Modelling light-sharing in agrivoltaics: the open-source Python Agrivoltaic Simulation Environment (PASE 1.0)
Driven by the urge to expand renewable energy generation and mitigate the intensifying extreme climatic events effects on crops, development of agrivoltaics is currently accelerating. However, harmonious deployment requires to assess both photovoltaic and crop yields to ensure simultaneous complianc...
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| Vydáno v: | Agroforestry systems Ročník 98; číslo 8; s. 2747 - 2764 |
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Springer Netherlands
01.12.2024
Springer Nature B.V Springer Science and Business Media B.V |
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| Abstract | Driven by the urge to expand renewable energy generation and mitigate the intensifying extreme climatic events effects on crops, development of agrivoltaics is currently accelerating. However, harmonious deployment requires to assess both photovoltaic and crop yields to ensure simultaneous compliance with energetic and agricultural objectives of stakeholders within evolving local legal contexts. Based on the community’s priority modelling needs, this paper presents the Python Agrivoltaic Simulation Environment (PASE), an MIT-licensed framework developed in partnership to assess the land productivity of agrivoltaic systems. The various expected benefits of this development are outlined, along with the open-source business model established with partners and the subsequent developments stemming from it. Examples illustrate how PASE effectively fulfils two primary requirements encountered by agrivoltaics stakeholders: predict irradiation on relevant surfaces and estimate agricultural and energy yields. In a dedicated experiment, PASE light model assumptions resulted in 1% error in the daily irradiation received by a sensor under two contrasted types of sky conditions. PASE’s ability to predict photovoltaic and crop yields and land equivalent ratio over several years is demonstrated for wheat on the BIODIV-SOLAR pilot. Ultimately, a sensitivity analysis of inter-row spacing demonstrates its usefulness to optimise systems according to different criteria. |
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| AbstractList | Driven by the urge to expand renewable energy generation and mitigate the intensifying extreme climatic events effects on crops, development of agrivoltaics is currently accelerating. However, harmonious deployment requires to assess both photovoltaic and crop yields to ensure simultaneous compliance with energetic and agricultural objectives of stakeholders within evolving local legal contexts. Based on the community’s priority modelling needs, this paper presents the Python Agrivoltaic Simulation Environment (PASE), an MIT-licensed framework developed in partnership to assess the land productivity of agrivoltaic systems. The various expected benefits of this development are outlined, along with the open-source business model established with partners and the subsequent developments stemming from it. Examples illustrate how PASE effectively fulfils two primary requirements encountered by agrivoltaics stakeholders: predict irradiation on relevant surfaces and estimate agricultural and energy yields. In a dedicated experiment, PASE light model assumptions resulted in 1% error in the daily irradiation received by a sensor under two contrasted types of sky conditions. PASE’s ability to predict photovoltaic and crop yields and land equivalent ratio over several years is demonstrated for wheat on the BIODIV-SOLAR pilot. Ultimately, a sensitivity analysis of inter-row spacing demonstrates its usefulness to optimise systems according to different criteria. |
| Author | De Cock, Nicolas Dittmann, Sebastian Leloux, Jonathan Perez, Etienne Lebeau, Frédéric Souquet, Pierre Drahi, Etienne Brunet, Pascal Bruhwyler, Roxane |
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| CitedBy_id | crossref_primary_10_1007_s10457_025_01248_y crossref_primary_10_1007_s40974_025_00358_8 crossref_primary_10_1016_j_ynexs_2025_100074 crossref_primary_10_1016_j_apenergy_2025_125558 |
| Cites_doi | 10.1016/j.fcr.2012.03.016 10.1080/01425918208909875 10.1007/s10457-023-00906-3 10.1109/PVSC45281.2020.9300652 10.1016/j.apenergy.2022.119560 10.1016/j.solener.2021.10.051 10.1016/j.apenergy.2017.09.113 10.1016/j.rser.2015.10.024 10.1016/j.rser.2023.114018 10.2760/208702 10.1093/insilicoplants/diad009 10.1016/j.solener.2019.09.041 10.1007/978-3-662-55565-1_17 10.5194/gmd-13-2315-2020 10.1016/j.atech.2022.100168 10.1016/j.eja.2019.01.009 10.1016/j.agwat.2018.07.001 10.1016/j.renene.2011.03.005 10.1109/CVPR52688.2022.00811 10.1016/j.jafr.2023.100875 10.1002/pip.2616 10.1016/j.apenergy.2021.118475 10.1016/j.compag.2023.108157 10.1016/j.rser.2020.110694 10.1002/9781118671603 10.17705/1cais.01637 10.2172/1660126 10.35690/978-2-7592-3679-4 10.1016/j.esd.2012.06.006 10.1016/j.seta.2023.103425 10.1016/j.apenergy.2018.03.081 10.1016/j.jclepro.2021.129091 |
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| Title | Modelling light-sharing in agrivoltaics: the open-source Python Agrivoltaic Simulation Environment (PASE 1.0) |
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