AN ENHANCED GENETIC ALGORITHM FOR ANNUAL PROFIT MAXIMIZATION OF WIND FARM

Prasun Bhattacharjee (), Rabin K. Jana () and Somenath Bhattacharya ()
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Prasun Bhattacharjee: Jadavpur University, India
Rabin K. Jana: Indian Institute of Management Raipur, India
Somenath Bhattacharya: Jadavpur University, India

Journal of Information Systems & Operations Management, 2021, vol. 15, issue 2, 14-23

Abstract: Due to the swelling human suffering caused by climate change and the rapidly exhausting reserve of fossil fuels, renewable energy generation processes have gained immense importance throughout the globe. Wind energy is a leading renewable power generation method. To advance the green transition of the electricity generation industry, wind farms should stay commercially sustainable. This paper aims to increase the yearly profit of a wind farm utilizing an enhanced genetic algorithm. A novel method of dynamically allotting the crossover and mutation probabilities has been proposed to increase the effectiveness of the genetic algorithm. The assessment results validate the superior competence of the proposed tactic over the standard invariable method of assigning the crossover and mutation factors.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:15:y:2021:i:2:p:14-23

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