Enhancing the Yearly Profit of a Wind Farm Using a Novel Transfer Function for Binary Particle Swarm Optimization Algorithm

Yıl 2022, Cilt: 06 Sayı: 1, 19 - 26, 31.08.2022

Prasun Bhattacharjee , Rabin K. Jana Somenath Bhattacharya

https://doi.org/10.34110/forecasting.1104066

Öz

While governments of quite a lot of nations and international alliances like the United Nations are perpetually striving for curtailing the emission of greenhouse gases for limiting the dangerous aftermaths of climate change, renewable energy resources like wind power can be utilized to realize an environment-friendly switchover of electricity generation projects. In this paper, Binary Particle Swarm Optimization Algorithm has been employed to enhance the yearly profit of a wind farm in Kayathar town of India with a novel transfer function. The optimization trial outcomes validate the superiority of the proposed transfer function when compared with similar ‘S’-type transfer functions.

Anahtar Kelimeler

Binary Particle Swarm Optimization, Kayathar, Transfer Function, Wind Farm, Yearly Profit

Destekleyen Kurum

Jadavpur University

Teşekkür

TEQIP Department

Kaynakça

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