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Ex-post analysis of energy subsidy removal through integrated energy systems modelling.

Authors :
Aryanpur, V.
Ghahremani, M.
Mamipour, S.
Fattahi, M.
Ó Gallachóir, B.
Bazilian, M.D.
Glynn, J.
Source :
Renewable & Sustainable Energy Reviews. Apr2022, Vol. 158, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

Energy subsidies can incentivise the overconsumption of energy resources and contribute to other economic or social distortions. In this paper, an ex-post analysis is presented that explores the extent to which electricity subsidy reform could have reduced Iran's energy demand during the period 1984–2017. It also quantifies the techno-economic and environmental benefits that could have been achieved through such reforms. A time-varying econometric model is linked to an energy systems optimisation model. The former estimates electricity demand under different subsidy removal scenarios, and the latter identifies the cost-optimal generation mix to meet the demand. The results of cost-optimal transition pathways under subsidy removal scenarios are compared with the real-world energy system development during the study horizon. The comparison reveals that the subsidy reform could have reduced the total cumulative electricity consumption by 22%. Renewable share in power generation could have increased from 5% to 15%. Moreover, the reform combined with a cost-optimal generation pathway would have saved $69 billion and avoided 944 million tons of CO 2 emissions. The analysis also shows that every five-year delay in subsidy removal causes about 100 million tons of additional CO 2 emissions. Finally, the paper presents lessons learnt for future energy modelling. • An ex-post analysis quantifies the benefits of energy subsidy reform in the power sector. • The total cumulative electricity consumption could have been reduced by 22%. • Renewable share in power generation could have tripled. • Subsidy reforms combined with cost-optimal generation could have saved $69 billion. • The paper presents lessons learnt for future energy modelling. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13640321
Volume :
158
Database :
Academic Search Index
Journal :
Renewable & Sustainable Energy Reviews
Publication Type :
Academic Journal
Accession number :
155208618
Full Text :
https://doi.org/10.1016/j.rser.2022.112116