The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey
Open accessAbstract
Multi-Criteria Decision Making (MCDM) techniques are gaining popularity in energy supply systems. The aim of this paper is to develop the multi-criteria decision support framework for ranking renewable energy supply systems in Turkey. Given the selection of renewable energy supply systems involves many conflicting criteria, multi criteria decision methods (Fuzzy TOPSIS) were employed for the analysis. The Interval Shannon's Entropy methodology was used to determine weight values of the criteria. In this study, α = 0.1, 0.5 and 0.9 values based sensitivity analysis were performed. Three α-cutting levels were identical to the sequence of alternatives. According to result, the first criterion in preference ranking of renewable energy sources in Turkey is the Amount of Energy Produced, followed by the ranking systems Land use, Operation and maintenance cost, Installed capacity, Efficiency, Payback period, Investment cost, Job creation, and Value of CO2 emission. Thus the multi-criteria analysis showed that the Hydro Power Station is determined to be the most renewable energy supply system in Turkey. Additionally, the Geothermal Power Station, Regulator and Wind Power Station are determined to be the second, third and fourth, respectively. The government of Turkey should invest, in order of priority, in these systems. The government should also evaluate the projects, which are related to these renewable energy resources.
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Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
Application of multi-criteria decision making to sustainable energy planning—A review
Pohekar, S. D., & Ramachandran, M. (2004) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2003.12.007 · Cited by 1,938
Cited by
Sustainable Energy Transition for Renewable and Low Carbon Grid Electricity Generation and Supply
Kabeyi, M. J. B., & Olanrewaju, O. A. (2022) · Frontiers in Energy Research · doi:10.3389/fenrg.2021.743114 · Cited by 1,177
A bibliometric-based survey on AHP and TOPSIS techniques
Zyoud, S. H., & Fuchs-Hanusch, D. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.02.016 · Cited by 492
Effects of normalization on the entropy-based TOPSIS method
Chen, P. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.06.035 · Cited by 404
Decision making in renewable energy investments: a review
Strantzali, E., & Aravossis, K. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.11.021 · Cited by 400
Kaya, İ., Çolak, M., & Terzi, F. (2019) · Energy Strategy Reviews · doi:10.1016/j.esr.2019.03.003 · Cited by 365
Metadata
- Authors
- Şengül, Ü., Eren, M., Eslamian Shiraz, S., Gezder, V., & Şengül, A. B.
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 75
- Pages
- 617-625
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W1963593953
- Cited by
- 557
- References
- 2
- FWCI
- 29.16
- Type
- journal article
- Language
- en
- Open access
- green
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- Şengül, Ü., Eren, M., Eslamian Shiraz, S., Gezder, V., & Şengül, A. B. (2015). Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable Energy. https://doi.org/10.1016/j.renene.2014.10.045
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