Enhancement of Annual Profit of a Wind Farm Using Artificial Intelligence-Based Meta-heuristic Methodology

Prasun Bhattacharjee; Rabin K. Jana; Somenath Bhattacharya

doi:10.26706/jpie.3.1.arset3489

Enhancement of Annual Profit of a Wind Farm Using Artificial Intelligence-Based Meta-heuristic Methodology

Prasun Bhattacharjee, Rabin K. Jana, Somenath Bhattacharya
Journal of Production and Industrial Engineering
Volume 3: Issue 1, June 2022, pp 11-15

Author's Information

Prasun Bhattacharjee¹

Corresponding Author

¹Jadavpur University, Kolkata, India

prasunbhatta@gmail.com

Rabin K. Jana2²

²Indian Institute of Management, Raipur, India

Somenath Bhattacharya³

³3Jadavpur University, Kolkata, India

Technical Article -- Peer Reviewed

Published online – 09 August 2022

Open Access article under Creative Commons License

Cite this article – Prasun Bhattacharjee, Rabin K. Jana, Somenath Bhattacharya,“Enhancement of Annual Profit of a Wind Farm Using Artificial Intelligence-Based Meta-heuristic Methodology”, Journal of Production and Industrial Engineering, RAME Publishers, vol. 3, issue 1, pp. 11-15, June 2022.

https://doi.org/10.26706/jpie.3.1.arset3489

Abstract:

As greenhouse gas emission is initiating climate change, renewable power resources like wind energy are aiding nations to accomplish the carbon neutrality goal as proposed in the Paris treaty of 2015. In this paper, a novel dynamic assignment process of factors for crossover and mutation methods of genetic algorithm for expanding the yearly profit of a wind farm at Jafrabad of India. The research solutions confirm the supremacy of the proposed technique over the standard static process of allocating the probabilities of crossover and mutation methods of genetic algorithm to augment the financial profitability of the wind power generation system.

Index Terms:

Artificial Intelligence, Genetic Algorithm, Layout Optimization, Profit Maximization, Wind Farm.

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