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Model Predictive Control Strategies to Activate the Energy Flexibility for Zones with Hydronic Radiant Systems

Author

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  • Ali Saberi Derakhtenjani

    (Center for Zero-Energy Building Studies, Concordia University, Montreal, QC H3G 1M8, Canada)

  • Andreas K. Athienitis

    (NSERC/Hydro-Quebec Industrial Research Chair, Center for Zero-Energy Building Studies, Concordia University, Montreal, QC H3G 1M8, Canada)

Abstract

This paper presents control strategies to activate energy flexibility for zones with radiant heating systems in response to changes in electricity prices. The focus is on zones with radiant floor heating systems for which the hydronic pipes are located deep in the concrete and, therefore, there is a significant thermal lag. A perimeter zone test-room equipped with a hydronic radiant floor system in an environmental chamber is used as a case study. A low order thermal network model for the perimeter zone, validated with experimental measurements, is utilized to study various control strategies in response to changes in the electrical grid price signal, including short term (nearly reactive) changes of the order of 10–15 min notice. An index is utilized to quantify the building energy flexibility with the focus on peak demand reduction for specific periods of time when the electricity prices are higher than usual. It is shown that the developed control strategies can aid greatly in enhancing the zone energy flexibility and minimizing the cost of electricity and up to 100% reduction in peak power demand and energy consumption is attained during the high-price and peak-demand periods, while maintaining acceptable comfort conditions.

Suggested Citation

  • Ali Saberi Derakhtenjani & Andreas K. Athienitis, 2021. "Model Predictive Control Strategies to Activate the Energy Flexibility for Zones with Hydronic Radiant Systems," Energies, MDPI, vol. 14(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1195-:d:504222
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    References listed on IDEAS

    as
    1. El Geneidy, Rami & Howard, Bianca, 2020. "Contracted energy flexibility characteristics of communities: Analysis of a control strategy for demand response," Applied Energy, Elsevier, vol. 263(C).
    2. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    3. Zhou, Yuekuan & Zheng, Siqian, 2020. "Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities," Applied Energy, Elsevier, vol. 262(C).
    4. Child, Michael & Kemfert, Claudia & Bogdanov, Dmitrii & Breyer, Christian, 2019. "Flexible electricity generation, grid exchange and storage for the transition to a 100% renewable energy system in Europe," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 139, pages 80-101.
    5. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    6. Narayanan, Arun & Mets, Kevin & Strobbe, Matthias & Develder, Chris, 2019. "Feasibility of 100% renewable energy-based electricity production for cities with storage and flexibility," Renewable Energy, Elsevier, vol. 134(C), pages 698-709.
    7. Xue, Xue & Wang, Shengwei & Yan, Chengchu & Cui, Borui, 2015. "A fast chiller power demand response control strategy for buildings connected to smart grid," Applied Energy, Elsevier, vol. 137(C), pages 77-87.
    8. Hu, Maomao & Xiao, Fu, 2020. "Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior," Energy, Elsevier, vol. 194(C).
    9. Niu, Jide & Tian, Zhe & Lu, Yakai & Zhao, Hongfang, 2019. "Flexible dispatch of a building energy system using building thermal storage and battery energy storage," Applied Energy, Elsevier, vol. 243(C), pages 274-287.
    10. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    11. 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.
    12. Pouria Bahramnia & Seyyed Mohammad Hosseini Rostami & Jin Wang & Gwang-jun Kim, 2019. "Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control," Energies, MDPI, vol. 12(24), pages 1-24, December.
    13. Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2020. "Performance Assessment of Data-Driven and Physical-Based Models to Predict Building Energy Demand in Model Predictive Controls," Energies, MDPI, vol. 13(12), pages 1-18, June.
    14. Arteconi, Alessia & Mugnini, Alice & Polonara, Fabio, 2019. "Energy flexible buildings: A methodology for rating the flexibility performance of buildings with electric heating and cooling systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Brunner, Christoph & Deac, Gerda & Braun, Sebastian & Zöphel, Christoph, 2020. "The future need for flexibility and the impact of fluctuating renewable power generation," Renewable Energy, Elsevier, vol. 149(C), pages 1314-1324.
    16. Aelenei, Daniel & Lopes, Rui Amaral & Aelenei, Laura & Gonçalves, Helder, 2019. "Investigating the potential for energy flexibility in an office building with a vertical BIPV and a PV roof system," Renewable Energy, Elsevier, vol. 137(C), pages 189-197.
    17. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    18. English, Jeffrey & Niet, Taco & Lyseng, Benjamin & Keller, Victor & Palmer-Wilson, Kevin & Robertson, Bryson & Wild, Peter & Rowe, Andrew, 2020. "Flexibility requirements and electricity system planning: Assessing inter-regional coordination with large penetrations of variable renewable supplies," Renewable Energy, Elsevier, vol. 145(C), pages 2770-2782.
    19. Junker, Rune Grønborg & Azar, Armin Ghasem & Lopes, Rui Amaral & Lindberg, Karen Byskov & Reynders, Glenn & Relan, Rishi & Madsen, Henrik, 2018. "Characterizing the energy flexibility of buildings and districts," Applied Energy, Elsevier, vol. 225(C), pages 175-182.
    20. Boßmann, T. & Staffell, I., 2015. "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain," Energy, Elsevier, vol. 90(P2), pages 1317-1333.
    21. Gao, Dian-ce & Sun, Yongjun & Lu, Yuehong, 2015. "A robust demand response control of commercial buildings for smart grid under load prediction uncertainty," Energy, Elsevier, vol. 93(P1), pages 275-283.
    22. Finck, Christian & Li, Rongling & Zeiler, Wim, 2020. "Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration," Applied Energy, Elsevier, vol. 263(C).
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    Cited by:

    1. Brown, Sarah & Beausoleil-Morrison, Ian, 2023. "Long-term implementation of a model predictive controller for a hydronic floor heating and cooling system in a highly glazed house in Canada," Applied Energy, Elsevier, vol. 349(C).

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