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

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.