2232. Identification of Future PV Waste Hotspots in Germany: A Monte Carlo-Based Infrastructure Demand Analysis Using Market Data
Invited abstract in session WB-5: Behavioral Decision Approaches for Risk & Innovation, stream Decision Theory and Multi-criteria Decision Making.
Wednesday, 10:45-12:15Room: H7
Authors (first author is the speaker)
| 1. | Moritz Czyrnia
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| Lehrstuhl für Industriebetriebslehre, TUBAF | |
| 2. | Bastian Gaidzik
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| Lehrstuhl für Industriebetriebslehre, TUBAF |
Abstract
The increasing volume of aging photovoltaic (PV) systems in Germany will soon lead to a substantial rise in decommissioned modules requiring sustainable end-of-life management. However, the current infrastructure for PV module collection and recycling remains fragmented and uncoordinated, lacking the spatial and capacity planning needed to handle future volumes. In this study, we develop a spatio-temporal forecasting model by combining national installation data from the German “Marktstammdatenregister“ with a Monte Carlo simulation that incorporates uncertainty in system lifetimes, technology types, and degradation rates. The simulation runs multiple scenarios to project PV waste generation until 2050 at district level, capturing regional differences and trends over time. We assess logistical robustness and environmental performance by modeling transport distances, facility capacities, and greenhouse gas emissions associated with waste flows. The expected outcome is the identification of high-priority regions where future recycling infrastructure is most urgently needed. These findings enable evidence-based planning and highlight where investment and policy efforts should be directed to establish an efficient and low-emission recovery system. The analysis should provide a decision-support framework for policymakers, municipalities, and recycling firms aiming to scale PV waste management in line with circular economy principles and national sustainability goals.
Keywords
- Simulation
- Sustainable Development
- Energy Policy and Planning
Status: accepted
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