Changing diets and a growing population increase food demand in a context where agriculture already covers 38% of land. At the same time, climate change adds pressure on agriculture by threatening yields through extreme weather and water shortages. Furthermore, renewable energy like solar power, often proposed as part of a solution to climate change, also implies increased land requirements. The ongoing development of Agrivoltaic systems (AVS) could help solve these challenges by reducing land competition and offering protection and stable climates for crops or animals when the PV panels are placed above them (Sarr et al., 2023). AVS come in various configurations impacting electric and agricultural production differently. However, few Life Cycle Assessment (LCA) studies addressing AVS have been published and thus, only cover these configurations partially. Understanding the environmental impacts of all possible AVS configurations in different futures is, however, key to support policy decisions on their future deployment. The aim of our research was therefore to identify which AVS configurations should be favored because of their comparatively lower impacts than alternative conventional systems. To do so, we combine a highly parameterized consequential LCA model of AVS with a scenario discovery algorithm. The approach is meant to be as exhaustive as possible by studying a wide range of possibilities thus covering future possible climates, reactions of the AVS systems to demand (consequential modelling), agricultural yields and practices, technological improvements, and land market contexts.