Abstract
References
- Atanassov K.T. (1986), Intuitionistic Fuzzy Sets, Fuzzy Sets and Systems, 20, 87-96, Elsevier.
- U.S. Department of Energy Energy Efficiency and Renewable Energy. (n.d.). The History of Solar.
- Renewable Energy Policy Network for the 21st Century. (2015). Renewables 2015, Global Status Report. Paris. U.S. Department of Energy Energy Efficiency and Renewable Energy. (n.d.). The History of Solar.
- Arvizu, D., Balaya , P., Luisa, C. F., Hollands, K. T., Jager-Walnau, A., Kondo, M., . . . Zilles, R. (2011). Special Report on Renewable Energy Resources and Climate Change Mitigation. Intergovernmental Panel on Climate Change. Cambridge University Press.
- Barlev, D., Vidu, R., & Stroeve, P. (2011, May). Innovation in concentrated solar power. Solar Energy Materials & Solar Cells, 95, 2703-2725.
- Wu, J., Huang, H.-B., and Cao,Q.-W. (2013). Research on AHP with interval-valued intuitionistic fuzzy sets and its application in multi-criteria decision making problems, Applied Mathematical Modelling, 37, 9898–9906.
Abstract
Solar energy technologies are mainly composed of
photovoltaics and concentrated solar power (solar thermal) technologies.
Photovoltaic technology converts sunlight into electricity directly whereas
solar thermal technology utilizes its heat. Innovative solar energy
technologies appear in the market relatively more often than other energy
technologies. Selection among these innovative solar energy technologies is a
multi-criteria decision making problem under uncertain environment conditions.
Intuitionistic fuzzy sets provide an efficient way of capturing uncertainty by
processing both membership and non-membership degrees in a set, whose sum of these
degrees is not necessarily equal to one. In this paper, we use an
interval-valued intuitionistic fuzzy AHP method for the multi-criteria
evaluation of some innovative solar energy technologies. An application of
solar energy technology selection is also presented through the proposed
method.
References
- Atanassov K.T. (1986), Intuitionistic Fuzzy Sets, Fuzzy Sets and Systems, 20, 87-96, Elsevier.
- U.S. Department of Energy Energy Efficiency and Renewable Energy. (n.d.). The History of Solar.
- Renewable Energy Policy Network for the 21st Century. (2015). Renewables 2015, Global Status Report. Paris. U.S. Department of Energy Energy Efficiency and Renewable Energy. (n.d.). The History of Solar.
- Arvizu, D., Balaya , P., Luisa, C. F., Hollands, K. T., Jager-Walnau, A., Kondo, M., . . . Zilles, R. (2011). Special Report on Renewable Energy Resources and Climate Change Mitigation. Intergovernmental Panel on Climate Change. Cambridge University Press.
- Barlev, D., Vidu, R., & Stroeve, P. (2011, May). Innovation in concentrated solar power. Solar Energy Materials & Solar Cells, 95, 2703-2725.
- Wu, J., Huang, H.-B., and Cao,Q.-W. (2013). Research on AHP with interval-valued intuitionistic fuzzy sets and its application in multi-criteria decision making problems, Applied Mathematical Modelling, 37, 9898–9906.
Details
| Journal Section | Articles |
|---|---|
| Authors | |
| Publication Date | June 30, 2017 |
| Published in Issue | Year 2017 Volume: 5 Issue: 1 |
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