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Accurately assessing the potential wind resources is a critical phase in planning a wind energy project. The viability of wind power is determined using the Weibull distribution function, and its parameters are derived through numerical techniques. This study presents a methodology to estimate India’s offshore wind potential by utilizing 22 years of Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data at a 50 m elevation to calculate wind power density. In this study three numerical methods (Graphical Method (GM), Modified Maximum Likelihood Method (MMLM) and Empirical Method of Justus (EMJ)) are applied to estimate Weibull distribution parameters along with three metaheuristic optimization algorithms the Social Spider Optimization algorithm, to evaluate the accuracy of these methods two statistical analysis methods have been used. When compared to the Genetic Algorithm (GA), the Social Spider Optimization (SSO) and Particle Swarm Optimization (PSO) were shown to be more efficient. The analyzed data offers useful early information on the wind potential, which is crucial for converting wind energy and figuring out whether or not wind energy generation is indeed feasible at a certain location.

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Optimization of Weibull Parameters for Offshore Wind Potential Assessment with Reanalysis Data Using Metaheuristic Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • Harsh Patidar,
  • Vikas Shende,
  • Prashant Baredar,
  • Archana Soni

摘要

Accurately assessing the potential wind resources is a critical phase in planning a wind energy project. The viability of wind power is determined using the Weibull distribution function, and its parameters are derived through numerical techniques. This study presents a methodology to estimate India’s offshore wind potential by utilizing 22 years of Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data at a 50 m elevation to calculate wind power density. In this study three numerical methods (Graphical Method (GM), Modified Maximum Likelihood Method (MMLM) and Empirical Method of Justus (EMJ)) are applied to estimate Weibull distribution parameters along with three metaheuristic optimization algorithms the Social Spider Optimization algorithm, to evaluate the accuracy of these methods two statistical analysis methods have been used. When compared to the Genetic Algorithm (GA), the Social Spider Optimization (SSO) and Particle Swarm Optimization (PSO) were shown to be more efficient. The analyzed data offers useful early information on the wind potential, which is crucial for converting wind energy and figuring out whether or not wind energy generation is indeed feasible at a certain location.