Abstract
The total world energy consumption is rising, and the alternative energy sources are sought to meet this demand. Renewable energy sources have distinctive features that make these sources environmental friendly and increase their share in total energy supply. Renewable energies, which are inexhaustible and renew themselves, are predicted to be the primary energy source for the future. The sun, which is the most important renewable energy source and the source of other energies, is also used for direct and indirect energy generation. In order to realize investments in solar energy systems that require high initial investment, their economic suitability must be assessed appropriately. Life cycle cost (LCC) and levelized cost of energy (LCOE) methods are widely used in economic evaluation and comparison of the large-scale solar energy system. Yet, solar energy investment decisions involve uncertainty and imprecision due to the vagueness in production levels and energy prices. An ample economic analysis should be able to evaluate the uncertainty and consider the dynamic costs and benefits. Pythagorean fuzzy sets are excellent tools for dealing with uncertainty and imprecision inherent in a system. In this study, the Pythagorean fuzzy set theory is applied so that the uncertainties and the opinions of the decision makers are more realistically incorporated into the economic analysis. The proposed Pythagorean LCC and LCOE methods enable dealing with the solar energy investments with fuzzy parameters. Alternative energy systems with different technological features and economic conditions can be more accurately compared using the proposed method.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96
Atanassov K (1989) Geometrical interpretation of the elements of the intuitionistic fuzzy objects. Preprint IM-MFAIS-1-89, Sofia. Reprinted: Int. J. Bioautomation, 2016, 20(S1):27–42
Atanassov KT (1999) Intuitionistic fuzzy sets. In: Intuitionistic fuzzy sets, pp 1–137. Springer
Atanassov KT (2012) On intuitionistic fuzzy sets theory. Springer, Heidelberg
Atanassov KT, Riecan B (2006) On two operations over intuitionistic fuzzy sets. J Appl Math Stat Inform (JAMSI) 2(2):145–148
Bolinger M, Seel J, LaCommare KH (2017) Utility-scale solar 2016: an empirical analysis of project cost, performance, and pricing trends in the United States. Lawrence Berkeley National Lab.(LBNL), Berkeley, CA, United States
BP (2017) Statistical review of world energy June 2017. https://www.bp.com/content/dam/bp/en/corporate/pdf/energy-economics/statistical-review-2017/bp-statistical-review-of-world-energy-2017-full-report.pdf. Accessed 10 Dec 2017
Buckley JJ, Eslami E, Feuring T (2013) Fuzzy mathematics in economics and engineering, vol 91. Physica, Heidelberg
Campbell M et al (2009) Minimizing utility-scale PV power plant LCOE through the use of high capacity factor configurations. In: 2009 34th IEEE photovoltaic specialists conference (PVSC). IEEE
Çoban V, Onar SÇ (2017) Modelling solar energy usage with fuzzy cognitive maps. In: Intelligence systems in environmental management: theory and applications, pp 159–187. Springer
Conkling RL (2011) Energy pricing: economics and principles. Springer, Berlin
Crawley GM (2016) Solar energy. World Scientific Publishing Co. Pte. Ltd, Hackensack
Dahl C (2015) International energy markets: understanding pricing, policies, and profits. PennWell Books, Tulsa
Darling SB et al (2011) Assumptions and the levelized cost of energy for photovoltaics. Energy Environ Sci 4(9):3133–3139
De SK, Biswas R, Roy AR (2000) Some operations on intuitionistic fuzzy sets. Fuzzy Sets Syst 114(3):477–484
Duffie JA, Beckman WA (2013) Solar engineering of thermal processes. Wiley, Hoboken
E.a.N.R.M. (ENRM) (2017a) Solar energy and technologies. http://www.yegm.gov.tr/yenilenebilir/gunes.aspx. Accessed 05 Dec 2017
E.a.N.R.M (ENRM) (2017b) Renewable energy resources support mechanism (YEKDEM). http://www.eie.gov.tr/yenilenebilir/YEKDEM.aspx. Accessed 20 Nov 2017
Energy HOMER (2017) Glossary. https://www.homerenergy.com/support/docs/3.10/glossary.html. Accessed 12 Dec 2017
Finance BNE (2015) New energy outlook 2015. https://data.bloomberglp.com/bnef/sites/4/2015/06/BNEF-NEO2015_Executive-summary.pdf. Accessed 10 Dec 2017
