Open-Source Development of The Python Agrivoltaic Simulation Environment and Case Studies with PASE 1.0
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| Název: | Open-Source Development of The Python Agrivoltaic Simulation Environment and Case Studies with PASE 1.0 Développement Open-source de l'Environnement de Simulation Agrivoltaïque en Python et Cas d'Etude avec PASE 1.0 |
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| Autoři: | Bruhwyler, Roxane |
| Přispěvatelé: | Lebeau, Frédéric |
| Informace o vydavateli: | ULiège - Université de Liège, 2025. |
| Rok vydání: | 2025 |
| Témata: | agrivoltaics, modelling, crop model, light model, open-source, Engineering, computing & technology, Energy, Life sciences, Agriculture & agronomy, Computer science, Ingénierie, informatique & technologie, Energie, Sciences du vivant, Agriculture & agronomie, Sciences informatiques |
| Popis: | Driven by the urge to expand renewable energy generation, the development of agrivoltaics is currently accelerating. However, harmonious deployment requires evaluating 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 needs in terms of modelling, this thesis has developed a first version of the Python Agrivoltaic Simulation Environment (PASE), aunique open-source tool for predicting the agricultural and photovoltaic productivityof a variety of agrivoltaic systems. In fact, a review of previous work on agrivoltaicmodelling carried out as part of this thesis highlighted the cruel lack of a generic tool,modular, well balanced between the different components to be modelled, as well asbeing open and auditable by peers. This work therefore presents PASE 1.0, a MIT-licensed modelling framework developed in partnership with companies and researchgroups to assess the land productivity of agrivoltaic systems. The long-term development vision of PASE is explained and the various benefits expected from it aredescribed, as well as the open-source business model established with the partners andits subsequent developments. PASE 1.0 version architecture is also presented and thevarious calculation modules are described. Case studies then illustrate how PASE 1.0effectively fulfills three primary requirements encountered by agrivoltaics stakeholders: predict irradiation on relevant surfaces, estimate agricultural and energy yieldsas well as water use efficiency, and ease understanding of processes underlying fieldobservations.Two pilot agrivoltaic sites equipped with pyranometers were reproduced in PASEto evaluate the ray casting model and its assumptions. These showed errors of 7.7and -5.7 % on the total irradiation received at ground level during the measurementperiods. For each demonstrator, the model was evaluated on days with contrasting skyconditions. For one day in particular, the model showed an accuracy equivalent to thatof bifacial_radiance.PASE 1.0 was used in conjunction with the PVLib and PVFactors tools to assessthe suitability of a vertical agrivoltaic installation in Chile, in a region facing severeand recurring droughts. This work highlighted the potential for bimodal productionof vertical installations to avoid curtailment problems when the photovoltaic potentialwas high around midday. For irrigated agriculture of the region, PASE 1.0 evaluatedthe amount of potential evapotranspiration that could be saved thanks to the shadinginduced by photovoltaic modules and their estimated wind-break effect at 1410 m3/ha.PASE 1.0 ability to predict photovoltaic and agricultural yields as well as the landequivalent ratio over several years was demonstrated for a wheat crop as part of theBIODIV-SOLAR pilot project. The potential of vertical bifacial agrivoltaic installations to offset energy production was once again highlighted, and a more detailed studyshowed the periods and sky conditions that were favourable for this type of installation compared with a south-facing photovoltaic plant. Evaluation of crop yields overseveral years showed that the presence of the photovoltaic modules led to an averageyield reduction of 18.9 % with SIMPLE and 4.21 % with STICS. These differenceshighlighted the importance of the crop model choice and the associated formalisms. Asensitivity analysis of inter-row spacing also demonstrated the usefulness of PASE todesign systems according to the criteria set out in the legal frameworks.Finally, the results of the agronomic trial for the year 2023 on the same pilot sitewith spring wheat were presented, showing a low overall yield and a better yield inthe agrivoltaic zone. PASE 1.0 was used in co-simulation with STICS to completethe interpretation of these agronomic observations. The simulation made it possible tohypothesise that part of the difference in yield could be attributed to the reduction inheat stress resulting from the shading of the photovoltaic modules. It was also possibleto detect a nitrogen stress that would explain the low overall yields. |
