IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v269y2023ics0360544223001858.html
   My bibliography  Save this article

Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change

Author

Listed:
  • Wei, Zhichen
  • Calautit, John

Abstract

With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.

Suggested Citation

  • Wei, Zhichen & Calautit, John, 2023. "Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change," Energy, Elsevier, vol. 269(C).
  • Handle: RePEc:eee:energy:v:269:y:2023:i:c:s0360544223001858
    DOI: 10.1016/j.energy.2023.126791
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223001858
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.126791?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Hirvonen, Janne & Kayo, Genku & Hasan, Ala & Sirén, Kai, 2016. "Zero energy level and economic potential of small-scale building-integrated PV with different heating systems in Nordic conditions," Applied Energy, Elsevier, vol. 167(C), pages 255-269.
    3. 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.
    4. Kim, Youngjin & Norford, Leslie K., 2017. "Optimal use of thermal energy storage resources in commercial buildings through price-based demand response considering distribution network operation," Applied Energy, Elsevier, vol. 193(C), pages 308-324.
    5. Chesser, Michael & Hanly, Jim & Cassells, Damien & Apergis, Nicholas, 2018. "The positive feedback cycle in the electricity market: Residential solar PV adoption, electricity demand and prices," Energy Policy, Elsevier, vol. 122(C), pages 36-44.
    6. Thomas Kemmler & Bernd Thomas, 2020. "Design of Heat-Pump Systems for Single- and Multi-Family Houses using a Heuristic Scheduling for the Optimization of PV Self-Consumption," Energies, MDPI, vol. 13(5), pages 1-18, March.
    7. Arteconi, A. & Hewitt, N.J. & Polonara, F., 2012. "State of the art of thermal storage for demand-side management," Applied Energy, Elsevier, vol. 93(C), pages 371-389.
    8. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    9. Navarro, Lidia & de Gracia, Alvaro & Niall, Dervilla & Castell, Albert & Browne, Maria & McCormack, Sarah J. & Griffiths, Philip & Cabeza, Luisa F., 2016. "Thermal energy storage in building integrated thermal systems: A review. Part 2. Integration as passive system," Renewable Energy, Elsevier, vol. 85(C), pages 1334-1356.
    10. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
    11. Papakostas, K. & Kyriakis, N., 2005. "Heating and cooling degree-hours for Athens and Thessaloniki, Greece," Renewable Energy, Elsevier, vol. 30(12), pages 1873-1880.
    12. Allison Thomson & Katherine Calvin & Steven Smith & G. Kyle & April Volke & Pralit Patel & Sabrina Delgado-Arias & Ben Bond-Lamberty & Marshall Wise & Leon Clarke & James Edmonds, 2011. "RCP4.5: a pathway for stabilization of radiative forcing by 2100," Climatic Change, Springer, vol. 109(1), pages 77-94, November.
    13. Langer, Lissy & Volling, Thomas, 2020. "An optimal home energy management system for modulating heat pumps and photovoltaic systems," Applied Energy, Elsevier, vol. 278(C).
    14. Tien, Paige Wenbin & Wei, Shuangyu & Calautit, John Kaiser & Darkwa, Jo & Wood, Christopher, 2022. "Real-time monitoring of occupancy activities and window opening within buildings using an integrated deep learning-based approach for reducing energy demand," Applied Energy, Elsevier, vol. 308(C).
    15. Carmichael, R. & Gross, R. & Hanna, R. & Rhodes, A. & Green, T., 2021. "The Demand Response Technology Cluster: Accelerating UK residential consumer engagement with time-of-use tariffs, electric vehicles and smart meters via digital comparison tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    16. Xue, Xue & Wang, Shengwei & Sun, Yongjun & Xiao, Fu, 2014. "An interactive building power demand management strategy for facilitating smart grid optimization," Applied Energy, Elsevier, vol. 116(C), pages 297-310.
    17. Happle, Gabriel & Fonseca, Jimeno A. & Schlueter, Arno, 2020. "Impacts of diversity in commercial building occupancy profiles on district energy demand and supply," Applied Energy, Elsevier, vol. 277(C).
    18. Sardi, Junainah & Mithulananthan, N. & Hung, Duong Quoc, 2017. "Strategic allocation of community energy storage in a residential system with rooftop PV units," Applied Energy, Elsevier, vol. 206(C), pages 159-171.
    19. Reynders, Glenn & Diriken, Jan & Saelens, Dirk, 2017. "Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings," Applied Energy, Elsevier, vol. 198(C), pages 192-202.
    20. Ma, Hongting & Li, Cong & Lu, Wenqian & Zhang, Zeyu & Yu, Shaojie & Du, Na, 2017. "Investigation on a solar-groundwater heat pump unit associated with radiant floor heating," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 972-977.
    21. Kensby, Johan & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Potential of residential buildings as thermal energy storage in district heating systems – Results from a pilot test," Applied Energy, Elsevier, vol. 137(C), pages 773-781.
    22. Kit Benjamin & Zhiwen Luo & Xiaoxue Wang, 2021. "Crowdsourcing Urban Air Temperature Data for Estimating Urban Heat Island and Building Heating/Cooling Load in London," Energies, MDPI, vol. 14(16), pages 1-26, August.
    23. Zhou, Guobing & He, Jing, 2015. "Thermal performance of a radiant floor heating system with different heat storage materials and heating pipes," Applied Energy, Elsevier, vol. 138(C), pages 648-660.
