Modelling to generate alternatives: A technique to explore uncertainty in energy-environment-economy models

摘要: In this study we describe a novel formulation of the so-called modelling to generate alternatives (MGA) methodology and use it explore near cost optimal solution space global energy-environment-economy model TIAM-UCL. Our implementation specifically aims find maximally different energy system transition pathways assess extent their diversity in region. From can determine stability results implied by least pathway which turn allows us both identify whether there are any consistent insights that emerge across MGA iterations while at same time highlighting systems very similar look different. It is critical such an uncertainty analysis communicated policy makers aid robust decision making. To demonstrate technique apply two scenarios, business as usual (BAU) case climate run. For former significant variability primary carrier consumption then projects further into leading to, for example, large differences portfolio fuels used emissions from electricity sector. When imposing constraint find, general, less than BAU case. Consistent do with oil transport being finding all scenarios and, mitigation case, sector seen reliably decarbonise before industry total permitted increase. Finally, compare our Hop-Skip-Jump formulation, also seeks obtain solutions, that, when applied way, identifies more diverse latter.