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Updated: Aug 10, 2025

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Estimation of wind characteristics at different topographical conditions using doppler remote sensing instrument-a

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Summary

This study analyzed wind potential using evolutionary algorithms and compared remote sensing with mast data. The Teaching-Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms showed superior efficiency over Genetic Algorithms for wind energy assessment.

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Area of Science:

  • Renewable Energy
  • Computational Intelligence
  • Meteorology

Background:

  • Accurate wind potential assessment is crucial for renewable energy development.
  • Evaluating wind data from diverse sites (flat, coastal, offshore) requires robust analytical methods.
  • Comparing remote sensing techniques with conventional mast measurements is essential for data validation.

Purpose of the Study:

  • To analyze wind potential on various terrains using novel evolutionary algorithms.
  • To compare the efficiency of Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching-Learning-Based Optimization (TLBO) for Weibull parameter estimation.
  • To validate remote sensing wind data against conventional measurements.

Main Methods:

  • Utilized evolutionary algorithms (GA, PSO, TLBO) and computational techniques for wind data analysis.
  • Estimated optimum Weibull parameters using nine different methods.
  • Employed goodness-of-fit tests, including Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), coefficient of determination (R²), and chi-square (X²), to evaluate method accuracy.
  • Compared wind density calculations derived from parameter estimates.

Main Results:

  • The TLBO and PSO algorithms demonstrated higher efficiency compared to the GA.
  • Goodness-of-fit tests confirmed the accuracy of the selected parameter estimation methods.
  • Analysis provided insights into the performance of remote sensing versus cup anemometer measurements for wind assessment.

Conclusions:

  • Evolutionary algorithms, particularly TLBO and PSO, offer efficient methods for wind potential analysis and Weibull parameter optimization.
  • The study validates the use of remote sensing data in conjunction with traditional methods for comprehensive wind resource evaluation.
  • Accurate wind energy assessment is enhanced by comparing advanced computational techniques with empirical measurements.