    24. Hou, Rui & Li, Shanshan & Wu, Minrong & Ren, Guowen & Gao, Wei & Khayatnezhad, Majid & gholinia, Fatemeh, 2021. "Assessing of impact climate parameters on the gap between hydropower supply and electricity demand by RCPs scenarios and optimized ANN by the improved Pathfinder (IPF) algorithm," Energy, Elsevier, vol. 237(C).
    25. Turner, W.J.N. & Walker, I.S. & Roux, J., 2015. "Peak load reductions: Electric load shifting with mechanical pre-cooling of residential buildings with low thermal mass," Energy, Elsevier, vol. 82(C), pages 1057-1067.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lu Jin & Liguo Shi & Dezhi Li & Kaicheng Liu & Ming Zhong & Jingshuai Pang, 2023. "Anti-Disturbance Integrated Control Method and Energy Consumption Analysis of Central Heating Systems Based on Resistance–Capacitance Reactance," Sustainability, MDPI, vol. 15(16), pages 1-20, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Yongbao & Chen, Zhe & Xu, Peng & Li, Weilin & Sha, Huajing & Yang, Zhiwei & Li, Guowen & Hu, Chonghe, 2019. "Quantification of electricity flexibility in demand response: Office building case study," Energy, Elsevier, vol. 188(C).
    2. Finck, Christian & Li, Rongling & Kramer, Rick & Zeiler, Wim, 2018. "Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems," Applied Energy, Elsevier, vol. 209(C), pages 409-425.
    3. Marszal-Pomianowska, Anna & Widén, Joakim & Le Dréau, Jérôme & Heiselberg, Per & Bak-Jensen, Birgitte & de Cerio Mendaza, Iker Diaz, 2020. "Operation of power distribution networks with new and flexible loads: A case of existing residential low voltage network," Energy, Elsevier, vol. 202(C).
    4. Tang, Hong & Wang, Shengwei & Li, Hangxin, 2021. "Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: State-of-the-art and future perspective," Energy, Elsevier, vol. 219(C).
    5. Hu, Maomao & Xiao, Fu & Wang, Shengwei, 2021. "Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    6. 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.
    7. Dmytro Romanchenko & Emil Nyholm & Mikael Odenberger & Filip Johnsson, 2019. "Flexibility Potential of Space Heating Demand Response in Buildings for District Heating Systems," Energies, MDPI, vol. 12(15), pages 1-23, July.
    8. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    9. Amadeh, Ali & Lee, Zachary E. & Zhang, K. Max, 2022. "Quantifying demand flexibility of building energy systems under uncertainty," Energy, Elsevier, vol. 246(C).
    10. Knudsen, Michael Dahl & Georges, Laurent & Skeie, Kristian Stenerud & Petersen, Steffen, 2021. "Experimental test of a black-box economic model predictive control for residential space heating," Applied Energy, Elsevier, vol. 298(C).
    11. Lizana, Jesús & Chacartegui, Ricardo & Barrios-Padura, Angela & Ortiz, Carlos, 2018. "Advanced low-carbon energy measures based on thermal energy storage in buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3705-3749.
    12. Tang, Rui & Wang, Shengwei & Shan, Kui & Cheung, Howard, 2018. "Optimal control strategy of central air-conditioning systems of buildings at morning start period for enhanced energy efficiency and peak demand limiting," Energy, Elsevier, vol. 151(C), pages 771-781.
    13. Saffari, Mohammad & de Gracia, Alvaro & Fernández, Cèsar & Belusko, Martin & Boer, Dieter & Cabeza, Luisa F., 2018. "Optimized demand side management (DSM) of peak electricity demand by coupling low temperature thermal energy storage (TES) and solar PV," Applied Energy, Elsevier, vol. 211(C), pages 604-616.
    14. Hu, Maomao & Xiao, Fu & Jørgensen, John Bagterp & Wang, Shengwei, 2019. "Frequency control of air conditioners in response to real-time dynamic electricity prices in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 92-106.
    15. Heidenthaler, Daniel & Leeb, Markus & Schnabel, Thomas & Huber, Hermann, 2021. "Comparative analysis of thermally activated building systems in wooden and concrete structures regarding functionality and energy storage on a simulation-based approach," Energy, Elsevier, vol. 233(C).
    16. Malik, Anam & Haghdadi, Navid & MacGill, Iain & Ravishankar, Jayashri, 2019. "Appliance level data analysis of summer demand reduction potential from residential air conditioner control," Applied Energy, Elsevier, vol. 235(C), pages 776-785.
    17. Monika Hall & Achim Geissler, 2021. "Comparison of Flexibility Factors and Introduction of A Flexibility Classification Using Advanced Heat Pump Control," Energies, MDPI, vol. 14(24), pages 1-19, December.
    18. Finck, Christian & Li, Rongling & Zeiler, Wim, 2019. "Economic model predictive control for demand flexibility of a residential building," Energy, Elsevier, vol. 176(C), pages 365-379.
    19. Clauß, John & Stinner, Sebastian & Sartori, Igor & Georges, Laurent, 2019. "Predictive rule-based control to activate the energy flexibility of Norwegian residential buildings: Case of an air-source heat pump and direct electric heating," Applied Energy, Elsevier, vol. 237(C), pages 500-518.
    20. Dominković, D.F. & Gianniou, P. & Münster, M. & Heller, A. & Rode, C., 2018. "Utilizing thermal building mass for storage in district heating systems: Combined building level simulations and system level optimization," Energy, Elsevier, vol. 153(C), pages 949-966.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:269:y:2023:i:c:s0360544223001858. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.