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
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