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In this paper the multiverse optimization (MVO) was used for estimating Weibull parameters. These parameters were further used to analyze the wind data available at a particular location in the Tirumala region in India. An effort had been made to study the wind potential in this region (13 • 41 30.4" N 79 • 21 34.4" E) using the Weibull parameters. The wind data had been measured at this site for a period of six years from January 2012 to December 2017. The analysis was performed at two different hub heights of 10 m and 65 m. The frequency distribution of wind speed, wind direction and mean wind speeds were calculated for this region. To compare the performance of the MVO, gray wolf optimizer (GWO), moth flame optimization (MFO), particle swarm optimization (PSO) and other numerical methods were considered. From this study, the performance had been analyzed and the best results were obtained by using the MVO with an error less than one. Along with the Weibull frequency distribution for the selected region, wind direction and wind speed were also provided. From the analysis, wind speed from 2 m/s to 10 m/s was present in sector 260-280 • and wind from 0-4 m/s were present in sector 170-180 • of the Tirumala region in India.optimization is that there exists information exchange among the solutions of candidates. In this way they can handle the local optima, bias of search space and premature convergence easier and faster. Some of the meta-heuristic optimization such as the genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO) and differential evolution algorithm (DEA) have overcome the limitations of single solution optimization methods. Therefore, in this paper a multiverse optimization (MVO) technique is implemented to estimate the parameters to adjust and fit the actual wind profile. This methodology serves as an innovative solution for any particular wind conditions provided a well-defined pattern has been provided. The MVO outperforms other optimization techniques and is being applied for wind energy applications to achieve rapid convergence in estimating Weibull parameters. This MVO algorithm is compared with PSO, which is best among the SI based technique and GWO, MFO as one of the most recent algorithms. The proposed algorithm has high exploitation ability due to combination of WEP/TDR constants and wormholes combined to provide high exploitation. Superior exploration of the proposed algorithm is due to white and black holes to exchange different objects.Here, the wind data for a period of six years from January 2012 to December 2017 in the Tirumala region (13 • 41 30.4" N 79 • 21 34.4" E) is being studied which is located in the southern part of India. In order to analyze the wind distribution, scale and shape parameters are determined using MVO. This gives two values, which is further utilized to determine the probability density function of the Weibull and Rayleigh distribution. With this study it has been estimated that there is sufficient wind potential in this region...

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