IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i2p118-d63094.html
   My bibliography  Save this article

A Comparison of Wind Energy Investment Alternatives Using Interval-Valued Intuitionistic Fuzzy Benefit/Cost Analysis

Author

Listed:
  • Cengiz Kahraman

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Macka Istanbul, Turkey)

  • Sezi Cevik Onar

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Macka Istanbul, Turkey)

  • Basar Oztaysi

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Macka Istanbul, Turkey)

Abstract

One of the tools for maintaining environmental sustainability is transformation from fossil-based energy sources to renewable energy sources in energy consumption. Among renewable energy alternatives, wind energy is the most prominent and reliable energy source for fulfilling energy demand. Traditional investment evaluation techniques based on discounted cash flows are not capable of capturing the uncertainty and vagueness in the data related to the wind energy investment parameters. Fuzzy capital budgeting techniques can capture this vagueness and model the imprecise estimations of parameter values. In this paper, we develop interval-valued intuitionistic fuzzy benefit-cost analysis for the evaluation of wind energy technology investments. The fuzzy benefit-cost analyses are based on both present worth and annual worth analyses. The developed analyses can handle the assessments of multiple experts through aggregation operators. In the proposed economic model, the components of each wind energy investment parameter are incorporated into the equations in detail. A real case study is also presented in this paper.

