Meta-analysis of Unit and Industry Level Scaling Dynamics in Energy Technologies and Climate Change Mitigation Scenarios

Wilson, C. ORCID: https://orcid.org/0000-0001-8164-3566 (2009). Meta-analysis of Unit and Industry Level Scaling Dynamics in Energy Technologies and Climate Change Mitigation Scenarios. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-09-029

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Abstract

Historical patterns of growth across a range of energy technologies are used to explore 'scaling'. The term scaling is used to describe a particular form of growth that is (i) both rapid and substantive, and (ii) occurs at multiple levels from the technical unit to the industry as a whole (e.g., from a wind turbine to total installed wind capacity). Unit and industry scaling dynamics are assessed in historical time series data on refineries, power plants (nuclear, coal, gas, wind), jet aircraft, cars and light bulbs. 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 from the meta-analysis. Firstly, the relationship between the extent and rate of scaling at the industry level, measured in terms of cumulative total capacity, is consistent across both supply-side and end use 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 conceptual framework with six enabling factors is developed to explain different technologies' scaling dynamics. Thirdly, there is little evidence to support a 'leapfrogging' of scaling dynamics as technologies diffuse spatially from initial to subsequent and late markets.

Applications of these findings are discussed. Firstly, the historical relationships between scaling parameters at the industry level are used to validate projections of low carbon technologies in future scenarios. Despite orders of magnitude projected increases in installed capacities of nuclear power, carbon capture and storage, and renewable energy by 2100, scenarios are found to be conservative in comparison with historical scaling relationships. Reasons why are discussed. Secondly, the conceptual framework of enabling factors for industry scaling is used to illustrate policy approaches for scaling low carbon technologies in the future.

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