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Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective

Author

Listed:
  • Dhunny, A.Z.
  • Allam, Z.
  • Lobine, D.
  • Lollchund, M.R.

Abstract

The impacts of climate change, largely fuelled by the consumption of fossil fuels and an unhealthy consuming lifestyle, are encouraging a wide and far ranging adoption of renewable energy sources. This is critical, and well received, for countries who are on the frontline of climate change, in particular Small Island Developing States (SIDS) and those with fragile, unique and complex natural ecosystems. While there has been research on the importance of renewable energy and on the increasing of its efficiency for bettering its adoption and resulting economic gain, there is however little literature on the design and its implementation in respect to the rich and fragile biodiversity of areas; which contribute greatly to local ecosystems, and even to liveability dimensions of fauna, flora as well as humans, regions and cities. To ensure optimal energy generation while preserving fragile ecosystems, a method for numerical Genetic Algorithm (GA) is proposed for wind farming optimization to determine both the sitting of wind turbines and the Levelised Cost of Energy (LCOE). Optimal sites were identified in the small island of Mauritius and the model was applied on a complex terrain around an airport to identify optimal sites for the sitting of wind turbines while analysing the energy offset in terms of demand and supply of the area to encourage decentralised and more stable energy networks. Based on a set of parameters including local regulations and guidelines, 3 scenarios with a layout of 12, 24 and 36 wind farming sitting arrangements were proposed with a minimal impact on the fauna and flora; including the pathways of migratory birds. This paper is aimed at energy, urban planners and policy makers looking at sustainable energy planning.

Suggested Citation

  • Dhunny, A.Z. & Allam, Z. & Lobine, D. & Lollchund, M.R., 2019. "Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective," Energy, Elsevier, vol. 185(C), pages 1282-1297.
    • Handle: RePEc:eee:energy:v:185:y:2019:i:c:p:1282-1297
    DOI: 10.1016/j.energy.2019.07.147
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    References listed on IDEAS