Insure S (2017) Top 5 largest solar power plants of the world. https://www.solarinsure.com/largest-solar-power-plants. Accessed 10 Nov 2017
International Energy Agency (IEA) (2017) World energy outlook 2017. https://www.eia.gov/outlooks/ieo/pdf/0484(2017).pdf. Accessed 28 Feb 2018
Kahraman C (2008) Fuzzy engineering economics with applications, vol 233. Springer, Berlin
Kahraman C, Çevik Onar S, Öztayşi B (2015) Engineering economic analyses using intuitionistic and hesitant fuzzy sets. J Intell Fuzzy Syst 29(3):1151–1168
Kahraman C, Onar SC, Oztaysi B (2017) Present worth analysis using pythagorean fuzzy sets. In: Advances in fuzzy logic and technology 2017, pp 336–342. Springer
Kalogirou SA (2013) Solar energy engineering: processes and systems. Academic Press, Oxford
Mendel JM, John RB (2002) Type-2 fuzzy sets made simple. IEEE Trans Fuzzy Syst 10(2):117–127
Mendel J, Wu D (2010) Perceptual computing: aiding people in making subjective judgments, vol 13. Wiley, Hoboken
Nayagam VLG, Sivaraman G (2011) Ranking of interval-valued intuitionistic fuzzy sets. Appl Soft Comput 11(4):3368–3372
N.R.E.L. (NREL) (2017) Distributed generation energy technology capital costs. https://www.nrel.gov/analysis/tech-cost-dg.html. Accessed 10 Nov 2017
P.D.o.E.a.M.E. (PDEME) (2017) Project decision metrics: levelized cost of energy (LCOE). https://www.e-education.psu.edu/eme801/node/560. Accessed 10 Nov 2017
Peng X, Yang Y (2015) Some results for Pythagorean fuzzy sets. Int J Intell Syst 30(11):1133–1160
Peng X, Yuan H, Yang Y (2017) Pythagorean fuzzy information measures and their applications. Int J Intell Syst 32:991–1029
Roubens M (1990) Inequality constraints between fuzzy numbers and their use in mathematical programming. In: Stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty, pp 321–330. Springer
Short W, Packey DJ, Holt T (1995) A manual for the economic evaluation of energy efficiency and renewable energy technologies. National Renewable Energy Lab., Golden, CO, United States
Sullivan WG, Wicks EM, Luxhoj JT (2009) Engineering economy. Pearson Prentice Hall, Upper Saddle River
Talavera D et al (2013) Sensitivity analysis on some profitability indices for photovoltaic grid-connected systems on buildings: the case of two top photovoltaic European areas. J Sol Energy Eng 135(1):011003
Timilsina GR, Kurdgelashvili L, Narbel PA (2012) Solar energy: markets, economics and policies. Renew Sustain Energy Rev 16(1):449–465
U.N. (UN) (2017) World Population Prospects 2017. https://esa.un.org/unpd/wpp/Graphs/Probabilistic/POP/TOT/. Accessed 20 Nov 2017
U.S. Department of Energy (USDE), Office of Indian Energy (2015). Levelized Cost of Energy (LCOE). https://energy.gov/sites/prod/files/2015/08/f25/LCOE.pdf. Accessed 25 Jan 2018
U.S.E.I.A. (USEIA) (2017a) Levelized costs and levelized avoided cost of new generation resources in the annual energy outlook 2017. https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.pdf. Accessed 20 Nov 2017
U.S.E.I.A. (USEIA) (2017b) Renewable and alternative fuels. https://www.eia.gov/renewable/. Accessed 20 Nov 2017
Vergura S, Lameira VJ (2011) Technical-financial comparison between a PV plant and a CSP plant. Sistem Gestao 6(2):210–220
World Energy Council (WEC) (2016) World energy resources 2016. https://www.worldenergy.org/publications/2016/world-energy-resources-2016/. Accessed 10 Dec 2017
Yager RR (2013) Pythagorean fuzzy subsets. In: IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), 2013 joint. IEEE
Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965
Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers, and decision making. Int J Intell Syst 28(5):436–452
Zatzman GM (2012) Sustainable energy pricing: nature, sustainable engineering, and the science of energy pricing. Wiley, Hoboken
Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Additional information
Communicated by C. Kahraman.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Çoban, V., Onar, S.Ç. Pythagorean fuzzy engineering economic analysis of solar power plants. Soft Comput 22, 5007–5020 (2018). https://doi.org/10.1007/s00500-018-3234-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-018-3234-6