Agrivoltaics and artificial intelligence. New geographies of power

Engineering notes

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Chinese explanation / 中文解读

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Original abstract

This paper explores the integration of Artificial Intelligence (AI) in agrivoltaic systems as a critical lens for understanding the socio-territorial implications of digital innovation in rural landscapes. Agrivoltaics, which combine agricultural production and solar energy generation on the same land, have emerged as a promising solution to the crises of energy transition and food security. However, their implementation raises significant questions about land use, community participation, and environmental justice. Through a series of case studies – including the European SYMBIOSYST project and two geospatial monitoring experiments using GIS and UAV technologies – the study investigates how AI-based tools such as predictive modelling, 3D digital twins, and sensor-integrated agritech platforms are reshaping the planning, governance, and visual representation of rural energy landscapes. While AI enhances the operational efficiency of agrivoltaic infrastructures and supports site-specific optimisation, it also introduces new spatial asymmetries, risks of algorithmic land grabbing, and challenges to data sovereignty. The analysis draws on critical geography to argue that AI should not be viewed merely as a technical enhancer but as a socio-technical actor that reconfigures power relations and decision-making in energy transitions. The cases discussed illustrate both the risks of centralised and extractive AI models and the opportunities for participatory and place-sensitive technological governance. The paper advocates for a geography-informed framework of AI adoption in the energy sector that promotes equity, transparency, and territorial justice.

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