Multi-cluster technology learning in times: A transport sector case study with TIAM-UCL
1 January 2015
The costs of technologies often fall over time due to a range of processesincluding learning-by-doing. This is a well-characterized concept in the economicsof innovation, in which learning about a particular technology, and hence costreduction, is related to cumulative investments in that technology. This chapterprovides a case study applying technology learning endogenously in a TIMESmodel. It describes many of the key challenges in modelling technology learningendogenously, both in terms of the interpretation and policy relevance of the results,and in terms of methodological challenges. The chapter then presents a case study,exploring a multi-cluster learning approach where many key technologies (fuelcells, automotive batteries, and electric drivetrains) are shared across a set oftransport modes (cars, buses and LGVs) and technologies (hybrid and plug-inhybrid fuel cell vehicles, battery electric vehicles, hybrid and plug-in hybrid petroland diesel vehicles). The multi-region TIAM-UCL Global energy system model hasbeen used to model the multi-cluster approach. The analysis is used to explore thecompetitive and/or complementary relationship between hydrogen and electricity aslow-carbon transport fuels.
Multi-cluster technology learning in times: A transport sector case study with TIAM-UCL. Lecture Notes in Energy, 30 261-278.
Anandarajah, G., McDowall, W. (2015)
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