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Energy Systems Modelling

ESM Research: the Future Technology Transformations (FTT) project

NOTE: JFM is moving away to become Assistant Professor at the department of Environmental Sciences, Radboud Universiteit Nijmegen, The Netherlands.
These PhD project subjects are still possible, although now at RU (not anymore in Cambridge), and without funding for the moment.
 
 
Group Leader:  Jean-Francois Mercure 
Group Members:
                    Pablo Salas
                    Aileen Lam
                    Siyuan He

Energy systems modelling research at ESM-4CMR revolves around the Future Technology Transformations (FTT) project, funded by the EPSRC. FTT is a general modelling framework of technology substitution dynamics for generating scenarios of future technology and energy use in order to calculate future greenhouse gas emission. It is adaptable to any framework (i.e. IAMs, E3 or economic models), but is also integrated within 4CMR's macroeconomic model of the global economy E3MG, in close partnership with Cambridge Econometrics. This work is also done in collaboration with researchers at the Tyndall Centre for Climate Change Research.

The diagram below shows the structure of the model, it’s component parts and how these interact dynamically with one another as the system is run in time steps into the future. This system also features the core driving GHG emissions in 4CMR integrated climate impacts assessment platform.

BoxModel.jpg

FTT components

FTT:Power is a simulation model of the global power sector, emphasising technology substitution. It projects the future evolution of the power sector in 21 regions, 24 power technologies and 13 types of natural resources. (see refs [3,4,5] below). 

The energy resources database is used to constrain all models of technological change of the FTT family, particularly FTT:Power. It generates increasing marginal costs of production of energy for 13 types of natural resources, for 190 countries which can be re-aggregated in any desired way. 
(see ref [1] for access to the whole database in paper form). 

The model of energy commodity price dynamics and non-renewable energy resource consumption operates between the natural resource database and the FTT family of technology models. It calculates marginal costs of production of non-renewable resources (oil, gas, coal and nuclear fuels) and is used to determine long term prices. The theory behind this model can be found in ref [2].

FTT:Transport is a model of technological change in the transport sector currently under development. It will simulate technology substitutions and fuel use in transport in order to explore transport policy. Currently under development.

FTT:Industry is a model under development of technological change in the major GHG emitters of the global industrial sector, which includes the metals, cement, chemicals and other industries. Currently under exploration.

FTT:Buildings is a model under development that groups possible changes of technology in buildings and households. This concerns primarily heating, cooling and lighting appliances. Connected to FTT:Power, this will change significantly the strain given to electricity production and thus to natural resources. 

The goal of the FTT project is to construct a simulation of technology substitutions, energy use and GHG emissions in all sectors of the global economy simultaneously. 

References
        
[1] J.-F. Mercure and P. Salas, An assessment of global energy resource economic potentials, Energy, 46, 322-336 (2012), Free text available on ArXiV arXiv:1205.4693v2

[2] J.-F. Mercure and P. Salas, On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities, Energy Policy
Open Access: http://dx.doi.org/10.1016/j.enpol.2013.08.040 
Also available on ArXiv arXiv:1209.0708 [q-fin.GN]

[3] J.-F. Mercure, FTT:Power : A global model of the power sector with induced technological change and natural resource depletion, Energy Policy 48, 799-811 (2012)
Free text available on ArXiv arXiv:1205.4868 
[4] J.-F. Mercure, An age structured demographic theory of technological change. 4th International Conference on Sustainability Transitions, Zurich, 2013 (2013). 
Preprint available on ArXiv: arxiv:1304.3602

[5] J.-F. Mercure, H. Pollitt, U. Chewpreecha, P. Salas, A.M. Foley, P.B. Holden, N.R. Edwards, The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector. Energy Policy 73  686–700 (2014) Open Access http://dx.doi.org/10.1016/j.enpol.2014.06.029

