We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Incorporating Uncertainty into World Energy Modelling: the PROMETHEUS Model.
- Authors
Fragkos, Panagiotis; Kouvaritakis, Nikos; Capros, Pantelis
- Abstract
In general, policy and most economic decisions like investments are formulated in a non-deterministic context. Their analysis can be considerably enhanced if probability information on future outcomes is available, especially in terms of unbiased estimates of the extent of unpredictability and stochastic dependence. For the sake of transparency, it is also important to be able to trace the justification of variability and its structure. This paper introduces PROMETHEUS, a stochastic model of the world energy system that is designed to produce joint empirical distributions of future outcomes concerning many variables that are important in terms of the evolution of the world energy system. The model methodology is based on Monte Carlo techniques, and the joint distributions of the model inputs are derived to a large extent not only from statistical econometric analysis but also from specialised studies. The emphasis is placed on the exhaustive coverage of variability including omitted variables. By incorporating detailed coverage of uncertainty into a comprehensive large-scale global energy system model, PROMETHEUS can be used to quantify probabilistic assessments of future model outcomes, which constitute critical parameters in formulating robust energy and climate policies. The description of the main model characteristics is complemented with an analytical example that illustrates the usefulness of stochastic PROMETHEUS results in the context of power generation investments under uncertainty.
- Subjects
ENERGY industries &; the economy; ECONOMETRICS; DEPENDENCE (Statistics); MONTE Carlo method; GOVERNMENT policy on climate change; STOCHASTIC analysis
- Publication
Environmental Modeling & Assessment, 2015, Vol 20, Issue 5, p549
- ISSN
1420-2026
- Publication type
Article
- DOI
10.1007/s10666-015-9442-x