Exploring the potential of agrivoltaics in German vineyards: A GIS-based assessment

Abstract

The growing demand for renewable energy and sustainable agricultural practices has highlighted the potential of agrivoltaics (Agri-PV) as a promising solution, particularly in the context of German viticulture. The integration of photovoltaic systems in vineyards offers benefits, including optimized land use and resilience to weather extremes.

This study investigates the spatial potential for deploying Agri-PV systems over vineyards, with the objective of balancing renewable energy generation with agricultural productivity. To achieve this, a Geographic Information System (GIS)-based approach was employed, integrating geospatial datasets with over 24,000 data points to assess both energy generation potential and compatibility with ongoing agricultural activities. Key exclusion criteria, such as protected areas and unsuitable terrains, were applied to refine the analysis. A multi-criteria evaluation framework prioritized areas based on energy production potential, land use compatibility and proximity to infrastructure.

Preliminary results show significant opportunities for Agri-PV deployment in southern and southwestern Germany. The findings underscore the role of GIS tools in strategic planning for dual land use, showing that suitability varies across German wine regions. The approach identified several high-potential locations, which could serve as focal points for further feasibility studies and pilot projects. Nevertheless, the expansion of renewable energy in Germany often faces challenges related to the underutilization of existing infrastructure. Limited accessibility due to the lack of grid connection points in rural areas and the fragmented agricultural structure, characterized by small and scattered vineyard plots, complicates large-scale Agri-PV integration.

The results provide stakeholders with key data for sustainable Agri-PV implementation. This study underlines the high potential of GIS tools and geodatasets in addressing spatial and infrastructural challenges for renewable energy development. Limitations in data availability, such as incomplete grid information, affect the accuracy of site selection. To mitigate this, the approach utilizes community-driven map material from local stakeholders.