Scaling Dynamics in Energy Technologies: Historical Evidence & Implications

Presentation for Energy Technology Innovation Policy Occasional Speaker Series

Historical patterns of growth across a range of energy technologies are used to explore "scaling". Scaling is used to describe a particular form of growth that is (i) both rapid and substantive, taking into account the overall size of the energy system, and (ii) occurs at multiple levels from the technical unit and/or plant to the industry as a whole (e.g., from a wind turbine or wind farm to total installed wind capacity or manufacturing output). Scaling dynamics are assessed in historical time series data on vehicles, jet aircraft, refineries, and power plants (nuclear, coal, gas, wind). In those cases for which S-shaped growth is clearly evidenced, logistic function parameters are used to compare scaling across different technologies.

Three broad findings emerge. First, the relationship between the rate and extent of scaling at the industry level, whether measured in terms of gross capacity or total unit numbers, is consistent across different technologies. Secondly, the relationship between scaling at the unit level and scaling at the industry level is contingent on certain technology and market characteristics. A qualitative framework with five types of enabling factors is developed to explain different technologies' scaling dynamics. Thirdly, the evidence for changing scaling dynamics between core and periphery markets is mixed. For some but not all technologies, a "leapfrogging" of scaling at the unit level is evidenced from initial to subsequent markets.

Applications of these findings are discussed. The quantitative relationships between scaling parameters at the industry level can be used to "calibrate" the technological growth represented in long range scenario models. Using IIASA's recent Integated Assessment Modeling Framework family of baseline and carbon-constrained futures, installed capacity projections for different power generation technologies are tested against the historical evidence. This leads to a consideration of the constant unit scale assumptions typically used in technologically-explicit scenario models. Finally, the qualitative framework of enabling factors points to some general policy approaches to scaling low-carbon technologies in the future.

Dr. Charlie Wilson is a post-doctoral research scholar at IIASA, the International Institute of Applied Systems Analysis in Vienna, Austria. This research is being carried out as part of the "Transitions to New Technologies" program under the supervision of Dr Arnulf Gruebler.