IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v377y2025ipas0306261924014909.html
   My bibliography  Save this article

Designing a predictive optimal water and energy irrigation (POWEIr) controller for solar-powered drip irrigation systems in resource-constrained contexts

Author

Listed:
  • Sheline, Carolyn
  • Grant, Fiona
  • Gelmini, Simone
  • Pratt, Shane
  • Winter V., Amos G.

Abstract

Sustainable agriculture intensification is necessary to meet the food needs of the growing global population without further exacerbating water scarcity or contributing to climate change. This paper presents the Predictive Optimal Water and Energy Irrigation (POWEIr) controller, a precision irrigation controller for solar-powered drip irrigation (SPDI) systems. The POWEIr controller optimizes SPDI energy and water use, provides an optimal irrigation schedule to the user, and is shown to reduce the overall system cost. An economic analysis shows that modeling season-long operation and improving solar energy use efficiency can save 18%–74% in the solar pump lifetime cost while delivering irrigation 31%–66% more reliably than existing commercial SPDI systems. The POWEIr controller uses a small, inexpensive set of sensors and leverages physics-based models and machine learning to make energy and crop water demand predictions. The POWEIr theory was validated with an experimental prototype of the controller that was used to operate a small-scale SPDI system. The results demonstrate that the POWEIr controller can use a small battery to ensure irrigation reliability despite prediction uncertainty and weather variability. On large water demand days the POWEIr controller prototype had up to 46% higher solar irrigation reliability compared to simulated typical practices and used six times less battery storage to deliver the required irrigation. This means that the POWEIr controller could enable more reliable irrigation with a smaller, less expensive battery for energy storage. The POWEIr controller has the potential to increase the adoption of precision irrigation technology and sustainable irrigation methods among farmers in resource-constrained contexts, which in turn could advance sustainable agriculture intensification globally.

