Next-generation reverse logistics networks of photovoltaic recycling: Perspectives and challenges

Eleftherios Iakovou,Efstratios N. Pistikopoulos,Julien Walzberg, Funda Iseri, Halil Iseri, Natasha J. Chrisandina, Shivam Vedant, Catherine Nkoutche

SOLAR ENERGY(2024)

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摘要
With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end -of -life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy -making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end -to -end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision -making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource -Task -Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.
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