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Sustainable electricity generation mix for Iran: A fuzzy analytic network process approach

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posted on 2022-10-19, 15:08 authored by Arash Sadeghi, Taimaz LarimianTaimaz Larimian

Electricity supply in Iran has been heavily dependent on fossil fuels. In light of the government's emphasis on reducing the consumption of conventional energy sources, combined with the worldwide attention to environmental issues, it is necessary for Iran to revise its current energy mix policy in power sector and move towards a more diversified energy portfolio. This paper aims to contribute to energy management studies through developing a new framework for assessing the mix of energy sources for producing electricity in Iran from the perspective of sustainable development. Multiple qualitative and quantitative criteria with conflicting nature need to be taken into consideration for evaluating competing energy options for electricity production in Iran. In order to address this issue and also to consider the complex interdependence among criteria and alternatives, this paper adopts a fuzzy analytic network process (FANP) method. Seven criteria and nineteen sub-criteria are defined and structured in the form of benefits, opportunities, costs and risks (BOCR) to evaluate the share of six energy resources. The results indicate that the best energy mix for the power sector in Iran is as follows: renewable energies (31.6%), natural gas (25%), coal (12.3%), fuel oil (12.6%), nuclear (8.7%) and gas oil (9.7%).

History

School

  • Architecture, Building and Civil Engineering

Published in

Sustainable Energy Technologies and Assessments

Volume

28

Pages

30 - 42

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Sustainable Energy Technologies and Assessments and the definitive published version is available at https://doi.org/10.1016/j.seta.2018.04.001

Acceptance date

2018-04-02

Publication date

2018-06-15

Copyright date

2018

ISSN

2213-1388

eISSN

2213-1396

Language

  • en

Depositor

Dr Taimaz Larimian. Deposit date: 18 October 2022

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