dc.contributor.author |
Effatpanah, Saeed Khojaste
|
|
dc.contributor.author |
Ahmadi, Mohammad Hossein
|
|
dc.contributor.author |
Aungkulanon, Pasura
|
|
dc.contributor.author |
Maleki, Akbar
|
|
dc.contributor.author |
Sadeghzadeh, Milad
|
|
dc.contributor.author |
Sharifpur, Mohsen
|
|
dc.contributor.author |
Chen, Lingen
|
|
dc.date.accessioned |
2023-03-02T05:21:58Z |
|
dc.date.available |
2023-03-02T05:21:58Z |
|
dc.date.issued |
2022-01-26 |
|
dc.description.abstract |
Over the last decade, the total primary energy consumption has increased from479 1015 BTU
in 2010 to 528 1015 BTU in 2020. To address this ever-increasing energy demand, as well as prevent
environmental pollution, clean energies are presented as a potential solution. In this regard, evaluating
and selecting the most appropriate clean energy solution for a specific area is of particular
importance. Therefore, in this study, a comparative analysis in Jiangsu province in China was performed
by describing and implementing five prominent multi-criteria decision-making methods in
the field of energy technology selection, including SAW, TOPSIS, ELECTRE, VIKOR, and COPRAS.
The decision problem here consists of four clean energy options, including solar photovoltaic, wind,
nuclear, and biomass, which have been evaluated by twelve basic and important criteria for ranking
clean energy options. The obtained results, according to all five MCDM methods, indicate that solar
photovoltaic was the optimal option in this study, followed by wind energy. The nuclear and biomass
options placed third and fourth, respectively, except in the ELECTRE method ranking, in which both
options scored the same and thus neither was superior. Finally, by conducting a comprehensive
two-stage sensitivity analysis, in the first stage, it was found that changes in the weights of land use
and water consumption criteria had the greatest impact on the performance of options, among which
biomass and nuclear showed high sensitivity to variations in criteria weights. In the second stage,
by defining five scenarios, the ranking of options was evaluated from different aspects so that the
decision maker/organization would be able to make appropriate decisions in different situations. |
en_US |
dc.description.department |
Mechanical and Aeronautical Engineering |
en_US |
dc.description.librarian |
am2023 |
en_US |
dc.description.uri |
https://www.mdpi.com/journal/sustainability |
en_US |
dc.identifier.citation |
Effatpanah, S.K.; Ahmadi,
M.H.; Aungkulanon, P.; Maleki, A.;
Sadeghzadeh, M.; Sharifpur, M.;
Chen, L. Comparative Analysis of
Five Widely-Used Multi-Criteria
Decision-Making Methods to
Evaluate Clean Energy Technologies:
A Case Study. Sustainability 2022, 14,
1403. https://DOI.org/10.3390/su14031403. |
en_US |
dc.identifier.issn |
2071-1050 (online) |
|
dc.identifier.other |
10.3390/su14031403 |
|
dc.identifier.uri |
https://repository.up.ac.za/handle/2263/89911 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
MDPI |
en_US |
dc.rights |
© 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license. |
en_US |
dc.subject |
Clean energy |
en_US |
dc.subject |
Multi-criteria decision-making |
en_US |
dc.subject |
Comparative analysis |
en_US |
dc.subject |
Sensitivity analysis |
en_US |
dc.subject |
Jiangsu province |
en_US |
dc.subject |
Simple additive weighting (SAW) |
en_US |
dc.subject |
Technique for order of preference by similarity to ideal solution (TOPSIS) |
en_US |
dc.subject |
Elimination et choix traduisant la realité (ELECTRE) |
en_US |
dc.subject |
Viekriterijumsko kompromisno rangiranje (VIKOR) |
en_US |
dc.subject |
Preference ranking organization method for enrichment evaluations (PROMETHEE) |
en_US |
dc.subject |
Complex proportional assessment (COPRAS) |
en_US |
dc.subject |
Step-wise weight assessment ratio analysis (SWARA) |
en_US |
dc.subject.other |
Engineering, built environment and information technology articles SDG-04 |
|
dc.subject.other |
SDG-04: Quality education |
|
dc.subject.other |
Engineering, built environment and information technology articles SDG-07 |
|
dc.subject.other |
SDG-07: Affordable and clean energy |
|
dc.subject.other |
Engineering, built environment and information technology articles SDG-09 |
|
dc.subject.other |
SDG-09: Industry, innovation and infrastructure |
|
dc.subject.other |
Engineering, built environment and information technology articles SDG-13 |
|
dc.subject.other |
SDG-13: Climate action |
|
dc.title |
Comparative analysis of five widely-used multi-criteria decision-making methods to evaluate clean energy technologies |
en_US |
dc.type |
Article |
en_US |