GET – Global Energy System model GET

The GET model is a global energy system model linked to a reduced complexity climate models in which greenhouse gases from other sectors of the economy is also taken into account. The model has a long history stretching back twenty years. The GET model has been used in several studies to analyze how climate targets can be achieved at lowest possible cost and which energy resources and technologies are important for a transition to a system with zero or even negative emissions of CO2 (where negative emissions can be achieved by bioenergy with carbon dioxide capture).

To provide a tool for decision makers to understand meeting global energy demand with global energy supply at a minimum cost and in a sustainable way, Chalmers University has developed a global energy model (GET-RC 6.1) that includes a detailed description of passenger vehicle technology options. The model can be used to better understand the fuel and vehicle technology choices available for passenger vehicles and how these fit into the larger global energy system, where different energy sectors compete for the same limited primary energy sources. The original linear programming Global Energy Transition (GET) model is designed to meet exogenously given energy demand levels, subject to a CO2 constraint, at the lowest global energy system cost (all costs are in US$). The GET model is being developed and extended to address research questions related to the sustainable development of the global energy system. Several different versions of the GET model are available. The aim of this report is to describe the version used in collaboration between staff at Ford Motor Company and Chalmers University of Technology during the period 2008-2013. The model version used, GET-RC 6.1, was developed to address research questions related to light duty passenger vehicles, where R stands for regionalized and C for cars. The report contains a description of the settings that are defined in the model (i.e., the sets, parameters and variables), the equations used in the model, suggestion for how to implement the model step by step, and the mathematical description of the model.