Mitigation strategies and energy technology learning: an assessment with the POLES model

This paper explores various dimensions of the learning process for low-carbon technologies under different mitigation scenarios. It uses the POLES model, which addresses learning as an endogenous phenomenon with learning curves, and a set of scenarios developed as part of the AMPERE project. It represents an analytical effort to understand the learning patterns of energy technologies in various contexts and tries to disentangle the different dimensions of the relation between these patterns and the deployment process. One result is, surprisingly, that apparent learning may be slower in mitigation scenarios with accelerated technology deployment when using two-factor learning curves. Second, the R&D analysis clearly shows that reductions in R&D budgets have significant impacts on long term technology costs. Third, solar technology which is more constrained by floor costs in the model benefits more from major technological breakthroughs than wind energy. Finally, ambitious stabilization targets can be met with limited cost increases in the electricity sector, thanks to the impact of learning effects on the improvement in technology costs and performances.