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Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis

Author

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  • Paulo Rotela Junior

    (Department of Production Engineering, Federal University of Paraíba, João Pessoa 58051-970, Brazil)

  • Eugenio Fischetti

    (Department of Production Engineering, Federal University of Paraíba, João Pessoa 58051-970, Brazil)

  • Victor G. Araújo

    (Department of Production Engineering, Federal University of Paraíba, João Pessoa 58051-970, Brazil)

  • Rogério S. Peruchi

    (Department of Production Engineering, Federal University of Paraíba, João Pessoa 58051-970, Brazil)

  • Giancarlo Aquila

    (Institute of Industrial Engineering and Management, Federal University of Itajubá, Itajubá 37500-000, Brazil)

  • Luiz Célio S. Rocha

    (Department of Management, Federal Institute of Education, Science and Technology Northern of Minas Gerais, Almenara 39900-000, Brazil)

  • Liviam S. Lacerda

    (Department of Production Engineering, Federal University of Paraíba, João Pessoa 58051-970, Brazil)

Abstract

Wind power has grown popular in past recent years due to environmental issues and the search for alternative energy sources. Thus, the viability for wind power generation projects must be studied in order to attend to the environmental concerns and still be attractive and profitable. Therefore, this article aims to perform a sensitive analysis in order to identify the variables that influence most in the viability of a wind power investment for small size companies in the Brazilian northeast. For this, a stochastic analysis of viability through Monte Carlo Simulation (MCS) will be made and afterwards, Artificial Neural Networks (ANN) models will be applied for the most relevant variables identification. Through the sensitivity, it appears that the most relevant factors in the analysis are the speed of wind, energy tariff and the investment amount. Thus, the viability of the investment is straightly tied to the region where the wind turbine is installed, and the government incentives may allow decreasing in the investment amount for wind power. Based on this, incentives programs for the production of clean energy include cheaper purchase of wind turbines, lower taxing and financing rates, can make wind power more profitable and attractive.

Suggested Citation

  • Paulo Rotela Junior & Eugenio Fischetti & Victor G. Araújo & Rogério S. Peruchi & Giancarlo Aquila & Luiz Célio S. Rocha & Liviam S. Lacerda, 2019. "Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis," Energies, MDPI, vol. 12(12), pages 1-10, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2281-:d:239917
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    References listed on IDEAS

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    1. Rocha, Luiz Célio Souza & Aquila, Giancarlo & Rotela Junior, Paulo & Paiva, Anderson Paulo de & Pamplona, Edson de Oliveira & Balestrassi, Pedro Paulo, 2018. "A stochastic economic viability analysis of residential wind power generation in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 412-419.
    2. Tao, Jacqueline Yujia & Finenko, Anton, 2016. "Moving beyond LCOE: impact of various financing methods on PV profitability for SIDS," Energy Policy, Elsevier, vol. 98(C), pages 749-758.
    3. Ringel, Marc, 2006. "Fostering the use of renewable energies in the European Union: the race between feed-in tariffs and green certificates," Renewable Energy, Elsevier, vol. 31(1), pages 1-17.
    4. Silva, Neilton Fidelis da & Rosa, Luiz Pinguelli & Freitas, Marcos Aurélio Vasconcelos & Pereira, Marcio Giannini, 2013. "Wind energy in Brazil: From the power sector's expansion crisis model to the favorable environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 686-697.
    5. Haufe, Marie-Christin & Ehrhart, Karl-Martin, 2018. "Auctions for renewable energy support – Suitability, design, and first lessons learned," Energy Policy, Elsevier, vol. 121(C), pages 217-224.
    6. Mohammadi, Amin & Mehrpooya, Mehdi, 2018. "A comprehensive review on coupling different types of electrolyzer to renewable energy sources," Energy, Elsevier, vol. 158(C), pages 632-655.
    7. Reichelstein, Stefan & Yorston, Michael, 2013. "The prospects for cost competitive solar PV power," Energy Policy, Elsevier, vol. 55(C), pages 117-127.
    8. Chakrabarty, Sayan & Boksh, F.I.M. Muktadir & Chakraborty, Arpita, 2013. "Economic viability of biogas and green self-employment opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 757-766.
    9. Ata, Rasit, 2015. "Artificial neural networks applications in wind energy systems: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 534-562.
    10. Arnold, Uwe & Yildiz, Özgür, 2015. "Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach," Renewable Energy, Elsevier, vol. 77(C), pages 227-239.
    11. Aquila, Giancarlo & Rotela Junior, Paulo & de Oliveira Pamplona, Edson & de Queiroz, Anderson Rodrigo, 2017. "Wind power feasibility analysis under uncertainty in the Brazilian electricity market," Energy Economics, Elsevier, vol. 65(C), pages 127-136.
    12. Anoune, Kamal & Bouya, Mohsine & Astito, Abdelali & Abdellah, Abdellatif Ben, 2018. "Sizing methods and optimization techniques for PV-wind based hybrid renewable energy system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 652-673.
    13. Holdermann, Claudius & Kissel, Johannes & Beigel, Jürgen, 2014. "Distributed photovoltaic generation in Brazil: An economic viability analysis of small-scale photovoltaic systems in the residential and commercial sectors," Energy Policy, Elsevier, vol. 67(C), pages 612-617.
    14. Montes, German Martinez & Martin, Enrique Prados & Bayo, Javier Alegre & Garcia, Javier Ordoñez, 2011. "The applicability of computer simulation using Monte Carlo techniques in windfarm profitability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4746-4755.
    15. Li, Cun-bin & Lu, Gong-shu & Wu, Si, 2013. "The investment risk analysis of wind power project in China," Renewable Energy, Elsevier, vol. 50(C), pages 481-487.
    16. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    17. Bigdeli, Nooshin & Afshar, Karim & Gazafroudi, Amin Shokri & Ramandi, Mostafa Yousefi, 2013. "A comparative study of optimal hybrid methods for wind power prediction in wind farm of Alberta, Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 20-29.
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