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FTT:Power Results Viewer

Scenario explorer for the model of technology diffusion Future Technology Transformations in the Power sector. Drag mouse to zoom in.

This viewer enables to explore various quantities in 21 E3MG-FTT regions of the world and 24 FTT electricity technologies. Details of the context of the scenarios of this page are in two papers:

Economic benefits of decarbonising the global electricity sector,
J.F. Mercure, P. Salas, A. Foley, U. Chewpreecha, H. Pollitt, P. B. Holden, N. R. Edwards, arXiv:1310.4403 

The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sectorJ.F. Mercure, P. Salas, A. Foley, U. Chewpreecha, H. Pollitt, P. B. Holden, N. R. Edwards, Energy Policy 73 686-700 (2014) (open access), and the same content at arXiv:1309.7626

Description of policies, parameters and quantities:

Carbon price
       Assumed price of emissions permits in real or hypothetical carbon markets around the world, in 2008$/ton CO2
Subsidies
       Assumed fraction of capital costs of electricity generators funded by governments (%)
FiTs
       Feed-in-Tariffs: Price offered to generator owners when FiTs apply (wind and solar), in terms of a percentage of the difference
       between generation costs and the price of electricity (e.g. 120% means that the owner obtains 20% more than the wholesale
       price of electricity)
Generation
       Electricity generated by type of system, GWh (the top of the chart = total electricity demand + losses)
Emissions
       CO2 emissions by type of system, in Mtons of CO2 (the top of the colour chart = total emissions)
Capacity
       Electricity generation capacity in GW
LCOE
       Levelised Cost of producing Electricity: Cost of producing electricity determined using net present values, by technology type
TLCOE
       LCOE including taxes and subsidies + carbon price (TLCOE). It can be negative if sequestrating emissions leads to negative
       carbon costs

Scenario descriptions: 
4 types of policies modelled: Carbon Pricing (CO2P), Technology subsidies (TSs), Feed-in-Tariffs (FiTs), Regulations (REGs) 

Individual climate policy instruments:
0 - Baseline extending current policies to 2050: no additional TSs worldwide, FiTs in some EU countries, CO2P in the EU
1 - Coal phase out: REGs worldwide banning building new coal power stations unless fitted with Carbon Capture and Storage (CCS)
2 - Low CO2P only 
3 - High CO2P only 
4 - TSs and FiTs only
Combinations of climate policies:
5 - Low CO2P with FiTs
6 - Low CO2P with TSs and FiTs
7 - High CO2P with TSs and FiTs
8 - Developed nations only adopt climate policies: high CO2P, TSs, FiTs
9 - High CO2P with TSs, FiTs and REGs in China banning the construction of new coal power stations. Decarbonises by 89%. 

FTT Model assumptions, values and theory

Cost data and learning rates for investor choices
All cost values and cost distribution widths used for calculating the choice matrix Fij, and learning rates, are given here.
Most of these values are also provided in Mercure, Energy Policy (2012) (free access ArXiv) in a table at the end.
These are derived from the IEA Projected Costs of Generating Electricity 2010, freely available on the IEA website.  

Cost-supply curves for the representation of natural resource use
Cost-supply curves used in FTT have been published in Mercure & Salas, Energy (2012) (free access ArXiv), including lots of detail in the supplementary information attached for reconstructing these curves with functional forms.
Data with more regional resolution than provided in the paper can also be obtained by contacting us. These data can be aggregated to any regional definition. The method using Matlab can be provided, but is rather complicated to use for the non-initiated.

Non-renewable commodity price dynamics
Our model for price dynamics was published in Mercure & Salas, Energy Policy (2013) (open access) with supplementary information.

Theory of technological change and timescales
An initial description of the theory of technological change in FTT is given in Mercure, Energy Policy, (2012).
An in-depth exploration of how the Lotka-Volterra system of equations can be inferred to emerge from industrial dynamics and market competition is given in my work under review, freely available on ArXiv, Mercure (2013).

An opensource Matlab version of the FTT model in 21 regions (consistent with E3MG) can be downloaded freely here:

FTT21x24v4MPhil.zip   (This version was updated on 19/11/15)

A new version of the same was developed in 53 regions (consistent with current E3ME-Global):

FTT53x24v5MPhil.zip   (This version was updated on 5/12/15)

Instructions to run the model are available in a Word file inside of the .zip bundle.

Note that this version has an exogenous electricity demand, which was calculated using E3MG/E. Therefore, the price-demand feedback is lost in the Matlab version. However it can be used to explore the 10 scenarios shown on this page and small variations around them. Note that differences observed between scenarios in the Matlab version and those shown here stem from the difference in version dynamics, not inconsistencies.

E3MG and E3ME, including the versions with implementations of FTT, is a commercially licensed FORTRAN software, available from our partners Cambridge Econometrics. In E3ME, FTT operates under 53 regions, soon to be updated further to 55 regions or more, covering most developed and G20 countries independently.

Last updated 12/2015