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Change","sub_category":"Integrated Assessment and Climate Policy","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# FTT StandAlone\n\n## Future Technology Transformation\nThis repository contains a family of Future Technology Transformation (FTT) models. Models that are included are:\n\n* FTT:Power (Mercure, 2012) - data up to 2019, update to 2021 expected in October\n* FTT:Heat (Knobloch et al, 2017) data up to 2020\n* FTT:Industrial heat *under construction*\n* FTT:Transport (Mercure et al, 2018) - data up to 2022\n* FTT:Freight *under construction*\n\n## Theoretical background\nThe FTT family of models are based on [evolutionary economics](https://en.wikipedia.org/wiki/Evolutionary_economics). The uptake of new technologies typically follows an S-curve, which can be represented well with evolutionary dynamics (Mercure et al, 2012). The core equations for all of the models in the model family are coupled logistic equations of the [Lotka-Volterra family](https://en.wikipedia.org/wiki/Lotka%E2%80%93Volterra_equations), also known as the predator-prey equations. These equations are used to determine the evolution of the shares of various technologies in the models. Each model contains between ~10 to 25 technologies competing for market share. \n\n## FTT and E3ME\nThis repository contains the public standalone version of FTT, written in Python. A FORTRAN version of the model family is often used together with a macro-economic model as: [E3ME-FTT](https://www.e3me.com/). This model is managed by Cambridge Econometrics, and informs some of the inputs for the standalone model. In specific, energy demand is an output from the coupled model. \n\n## Installation and running the model\n1. Run the install_ce_conda_3.9_external_users.cmd script in _Python_installation to install the prerequisite packages. On top of Anaconda's standard packages, bottle and paste are required. \n2. You can run the front-end of the model by starting the FTT_Stand_Alone_Launcher.cmd. Alternatively, you can run the model from the run_file.py script for development, but this does not save the data. The basic settings can be edited in the settings.ini file.\n    1. The first time you run the model, csv input files will be created. This takes a few additional minutes. \n\n## References\n* Knobloch, F., Pollitt H., Chewpreecha U., Daioglou V. and Mercure J-F. (2018) ‘[Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5°C](https://link.springer.com/article/10.1007/s12053-018-9710-0)’, Energy Efficiency **12**, Issue 2, pp 521–550.\n* Mercure (2012) FTT:Power : [A global model of the power sector with induced technological change and natural resource depletion](https://www.sciencedirect.com/science/article/pii/S0301421512005356 ). Energy Policy **48**.\n* Mercure, J-F., Lam, A., Billington, S. and Pollitt, H. (2018) ‘[Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2°C](https://pubmed.ncbi.nlm.nih.gov/30930506/)’, Climatic Change, November 2018, Volume 151, Issue 2, pp 109–129.\n*  Vercoulen, P.; Lee, S.; Han, X.; Zhang, W.; Cho, Y.; Pang, J. (2023) '[Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with E3ME-FTT:Steel](https://www.mdpi.com/1996-1073/16/11/4498). Energies **16**, 4498. https://doi.org/10.3390/en16114498 \n","funding_links":[],"readme_doi_urls":["https://doi.org/10.3390/en16114498"],"works":{"https://doi.org/10.3390/en16114498":{"id":"https://openalex.org/W4379233423","doi":"https://doi.org/10.3390/en16114498","title":"Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with E3ME-FTT:Steel","display_name":"Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with 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