Boosting the annual profit of an offshore wind farm in India with a bio-inspired meta-heuristic scheme

Abstract

Since the time of rapid industrial revolutions across the continents of the world, incessant emission of greenhouse gasses is severely deteriorating the quality of breathable air and causing abnormal increments in the surface air temperature. Global warming is a responsible factor for the melting of the polar ice caps, rising sea levels, uncharacteristic weather patterns, and immeasurable human distress throughout every corner of the planet. International communities are struggling to abate the global carbon footprint through the effective utilization of renewable resources of energy. Being the second most peopled realm in the globe, it turns out to be exceedingly momentous for India to resourcefully exploit its low-carbon sources of electricity like wind power to accomplish its net-zero emission ambition by 2070 while upholding the progress of its colossal economic structure. Although India presently sustains the fourth largest wind power generation competence in the world, it needs to develop its offshore wind power generation capacity rapidly for keeping up with its emission-cut aims. This paper attempts for augmenting the financial profitability of an offshore wind power generation system in the Bay of Khambhat near the seashore of Gujarat, India. An innovative modification of the Genetic Algorithm has been proposed to increase the annual profit of the proposed wind farm. The optimization trial outcomes authenticate the pre-eminence of the projected dynamic procedure for apportioning the factors of crossover and mutation functions over the standard static methods for assigning those proportions of the Genetic Algorithm.