IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v171y2019icp49-60.html
   My bibliography  Save this article

Geothermal heat exchanger energy prediction based on time series and monitoring sensors optimization

Author

Listed:
  • Baruque, Bruno
  • Porras, Santiago
  • Jove, Esteban
  • Calvo-Rolle, José Luis

Abstract

In recent years, the use of renewable energies has been promoted in most of developed countries due to the climate change threat. In this scenario, the importance of geothermal installations has increased. This paper focuses on a heat exchanger present on a geothermal installation. The main aim is to achieve an accurate prediction system using the previous readings of some of the sensors located along the heat exchanger. Different time series modeling techniques were applied obtaining satisfactory results in the prediction of the heat exchanger state during one year. This prediction is made 1 h, 3 h and 6 h in advance. Also, a strong correlation between the sensor readings is concluded, offering the possibility to dispense some of them.

Suggested Citation

  • Baruque, Bruno & Porras, Santiago & Jove, Esteban & Calvo-Rolle, José Luis, 2019. "Geothermal heat exchanger energy prediction based on time series and monitoring sensors optimization," Energy, Elsevier, vol. 171(C), pages 49-60.
    • Handle: RePEc:eee:energy:v:171:y:2019:i:c:p:49-60
    DOI: 10.1016/j.energy.2018.12.207
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218325817
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.12.207?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. Tso, Geoffrey K.F. & Yau, Kelvin K.W., 2007. "Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks," Energy, Elsevier, vol. 32(9), pages 1761-1768.
    2. Florides, Georgios & Kalogirou, Soteris, 2007. "Ground heat exchangers—A review of systems, models and applications," Renewable Energy, Elsevier, vol. 32(15), pages 2461-2478.
    3. Shaikh, Pervez Hameed & Nor, Nursyarizal Bin Mohd & Nallagownden, Perumal & Elamvazuthi, Irraivan & Ibrahim, Taib, 2014. "A review on optimized control systems for building energy and comfort management of smart sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 409-429.
    4. Luis Gonzaga Baca Ruiz & Manuel Pegalajar Cuéllar & Miguel Delgado Calvo-Flores & María Del Carmen Pegalajar Jiménez, 2016. "An Application of Non-Linear Autoregressive Neural Networks to Predict Energy Consumption in Public Buildings," Energies, MDPI, vol. 9(9), pages 1-21, August.
    5. Ozgener, Onder & Ozgener, Leyla, 2015. "Modeling of driveway as a solar collector for improving efficiency of solar assisted geothermal heat pump system: a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 210-217.
    6. Ozgener, Leyla & Ozgener, Onder, 2009. "Monitoring of energy exergy efficiencies and exergoeconomic parameters of geothermal district heating systems (GDHSs)," Applied Energy, Elsevier, vol. 86(9), pages 1704-1711, September.
    7. Jacobsson, Staffan & Lauber, Volkmar, 2006. "The politics and policy of energy system transformation--explaining the German diffusion of renewable energy technology," Energy Policy, Elsevier, vol. 34(3), pages 256-276, February.
    8. Erasmo Cadenas & Wilfrido Rivera & Rafael Campos-Amezcua & Christopher Heard, 2016. "Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model," Energies, MDPI, vol. 9(2), pages 1-15, February.
    9. Ozgener, Leyla, 2011. "A review on the experimental and analytical analysis of earth to air heat exchanger (EAHE) systems in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4483-4490.
    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. Khaled Salhein & Javed Ashraf & Mohamed Zohdy, 2021. "Output Temperature Predictions of the Geothermal Heat Pump System Using an Improved Grey Prediction Model," Energies, MDPI, vol. 14(16), pages 1-12, August.
    2. Zhengchao Xie & Xiao Wang & Lijun Zheng & Hao Chang & Fei Wang, 2022. "A Period-Based Neural Network Algorithm for Predicting Building Energy Consumption of District Heating," Energies, MDPI, vol. 15(17), pages 1-22, August.
    3. Yu, Ruyang & Zhang, Kai & Ramasubramanian, Brindha & Jiang, Shu & Ramakrishna, Seeram & Tang, Yuhang, 2024. "Ensemble learning for predicting average thermal extraction load of a hydrothermal geothermal field: A case study in Guanzhong Basin, China," Energy, Elsevier, vol. 296(C).

