IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v155y2020icp396-406.html
   My bibliography  Save this article

Estimating regional potential for micro-hydropower energy recovery in irrigation networks on a large geographical scale

Author

Listed:
  • Crespo Chacón, Miguel
  • Rodríguez Díaz, Juan Antonio
  • García Morillo, Jorge
  • McNabola, Aonghus

Abstract

Micro-hydropower has been highlighted as a potential technology suitable for installation in irrigation networks to reduce system overpressures and to reduce the net energy consumption of the irrigation process. However, the full impact of this technology on a large regional scale is unknown. Artificial Neural Networks and regression models were used in this research to predict the energy recovery potential for micro-hydropower in on-demand pressurised irrigation networks across a large spatial scale. Predictors of energy recovery potential across spatial unit areas included: Irrigated land surface area, irrigation crop water requirements, rainfall, evapotranspiration, and mean topographical slope. The model was used to predict the energy recovery potential across the 164,000 ha of the Spanish provinces of Seville and Cordoba in the absence of hydraulic models. A total of 21.05 GWh was identified as the energy potential which could have been recovered using micro-hydropower during the 2018 irrigation season. This amount of energy would have potentially reduced the energy consumption of the irrigation process in this region by approximately 12.8%. A reduction in energy consumption in the agriculture sector of this magnitude could have significant impacts on food production and climate change. The main novelty of this paper lies in the assessment of micro hydropower resources in operating irrigation networks on a large geographical scale, in areas where no information is available. It provides an approximation of the existing potential using computational methods.

Suggested Citation

  • Crespo Chacón, Miguel & Rodríguez Díaz, Juan Antonio & García Morillo, Jorge & McNabola, Aonghus, 2020. "Estimating regional potential for micro-hydropower energy recovery in irrigation networks on a large geographical scale," Renewable Energy, Elsevier, vol. 155(C), pages 396-406.
    • Handle: RePEc:eee:renene:v:155:y:2020:i:c:p:396-406
    DOI: 10.1016/j.renene.2020.03.143
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120304766
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.03.143?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. Gallagher, J. & Harris, I.M. & Packwood, A.J. & McNabola, A. & Williams, A.P., 2015. "A strategic assessment of micro-hydropower in the UK and Irish water industry: Identifying technical and economic constraints," Renewable Energy, Elsevier, vol. 81(C), pages 808-815.
    2. García Morillo, J. & McNabola, A. & Camacho, E. & Montesinos, P. & Rodríguez Díaz, J.A., 2018. "Hydro-power energy recovery in pressurized irrigation networks: A case study of an Irrigation District in the South of Spain," Agricultural Water Management, Elsevier, vol. 204(C), pages 17-27.
    3. R. Perea & E. Poyato & P. Montesinos & J. Díaz, 2015. "Irrigation Demand Forecasting Using Artificial Neuro-Genetic Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5551-5567, December.
    4. Crespo Chacón, Miguel & Rodríguez Díaz, Juan Antonio & García Morillo, Jorge & McNabola, Aonghus, 2020. "Hydropower energy recovery in irrigation networks: Validation of a methodology for flow prediction and pump as turbine selection," Renewable Energy, Elsevier, vol. 147(P1), pages 1728-1738.
    5. Fernández García, I. & Rodríguez Díaz, J.A. & Camacho Poyato, E. & Montesinos, P. & Berbel, J., 2014. "Effects of modernization and medium term perspectives on water and energy use in irrigation districts," Agricultural Systems, Elsevier, vol. 131(C), pages 56-63.
    6. Rodriguez-Diaz, J.A. & Camacho-Poyato, E. & Lopez-Luque, R. & Perez-Urrestarazu, L., 2008. "Benchmarking and multivariate data analysis techniques for improving the efficiency of irrigation districts: An application in spain," Agricultural Systems, Elsevier, vol. 96(1-3), pages 250-259, March.
    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. Arciuolo, Thomas F. & Faezipour, Miad, 2022. "Yellowstone Caldera Volcanic Power Generation Facility: A new engineering approach for harvesting emission-free green volcanic energy on a national scale," Renewable Energy, Elsevier, vol. 198(C), pages 415-425.
    2. Kucukali, Serhat & Al Bayatı, Omar & Maraş, H. Hakan, 2021. "Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool," Renewable Energy, Elsevier, vol. 172(C), pages 633-650.
    3. Bortoluzzi, Mirian & Furlan, Marcelo & dos Reis Neto, José Francisco, 2022. "Assessing the impact of hydropower projects in Brazil through data envelopment analysis and machine learning," Renewable Energy, Elsevier, vol. 200(C), pages 1316-1326.
    4. Kemi Adeyeye & John Gallagher & Aonghus McNabola & Helena M. Ramos & Paul Coughlan, 2021. "Socio-Technical Viability Framework for Micro Hydropower in Group Water-Energy Schemes," Energies, MDPI, vol. 14(14), pages 1-21, July.
    5. Morabito, Alessandro & Vagnoni, Elena & Di Matteo, Mariano & Hendrick, Patrick, 2021. "Numerical investigation on the volute cutwater for pumps running in turbine mode," Renewable Energy, Elsevier, vol. 175(C), pages 807-824.
    6. Shojaeefard, Mohammad Hassan & Saremian, Salman, 2024. "Analyzing the impact of blade geometrical parameters on energy recovery and efficiency of centrifugal pump as turbine installed in the pressure-reducing station," Energy, Elsevier, vol. 289(C).
    7. Helena M. Ramos & Jorge G. Morillo & Juan A. Rodríguez Diaz & Armando Carravetta & Aonghus McNabola, 2021. "Sustainable Water-Energy Nexus towards Developing Countries’ Water Sector Efficiency," Energies, MDPI, vol. 14(12), pages 1-18, June.