Suggested Citation

  • Cengiz Kahraman & Sezi Cevik Onar & Basar Oztaysi, 2016. "A Comparison of Wind Energy Investment Alternatives Using Interval-Valued Intuitionistic Fuzzy Benefit/Cost Analysis," Sustainability, MDPI, vol. 8(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:118-:d:63094
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/2/118/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/8/2/118/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ciabattoni, Lucio & Grisostomi, Massimo & Ippoliti, Gianluca & Longhi, Sauro, 2014. "Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario," Energy, Elsevier, vol. 74(C), pages 359-367.
    2. Mostafaeipour, Ali & Jadidi, Mohsen & Mohammadi, Kasra & Sedaghat, Ahmad, 2014. "An analysis of wind energy potential and economic evaluation in Zahedan, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 641-650.
    3. Perkin, Samuel & Garrett, Deon & Jensson, Pall, 2015. "Optimal wind turbine selection methodology: A case-study for Búrfell, Iceland," Renewable Energy, Elsevier, vol. 75(C), pages 165-172.
    4. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    5. Onar, Sezi Cevik & Oztaysi, Basar & Otay, İrem & Kahraman, Cengiz, 2015. "Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets," Energy, Elsevier, vol. 90(P1), pages 274-285.
    6. Kahraman, Cengiz & Tolga, Ethem & Ulukan, Ziya, 2000. "Justification of manufacturing technologies using fuzzy benefit/cost ratio analysis," International Journal of Production Economics, Elsevier, vol. 66(1), pages 45-52, June.
    7. Cengiz Kahraman, 2008. "Multi-Criteria Decision Making Methods and Fuzzy Sets," Springer Optimization and Its Applications, in: Cengiz Kahraman (ed.), Fuzzy Multi-Criteria Decision Making, pages 1-18, Springer.
    8. Rahimi, Sahand & Meratizaman, Mousa & Monadizadeh, Sina & Amidpour, Majid, 2014. "Techno-economic analysis of wind turbine–PEM (polymer electrolyte membrane) fuel cell hybrid system in standalone area," Energy, Elsevier, vol. 67(C), pages 381-396.
    9. Ucar, Aynur & Balo, Figen, 2010. "Assessment of wind power potential for turbine installation in coastal areas of Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1901-1912, September.
    10. Schallenberg-Rodriguez, Julieta, 2013. "A methodological review to estimate techno-economical wind energy production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 272-287.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Kejia & Tan, Qian & Zhang, Tianyuan & Wang, Shuping, 2020. "Assessing technology portfolios of clean energy-driven desalination-irrigation systems with interval-valued intuitionistic fuzzy sets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    2. Jaber Valinejad & Mousa Marzband & Mudathir Funsho Akorede & Ian D Elliott & Radu Godina & João Carlos de Oliveira Matias & Edris Pouresmaeil, 2018. "Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market," Sustainability, MDPI, vol. 10(10), pages 1-19, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nansheng Pang & Mengfan Nan & Qichen Meng & Siyang Zhao, 2021. "Selection of Wind Turbine Based on Fuzzy Analytic Network Process: A Case Study in China," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    2. Engelhorn, Thorsten & Müsgens, Felix, 2018. "How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany," Energy Economics, Elsevier, vol. 72(C), pages 542-557.
    3. Onar, Sezi Cevik & Oztaysi, Basar & Otay, İrem & Kahraman, Cengiz, 2015. "Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets," Energy, Elsevier, vol. 90(P1), pages 274-285.
    4. Shafiqur Rehman & Salman A. Khan, 2016. "Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia," Energies, MDPI, vol. 9(11), pages 1-26, October.
    5. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    6. Watts, David & Durán, Pablo & Flores, Yarela, 2017. "How does El Niño Southern Oscillation impact the wind resource in Chile? A techno-economical assessment of the influence of El Niño and La Niña on the wind power," Renewable Energy, Elsevier, vol. 103(C), pages 128-142.
    7. Alizadeh, Reza & Soltanisehat, Leili & Lund, Peter D. & Zamanisabzi, Hamed, 2020. "Improving renewable energy policy planning and decision-making through a hybrid MCDM method," Energy Policy, Elsevier, vol. 137(C).
    8. Shafiqur Rehman & Salman A. Khan & Luai M. Alhems, 2020. "A Rule-Based Fuzzy Logic Methodology for Multi-Criteria Selection of Wind Turbines," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
    9. A. G. Olabi & Tabbi Wilberforce & Khaled Elsaid & Tareq Salameh & Enas Taha Sayed & Khaled Saleh Husain & Mohammad Ali Abdelkareem, 2021. "Selection Guidelines for Wind Energy Technologies," Energies, MDPI, vol. 14(11), pages 1-34, June.
    10. Vincenzo Franzitta & Domenico Curto & Davide Rao, 2016. "Energetic Sustainability Using Renewable Energies in the Mediterranean Sea," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
    11. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.
    12. Reddy, Sohail R., 2021. "A machine learning approach for modeling irregular regions with multiple owners in wind farm layout design," Energy, Elsevier, vol. 220(C).
    13. Munir Ali Elfarra & Mustafa Kaya, 2018. "Comparison of Optimum Spline-Based Probability Density Functions to Parametric Distributions for the Wind Speed Data in Terms of Annual Energy Production," Energies, MDPI, vol. 11(11), pages 1-15, November.
    14. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
    15. Ayman Al-Quraan & Bashar Al-Mhairat, 2022. "Intelligent Optimized Wind Turbine Cost Analysis for Different Wind Sites in Jordan," Sustainability, MDPI, vol. 14(5), pages 1-24, March.
    16. Liang, Yushi & Wu, Chunbing & Ji, Xiaodong & Zhang, Mulan & Li, Yiran & He, Jianjun & Qin, Zhiheng, 2022. "Estimation of the influences of spatiotemporal variations in air density on wind energy assessment in China based on deep neural network," Energy, Elsevier, vol. 239(PC).
    17. Radünz, William Corrêa & Mattuella, Jussara M. Leite & Petry, Adriane Prisco, 2020. "Wind resource mapping and energy estimation in complex terrain: A framework based on field observations and computational fluid dynamics," Renewable Energy, Elsevier, vol. 152(C), pages 494-515.
    18. Bertolini, Marina & D'Alpaos, Chiara & Moretto, Michele, 2018. "Do Smart Grids boost investments in domestic PV plants? Evidence from the Italian electricity market," Energy, Elsevier, vol. 149(C), pages 890-902.
    19. Kuo, Jim Y.J. & Romero, David A. & Amon, Cristina H., 2015. "A mechanistic semi-empirical wake interaction model for wind farm layout optimization," Energy, Elsevier, vol. 93(P2), pages 2157-2165.
    20. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:118-:d:63094. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.