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Artificial Intelligence-Driven Competent Plan Of An Indian Wind Farm

Author

Listed:
  • Prasun Bhattacharjee

    (Jadavpur University)

  • Somenath Bhattacharya

    (Jadavpur University)

Abstract

India is at the moment the fifth largest economy and sustains the second biggest population in the world. To uphold its phenomenal economic growth, it would need cheap and reliable energy resources in the coming decades like any other nation. Moreover, the central government of India has announced its goal to attain carbon neutrality by 2070 following the pledges of the Paris treaty of 2015. To realize such a great aim, India needs to use its environment-friendly energy generation technologies rapidly and efficiently. Wind energy can help coastal states of India to generate electricity with a minimal carbon footprint and boost their economic progress. This current paper focuses on designing a wind farm in the western part of India using artificial intelligence methodologies. An innovative technique to escalate the efficiency of the genetic algorithm has been proposed to augment the economic output of the wind farm.

Suggested Citation

  • Prasun Bhattacharjee & Somenath Bhattacharya, 2022. "Artificial Intelligence-Driven Competent Plan Of An Indian Wind Farm," Journal of Information Systems & Operations Management, Romanian-American University, vol. 16(2), pages 1-11, December.
    • Handle: RePEc:rau:jisomg:v:16:y:2022:i:2:p:1-11
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    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/WI22/JISOM-WI22-A01.pdf
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    References listed on IDEAS

    as
    1. Prasun BHATTACHARJEE & Rabin K. JANA & Somenath BHATTACHARYA, 2021. "An Enhanced Genetic Algorithm For Annual Profit Maximization Of Wind Farm," Journal of Information Systems & Operations Management, Romanian-American University, vol. 15(2), pages 14-23, December.
    2. Krishnamoorthy R & Udhayakumar K & Kannadasan Raju & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization," Energies, MDPI, vol. 13(12), pages 1-41, June.
    3. Wilson, Dennis & Rodrigues, Silvio & Segura, Carlos & Loshchilov, Ilya & Hutter, Frank & Buenfil, Guillermo López & Kheiri, Ahmed & Keedwell, Ed & Ocampo-Pineda, Mario & Özcan, Ender & Peña, Sergio Iv, 2018. "Evolutionary computation for wind farm layout optimization," Renewable Energy, Elsevier, vol. 126(C), pages 681-691.
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