A Swarm Intelligence Approach for Statistical Modeling of Wind Speed and Direction: A Case Study of New York Bight
Publication: Computing in Civil Engineering 2023
ABSTRACT
We present statistical modeling of wind speed and direction in the New York Bight region using a Weibull distribution for wind speed and a mixture of von Mises distributions for wind direction. The historic wind data for the years 2019−2021 with a 6-min sampling frequency are divided into two half-yearly intervals based on wind power, representing different seasonal behaviors. The parameters of von Mises distributions are estimated using four different metaheuristic optimization algorithms. The suitability of the distributions is judged based on the Pearson correlation coefficient, which indicates good fits for the proposed models. The results demonstrate the flexibility of the proposed models in representing the probability density function of wind direction regimes in zones with several modes or prevailing wind directions. This research provides valuable insights into the evaluation process of wind energy resources of the New York/New Jersey Bight region, including wind farm layout optimization.
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Information & Authors
Information
Published In
Computing in Civil Engineering 2023
Pages: 176 - 185
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Case studies
- Climates
- Energy engineering
- Energy sources (by type)
- Engineering fundamentals
- Environmental engineering
- Infrastructure
- Intelligent transportation systems
- Materials characterization
- Materials engineering
- Mathematics
- Methodology (by type)
- Mixtures
- Renewable energy
- Research methods (by type)
- Seasonal variations
- Statistics
- Structural engineering
- Transportation engineering
- Transportation management
- Wind direction
- Wind engineering
- Wind power
- Wind speed
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