ASU Insight: Different Technologies Different Learning Rates - Policy implications for energy investments

March 11, 2016

New Tools for Science Policy
Different Technologies, Different Learning Rates: Policy implications for energy investments

Learning curves have become a robust technique for modeling technological change in energy portfolios and as inputs into forecasting models. However traditional financial strategies have been applied to energy generation portfolios without full consideration of the effect of learning rates.


The simplicity and universality of the experience curve (or performance curve) framework led R&D managers to apply it to everything from airplane manufacturing to nuclear power plants.  It has been well understood for some time that different technologies have very different learning rates, but there was little or no theory as to why. Deborah Strumsky will discuss recent work that provided insights on the underlying determinants of learning rates differences across technologies, and the extent to which policies are able to accelerate or influence them.

Dr. Strumsky will discuss the implications of her research for policies related to mitigating climate change. Learning curves have become a robust technique for modeling technological change in energy portfolios and as inputs into forecasting models. However traditional financial strategies have been applied to energy generation portfolios without full consideration of the effect of learning rates. Dr. Strumsky will offer simulation results from recent work on improved energy portfolio investment strategies, and what it may mean for technologies like photovoltaics.

Speaker:

Deborah Strumsky
Assistant Research Professor, ASU-SFI Center for Biosocial Complex Systems