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At what valuation of sustainability can we abandon fossil fuels? A comprehensive multistage decision support model for electricity planning

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  • Shakouri G., H.
  • Aliakbarisani, S.

Abstract

Predominance of fossil-fuel technologies and lack of enough incentives to expand sustainable technologies has intensified energy issues and the global warming problem. Combining mathematical programming and decision-making techniques, this paper proposes a novel comprehensive multistage method to insert sustainability costs in determining the optimum strategy of energy system expansion for an energy-rich developing country. Since the sustainability attributes have the same value respecting all conversion technologies, a nonlinear equal-weight data envelopment analysis is used to evaluate the technologies based on environmental, social and economic sustainability dimensions, the weightings associated with which are calculated. Sustainability costs, including pollutant emission costs, water and land utilization, etc. are then calibrated by the weightings and a mixed integer programming model is used to determine the optimum share of each technology in electricity generation for Iran, during the period of 2013–2040. The results suggest a late shift from fossil-fuel consumption by increasing the share of renewable energies. The model demonstrates that in countries with excessive fossil-fuel resources and high contribution of fossil-fuel technologies, including sustainability costs/benefits cannot lead to commercialization of renewable energy technologies, unless governments design effective incentive/tax policies, or fuel prices ascend enough again. The recent fuel price drop even deteriorates the situation.

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  • Shakouri G., H. & Aliakbarisani, S., 2016. "At what valuation of sustainability can we abandon fossil fuels? A comprehensive multistage decision support model for electricity planning," Energy, Elsevier, vol. 107(C), pages 60-77.
  • Handle: RePEc:eee:energy:v:107:y:2016:i:c:p:60-77
    DOI: 10.1016/j.energy.2016.03.124
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