LAPSE:2023.28377
Published Article

LAPSE:2023.28377
Decision Support Tool for the Optimal Sizing of Solar Irrigation Systems
April 11, 2023
Abstract
Solar photovoltaic (PV) irrigation is increasingly used in agriculture, driven by its low operation cost and virtually zero emissions, providing electricity access in rural areas. However, the high investment cost requires an optimal design. The objective of this work was to develop a user-friendly tool to optimally size a PV generator that satisfies crop irrigation needs under local constrictions. The ODSIS (Optimal Design of Solar Irrigation System) tool, was organized in three calculation modules, preceded by two complements, which determine the daily crop irrigation needs and power demand of the pumping system. Then, the first module sizes the PV plant, considering a multiplication factor, and provides the PV production potential throughout each day of the season. The second and third modules evaluate the total investment cost and equivalent greenhouse gas emissions avoided by comparison with traditional energy sources. This tool was applied to a case study in Senegal for which a multiplication factor of 1.4 was obtained for the optimal PV plant size. Between 22% to 64% of the investment cost corresponded to the PV pumping system, depending on the irrigation technique. The use of PV energy in the case study would represent an annual economic saving for the farmer after 5 to 8 years of payback period, avoiding the emission of between 29.8 and 37.9 tCO2eq/year for the case study area.
Solar photovoltaic (PV) irrigation is increasingly used in agriculture, driven by its low operation cost and virtually zero emissions, providing electricity access in rural areas. However, the high investment cost requires an optimal design. The objective of this work was to develop a user-friendly tool to optimally size a PV generator that satisfies crop irrigation needs under local constrictions. The ODSIS (Optimal Design of Solar Irrigation System) tool, was organized in three calculation modules, preceded by two complements, which determine the daily crop irrigation needs and power demand of the pumping system. Then, the first module sizes the PV plant, considering a multiplication factor, and provides the PV production potential throughout each day of the season. The second and third modules evaluate the total investment cost and equivalent greenhouse gas emissions avoided by comparison with traditional energy sources. This tool was applied to a case study in Senegal for which a multiplication factor of 1.4 was obtained for the optimal PV plant size. Between 22% to 64% of the investment cost corresponded to the PV pumping system, depending on the irrigation technique. The use of PV energy in the case study would represent an annual economic saving for the farmer after 5 to 8 years of payback period, avoiding the emission of between 29.8 and 37.9 tCO2eq/year for the case study area.
Record ID
Keywords
greenhouse gas emissions, investment cost, manual and drip irrigation, PV energy production, sizing optimization tool
Subject
Suggested Citation
Sarr A, Mérida-García A, Diop L, Mateos L, Lamaddalena N, Rodríguez-Díaz JA. Decision Support Tool for the Optimal Sizing of Solar Irrigation Systems. (2023). LAPSE:2023.28377
Author Affiliations
Sarr A: Renewable Energy and Energy Efficiency Laboratory, International Institute for Water and Environmental Engineering, Rue de la Science, Ouagadougou 01 BP 594, Burkina Faso
Mérida-García A: Civil Structural and Environmental Engineering Department, Trinity College Dublin, D02 PN40 Dublin, Ireland; Department of Agronomy, University of Cordoba, 14071 Córdoba, Spain [ORCID]
Diop L: Faculty of Agronomic Sciences, Aquaculture and Food Technology, Gaston Berger University, Saint-Louis P.O. Box 234, Senegal [ORCID]
Mateos L: Institute for Sustainable Agriculture, Consejo Superior de Investigaciones Científicas (CSIC), 28006 Córdoba, Spain
Lamaddalena N: Irrigated Agriculture, Mediterranean Agronomic Institute of Bari (CIHEAM BARI), 70010 Bari, Italy
Rodríguez-Díaz JA: Department of Agronomy, University of Cordoba, 14071 Córdoba, Spain [ORCID]
Mérida-García A: Civil Structural and Environmental Engineering Department, Trinity College Dublin, D02 PN40 Dublin, Ireland; Department of Agronomy, University of Cordoba, 14071 Córdoba, Spain [ORCID]
Diop L: Faculty of Agronomic Sciences, Aquaculture and Food Technology, Gaston Berger University, Saint-Louis P.O. Box 234, Senegal [ORCID]
Mateos L: Institute for Sustainable Agriculture, Consejo Superior de Investigaciones Científicas (CSIC), 28006 Córdoba, Spain
Lamaddalena N: Irrigated Agriculture, Mediterranean Agronomic Institute of Bari (CIHEAM BARI), 70010 Bari, Italy
Rodríguez-Díaz JA: Department of Agronomy, University of Cordoba, 14071 Córdoba, Spain [ORCID]
Journal Name
Processes
Volume
11
Issue
3
First Page
942
Year
2023
Publication Date
2023-03-20
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr11030942, Publication Type: Journal Article
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LAPSE:2023.28377
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https://doi.org/10.3390/pr11030942
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Apr 11, 2023
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