Comparative analysis of seasonal wind power using Weibull, Rayleigh and Champernowne distributions
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View abstract on PubMed
Summary
This summary is machine-generated.The Champernowne distribution accurately models wind speed variability, outperforming traditional models for wind energy assessment in regions with low wind speeds. This novel approach improves power density estimates and guides site suitability analysis.
Area Of Science
- Renewable Energy
- Statistical Modeling
- Meteorology
Background
- Accurate wind speed modeling is vital for wind energy potential assessment, especially in areas with low wind speeds and frequent calm periods.
- Traditional models like Weibull and Rayleigh-Rice may not fully capture wind speed intermittency.
- Understanding wind patterns is key to determining the feasibility of wind energy projects.
Purpose Of The Study
- To evaluate the Champernowne distribution as a novel statistical model for wind speed analysis.
- To compare its performance against established distributions (Weibull, Rayleigh-Rice) using various statistical metrics.
- To assess wind energy potential and suitability for Ben Guerir, Morocco.
Main Methods
- Collected three years of wind speed data (2021-2023) at 10 m hub height in Ben Guerir, Morocco.
- Applied statistical metrics including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC).
- Compared the fitting accuracy and predictive power of the Champernowne distribution against two-parameter Weibull, three-parameter Weibull, and Rayleigh-Rice distributions.
Main Results
- The Champernowne distribution demonstrated superior performance across all metrics, achieving the lowest RMSE (0.00036) and MAE (0.00022).
- It provided more accurate wind power density estimates (23% error) compared to Weibull (33%) and Rayleigh-Rice (42%) distributions.
- Despite low mean wind speeds (2.7 m/s), the site's power density ranged from 18 to 54 W/m², suggesting unsuitability for large-scale projects.
Conclusions
- The Champernowne distribution is a robust and accurate tool for modeling wind speed, particularly in regions with intermittent wind patterns.
- Conventional large-scale wind energy projects are not recommended for Ben Guerir; small Vertical-Axis Wind Turbines (VAWTs) or alternative strategies should be considered.
- This study provides a foundation for improved wind energy assessments and planning in challenging locations.
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