Analyzing Dynamic Prospective Data Integration in Energy Industry Life Cycle Assessment on a Case Study of a Power Transformer

The results of life cycle assessments (LCAs) are used for sustainable decision-making. Parameters that impact environmental performance during a product’s lifetime, e.g., operational electricity mix, are subject to future change. Especially in energy technologies with a long lifespan, future developments need to be included early in the tender stage by utilizing prospective LCA. Existing studies of transformers show that the significant global warming potential (GWP) impact results from operational electricity losses. The influence on industrial LCA from considering future developments already in a project’s tender phase is analyzed in this paper by implementing a future German electricity mix for the operation stage of a power transformer. The results show a reduction of 85% in the transformer’s GWP by integration of prospective data from 2030 and 2050 and 90% when prospective data are integrated in 5-year steps until 2050. This reflection of further developments makes product LCA results more accurate and therefore impacts, e.g., reported scope 3 emissions. The increased resolution of a product model allows focusing on parameters that are relevant during a product’s lifetime and developing, e.g., tailor-made circularity measures to improve the product’s environmental performance, thereby supporting sustainable decision-making.