Energy Technology Learning - Key to Transform into a Low - Carbon Society

Abstract

Experience enhances capacity for effective action. Exploiting markets to provide experience on new technologies is the key to a low-carbon society. As market actors in the whole chain from technology producer to technology operator and user accumulate experience, both cost and technical performance of the technology improves. This process is referred to as technology learning (IEA, 2000). Learning curves (Wright, 1936) and experience curves (BCG, 1968; Abell and Hammond, 1979) measure the results of the process.1 Understanding the process of technology learning is of fundamental importance for a costefficient technology-led transformation into a low-carbon society. The implications of the process for energy technology policy were discussed at a workshop convened by the International Energy Agency in 1999. The IEA Workshop recommended that experience and learning curves “are used to analyse the cost and benefits of programmes to promote environment friendly technologies” and “explicitly considered in exploring scenarios to reduce CO2 emissions and calculating the cost of reaching emissions targets” (IEA, 2000, Appendix B). The IEA Committee on Energy Research and Technology (CERT) supported the findings of the Workshop and initiated an international collaboration (IEA, 2000, Appendix C). Technology learning is a key process in the global scenario analysis within the IEA Energy Technology Perspectives bi-annual publications (IEA, 2006; 2008; 2010a). More importantly, the IEA work together with other recent high-level policy documents embrace the insights from experience and learning curves into the crucial role of government deployment programmes to make low-carbon energy technologies cost-efficient (Stern, 2006; EESC, 2009). The IEA 1999 Workshop and subsequent work pointed to two major areas where technology learning should inform and guide energy technology policy: exploring and calculating cost for CO2-reduction scenarios and designing efficient deployment programmes. Kahouli-Brahmi (2008) provides an overview of global scale models incorporating technology learning to investigate CO2-reduction scenarios. The first investigations by