Search Results - mario+arrieta-prieto

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Spatio-temporal Forecasting of Very-Short Term Predictive Densities in the context of Wind Power Output
RPI ID: 2020-012-401 Innovation Summary: A probabilistic forecasting method is developed to predict wind power output using spatio-temporal modeling techniques. The system integrates historical wind data, weather forecasts, and turbine performance metrics to generate uncertainty-aware predictions. It applies Bayesian inference and Gaussian processes...
Published: 3/10/2026   |   Inventor(s): Mario Arrieta-Prieto, Kristen Schell
Keywords(s): Alternative Energy, ARIMAX, copula, drawable vine (d-vine) copula, Forecasting, Model, predictive densities, probabilistic forecasting, Time series, wind power
Category(s): Energy, Environment and Smart Systems