Complex models of the global energy system are used to generate low carbon future scenarios to inform decision making on climate change mitigation (Riahi et al. 2007). Low carbon scenarios are characterised by widespread deployment of low carbon energy supply technologies (e.g., solar, bioenergy) and energy efficient end-use technologies (e.g., passive housing, hybrid electric vehicles). Technological change is ‘endogenised' or generated internally within the models by processes such as ‘learning' which describes how the performance of technologies improves as a function of experience (Pizer & Popp 2008).

The modelling of future technological change in the energy system is founded on historical evidence. There is an extensive literature examining the characteristics, processes and outcomes of technological change observed historically (Grubler 1998, Wilson 2012). Of particular relevance to low carbon future scenarios are examples of technological change which have been induced or driven by policy or regulation.

The central aims of this project are twofold: (1) to improve our understanding of the drivers of technological diffusion and induced (policy-driven) technological change historically; (2) to use historical evidence to inform how technological change is represented and calibrated in models of the global energy system. These are broad aims, and applicants are encouraged to define their own more specific area of research. This could focus on particular types of technology, particular policy settings, particular geographies or markets, or particular mechanisms of change.

With this in mind, the project will involve the following steps: (i) gathering technology-specific time series data to describe the historical diffusion of energy technologies; (ii) testing reduced-form equations that relate cost, efficiency and other technology characteristics to observed diffusion dynamics; (iii) developing a conceptual framework to capture the salient features of technological diffusion in a way that can be implemented in global energy system models; (iv) assessing the role of technological change in mitigating climate change using observed technological change historically as a reference point. Depending on the expertise and modelling experience of the successful applicant, this could involve collaboration with an existing modelling group, development of a simplified modelling framework, or work at a more conceptual level.

This project will be supervised within the Tyndall Centre network of universities. Opportunities exist for collaboration with other Tyndall Centre partners including the 4CMR group at Cambridge. This project is also associated with a major EU research consortium developing the next generation of energy system models, and opportunities for collaboration exist within this consortium, particularly with the MESSAGE group at the International Institute for Applied Systems Analysis (IIASA) in Austria.

Grubler, A. (1998). Technology and Global Change. Cambridge, UK, Cambridge University Press.

Pizer WA, Popp D (2008) Endogenizing technological change: Matching empirical evidence to modeling needs. Energy Economics 30 (6):2754-2770

Riahi, K., A. Grubler, et al. (2007). "Scenarios of long-term socio-economic and environmental development under climate stabilization." Technological Forecasting and Social Change 74(7): 887-935.

Wilson, C. (2012). "Up-Scaling, Formative Phases, and Learning in the Historical Diffusion of Energy Technologies." Energy Policy.