    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. Yıldız, Ahmet & Ozgener, Onder & Ozgener, Leyla, 2012. "Energetic performance analysis of a solar photovoltaic cell (PV) assisted closed loop earth-to-air heat exchanger for solar greenhouse cooling: An experimental study for low energy architecture in Aeg," Renewable Energy, Elsevier, vol. 44(C), pages 281-287.
    2. Ozgener, Leyla, 2011. "A review on the experimental and analytical analysis of earth to air heat exchanger (EAHE) systems in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4483-4490.
    3. Mihalakakou, Giouli & Souliotis, Manolis & Papadaki, Maria & Halkos, George & Paravantis, John & Makridis, Sofoklis & Papaefthimiou, Spiros, 2022. "Applications of earth-to-air heat exchangers: A holistic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    4. Rachana Vidhi, 2018. "A Review of Underground Soil and Night Sky as Passive Heat Sink: Design Configurations and Models," Energies, MDPI, vol. 11(11), pages 1-24, October.
    5. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    6. Alcaraz, Mar & García-Gil, Alejandro & Vázquez-Suñé, Enric & Velasco, Violeta, 2016. "Use rights markets for shallow geothermal energy management," Applied Energy, Elsevier, vol. 172(C), pages 34-46.
    7. Soni, Suresh Kumar & Pandey, Mukesh & Bartaria, Vishvendra Nath, 2016. "Hybrid ground coupled heat exchanger systems for space heating/cooling applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 724-738.
    8. H.Ali, Mohammed & Kurjak, Zoltan & Beke, Janos, 2023. "Investigation of earth air heat exchangers functioning in arid locations using Matlab/Simulink," Renewable Energy, Elsevier, vol. 209(C), pages 632-643.
    9. Zina Boussaada & Octavian Curea & Ahmed Remaci & Haritza Camblong & Najiba Mrabet Bellaaj, 2018. "A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation," Energies, MDPI, vol. 11(3), pages 1-21, March.
    10. Bordoloi, Namrata & Sharma, Aashish & Nautiyal, Himanshu & Goel, Varun, 2018. "An intense review on the latest advancements of Earth Air Heat Exchangers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 261-280.
    11. Benhammou, Mohammed & Draoui, Belkacem, 2015. "Parametric study on thermal performance of earth-to-air heat exchanger used for cooling of buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 348-355.
    12. Singh, Ramkishore & Sawhney, R.L. & Lazarus, I.J. & Kishore, V.V.N., 2018. "Recent advancements in earth air tunnel heat exchanger (EATHE) system for indoor thermal comfort application: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2162-2185.
    13. Gomat, Landry Jean Pierre & Elombo Motoula, Smaël Magloire & M’Passi-Mabiala, Bernard, 2020. "An analytical method to evaluate the impact of vertical part of an earth-air heat exchanger on the whole system," Renewable Energy, Elsevier, vol. 162(C), pages 1005-1016.
    14. Ozgener, Onder & Ozgener, Leyla & Goswami, D. Yogi, 2017. "Seven years energetic and exergetic monitoring for vertical and horizontal EAHE assisted agricultural building heating," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 175-179.
    15. Marcel Bednarz & Tom Broekel, 2020. "Pulled or pushed? The spatial diffusion of wind energy between local demand and supply," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(4), pages 893-916.
    16. Kyriakopoulos, Grigorios L. & Arabatzis, Garyfallos & Tsialis, Panagiotis & Ioannou, Konstantinos, 2018. "Electricity consumption and RES plants in Greece: Typologies of regional units," Renewable Energy, Elsevier, vol. 127(C), pages 134-144.
    17. Rivera, Jaime A. & Blum, Philipp & Bayer, Peter, 2015. "Ground energy balance for borehole heat exchangers: Vertical fluxes, groundwater and storage," Renewable Energy, Elsevier, vol. 83(C), pages 1341-1351.
    18. Alexandru Pîrjan & Simona-Vasilica Oprea & George Căruțașu & Dana-Mihaela Petroșanu & Adela Bâra & Cristina Coculescu, 2017. "Devising Hourly Forecasting Solutions Regarding Electricity Consumption in the Case of Commercial Center Type Consumers," Energies, MDPI, vol. 10(11), pages 1-36, October.
    19. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    20. Neij, Lena & Heiskanen, Eva & Strupeit, Lars, 2017. "The deployment of new energy technologies and the need for local learning," Energy Policy, Elsevier, vol. 101(C), pages 274-283.

    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:171:y:2019:i:c:p:49-60. 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.