Existing mathematical models and tools for energy infrastructure planning primarily focus on designing and constructing new infrastructure, often neglecting decommissioning considerations [3]. While some models incorporate decommissioning decisions, they typically emphasize long-term planning, lack the granularity needed to capture the variability of intermittent energy sources, and do not evaluate different end-of-life options [4-6]. A growing global challenge is managing aging infrastructure, particularly as concerns over waste safety intensify and landfill capacity continues to decline. Additionally, emerging technologies such as solar panels, batteries, and electrolyzers rely on critical materials with high recovery potential, making end-of-life decisions increasingly important [7]. Therefore, next-generation energy systems must integrate end-of-life considerations to ensure sustainability by integrating the economic and environmental impacts of possible decommissioning strategies during system design.
In this work, we extend the model developed in [8], which introduces a multi-scale optimization framework for the design and planning of urban energy systems, to incorporate decommissioning analysis and end-of-life options, explicitly accounting for disposal, incineration, and recycling pathways for different energy technologies. The model optimizes system configuration and operation while assessing technology lifetimes' economic and environmental implications and decommissioning strategies. We apply this framework to a case study of the energy transition on a university campus, solving the model at an hourly resolution over a 35-year horizon to capture the variability of intermittent energy sources and interdependencies of multi-energy sources. The results provide insights into the role of end-of-life strategies in shaping sustainable energy infrastructure planning.
References
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