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A review of advanced ground source heat pump control: Artificial intelligence for autonomous and adaptive control

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  • Noye, Sarah
  • Mulero Martinez, Rubén
  • Carnieletto, Laura
  • De Carli, Michele
  • Castelruiz Aguirre, Amaia

Abstract

Geothermal energy has the potential to contribute significantly to the CO2 reduction targets as a renewable source for building heating and cooling but is yet under exploited, mostly due to its high initial investment cost. A lot of research is being carried out to optimise Ground Source Heat Pump (GSHP) systems’ design, but a good control strategy is also fundamental to achieve long-term performance and reduced payback time.

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  • Noye, Sarah & Mulero Martinez, Rubén & Carnieletto, Laura & De Carli, Michele & Castelruiz Aguirre, Amaia, 2022. "A review of advanced ground source heat pump control: Artificial intelligence for autonomous and adaptive control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    • Handle: RePEc:eee:rensus:v:153:y:2022:i:c:s136403212100959x
    DOI: 10.1016/j.rser.2021.111685
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    1. Sivasakthivel, T. & Murugesan, K. & Sahoo, P.K., 2014. "Optimization of ground heat exchanger parameters of ground source heat pump system for space heating applications," Energy, Elsevier, vol. 78(C), pages 573-586.
    2. Chengdong Li & Zixiang Ding & Dongbin Zhao & Jianqiang Yi & Guiqing Zhang, 2017. "Building Energy Consumption Prediction: An Extreme Deep Learning Approach," Energies, MDPI, vol. 10(10), pages 1-20, October.
    3. Gang, Wenjie & Wang, Jinbo & Wang, Shengwei, 2014. "Performance analysis of hybrid ground source heat pump systems based on ANN predictive control," Applied Energy, Elsevier, vol. 136(C), pages 1138-1144.
    4. Xia, Lei & Ma, Zhenjun & Kokogiannakis, Georgios & Wang, Shugang & Gong, Xuemei, 2018. "A model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors," Applied Energy, Elsevier, vol. 228(C), pages 1399-1412.
    5. Yang, Lei & Nagy, Zoltan & Goffin, Philippe & Schlueter, Arno, 2015. "Reinforcement learning for optimal control of low exergy buildings," Applied Energy, Elsevier, vol. 156(C), pages 577-586.
    6. Østergård, Torben & Jensen, Rasmus Lund & Maagaard, Steffen Enersen, 2018. "A comparison of six metamodeling techniques applied to building performance simulations," Applied Energy, Elsevier, vol. 211(C), pages 89-103.
    7. Gang, Wenjie & Wang, Jinbo, 2013. "Predictive ANN models of ground heat exchanger for the control of hybrid ground source heat pump systems," Applied Energy, Elsevier, vol. 112(C), pages 1146-1153.
    8. Ikeda, Shintaro & Choi, Wonjun & Ooka, Ryozo, 2017. "Optimization method for multiple heat source operation including ground source heat pump considering dynamic variation in ground temperature," Applied Energy, Elsevier, vol. 193(C), pages 466-478.
    9. Weeratunge, Hansani & Narsilio, Guillermo & de Hoog, Julian & Dunstall, Simon & Halgamuge, Saman, 2018. "Model predictive control for a solar assisted ground source heat pump system," Energy, Elsevier, vol. 152(C), pages 974-984.
    10. Frederik Ruelens & Sandro Iacovella & Bert J. Claessens & Ronnie Belmans, 2015. "Learning Agent for a Heat-Pump Thermostat with a Set-Back Strategy Using Model-Free Reinforcement Learning," Energies, MDPI, vol. 8(8), pages 1-19, August.
    11. Atam, Ercan & Helsen, Lieve, 2016. "Ground-coupled heat pumps: Part 1 – Literature review and research challenges in modeling and optimal control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1653-1667.
    12. Mohanraj, M. & Jayaraj, S. & Muraleedharan, C., 2012. "Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1340-1358.
    13. Sivasakthivel, T. & Murugesan, K. & Thomas, H.R., 2014. "Optimization of operating parameters of ground source heat pump system for space heating and cooling by Taguchi method and utility concept," Applied Energy, Elsevier, vol. 116(C), pages 76-85.
    14. Fan, Cheng & Xiao, Fu & Zhao, Yang, 2017. "A short-term building cooling load prediction method using deep learning algorithms," Applied Energy, Elsevier, vol. 195(C), pages 222-233.
    15. Edwards, K.C. & Finn, D.P., 2015. "Generalised water flow rate control strategy for optimal part load operation of ground source heat pump systems," Applied Energy, Elsevier, vol. 150(C), pages 50-60.
    16. Self, Stuart J. & Reddy, Bale V. & Rosen, Marc A., 2013. "Geothermal heat pump systems: Status review and comparison with other heating options," Applied Energy, Elsevier, vol. 101(C), pages 341-348.
    17. Hu, Bin & Li, Yaoyu & Mu, Baojie & Wang, Shaojie & Seem, John E. & Cao, Feng, 2016. "Extremum seeking control for efficient operation of hybrid ground source heat pump system," Renewable Energy, Elsevier, vol. 86(C), pages 332-346.
    18. Cai, Mengmeng & Pipattanasomporn, Manisa & Rahman, Saifur, 2019. "Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques," Applied Energy, Elsevier, vol. 236(C), pages 1078-1088.
    19. Atam, Ercan & Helsen, Lieve, 2016. "Ground-coupled heat pumps: Part 2—Literature review and research challenges in optimal design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1668-1684.
    20. Wu, Wei & Wang, Baolong & You, Tian & Shi, Wenxing & Li, Xianting, 2013. "A potential solution for thermal imbalance of ground source heat pump systems in cold regions: Ground source absorption heat pump," Renewable Energy, Elsevier, vol. 59(C), pages 39-48.
    21. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    22. Ma, Zhenjun & Xia, Lei & Gong, Xuemei & Kokogiannakis, Georgios & Wang, Shugang & Zhou, Xinlei, 2020. "Recent advances and development in optimal design and control of ground source heat pump systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    23. Xia, Lei & Ma, Zhenjun & Kokogiannakis, Georgios & Wang, Zhihua & Wang, Shugang, 2018. "A model-based design optimization strategy for ground source heat pump systems with integrated photovoltaic thermal collectors," Applied Energy, Elsevier, vol. 214(C), pages 178-190.
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    Cited by:

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    2. Zhang, Xueping & Li, Gui & Han, Zongwei & Yang, Ziwei & Bi, Weiqiang & Li, Xiuming & Yang, Lingyan, 2023. "Study on the influence of buried pipe fault on the operation of ground source heat pump system," Renewable Energy, Elsevier, vol. 210(C), pages 12-25.
    3. Omar Al-Ani & Sanjoy Das, 2022. "Reinforcement Learning: Theory and Applications in HEMS," Energies, MDPI, vol. 15(17), pages 1-37, September.
    4. Chen, Zhi & Lian, Xingwei & Tan, Jinjia & Xiao, Henglin & Ma, Qiang & Zhuang, Yan, 2023. "Study on heat-exchange efficiency and energy efficiency ratio of a deeply buried pipe energy pile group considering seepage and circulating-medium flow rate," Renewable Energy, Elsevier, vol. 216(C).
    5. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
    6. Davide Menegazzo & Giulia Lombardo & Sergio Bobbo & Michele De Carli & Laura Fedele, 2022. "State of the Art, Perspective and Obstacles of Ground-Source Heat Pump Technology in the European Building Sector: A Review," Energies, MDPI, vol. 15(7), pages 1-25, April.

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