| Druh dokumentu: | doctoral thesis http://purl.org/coar/resource_type/c_db06 doctoralThesis |
| Jazyk: | English |
| Relation: | https://gitlab.uliege.be/pase/pase_1.0 |
| Přístupová URL adresa: | https://orbi.uliege.be/handle/2268/326176 |
| Rights: | open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
| Přístupové číslo: | edsorb.326176 |
| Databáze: | ORBi |
| Abstrakt: | Driven by the urge to expand renewable energy generation, the development of agrivoltaics is currently accelerating. However, harmonious deployment requires evaluating 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 needs in terms of modelling, this thesis has developed a first version of the Python Agrivoltaic Simulation Environment (PASE), aunique open-source tool for predicting the agricultural and photovoltaic productivityof a variety of agrivoltaic systems. In fact, a review of previous work on agrivoltaicmodelling carried out as part of this thesis highlighted the cruel lack of a generic tool,modular, well balanced between the different components to be modelled, as well asbeing open and auditable by peers. This work therefore presents PASE 1.0, a MIT-licensed modelling framework developed in partnership with companies and researchgroups to assess the land productivity of agrivoltaic systems. The long-term development vision of PASE is explained and the various benefits expected from it aredescribed, as well as the open-source business model established with the partners andits subsequent developments. PASE 1.0 version architecture is also presented and thevarious calculation modules are described. Case studies then illustrate how PASE 1.0effectively fulfills three primary requirements encountered by agrivoltaics stakeholders: predict irradiation on relevant surfaces, estimate agricultural and energy yieldsas well as water use efficiency, and ease understanding of processes underlying fieldobservations.Two pilot agrivoltaic sites equipped with pyranometers were reproduced in PASEto evaluate the ray casting model and its assumptions. These showed errors of 7.7and -5.7 % on the total irradiation received at ground level during the measurementperiods. For each demonstrator, the model was evaluated on days with contrasting skyconditions. For one day in particular, the model showed an accuracy equivalent to thatof bifacial_radiance.PASE 1.0 was used in conjunction with the PVLib and PVFactors tools to assessthe suitability of a vertical agrivoltaic installation in Chile, in a region facing severeand recurring droughts. This work highlighted the potential for bimodal productionof vertical installations to avoid curtailment problems when the photovoltaic potentialwas high around midday. For irrigated agriculture of the region, PASE 1.0 evaluatedthe amount of potential evapotranspiration that could be saved thanks to the shadinginduced by photovoltaic modules and their estimated wind-break effect at 1410 m3/ha.PASE 1.0 ability to predict photovoltaic and agricultural yields as well as the landequivalent ratio over several years was demonstrated for a wheat crop as part of theBIODIV-SOLAR pilot project. The potential of vertical bifacial agrivoltaic installations to offset energy production was once again highlighted, and a more detailed studyshowed the periods and sky conditions that were favourable for this type of installation compared with a south-facing photovoltaic plant. Evaluation of crop yields overseveral years showed that the presence of the photovoltaic modules led to an averageyield reduction of 18.9 % with SIMPLE and 4.21 % with STICS. These differenceshighlighted the importance of the crop model choice and the associated formalisms. Asensitivity analysis of inter-row spacing also demonstrated the usefulness of PASE todesign systems according to the criteria set out in the legal frameworks.Finally, the results of the agronomic trial for the year 2023 on the same pilot sitewith spring wheat were presented, showing a low overall yield and a better yield inthe agrivoltaic zone. PASE 1.0 was used in co-simulation with STICS to completethe interpretation of these agronomic observations. The simulation made it possible tohypothesise that part of the difference in yield could be attributed to the reduction inheat stress resulting from the shading of the photovoltaic modules. It was also possibleto detect a nitrogen stress that would explain the low overall yields. |
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