Comparative analysis of wind potential and characteristics using metaheuristic optimization algorithms at different places in India

The accuracy in analysis of wind speed is very critical to assess wind potential at any site. Wind power potential has been estimated using statistical distribution methods at numerous places around the world. The main aim of this article is to analyse wind potential and to compare between metaheuristic optimization algorithms and numerical approaches utilising the wind data at various places in India measured from masts and remote sensing technologies. The Weibull distribution fitness test is calculated using real-time wind data from various locations. The optimal Weibull parameters are estimated using numerical methods such as empirical method of Justus, maximum likelihood method, graphical method, modified maximum likelihood method and Wind Atlas Analysis and Application Program (WAsP). Furthermore, to assess Weibull distribution function for different sites (onshore, nearshore and offshore) in India, the social spider optimization is compared to particle swarm optimization and genetic algorithm. To examine the accuracy of various approaches, further goodness-of-fit method is estimated. The mean power density is maximum for offshore, followed by nearshore and onshore site with 452.32 W/m2, 431.53 W/m2, and 283 W/m2, respectively, at 120 m height. WAsP approach outperforms other numerical approaches used in this work. When compared to the genetic algorithm, the social spider optimization and particle swarm optimization were shown to be more efficient. The suggested method is more accurate than the numerical approaches utilised for wind potential assessment, according to the results.