    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. Crespo Chacón, Miguel & Rodríguez Díaz, Juan Antonio & García Morillo, Jorge & McNabola, Aonghus, 2020. "Hydropower energy recovery in irrigation networks: Validation of a methodology for flow prediction and pump as turbine selection," Renewable Energy, Elsevier, vol. 147(P1), pages 1728-1738.
    2. Venturini, Mauro & Manservigi, Lucrezia & Alvisi, Stefano & Simani, Silvio, 2018. "Development of a physics-based model to predict the performance of pumps as turbines," Applied Energy, Elsevier, vol. 231(C), pages 343-354.
    3. Kucukali, Serhat & Al Bayatı, Omar & Maraş, H. Hakan, 2021. "Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool," Renewable Energy, Elsevier, vol. 172(C), pages 633-650.
    4. Maria Castorino, Giulia Anna & Manservigi, Lucrezia & Barbarelli, Silvio & Losi, Enzo & Venturini, Mauro, 2023. "Development and validation of a comprehensive methodology for predicting PAT performance curves," Energy, Elsevier, vol. 274(C).
    5. Mérida García, Aida & Gallagher, John & Rodríguez Díaz, Juan Antonio & McNabola, Aonghus, 2024. "An economic and environmental optimization model for sizing a hybrid renewable energy and battery storage system in off-grid farms," Renewable Energy, Elsevier, vol. 220(C).
    6. Itani, Youssef & Soliman, Mohamed Reda & Kahil, Maher, 2020. "Recovering energy by hydro-turbines application in water transmission pipelines: A case study west of Saudi Arabia," Energy, Elsevier, vol. 211(C).
    7. Chacón, Miguel Crespo & Rodríguez Díaz, Juan Antonio & Morillo, Jorge García & McNabola, Aonghus, 2021. "Evaluation of the design and performance of a micro hydropower plant in a pressurised irrigation network: Real world application at farm-level in Southern Spain," Renewable Energy, Elsevier, vol. 169(C), pages 1106-1120.
    8. Firat Arslan & Juan Ignacio Córcoles Tendero & Juan Antonio Rodríguez Díaz & Demetrio Antonio Zema, 2023. "Comparison of Irrigation Management in Water User Associations of Italy, Spain and Turkey Using Benchmarking Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 55-74, January.
    9. J. Rodríguez Díaz & P. Montesinos & E. Poyato, 2012. "Detecting Critical Points in On-Demand Irrigation Pressurized Networks – A New Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1693-1713, April.
    10. Bekker, A. & Van Dijk, M. & Niebuhr, C.M., 2022. "A review of low head hydropower at wastewater treatment works and development of an evaluation framework for South Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    11. Hypolite, Gautier & Boutin, Olivier & Sole, Sandrine Del & Cloarec, Jean-François & Ferrasse, Jean-Henry, 2023. "Evaluation of a water network’s energy potential in dynamic operation," Energy, Elsevier, vol. 271(C).
    12. González Perea, R. & Camacho Poyato, E. & Rodríguez Díaz, J.A., 2021. "Forecasting of applied irrigation depths at farm level for energy tariff periods using Coactive neuro-genetic fuzzy system," Agricultural Water Management, Elsevier, vol. 256(C).
    13. Kandi, Ali & Meirelles, Gustavo & Brentan, Bruno, 2022. "Employing demand prediction in pump as turbine plant design regarding energy recovery enhancement," Renewable Energy, Elsevier, vol. 187(C), pages 223-236.
    14. Jiménez-Aguirre, M.T. & Isidoro, D., 2018. "Hydrosaline Balance in and Nitrogen Loads from an irrigation district before and after modernization," Agricultural Water Management, Elsevier, vol. 208(C), pages 163-175.
    15. Carricondo-Antón, J.M. & Jiménez-Bello, M.A. & Manzano Juárez, J. & Royuela Tomas, A. & Sala, A., 2022. "Evaluating the use of meteorological predictions in directly pumped irrigational operations using photovoltaic energy," Agricultural Water Management, Elsevier, vol. 266(C).
    16. Soto-García, M. & Martínez-Alvarez, V. & García-Bastida, P.A. & Alcon, F. & Martin-Gorriz, B., 2013. "Effect of water scarcity and modernisation on the performance of irrigation districts in south-eastern Spain," Agricultural Water Management, Elsevier, vol. 124(C), pages 11-19.
    17. Salgado, Ramiro & Mateos, Luciano, 2021. "Evaluation of different methods of estimating ET for the performance assessment of irrigation schemes," Agricultural Water Management, Elsevier, vol. 243(C).
    18. Tarjuelo, José M. & Rodriguez-Diaz, Juan A. & Abadía, Ricardo & Camacho, Emilio & Rocamora, Carmen & Moreno, Miguel A., 2015. "Efficient water and energy use in irrigation modernization: Lessons from Spanish case studies," Agricultural Water Management, Elsevier, vol. 162(C), pages 67-77.
    19. Moreno-Pérez, M. Fátima & Roldán-Cañas, José, 2013. "Assessment of irrigation water management in the Genil-Cabra (Córdoba, Spain) irrigation district using irrigation indicators," Agricultural Water Management, Elsevier, vol. 120(C), pages 98-106.
    20. van Halsema, Gerardo E. & Vincent, Linden, 2012. "Efficiency and productivity terms for water management: A matter of contextual relativism versus general absolutism," Agricultural Water Management, Elsevier, vol. 108(C), pages 9-15.

    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:renene:v:155:y:2020:i:c:p:396-406. 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/renewable-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.