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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Energyarrow_drop_down
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Energy
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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A Layered Uncertainties Scenario Synthesizing (LUSS) model applied to evaluate multiple potential long-run outcomes for Iran's natural gas exports

Authors: Reza Hafezi; AmirNaser Akhavan; Saeed Pakseresht; David A. Wood;

A Layered Uncertainties Scenario Synthesizing (LUSS) model applied to evaluate multiple potential long-run outcomes for Iran's natural gas exports

Abstract

Abstract For decades, energy has prevailed as a critical policymaking concern at national and international levels. Today, energy systems, the global markets and their trends are more complex, and it is crucial for any nation or organization which seeks to grow its share in the energy markets to develop insights about potential future trends and changes. Although Iran has one the largest natural gas reserves in the world, it currently contributes little to international market supply and recently has targeted the enhancement of its role in the market. To achieve this, it must carefully consider the complexity of existing global energy markets and how they are likely to evolve in the future. Here, we develop and discuss a novel scenario synthesizing model to address the inherent uncertainty of the energy future. The model starts with a structured environmental analysis step to establish the meaningful driving forces and other influences on the natural gas global markets. The influences identified are then categorized under four classes: critical uncertainties, driving forces, descriptive, and neutral (which are removed from the study). Applying a simulation-based method, a layered scenario development model is constructed to develop plausible scenarios for two feature classes: critical uncertainties and driving forces. The developed scenarios are then combined to generate possible scenario streams. A third layer simulation is applied to generate final plausible scenarios. As a final step, scenarios are clustered to define relatively independent scenario streams, and each is discussed using descriptive features.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%