               
PhD opportunities

Opportunities for PhD projects connected with the FTT energy systems modelling system are available (although funding from 4CMR is not available at the moment). Several avenues exist for carrying out important improvements or constructing entirely new components of the FTT system. Please contact Dr Mercure for PhD project opportunities at jm801@cam.ac.uk . PhD Projects which we are hoping to allocate are the following:

Biomass and bioenergy modelling
Bioenergy possibilities and issues currently generate significant uncertainty in energy modelling. This is due to many factors, which when combine generate a very complex system that is currently not very well understood. The prospect to generate renewable energy using biomass (crops or residues) is currently creating very large markets for bioenergy commodities, which have the potential for very large problems, for instance a competition for land with food production and large additional land use change GHG emissions. The market for transport biofuels is currently leading people to transform large areas of land to dedicate them for their production, displacing food production or destroying forests. Secondly, the potential for sustainable bioenergy production is not very well known and strongly depends on scenarios of future land-use. We propose in this project to collaborate with world leaders in land-use modelling in order to bring in large amounts of information to the FTT project, and use this in the creation of better informed scenarios of future energy use and GHG emissions using the FTT modelling framework.

Substitution possibilities in industrial sectors
Evaluating the costs of emissions reductions requires gathering knowledge on all possible technology substitution possibilities which enable the economy to keep going while reducing emissions. Associated to these technology substitutions are learning curves, through which the costs of emissions reductions change as these systems develop. Thus the costs of mitigation are very complex to evaluate, but this can be done using a model such as the FTT framework. While costs of mitigation in the power sector have been studied fairly well in recent years, those of the industrial sector have been explored primarily using simple fixed cost assumptions. This project is to contribute in the development of FTT:Industry, which explores global emissions and energy use reduction possibilities in industries such as iron and steel and other metals, the cement industry, chemicals and petrochemicals etc. This project will be critical in enabling the FTT-E3MG modelling framework to account for all industrial emissions. 

A stochastic demographic model of technology evolution and use
Emissions reductions occur predominantly through technological change, i.e. switching between high and low emissions systems or from systems with high to low energy intensity in order to produce the same goods or services. Technological change comes through the replacement of existing technology, and therefore the rates of change are related to scrapping rates, lifetimes, investment payback times etc. However, the rates of change also depend critically on the existing stock of technology and its age distribution. Technology competition in the marketplace has been shown to follow a similar behaviour as competing species in ecosystems, and can be modelled using similar mathematical tools. Such theories are closely linked mathematically to demographic models of human population. This project concerns contributing to the development of a demographic theoretical model of technology and its application to climate change mitigation and technology forecasting.

Ongoing projects

Pablo Salas, PhD candidate: The effect of uncertainty over the drivers of technological transitions in the global power sector, particularly on energy investmentThis involves a more detailed formulation of the core decision-making component of FTT:Power. Investors face uncertainty affecting their decisions concerning power sector investments, such as uncertainty over future energy policy, the price of carbon or fuel prices. FTT:Power currently uses a model core decision-making component where investors are myopic and have no foresight, but see no uncertainty either. Uncertainty often has the effect of inducing investors to delay action waiting for more information, which can be treated using real options theory. The impact of different assumptions over the structure of invertor decisions can be evaluated by changing the assumptions at the core of FTT:Power.

Aileen Lam, PhD candidate:  As the second most important source of emissions, the transport sector accounts for more than one fifth of global energy use and energy related carbon dioxide emissions (IEA, 2009). This sector of energy use therefore has the potential to contribute significantly to climate change (IPCC, 2007, p328). The decarbonisation of road transport depends largely on the substitution of advanced low emissions technologies such as electric vehicles, fuel cells or hybrid-electric power trains. This PhD project concerns the construction of a model of technological change in the global transport sector using technology diffusion and learning curves, FTT:Transport. This model will generate global emissions and scenarios of changes in global road transport technology and emissions given particular sets of road transport policy around the world. The model will also generate global energy use in transport per type of fuel and enable to explore whether energy can be used sustainably under different scenarios.

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