Suggested Citation

  • Sheline, Carolyn & Grant, Fiona & Gelmini, Simone & Pratt, Shane & Winter V., Amos G., 2025. "Designing a predictive optimal water and energy irrigation (POWEIr) controller for solar-powered drip irrigation systems in resource-constrained contexts," Applied Energy, Elsevier, vol. 377(PA).
    • Handle: RePEc:eee:appene:v:377:y:2025:i:pa:s0306261924014909
    DOI: 10.1016/j.apenergy.2024.124107
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924014909
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.124107?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. I. Fernández García & J. Rodríguez Díaz & E. Camacho Poyato & P. Montesinos, 2013. "Optimal Operation of Pressurized Irrigation Networks with Several Supply Sources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2855-2869, June.
    2. van der Kooij, Saskia & Zwarteveen, Margreet & Boesveld, Harm & Kuper, Marcel, 2013. "The efficiency of drip irrigation unpacked," Agricultural Water Management, Elsevier, vol. 123(C), pages 103-110.
    3. Angel L. Cedeño & Reinier López Ahuar & José Rojas & Gonzalo Carvajal & César Silva & Juan C. Agüero, 2022. "Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming," Energies, MDPI, vol. 15(17), pages 1-21, September.
    4. Grant, Fiona & Sheline, Carolyn & Sokol, Julia & Amrose, Susan & Brownell, Elizabeth & Nangia, Vinay & Winter, Amos G., 2022. "Creating a Solar-Powered Drip Irrigation Optimal Performance model (SDrOP) to lower the cost of drip irrigation systems for smallholder farmers," Applied Energy, Elsevier, vol. 323(C).
    5. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    6. Zavala, V. & López-Luque, R. & Reca, J. & Martínez, J. & Lao, M.T., 2020. "Optimal management of a multisector standalone direct pumping photovoltaic irrigation system," Applied Energy, Elsevier, vol. 260(C).
    7. Cetin, O. & Bilgel, L., 2002. "Effects of different irrigation methods on shedding and yield of cotton," Agricultural Water Management, Elsevier, vol. 54(1), pages 1-15, March.
    8. Lowder, Sarah K. & Skoet, Jakob & Raney, Terri, 2016. "The Number, Size, and Distribution of Farms, Smallholder Farms, and Family Farms Worldwide," World Development, Elsevier, vol. 87(C), pages 16-29.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Zha, Junjie & Ge, Maosheng & Tang, Zhengwen & Lei, Junyao & Zhao, Haoyu & Zhang, Yongqiang, 2024. "The incorporation of solar energy and compressed air into the energy supply system enhances the environmentally friendly and efficient operation of drip irrigation systems," Agricultural Water Management, Elsevier, vol. 302(C).
    3. Luis Bauluz & Yajna Govind & Filip Novokmet, 2020. "Global Land Inequality," PSE Working Papers halshs-03022318, HAL.
    4. Godfred Addai & Jungho Suh & Douglas Bardsley & Guy Robinson & Lawrence Guodaar, 2024. "Exploring sustainable development within rural regions in Ghana: A rural web approach," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(4), pages 3890-3907, August.
    5. Giuliani, Nicola & Aguzzoni, Agnese & Penna, Daniele & Tagliavini, Massimo, 2023. "Estimating uptake and internal transport dynamics of irrigation water in apple trees using deuterium-enriched water," Agricultural Water Management, Elsevier, vol. 289(C).
    6. Forough Jafary & Chris Bradley, 2018. "Groundwater Irrigation Management and the Existing Challenges from the Farmers’ Perspective in Central Iran," Land, MDPI, vol. 7(1), pages 1-21, January.
    7. Livia Marchetti & Valentina Cattivelli & Claudia Cocozza & Fabio Salbitano & Marco Marchetti, 2020. "Beyond Sustainability in Food Systems: Perspectives from Agroecology and Social Innovation," Sustainability, MDPI, vol. 12(18), pages 1-24, September.
    8. Chen, Dali & Bao, Jinglong & Chen, Tao & Bai, Mengjie & Pan, Jia & Yuan, Haiying & Wang, Yanrong & Nan, Zhibiao & Hu, Xiaowen, 2024. "Effect of drip irrigation and boron application on enhancing seed production of sainfoin (Onobrychis viciifolia) in Northwest China," Agricultural Water Management, Elsevier, vol. 306(C).
    9. Imran Ali Lakhiar & Haofang Yan & Chuan Zhang & Guoqing Wang & Bin He & Beibei Hao & Yujing Han & Biyu Wang & Rongxuan Bao & Tabinda Naz Syed & Junaid Nawaz Chauhdary & Md. Rakibuzzaman, 2024. "A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints," Agriculture, MDPI, vol. 14(7), pages 1-40, July.
    10. Hurley, Mason, 2016. "Re-examining Changes in Farm Size Distributions Worldwide Using a Modified Generalized Method of Moments Approach," Master's Theses and Plan B Papers 249287, University of Minnesota, Department of Applied Economics.
    11. Yuewen Huo & Songlin Ye & Zhou Wu & Fusuo Zhang & Guohua Mi, 2022. "Barriers to the Development of Agricultural Mechanization in the North and Northeast China Plains: A Farmer Survey," Agriculture, MDPI, vol. 12(2), pages 1-14, February.
    12. Dang, Hai-Anh H & Carletto, Calogero, 2022. "Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation," IZA Discussion Papers 14997, Institute of Labor Economics (IZA).
    13. Ruiqi Zhang & Chunguang Hu & Yucheng Sun, 2024. "Decoding the Characteristics of Ecosystem Services and the Scale Effect in the Middle Reaches of the Yangtze River Urban Agglomeration: Insights for Planning and Management," Sustainability, MDPI, vol. 16(18), pages 1-26, September.
    14. Hung‐Hao Chang & Ashok K. Mishra & Tzong‐Haw Lee, 2019. "A supply‐side analysis of agritourism: Evidence from farm‐level agriculture census data in Taiwan," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(3), pages 521-548, July.
    15. Peipei Yang & Wenxu Dong & Marius Heinen & Wei Qin & Oene Oenema, 2022. "Soil Compaction Prevention, Amelioration and Alleviation Measures Are Effective in Mechanized and Smallholder Agriculture: A Meta-Analysis," Land, MDPI, vol. 11(5), pages 1-18, April.
    16. Regan, Courtney M. & Connor, Jeffery D. & Summers, David M. & Settre, Claire & O’Connor, Patrick J. & Cavagnaro, Timothy R., 2020. "The influence of crediting and permanence periods on Australian forest-based carbon offset supply," Land Use Policy, Elsevier, vol. 97(C).
    17. Ruth Hill & Carolina Mejia-Mantilla & Kathryn Vasilaky, 2021. "Is the Price Right? Returns to Input Adoption in Uganda," Working Papers 2105, California Polytechnic State University, Department of Economics.
    18. T. S. Amjath-Babu & Pramod K. Aggarwal & Sonja Vermeulen, 2019. "Climate action for food security in South Asia? Analyzing the role of agriculture in nationally determined contributions to the Paris agreement," Climate Policy, Taylor & Francis Journals, vol. 19(3), pages 283-298, March.
    19. Rauch, Theo & Brüntrup, Michael, 2021. "Approaches for supporting smallholders in the Global South: Contentious issues, experiences, syntheses," Briefing Papers 1/2021, German Institute of Development and Sustainability (IDOS).
    20. Britos, Braulio & Hernandez, Manuel A. & Robles, Miguel & Trupkin, Danilo R., 2022. "Land market distortions and aggregate agricultural productivity: Evidence from Guatemala," Journal of Development Economics, Elsevier, vol. 155(C).

    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:appene:v:377:y:2025:i:pa:s0306261924014909. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.