<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The global surge in photovoltaic (PV) panel deployment since the 2000s has contributed to advancing the renewable energy sector. However, this proliferation raises concerns about the increasing number of PV modules that will end their operational life in the coming years, necessitating effective planning for their decommissioning and recovery. This paper addresses this imminent challenge by presenting a predictive model to estimate the volume of decommissioned PV modules from existing installations. To consider the variability associated with the operational life duration of PV panels, two different scenarios were considered: early loss and regular loss, both modelled through the Weibull function. Furthermore, the article proposes a methodology for the economic valorization of materials recovered from decommissioned PV modules, according to the different technologies employed. This approach encourages sustainable practices by assigning an economic value to recovered materials and promoting a circular economy in the renewable energy sector. The economic valuation methodology adds practicality to dismantling, emphasising responsible waste management’s potential economic benefits. To illustrate the applicability of the model, the study focuses on the Italian case, providing a detailed regional breakdown. The regional analysis not only improves the accuracy of the predictive model but also offers insights into localised PV module disposal patterns. By adapting the methodology to the individual Italian regions, the article serves as a concrete and valuable resource during the programming and planning phases, facilitating the implementation of a strategy to efficiently recover PV modules and minimising the environmental impact associated with decommissioning activities.</p>
</abstract>

The global surge in photovoltaic (PV) panel deployment since the 2000s has contributed to advancing the renewable energy sector. However, this proliferation raises concerns about the increasing number of PV modules that will end their operational life in the coming years, necessitating effective planning for their decommissioning and recovery. This paper addresses this imminent challenge by presenting a predictive model to estimate the volume of decommissioned PV modules from existing installations. To consider the variability associated with the operational life duration of PV panels, two different scenarios were considered: early loss and regular loss, both modelled through the Weibull function. Furthermore, the article proposes a methodology for the economic valorization of materials recovered from decommissioned PV modules, according to the different technologies employed. This approach encourages sustainable practices by assigning an economic value to recovered materials and promoting a circular economy in the renewable energy sector. The economic valuation methodology adds practicality to dismantling, emphasising responsible waste management’s potential economic benefits. To illustrate the applicability of the model, the study focuses on the Italian case, providing a detailed regional breakdown. The regional analysis not only improves the accuracy of the predictive model but also offers insights into localised PV module disposal patterns. By adapting the methodology to the individual Italian regions, the article serves as a concrete and valuable resource during the programming and planning phases, facilitating the implementation of a strategy to efficiently recover PV modules and minimising the environmental impact associated with decommissioning activities.

A Predictive Framework for Photovoltaic Waste Quantities and Recovery Values: Insights and Application to the Italian Context

Department of Mechanical and Industrial Engineering

Environmental and Climate Technologies

This work is licensed under the Creative Commons Attribution 4.0 International License.

The global surge in photovoltaic (PV) panel deployment since the 2000s has contributed to advancing the renewable energy sector. However, this proliferation...

A Predictive Framework for Photovoltaic Waste Quantities and Recovery Values: Insights and Application to the Italian Context

Online veröffentlicht: 17. Juli 2024

Seitenbereich: 243 - 257

Eingereicht: 01. Apr. 2024

Akzeptiert: 13. Mai 2024

DOI: https://doi.org/10.2478/rtuect-2024-0020

Schlüsselwörter
Circular economy, economic assessment, end of life, modules, recovery, sustainability

© 2024 Andrea Franzoni et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Predictive Framework for Photovoltaic Waste Quantities and Recovery Values: Insights and Application to the Italian Context

Online veröffentlicht: 17. Juli 2024

Seitenbereich: 243 - 257

Eingereicht: 01. Apr. 2024

Akzeptiert: 13. Mai 2024

DOI: https://doi.org/10.2478/rtuect-2024-0020

SchlüsselwörterCircular economy, economic assessment, end of life, modules, recovery, sustainability

© 2024 Andrea Franzoni et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Circular economy, economic assessment, end of life, modules, recovery, sustainability