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Integrated Approach for Offshore Wind Turbine Site Selection: Implications for Sustainability in Power Supply Chain

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  • Koppiahraj Karuppiah

    (Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, Tamilnadu, India)

  • Bathrinath Sankaranarayanan

    (Department of Mechanical Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamilnadu, India)

  • Syed Mithun Ali

    (Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh)

  • Uthayakumar Marimuthu

    (Department of Mechanical Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamilnadu, India)

Abstract

Offshore wind turbine (OWT), a sustainable energy source, has recently gained wide attention. The energy demand for India is soaring high as it is a fast-developing nation in terms of industrialization; however, the interest shown by India toward renewable energy is low, especially for OWTs. This study aims to identify, categorize, and evaluate the criteria needed to be considered in the installation of OWTs and selection of potential locations in India. Based on literature analysis and exploratory interviews with experts, six aspects, namely, climatic conditions, regional features, investments and benefits, environmental impact, economic impact, and social and technical impact, with a total of twenty-six criteria, were identified and evaluated. An integrated approach of data envelopment analysis (DEA) with grey analytical hierarchy process (GAHP) and grey Complex proportional assessment (GCOPRAS) is used to evaluate the criteria and also to identify the locations for OWTs. Soil condition, extreme wind speed, seismic movement, tidal flow, and closeness to the power transmission grid have been identified as the top five criteria to be considered in the installation of OWTs. Gujarat, Tamil Nadu, Odisha, the Lakshadweep Islands, and the Andaman and Nicobar Islands have been identified as potential locations for installing OWTs in India. The outcomes of this study will deliver better insights for the practitioners about the criteria that need to be considered in OWTs. Further, this study sheds light on the importance of OWTs in an Indian context, which can possibly attract more investments.

Suggested Citation

  • Koppiahraj Karuppiah & Bathrinath Sankaranarayanan & Syed Mithun Ali & Uthayakumar Marimuthu, 2024. "Integrated Approach for Offshore Wind Turbine Site Selection: Implications for Sustainability in Power Supply Chain," Energies, MDPI, vol. 17(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3419-:d:1433331
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    References listed on IDEAS

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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Betakova, Vendula & Vojar, Jiri & Sklenicka, Petr, 2015. "Wind turbines location: How many and how far?," Applied Energy, Elsevier, vol. 151(C), pages 23-31.
    3. Mahdy, Mostafa & Bahaj, AbuBakr S., 2018. "Multi criteria decision analysis for offshore wind energy potential in Egypt," Renewable Energy, Elsevier, vol. 118(C), pages 278-289.
    4. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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