The controller manages the heating system of an experimentally characterized model of a residential dwelling in a social block built during the decade of the 1960s located in the neighborhood of Otxarkoaga (Bilbao, Spain), so as to obtain an optimal energy efficiency performance. Due to the characteristics of the construction in those days, this kind of buildings suffer problems related to the use of awkward building materials and inefficient heating systems. A comparison with traditionally used ON-OFF hysteresis control is presented in order to demonstrate the energetic improvement provided by the MPC scheme. Besides, the variation of different parameters of the MPC is also studied to determine its influence over the energy consumption and comfort conditions.

Suggested Citation

  • Edorta Carrascal & Izaskun Garrido & Aitor J. Garrido & José María Sala, 2016. "Optimization of the Heating System Use in Aged Public Buildings via Model Predictive Control," Energies, MDPI, vol. 9(4), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:4:p:251-:d:66868
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    References listed on IDEAS

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    1. Ashouri, Araz & Petrini, Flavio & Bornatico, Raffaele & Benz, Michael J., 2014. "Sensitivity analysis for robust design of building energy systems," Energy, Elsevier, vol. 76(C), pages 264-275.
    2. Gwerder, M. & Lehmann, B. & Tödtli, J. & Dorer, V. & Renggli, F., 2008. "Control of thermally-activated building systems (TABS)," Applied Energy, Elsevier, vol. 85(7), pages 565-581, July.
    3. Verbai, Zoltán & Lakatos, Ákos & Kalmár, Ferenc, 2014. "Prediction of energy demand for heating of residential buildings using variable degree day," Energy, Elsevier, vol. 76(C), pages 780-787.
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    Cited by:

    1. Clara Ceccolini & Roozbeh Sangi, 2022. "Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review," Energies, MDPI, vol. 15(4), pages 1-30, February.
    2. Edorta Carrascal-Lekunberri & Izaskun Garrido & Bram Van der Heijde & Aitor J. Garrido & José María Sala & Lieve Helsen, 2017. "Energy Conservation in an Office Building Using an Enhanced Blind System Control," Energies, MDPI, vol. 10(2), pages 1-23, February.
    3. Germán Ramos Ruiz & Eva Lucas Segarra & Carlos Fernández Bandera, 2018. "Model Predictive Control Optimization via Genetic Algorithm Using a Detailed Building Energy Model," Energies, MDPI, vol. 12(1), pages 1-18, December.
    4. Izaskun Garrido & Aitor J. Garrido & Stefano Coda & Hoang B. Le & Jean Marc Moret, 2016. "Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV)," Energies, MDPI, vol. 9(8), pages 1-14, August.
    5. Santos-Herrero, J.M. & Lopez-Guede, J.M. & Flores-Abascal, I., 2021. "Modeling, simulation and control tools for nZEB: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    6. Mohammad Reza Zavvar Sabegh & Chris Bingham, 2019. "Model Predictive Control with Binary Quadratic Programming for the Scheduled Operation of Domestic Refrigerators," Energies, MDPI, vol. 12(24), pages 1-20, December.
    7. Yaser Imad Alamin & María Del Mar Castilla & José Domingo Álvarez & Antonio Ruano, 2017. "An Economic Model-Based Predictive Control to Manage the Users’ Thermal Comfort in a Building," Energies, MDPI, vol. 10(3), pages 1-18, March.

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