    as
    1. repec:hal:spmain:info:hdl:2441/11505qn4ak95irt0cafaeim81j is not listed on IDEAS
    2. Lin, Boqiang & Chen, Yufang, 2019. "Does electricity price matter for innovation in renewable energy technologies in China?," Energy Economics, Elsevier, vol. 78(C), pages 259-266.
    3. Emami, Alireza & Noghreh, Pirooz, 2010. "New approach on optimization in placement of wind turbines within wind farm by genetic algorithms," Renewable Energy, Elsevier, vol. 35(7), pages 1559-1564.
    4. Pookpunt, Sittichoke & Ongsakul, Weerakorn, 2013. "Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients," Renewable Energy, Elsevier, vol. 55(C), pages 266-276.
    5. Marmidis, Grigorios & Lazarou, Stavros & Pyrgioti, Eleftheria, 2008. "Optimal placement of wind turbines in a wind park using Monte Carlo simulation," Renewable Energy, Elsevier, vol. 33(7), pages 1455-1460.
    6. Spiegel-Feld, Danielle & Rudyk, Bryce & Philippidis, George, 2016. "Allocating the economic benefits of renewable energy between stakeholders on Small Island Developing States (SIDS): Arguments for a balanced approach," Energy Policy, Elsevier, vol. 98(C), pages 744-748.
    7. Dhunny, A.Z. & Lollchund, M.R. & Rughooputh, S.D.D.V., 2017. "Wind energy evaluation for a highly complex terrain using Computational Fluid Dynamics (CFD)," Renewable Energy, Elsevier, vol. 101(C), pages 1-9.
    8. Gasparatos, Alexandros & Doll, Christopher N.H. & Esteban, Miguel & Ahmed, Abubakari & Olang, Tabitha A., 2017. "Renewable energy and biodiversity: Implications for transitioning to a Green Economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 161-184.
    9. 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.
    10. George C. Ledec & Kennan W. Rapp & Roberto G. Aiello, 2011. "Greening the Wind : Environmental and Social Considerations for Wind Power Development," World Bank Publications - Books, The World Bank Group, number 2388.
    11. Rebecca R. Hernandez & Madison K. Hoffacker & Christopher B. Field, 2015. "Efficient use of land to meet sustainable energy needs," Nature Climate Change, Nature, vol. 5(4), pages 353-358, April.
    12. Grady, S.A. & Hussaini, M.Y. & Abdullah, M.M., 2005. "Placement of wind turbines using genetic algorithms," Renewable Energy, Elsevier, vol. 30(2), pages 259-270.
    13. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    14. Inglesi-Lotz, Roula, 2016. "The impact of renewable energy consumption to economic growth: A panel data application," Energy Economics, Elsevier, vol. 53(C), pages 58-63.
    15. Dornan, Matthew, 2014. "Access to electricity in Small Island Developing States of the Pacific: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 726-735.
    16. Song, M.X. & Chen, K. & He, Z.Y. & Zhang, X., 2014. "Optimization of wind farm micro-siting for complex terrain using greedy algorithm," Energy, Elsevier, vol. 67(C), pages 454-459.
    17. Gao, Cheng-kang & Na, Hong-ming & Song, Kai-hui & Dyer, Noel & Tian, Fan & Xu, Qing-jiang & Xing, Yu-hong, 2019. "Environmental impact analysis of power generation from biomass and wind farms in different locations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 307-317.
    18. Sándor Szabó & Ioannis Kougias & Magda Moner-Girona & Katalin Bódis, 2015. "Sustainable Energy Portfolios for Small Island States," Sustainability, MDPI, vol. 7(9), pages 1-19, September.
    19. Bulavskaya, Tatyana & Reynès, Frédéric, 2018. "Job creation and economic impact of renewable energy in the Netherlands," Renewable Energy, Elsevier, vol. 119(C), pages 528-538.
    20. Aparna Katre & Arianna Tozzi, 2018. "Assessing the Sustainability of Decentralized Renewable Energy Systems: A Comprehensive Framework with Analytical Methods," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    21. Weisser, Daniel, 2004. "On the economics of electricity consumption in small island developing states: a role for renewable energy technologies?," Energy Policy, Elsevier, vol. 32(1), pages 127-140, January.
    22. Bagheri, Mehdi & Shirzadi, Navid & Bazdar, Elahe & Kennedy, Christopher A., 2018. "Optimal planning of hybrid renewable energy infrastructure for urban sustainability: Green Vancouver," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 254-264.
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    Cited by:

    1. Konstantina Ragazou & Alexandros Garefalakis & Eleni Zafeiriou & Ioannis Passas, 2022. "Agriculture 5.0: A New Strategic Management Mode for a Cut Cost and an Energy Efficient Agriculture Sector," Energies, MDPI, vol. 15(9), pages 1-17, April.
    2. Wu, Yunna & Liao, Mingjuan & Hu, Mengyao & Lin, Jiawei & Zhou, Jianli & Zhang, Buyuan & Xu, Chuanbo, 2020. "A decision framework of low-speed wind farm projects in hilly areas based on DEMATEL-entropy-TODIM method from the sustainability perspective: A case in China," Energy, Elsevier, vol. 213(C).
    3. Ali Sadollah & Mohammad Nasir & Zong Woo Geem, 2020. "Sustainability and Optimization: From Conceptual Fundamentals to Applications," Sustainability, MDPI, vol. 12(5), pages 1-34, March.
    4. Dhunny, A.Z. & Doorga, J.R.S. & Allam, Z. & Lollchund, M.R. & Boojhawon, R., 2019. "Identification of optimal wind, solar and hybrid wind-solar farming sites using fuzzy logic modelling," Energy, Elsevier, vol. 188(C).
    5. Ayyoob Sharifi & Zaheer Allam, 2022. "On the taxonomy of smart city indicators and their alignment with sustainability and resilience," Environment and Planning B, , vol. 49(5), pages 1536-1555, June.

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