Making informed estimates of future energy technology costs is central to understanding the cost of the low-carbon transition. A number of methods have been used to make such estimates: extrapolating empirically derived learning rates; use of expert elicitations; and engineering assessments which analyse future developments for technology components’ cost and performance parameters. In addition, there is a rich literature on different energy technology innovation systems analysis frameworks, which identify and analyse the many processes that drive technologies’ development, including those that make them increasingly cost-competitive and commercially ready. However, there is a surprising lack of linkage between the fields of technology cost projections and technology innovation systems analysis. There is a clear opportunity to better relate these two fields, such that the detailed processes included in technology innovation systems frameworks can be fully considered when estimating future energy technology costs.

Here we demonstrate how this can be done. We identify that learning curve, expert elicitation and engineering assessment methods already either implicitly or explicitly incorporate some elements of technology innovation systems frameworks, most commonly those relating to R&D and deployment-related drivers. Yet they could more explicitly encompass a broader range of innovation processes. For example, future cost developments could be considered in light of the extent to which there is a well-functioning energy technological innovation system (TIS), including support for the direction of technology research, industry experimentation and development, market formation including by demand-pull policies and technology legitimation. We suggest that failure to fully encompass such processes may have contributed to overestimates of nuclear cost reductions and under-estimates of offshore wind cost reductions in the last decade.