The new research responds to the need of more solid empirically founded representation of technology diffusion or upscaling constraints. These are critical for understanding the pace at which energy systems may change, and are thus central to a more informed discussion on the attainability of ambitious climate change targets. The prototype of the model was developed by Volker Krey in collaboration with Arnulf Grubler of Transitions to New Technologies (TNT).
A second stream of research on technology dynamics by the TNT and Energy (ENE) programs with the University of East Anglia analyzed historical growth patterns of energy technologies. The research covered a wide range, from energy supply technologies such as oil refineries and different types of power plants (fossil, nuclear, wind, photovoltaics) to end-use technologies of various kinds (e.g., passenger aircraft, cars, compact fluorescent light bulbs, and mobile phones).
A comparative analysis of historical growth dynamics with those in integrated assessment models was carried out together with colleagues from the ReMIND modeling team at PIK. The study, which appeared in the journal Climatic Change , suggests that the models tend to be conservative in their projected technology diffusion rates compared to what has been observed historically.
 Wilson C, Grubler A, Bauer N, Krey V, Riahi K (2013). Future capacity growth of energy technologies: Are scenarios consistent with historical evidence? Climatic Change, 118(2):381-395
Research Institute of Innovative Technology for the Earth (RITE), Japan;
University of East Anglia, UK;
Potsdam Institute for Climate Research Impact (PIK), Germany,
Last edited: 22 May 2014
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