Very‐short‐term probabilistic forecasting of wind power with generalized logit–normal distributions

211 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Forecasting: theory and practice (2020, background): “The use of transformations is recommended, though the choice of transformation depends on the nature of individual time series (Pinson, 2012).”
Energy Forecasting: A Review and Outlook (2020, background): “for wind speed [56] and generalized logit-Normal for wind power [57].”
Probabilistic Forecasts of Wind Power Generation Accounting for Geographically Dispersed Information (2014, background): “This translates to new challenges for the prediction of wind power generation at high temporal resolutions (in the order of few minutes), as recently addre ssed by [19] (and references therein).”
A Spatio-Temporal Analysis Approach for Short-Term Forecast of Wind Farm Generation (2014, methodology): “The procedure for building AR models with truncated log-normal distributions can be found in [16].”
Wind Energy: Forecasting Challenges for Its Operational Management (2013, methodology): “are difficult to outperform, possibly after data transformation (Pinson, 2012).”