PV in the circular economy, a dynamic framework analyzing technology evolution and reliability impacts

Abstract

Summary Rapid, terawatt-scale deployment of photovoltaic (PV) modules is required to decarbonize the energy sector. Despite efficiency and manufacturing improvements, material demand will increase, eventually resulting in waste as deployed modules reach end of life. Circular choices for decommissioned modules could reduce waste and offset virgin materials. We present PV ICE, an open-source python framework using modern reliability data, which tracks module material flows throughout PV life cycles. We provide dynamic baselines capturing PV module and material evolution. PV ICE includes multimodal end of life, circular pathways, and manufacturing losses. We present a validation of the framework and a sensitivity analysis. Results show that manufacturing efficiencies strongly affect material demand, representing >20% of the 9 million tons of waste cumulatively expected by 2050. Reliability and circular pathways represent the best opportunities to reduce waste by 56% while maintaining installed capacity. Shorter-lived modules generate 81% more waste and reduce 2050 capacity by 6%.

Circular economy priorities for photovoltaics in the energy transition

“…Most deployment scenarios assume a constant lifetime, but c-Si PV module and system lifetimes have steadily increased, from around 15 years in the 1990s to between 32 and 35 years currently [41]. PV ICE baselines capture historical and expected technology changes and improvements, including lifetime, reliability, module efficiency, and material efficiency and composition [38]. Lifetime and reliability parameters are varied, while module and material improvements are identical across all scenarios; more details are available in the Methods section and in Ovaitt and Mirletz 2022 [38].…”

“…PV ICE baselines capture historical and expected technology changes and improvements, including lifetime, reliability, module efficiency, and material efficiency and composition [38]. Lifetime and reliability parameters are varied, while module and material improvements are identical across all scenarios; more details are available in the Methods section and in Ovaitt and Mirletz 2022 [38]. We use PV ICE baselines as our best conservative guess of future c-Si module properties and as a comparison point for our what-if analysis results.…”

“…In this work, we define effective capacity as all cumulative nameplate installations (in this deployment case, 1.75 TW) minus failures, EoL retirements, and expected power degradation; this quantity is inherently cumulative and represents available generation capacity which will always be smaller than the nameplate installed capacity. Effective capacity calculations include continuing improvements in module efficiency and account for power degradation [38]. Effective capacity is strongly dependent on module lifetime.…”

“…Both strategies will be evaluated on their ability to deploy and maintain decarbonization capacities as well as quantities of extraction and waste. PV ICE is a quantitative dynamic framework for evaluating PV module and system materials, manufacturing, design, and life cycle management options [38,39]. PV ICE uses dynamic, user-defined module properties, component material composition, and deployment forecasts to calculate the effective capacity (defined below), virgin material demands, and life cycle wastes accounting for circular material flows.…”

Environmental and Circular Economy Implications of Solar Energy in a Decarbonized U.S. Grid

“…Please note that different from the results provided in the report, Appendix Tables B-2 and B-4 also consider polymers, including backsheet and encapsulants, which have recently been added to PViCE, documented inOvaitt et al. (2022) 305.…”