Modelling the renewable transition: Scenarios and pathways for a decarbonized future using pymedeas, a new open-source energy systems model
Authors: J. Solé, R. Samsó, E. García-Ladona, A. García-Olivares, J. Ballabrera-Poym T. Madurell, A. Turiel, O. Osychenko, D. Álvarez, U. Bardi, M. Baumann, K. Buchmann, Í. Capellán-Pérez, M. Černý, Ó. Carpintero, I. De Blas, C. De Castro, J.-D. De Lathouwerg, C. Duce, L. Eggler, J.M. Enríquez, S. Falsini, K. Feng, N. Ferreras, F. Frechoso, K. Hubacek, A. Jonese, R. Kaclíkovái, C. Kerschner, C. Kimmich, L.F. Lobejón, P.L. Lomas, G. Martelloni, M. Mediavilla, L.J. Miguel, D.Natalini, J. Nieto, A. Nikolaev, G. Parrado, S. Papagianni, I. Perissi, C. Ploiner, L. Radulov, P. Rodrigo, L. Sun, M.Theofilidi.
Journal: Renewable and Sustainable Energy Reviews, ISSN: 1364-0321, Vol: 132, Page: 110105.
Highlights
- New Open Source Energy-Economy-Resources Integrated Assessment Model in Python
- Importance of biophysical limits for the massive development of RES
- Impact of efficiency and climate change in the energy transition
- Raw materials needed for the renewable transition
Abstract
This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.
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Last modified: | 01 August 2022 2.59 p.m. |
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