Time VQ-VAE models generate daily wind vector series that reproduce diurnal volatility patterns but fail to match the distribution of extreme wind speeds.
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A conditional probabilistic framework using monthly Weibull parameters forecasted by Kalman filter on VAR(1), three Weibull-stationary SDE models, and XGBoost power curve mapping achieves CRPS of 1.57 m/s and low Wasserstein distances on real turbine data, preferring the diffusion-first model for sp
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Stochastic weather generators for high-frequency wind vector time series
Time VQ-VAE models generate daily wind vector series that reproduce diurnal volatility patterns but fail to match the distribution of extreme wind speeds.
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Weibull-Stationary Stochastic Differential Equations for Conditional Long-Horizon Wind Power Forecasting
A conditional probabilistic framework using monthly Weibull parameters forecasted by Kalman filter on VAR(1), three Weibull-stationary SDE models, and XGBoost power curve mapping achieves CRPS of 1.57 m/s and low Wasserstein distances on real turbine data, preferring the diffusion-first model for sp